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Volume-7 Issue-4, November 2018, ISSN: 2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication

Page No.

1.

Authors:

Ajala F. A., Adigun A.A, Oke A.O

Paper Title:

Development of Hybrid Compression Algorithm for Medical Images using Lempel-Ziv-Welch and Huffman Encoding

Abstract: Image compression is of utmost importance in data processing, because of the cost savings it offers and because of the large volume of data transferred from one end to the other. The smaller the size of the data the better transmission speed and it also saves time. In communication, transmission of data efficiently, fast and noise free is essential.. Both the LZW and Huffman image compression algorithm are lossless in manner and these methods and some versions of them are very common in use of compressing images. On the average Huffman gives better compression results, while LZW give a better signal-noise-ratio and when the compression efficiency gap between the LZW algorithm and its Huffman counterpart is the largest. In this work, Hybrid of LZW and Huffman image compression was developed and used. It gives better compression ratio and SNR than Huffman Encoding and LZW Algorithm. It also provides cheap, reliable and efficient system for image compression in digital communication system. The average result shows that Huffman encoding has 59.46% and LZW has1,99% of compression ratio, whereas the hybrid of Huffman and LZW has compression ratio of 47.61% but has 92.76% of Signal to Noise Ratio that produce better result of the original image.

Keywords: Compression, Transmission, Huffman, LZW, Encoding.

References:

  1. Subramanya A, (2002) “Image Compression Technique,” Potentials IEEE, Vol. 20, Issue 1, pp 19-23,
  2. Meyer B and P. Tischer, (2010) “TMW—A New Method for Lossless Image Compression,” Australia,
  3. Huffman D (1952), A Method for the Construction of Minimum Redundancy Codes,‖ Proc. IRE, pp. 1098-1101,
  4. Rajeswari R and R. Rajesh, (2011) “WBMP Compression,” In- ternational Journal of Wisdom Based Computing, Vol. 1, No. 2,
  5. Ramya R, and K. Mala, (2007) A hybrid Compression Algorithm for Compound Images, IEEE International Conference on Computational Intelligence and Multimedia Applications, Vol.3, pp 68-72.
  6. Sunil Kumar and R.C.Jain, (2007) “Low complexity fractal-based image compression techniques,” IEEE Transactions on Consumer Electronics, Vol.43, no.4, pp 987-993,
  7. Mohammed, (2008)“Highly scalable hybrid image coding scheme,” Digital Signal Processing, Vol.18, no.3, pp 364-374,
  8. Zhe-Ming L.U.and P.E.I.Hui, (2005) “Hybrid image compression scheme based on PVQ and DCTVQ,” IEICE transactions on information and systems, Vol.88, no.10, pp 2422-2426,
  9. ZIV, J., AND LEMPEL(1978), A. Compression of individual sequences via variable-rate coding. IEEE Transactions on Information Theory 24, 530–536

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2.

Authors:

Savita Sharma, Mausham Taneja

Paper Title:

The Effect of Training on Employee Performance

Abstract: The Success or failure of modern business organizations depends on the quality of their human resources. Well trained and highly developed employees are considered a cornerstone for such success. The employee is a bloodstream of any business. The accomplishment or disaster of the firm depends on its employee performance. Hence, top management realized the importance of investing in training and development for the sake of improving employee performance. Training and Development, On the Job Training, Training Design and Delivery style are four of the most important aspects of organizational studies. The focus of the current study is to understand the effect of Training and Development, On the Job Training, Training Design and Delivery style on Organizational performance. Low job satisfaction and low motivation do not only reduce the performance of the health systems but also constitute a serious push factor for migration of health workers, both from rural areas to the cities and to other countries. Employees – the vital part of the organization should be developed as they are contributing to the organization ‟s success. Organizations require the employees of highly skilled, knowledgeable with the right attitude for its smooth functioning and development. The present investigation is good to go to discover the effect of training on employee work execution conduct among modern laborers of ventures situated in the National Capital Region. This paper focus on the current practices being followed in organizations for training and development of the employees in industry with analyze the impact of training and development programmers on employees’ work performance in the industries located in Gautama Buddha Nagar, to highlight the problems responsible for the unsuccessful implementation of the training and development programmers in the industries of Uttar Pradesh with some good suggestion to measures for the successful implementation of training and development programmers in the organizations to uplift the level of employees’ work performance.

Keywords: Training, Employee performance. Competence, Job Performance, Employee Quality, Training, and Development, On the Job Training, Training Design, Delivery style, Organizational Performance.

References:

  1. Stone R J. (2002), Human Resource Management 2nd Edition, Jhon Wiley & Sons 2002.
  2. George, S. A. & Scott, B. W. 2012, Managing Human Resource, 16th Edition.
  3. Fakhar Ul Afaq, Anwar Khan (2008), “Case of Pearl Continental hotels in Pakistan, Relationship of training with Employees’ Performance in Hoteling Industry”.
  4. Richard Chang Associates, INC., “Measuring the impact of training, demonstrate the measurable results and return on investment.”
  5. McKinsey Quarterly (2006), “An executive take on the top business trends”, a McKinsey Global Survey.
  6. Meyer, P.J. and Smith, A.C. (2000), “HRM practices and organizational commitment: a test of a mediation model”, Canadian Journal of Administrative Sciences, Vol. 17 No. 4, pp. 319-31.
  7. Colarelli, S. M., & Monteiro, M. S. 1996. Some contextual influences on training utilization. The Journal of Applied Behavioral Science, 32(3): 306-322.
  8. Tai, W. T., (2006). Effects of Training Framing, General Self-efficacy and Training Motivation on Trainees’ Training Effectiveness, Emerald Group Publishers, 35(1), pp. 51-65.
  9. Gerhart, B., Milkovich, G. T., & Murray, B. 1992. Pay, performance, and participation. In D. Lewin, O. Mitchell, & P. Sherer (Eds.), Research Frontiers in Industrial Relations, pp. 193-238. Madison, WI: Industrial Relations Research Association.
  10. Harvey, M. 2002. Human Resource Management in Africa: Alice’s Adventures in Wonderland. International Journal of Human Resource Management. 13,7, 1119 – 1145.
  11. Brotherton, J., Evans, C., (2010). The Importance of the Trainer: Factors Affecting the Retention of Clients in the Training Services Sector, Industrial and Commercial Training.
  12. Emerald Group Publishers, 42(1), pp. 23-31. Brinkerh off, R. O., (2006). Increasing Impacts of Training Investments: An Evaluation Strategy for Building Organizational Learning Capability, Industrial and Commercial Banking. Emerald Group of Publishers, 38(6), pp. 302-307.

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3.

Authors:

M. S. Minu, Deepak Adithya K. N.

Paper Title:

Real Time College Bus Monitoring and Notification System

Abstract: In today economic and traffic condition no one can predicts at wat time and when the required transportation of a person can arrive .The aim of the paper work to provide a app which can be used for college students so that they can manage the time during all days usefully and get to their transport point at the right time and not lose the bus or any other college transportation receive provided by the college. I intent to use IOT and concepts with the help of Arduino to complete and implement this product. This paper also aims to add feature like estimate time of arrival, notification, students data base etc. 

Keywords: Arduino, Economic and Traffic, College Students.

References:

  1. Manash​ ​Pratim​ ​Gohain,​ ​Speed​ ​Governors,​ ​GPS​ ​must​ ​for school​ ​buses, The ​ ​Times​ ​of​ ​India, February​ ​24, 2017
  2. Pham Hoang Oat, Micheal Drieberg and Nguyen Chi Cuong, Development of Vehicle Tracking System using GPS         and GSM Modem , 2013 IEEE Conference on Open Systems  (ICOS),​ ​December​ ​2​ ​-​ ​4,​ ​2013,​ ​Sarawak,​ ​Malaysia.
  3. Maliha Mahbub, Anuradha Mandal, Sabira Khanam, M. Shamim Kaiser and Shamim Al Mamun, ”Improvement of RFID Tag Detection Using Smart Antenna For Tag Based School Monitoring System”, International  Conference on     Electrical Engineering and Information & Communication      Technology​ ​(ICEEICT)​ ​2014
  4. Yuanqing Zheng; Pengfei Zhou; Mo Li, "How Long to Wait? Predicting Bus Arrival Time with Mobile Phone Based Participatory Sensing, "Mobile Computing, IEEE Transactions on,​ ​vol.13,​ ​no.6,​ ​pp.1228,​ ​1241,​ ​June​ ​2014.
  5. Isa, H. L., Saad, S. A., Badrul Hisham, A. Aisha, &Ishak, M. H. I., "Improvement of GPS Accuracy in Positioning by Using DGPS Technique BT –Modeling, Design and Simulation of Systems: 17th Asia Simulation Conference, Asia Sim 2017, Melaka, Malaysia, August 27 – 29, 2017, Proceedings, Part II,"In M. S. Mohamed Ali, H. Wahid, N. A. Mohd Subha, S. Sahlan, M. A. Md. Yunus, & A. R. Wahap (Eds.), (pp. 3–11)Singapore: Springer Singapore, 2017.
  6. Maruthi, R., "SMS based Bus Tracking System using Open Source Technologies," Int. J. Comput. Appl. (0975 – 8887), pp. vol. 86, 44– 46, 2014.
  7. Rahman, A. A., & Sidek, S., Abdullah, A. R., "The critical flaw in the implementation of GPS tracking system in express bus industry," 10th IEEE Int. Conf. Serv. Oper. Logist. Informatics, SOLI 2015 - conjunction with ICT4ALL 2015, pp. 71–76, 2015.
  8. Ramadan, M. N., Al-kheder, S., Al-khedher, M. a, & Member, S., a, "Intelligent Anti-Theft and Tracking System for Automobiles," Int. J. Mach. Learn. Computer, pp. vol. 2, 88–92, 2012.

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4.

Authors:

Ritu Maheshwari, Anil Rajput, Anil K. Gupta

Paper Title:

Performance of “VCPHCF-RTT” Security Agent in Private Virtual Cloud Infrastructure

Abstract: Cloud Security issue is one of the biggest challenges that hampers the growth of Cloud for its various service provisioning. An on-demand access to a shared pool of computing resources in the cloud is the major service provisioning that involves delivering hosted services over the Internet. Security of Private Virtual Cloud Infrastructure will be proposed against IP-Spoofing based DDoS Attacks using Private Virtual Cloud Infrastructure Model. Virtualization Enhancement will be done in Cloud using proposed Security Agent VCPHCF-RTT. Performance Parameters will be analysed after introspection to cloud security techniques to resolve focussed Research Problem Issues and Challenges. VCPHCF-RTT improves the efficiency of the probability based Hop Count Filtering technique using HCF at intermediate nodes between the Virtual Machines of Client VM and Server VM along with RTT. It reduces the probability of guessing the RTT and VCHCF parameter values both at the intermediate routers by the attackers. The robustness of VCPHCF-RTT has been shown in this paper against CHCF and PHCF techniques.

Keywords: Distributed Denial of Service (DDoS), Clouds, Virtual Machines (VM), Filter, Hop Count Filtering (HCF), Time-to-live (TTL), Virtual Cloud Probabilistic Hop Count Filtering using Round Trip Time (VCPHCF-RTT). 

References:

  1. Chi-Chun, H. Chun-Chieh, K. Joy, “A Cooperative Intrusion Detection System Framework for Cloud Computing Networks,” IEEE 39th International Conference on Parallel Processing Workshops, pp. 280-284, 2010.
  2. Kourai, T.Azumi, S. Chiba, “A Self-Protection mechanism against Stepping Stone Attacks for IaaS Clouds,” IEEE 9th International Conference on Ubiquitous Intelligence and Computing, pp. 539-546, 2012.
  3. Shrivastava, R. Sharma, A. Verma, “MAS based Framework to protect Cloud Computing against DDoS Attack,” International Journal of Research in Engineering and Technology, IJRET, vol. 2(12), pp. 36-40, December, 2013.
  4. Sheng-Wei, Y. Fang, “Securing KVM – based Cloud Systems via Virtualization Introspection,” IEEE 47th Hawaii International Conference on System Science, pp. 5028-5037, 2014.
  5. Kumara M.A., C.D. Jaidhar, “Hypervisor and Virtual Machine Dependent Intrusion Detection and Prevention System for Virtualized Cloud Environment,” 1st International Conference on Telematics and Future Generation Networks, pp. 1-6, 2015.
  6. Biswa Ranjan Swain, Bibhudatta Sahoo, “Mitigating DDoS attack and Saving Computational Time using a Probabilistic approach and HCF method,” IEEE International Conference on Advance Computing, NIT, Rourkela, India, pp. 1170-1172, 6-7, March 2009
  7. Maheshwari, C. Rama Krishna, M. Sridhar Brahma “Defending Network System against IP Spoofing based Distributed DoS attacks using DPHCF-RTT Packet Filtering Technique,” IEEE International Conference on Issues and Challenges in Intelligent Computing Techniques, KIET, Ghaziabad, India, pp. 211-214, 8th February 2014.
  8. Jayashree, K.S. Easwarakumar, V. Anandharaman, K. Aswin, S. Raja Vijay, “A Proactive Statistical Defense Solution for DDOS Attacks in Active Networks,” 1st IEEE International Conference on Emerging Trends in Engineering & Technology, Anna University, Chennai, India, pp. 878-881, 16-18, July, 2008.
  9. Sen, “A Robust mechanism for defending distributed denial of service attacks on web servers,” International Journal of Network Security and its Applications, vol. 3 (2), pp. 162-179, March 2011.
  10. Wu, R. Zheng, J. Pu, Shibao Sun, “An Adaptive Control Mechanism for Mitigating DDoS Attacks,” IEEE International Conference on Automation and Logistics, Henan University of Science and Technology, Luoyang, China, pp. 1760-1764, 5-7, August, 2009.
  11. Wang, C.Jin and K. Shang, “Defense Against Spoofed IP Traffic Using Hop-Count Filtering,” IEEE Transaction on Networking, vol. 15 (1), pp. 40-53, February, 2007.
  12. Zhang, J. eng, Z. Qin, M. Zhou, “Detecting the DDoS Attacks Based on SYN proxy and Hop-Count Filter,” IEEE International Conference on Communications, Circuits and Systems, University of Electronic Science and Technology, China, pp. 457-461, 11-13, July, 2007.
  13. B. Mopari, S.G. Pukale, M.L. Dhore, "Detection and defense against DDoS attack with IP spoofing," IEEE International Conference on Computing, Communication and Networking, Vishwakarma Institute of Technology, Pune, India, pp. 1-5, 18-20, December, 2008.
  14. Jin, H. Wang, K. G. Shin, “Hop-count filtering: an effective defense against spoofed traffic,” 2003, [Online]. Available: http://www.citeseerx.ist.psu.edu
  15. A. Mukaddam, I. H. Elhajj, “Hop count variability,” 6th IEEE International Conference on Internet Technology and Secured Transactions, American University of Beirut, Lebanon, pp. 240-244, 11-14, December , 2011.

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5.

Authors:

Pankaj Kumar Gautam, Sudhasnhu Pandey, Vishwajeet Kumar Nanda

Paper Title:

Robot Control by Accelerometer Based Hand Gesture using Arduino Microcontroller

Abstract: Most of robots are controlled by wireless connection (like remote or cell phones) or by direct (wired) connection. In this project work we have designed a robot which is to be controlled by hand gesture of human and an accelerometer is used to move robot according to hand movement. In this work the hardware requirements and complexity has been removed because of not using remote control. Arduino microcontroller makes it a self activated robot, which drives itself according to hand gesture of human standing in front of it. It follows the users hand gesture using accelerometer which makes itself driven robot.

Keywords: Accelerometer, Arduino-Uno, Hand Gesture, Microcontroller, Robot. 

References:

  1. J. Boehme, A .Brakensiek, U.D. Braumann, M. Krabbes, and H.M. Gross. “Neural networks for gesture based remote control of a mobile robot”. In Proc.1998 IEEE World Congress on Computational Intelligence WCCI 1998 – IJCNN 1998, pages 372-377, Anchorage, 1998. IEEE Computer Society Press.
  2. Bretzner, I. Laptev, and T. Lindberg, "Hand Gesture Recognition using Multi-Scale Color Features, Hierarchical Models and Particle Filtering", IEEE International Conf. on Automatic Face and Gesture Recognition, 2002.
  3. Rosales, V. Athitsos, L. Sigal, and S. Sclaroff, "3D Hand Pose Reconstruction Using Specialized Mappings", IEEE International      Con. on Computer Vision, pp. 378- 385, 2001.
  4. “Accelerometer-Based Control of an Industrial Robotic Arm” Pedro Neto, J. Norberto Pires, Member, IEEE, and A. Paulo Moreira, Member, IEEE.
  5. Cui and J.J. Weng. “Hand sign recognition from intensity image sequences with complex backgrouns”. In Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, Killington, Vermont, 1996.
  6. arduino.com.
  7. analog.com/static/imported- files/data_sheets/ADXL335.pdf.

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6.

Authors:

Simran Verma, Taruna Dhingra, Rashmi Rameshwari

Paper Title:

In Slilico Methods for Eradication of Papaya Leaf Curl Disease from Carica Papaya

Abstract: Carica papaya is a common fruit found in India. It has various medicinal properties. several viral diseases of papaya cause huge lose to agricultural economy to a large scale. The most commonly reported is Papaya leaf curl disease which is caused by Papaya leaf curl virus. Papaya leaf curl virus belongs to the genus Begomovirus i.e. has bipartite genome. Its C2(L2) gene in segment A of genome functions as transcription activator. To remove the infection of this virus from papaya gene silencing feature was considered. Out of several methods for gene silencing, RNA interference was studied in detailed to remove Papaya leaf curl disease through in silico. AGO1, QDE-2, and RDE-1are the related proteins required for transcriptional gene silencing in plants. These protein belong to Argonaute family and play central role in RNA silencing processes. RISC is the RNA induced silencing complex responsible for gene silencing. GW(Genome Wide Micro RNAs proteins) stand for (miRNA). It guides argonaute proteins to target mRNAs leading to gene silencing. The maximum homology of Papaya leaf curl virus was found to be with Tobacco Curly Shoot Virus. It has been found from literature that Carica papaya shares common ancestor with Arabidopsis Thaliana. The related proteins i.e. AGO1, QDE-2, and RDE is common protein found in both the species. These proteins are required for transcriptional gene silencing in plants. This suggests that these proteins can help in transcriptional gene silencing in Carica papaya too. This transcriptional gene silencing will repress the gene C2(L2) and thus stop further infection of virus. Bemisia tabaci is the insect vector of Papaya leaf curl virus. Controlling the population of this insect vector can reduce the chances of this virus infecting Carica papaya. Dimethoate is an insecticide used to kill this insect vector and is hazardous for human life. Anatoxin is a naturally occurring organophosphate isolated from blue-green algae and can be used as an efficient insecticide against Bemisia Tabaci.

Keywords: Carica Papaya, Papaya Leaf Curl Virus, Gene silencing, Dimethoate, Bemisia Tabaci

References:

  1. Aravind, G., Bhowmik, D., Duraivel, S., & Harish, G. (2013). Traditional and medicinal uses of Carica papaya. Journal of Medicinal Plants Studies, 1(1), 7-15.Vinod Kumar, 2012
  2. El-Zaher, E. H. A. (2014). Antifungal activity of Carica papaya seed extract against Aspergillus flavus as serious mycotoxins producing organism and causal organism for aspergillosis. Egypt. J. Exp. Biol.(Bot.), 10(1), 51-62.
  3. Anibijuwon, I. I., & Udeze, A. O. (2009). Antimicrobial activity of Carica papaya (pawpaw leaf) on some pathogenic organisms of clinical origin from South-Western Nigeria. Ethnobotanical Leaflets, 2009(7), 4.
  4. Purcifull, D. E. (1972). Papaya ringspot virus, no. 84. Description of Plant Viruses. Comm. Mycol. Inst. Assoc. Appl. Biol., Kew, Surrey, England.
  5. Thomas, K. M., & Krishnaswamy, C. S. (1939). First report of papaya leaf curl virus infecting papaya plants. Curr. Sci, 8, 316.
  6. Chandra, K. J., & Samuel, L. D. K. (1999). Viral and phytoplasmal diseases of papaya in India. Diseases of horticultural crops-fruits. Indus Publishing Company, New Delhi, 493-515.
  7. Lokhande, N. M., Moghe, P. G., Matte, A. D., & Hiware, B. J. (1992). Occurrence of papaya ringspot virus (PRSV) in Vidharbha regions of Maharashtra. Journal of Soils and Crops, 2, 36-39.
  8. Pita, J. S., Fondong, V. N., Sangare, A., Otim-Nape, G. W., Ogwal, S., & Fauquet, C. M. (2001). Recombination, pseudorecombination and synergism of geminiviruses are determinant keys to the epidemic of severe cassava mosaic disease in Uganda. Journal of General Virology, 82(3), 655-665.
  9. Fagard, M., Boutet, S., Morel, J. B., Bellini, C., & Vaucheret, H. (2000). AGO1, QDE-2, and RDE-1 are related proteins required for post-transcriptional gene silencing in plants, quelling in fungi, and RNA interference in animals. Proceedings of the National Academy of Sciences, 97(21), 11650-11654.
  10. Bohmert, K., Camus, I., Bellini, C., Bouchez, D., Caboche, M., & Benning, C. (1998). AGO1 defines a novel locus of Arabidopsis controlling leaf development. The EMBO journal, 17(1), 170-180.
  11. Hutvagner, G., & Simard, M. J. (2008). Argonaute proteins: key players in RNA silencing. Nature reviews Molecular cell biology, 9(1), 22.
  12. Tang, G. (2005). siRNA and miRNA: an insight into RISCs. Trends in biochemical sciences, 30(2), 106-114.
  13. Pontier, D., Picart, C., Roudier, F., Garcia, D., Lahmy, S., Azevedo, J., & Colot, V. (2012). NERD, a plant-specific GW protein, defines an additional RNAi-dependent chromatin-based pathway in    Molecular cell, 48(1), 121-132.
  14. Ren, G., Xie, M., Zhang, S., Vinovskis, C., Chen, X., & Yu, B. (2014). Methylation protects microRNAs from an AGO1-associated activity that uridylates 5′ RNA fragments generated by AGO1 cleavage. Proceedings of the National Academy of Sciences, 111(17), 6365-6370.
  15. Gupta, R. C., & Milatovic, D. (2014). Insecticides. In Biomarkers in toxicology (pp. 389-407).
  16. Varun, P., Ranade, S. A., & Saxena, S. (2017). A molecular insight into papaya leaf curl—a severe viral disease. Protoplasma, 254(6), 2055-2070.
  17. Eulalio, A., Tritschler, F., & Izaurralde, E. (2009). The GW182 protein family in animal cells: new insights into domains required for miRNA-mediated gene silencing. Rna.

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7.

Authors:

Rishi Choubey, V.B. Reddy

Paper Title:

Performance Analysis and Channel Estimation Based on K-Means based Correlation

Abstract: In this paper an efficient k-means based approach has been used for channel estimation and performance analysis. For experimentation 2×2, 3×3, 4×4, 5×5 systems (MIMO−OFDM) have been used. The parameter considered are subcarriers, spreading code length, timing jitters, channel variations and temperature correlation. The system is considered with the correlated timing jitters. First the subcarrier is considered according to the system with the variable spreading length along with the variable timing jitters. For finding the nearer subcarriers in the related frequency k-means algorithm have been applied. It is helpful in finding the related correlation. Additive white Gaussian noise (AWGN) and Rayleigh fading channel have been considered. The results clearly indicate that the improved performance has been obtained in case of increasing the systems or the subcarriers after the related similarity correlation through our approach. It is also found better in terms of different parametric variations.

Keywords: AWGN, Rayleigh Channel, Channel Estimation, K-Means

References:

  1. Frederiksen FB, Prasad R. An overview of OFDM and related techniques towards development of future wireless multimedia communications. In Radio and Wireless Conference 2002 (pp. 19-22). IEEE.
  2. Bingham JA. Multicarrier modulation for data transmission: An idea whose time has come. IEEE Communications magazine. 1990;28(5):5-14.
  3. Wang Z, Ma X, Giannakis GB. OFDM or single-carrier block transmissions? IEEE Transactions on Communications. 2004;52(3):380-94.
  4. Trivedi S, Raeen MS, Pawar SS. BER analysis of MIMO-OFDM system using BPSK modulation scheme. International Journal of Advanced Computer Research. 2012; 2(5):219-26.
  5. Xia P, Giannakis GB. Design and analysis of transmit-beamforming based on limited-rate feedback. IEEE Transactions on Signal Processing. 2006 May;54(5):1853-63.
  6. Paramita S, Singh SS, Mohanta J. Time and frequency synchronization in OFDM system. International Journal of Advanced Computer Research. 2014;4(3):856.
  7. Muzakkari BA, Mohamed MA, Kadir MF, Mohamad Z, Jamil N. Recent advances in energy efficient-QoS aware MAC protocols for wireless sensor networks. International Journal of Advanced Computer Research. 2018; 8(38): 212-228.
  8. Shalini J,Manjunatha YR. Efficient reconfigurable architecture for advanced orthogonal frequency division multiplexing (AOFDM) transmitter. International Journal of Advanced Computer Research. 2018; 8(37):171-179.
  9. Khandelwal A, Jain YK. An efficient k-means algorithm for the cluster head selection based on SAW and WPM. International Journal of Advanced Computer Research. 2018; 8(37):191-202.
  10. Zhou S, Wang Z, Giannakis GB. Quantifying the power loss when transmit beamforming relies on finite-rate feedback. IEEE Transactions on Wireless Communications. 2005;4(4):1948-57.
  11. Tarokh V, Seshadri N, Calderbank AR. Space-time codes for high data rate wireless communication: Performance criterion and code construction. IEEE Transactions on Information Theory. 1998;44(2):744-65.
  12. Foschini GJ. Layered space‐time architecture for wireless communication in a fading environment when using multi‐element antennas. Bell labs Technical Journal. 1996;1(2):41-59.
  13. Anitha K, Sujatha BK. FPGA implementation of high throughput digital QPSK modulator using verilog HDL. International Journal of Advanced Computer Research. 2014;4(1):217.
  14. Wu S. A PID controller parameter tuning method based on improved PSO. International Journal of Advanced Computer Research. 2018;8(34):41-6.
  15. Telatar E. Capacity of Multi‐antenna Gaussian Channels. European transactions on telecommunications. 1999;10(6):585-95.
  16. Daksh JK, Mohan R, Sharma S. Performance analysis with space-time coding in MIMO-OFDM systems with multiple antennas. International Journal of Advanced Computer Research. 2013;3(2):126-9.
  17. Choubey R, Mohan R, Sharma S. A survey of BER performance of generalized MC DS-CDMA system. International Journal of Advanced Computer Research. 2013;3(2):130-3.
  18. Daksh JK, Mohan R, Sharma S. A survey of Performance Analysis in MIMO-OFDM Systems. International Journal of Advanced Computer Research. 2013;3(2):91-4.
  19. Dubey AK, Khandagre Y, Kushwaha GR, Hemnani K, Tiwari R, Shrivastava N. PAPR Reduction in OFDM by Using Modernize SLM Technique. InRecent Trends in Wireless and Mobile Networks 2011 (pp. 397-405). Springer Berlin Heidelberg.
  20. Irandegani M, Bagherizadeh M. Designing an asynchronous multi-channel media access control protocol based on service quality for wireless sensor networks. International Journal of Advanced Computer Research. 2017;7(32):190.
  21. Dalwadi DC, Soni HB. A novel channel estimation technique of MIMO-OFDM system based on Extended Kalman filter. Ininternational conference on electronics and communication systems 2017 (pp. 158-163). IEEE.
  22. Hayder AS, Nakhai MR, Le TA. Enhanced sparse Bayesian learning-based channel estimation for massive MIMO-OFDM systems. InEuropean conference on networks and communications 2017 (pp. 1-5). IEEE.
  23. Ghosh M, Srinivasarao C, Sahoo HK. Adaptive channel estimation in MIMO-OFDM for indoor and outdoor environments. Ininternational conference on wireless communications, signal processing and networking 2017 (pp. 2743-2747). IEEE.
  24. Venkatasubramanian A, Krithika V, Partibane B. Channel estimation for a multi-user MIMO-OFDM-IDMA system. Ininternational conference on communication and signal processing 2017 (pp. 1823-1827). IEEE.
  25. Nair AS, Jones SR. Design of low complexity H-inf algorithm for channel estimation in multiuser multicell MIMO OFDM systems. Ininternational conference on intelligent computing, instrumentation and control technologies 2017 (pp. 824-830). IEEE.
  26. Sherin KJ, Abhitha E. ICI mitigation in MIMO-OFDM by iterative equalization using OPT in time varying channels. In international conference on intelligent computing and control 2017 (pp. 1-6). IEEE.
  27. Inkamchua N, Boonsrimuang P, Mata T, Sopin A. Proposal of channel estimation scheme for practical V-BLAST MIMO-OFDM system. Ininternational conference on information technology and electrical engineering 2017 (pp. 1-5). IEEE.
  28. Munshi A, Unnikrishnan S. Modeling and simulation of MIMO-OFDM systems with classical and Bayesian channel estimation. Ininternational conference on advances in computing, communication and control 2017 (pp. 1-4). IEEE.
  29. Ladaycia A, Belouchrani A, Abed-Meraim K, Mokraoui A. Em-based semi-blindMIMO-OFDM channel estimation. In international conference on acoustics, speech and signal processing 2018 (pp. 3899-3903). IEEE.
  30. Kong W, Li H, Song S, Fan Y, Zhang W. Compressive sensing based channel estimation for MIMO-OFDM systems. In conference on industrial electronics and applications 2018 (pp. 2164-2169). IEEE.

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8.

Authors:

A.S. Madhusudhan Rao

Paper Title:

Energy Dependent γ- ray Attenuation Studies on Cs Halides & Determination of Photon Interaction Parameters

Abstract: Experimental determination of mass attenuation coefficient (μm) of Cs halides at different γ-energies has been taken up. Mixture rule is used to calculate the values of μm of compounds. Experimentally determined μm is compared with the calculated and X-Com values. Other physical parameters of the Cs halides are evaluated using the experimental, calculated and the X-Com values of μm and are reported for first time.

Keywords: Physical parameters, Cs halides, Pellets, X-Com, Mixture Rule.

References:

  1. Turgut U, Simsek A, Buyukkasapp E and Ertugrul M, Spectrochim Acta B, 57, 261 (2002)
  2. Sahin A. Un Y. Nucl. Instrum. Methods B. 269, 1506-1511(2011).
  3. Abdel-Rahman, M.A., Badawi, E.A., Abdel-Hady, Y.L., Kamel, N., Nucl.Instrum. Methods A 447, 432–436 (2000).
  4. Kurudirek M., Aygun M., Erzeneoğlu S.Z., Appl. Radiat. Isot., 68, 1006-1011(2010).
  5. Singh H, Singh K, Gerward L, Sahota H.S, and Nathuram R, Nucl.Instrum. & Meth. B207, 257 (2003).
  6. S. Madhusudhan Rao et al, Determination of Photon Interaction Parameters of CaO and MgO for Multi-Energetic Photons using γ-Ray Attenuation Technique, IOSR-JAP, Volume 8, Issue 2 Ver. I (Mar. - Apr. 2016), PP 103-109
  7. Gerward, N. Guilbert, K.B. Jensen, H. Levring, X-ray absorption in matter. Reengineering XCOM, Radiation Physics and Chemistry, 60 (2001) 23–24.

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9.

Authors:

Abhishek Anurag, R. Kamatchi

Paper Title:

Analysis of “Defect Root Cause and Corrective Actions” and its impact on “Software System Quality”

Abstract: Nature of software systems and its usage have changed significantly, so its complexity has grown exponentially. It is very difficult and challenging to maintain quality of software systems as user requirements and environment in which system is being used are constantly changing. If user requirements are not met, it is defined as defect. Defect must be analyzed, root caused and fixed to help improve software system quality. In this research study defects are analyzed based on root cause analysis, and different root cause categories and corresponding corrective actions are identified. This study analyses different attributes of defects which are interdependent with root cause & corrective actions and how they impact software system quality.

Keywords: Software Quality; Defect Attributes; Root Cause Analysis; Corrective Actions

References:

  1. Ian Somerville, “Software Engineering”, 8th ed., Addison-Wesley, pp. 5–6, 1982.
  2. M. Juran, "Juran's Quality Control Handbook", McGraw-Hill, 1988.
  3. Cagla Atagoren and Oumout Chouseinoglou, “A Case Study in Defect Measurement and Root Cause Analysis in a Turkish Software Organization”, In: Lee R. (eds) Software Engineering Research, Management and Applications. Studies in Computational Intelligence, vol 496. Springer, Heidelberg, pp. 55-72, 2014.
  4. Abhishek Anurag, Dr. Kamatchi Iyer, “A Case Study of existing Quality Model based on Defects & Tests Management of Embedded Software System”, International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR) @ tjprc.org, ISSN (Print): 2249-6831; ISSN (Online): 2249-7943; Impact Factor (JCC): 8.9034; Index Copernicus Value (ICV): 60.28; NAAS Rating: 3.76; IBI Factor: 3.2. Paper Id.: IJCSEITRJUN20183, Vol – Issue: 8 – 2, pp. 15-30, Published: June 30, 2018; http://www.tjprc.org/view-achives.php?keyword=Abhishek+Anurag&jtype=2&from_date=&to_date=&journal=14.
  5. Abhishek Anurag, “Study on Software Quality improvement based on Root Cause & Corrective Actions”, International Journal of Advanced in Management, Technology and Engineering Sciences @ http://ijamtes.org/, IJAMTES/319, Volume 8, Issue IV, A UGC Approved peer reviewed/referred Journal ISSN No: 2249-7455, Scientific Journal Impact Factor - 6.3, pp. 252-260, April/2018.
  6. Marek Leszak, Dewayne E. Perry and Dieter Stoll, “A case study in root cause defect analysis”, Proceeding ICSE '00 Proceedings of the 22nd international conference on Software Engineering, ACM New York, ISBN:1-58113-206-9, pp. 428-437, June 04 - 11, 2000.

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10.

Authors:

Kilina E.F, Petrosian E. Kh, Lipovka A.Yu, Kukina I.V

Paper Title:

Universal Smart Tool for Assessing and Developing Urban Morphology

Abstract: The city occupies an important place in the country's settlement system. The urban population of the Russian Federation is more than 74% of the total population of the country. The city gives residents many opportunities, but also a large number of problems for city planners. An important component of a smart city is smart planning - urban strategic development of the city, the use of high technologies and smart tools for analysis, drawing and visualization. Smart planning can be divided into stages of urban development: big data analysis and modelling, data collection, strategic planning and forecasting, and promoting smart life. The purpose of the study is a comprehensive review of intelligent design and the creation of a universal tool for urban planning, planning and evaluation of the structure of the city. The morphology of the city is chosen as a tool for visualizing the design and modelling of a smart city, because, in the practice of urban planning, specialists are faced with the rapid growth of cities and people. This leads to uncontrolled land use. As a result, a universal tool for urban planning, modelling and evaluation of the urban morphology “Urban blok" has been developed.

Keywords: Planning, Programming, Smart Tool, Urban Morphology.

References:

  1. P. Kupriyanovskiy, S.A. Sinyagov, and P.A. Tishchenko, “Smart City: the use of GIS - and FM-technologies in the implementation of urban planning policy,” ArcReview: Geoinformation systems for business and society, vol. 2(61), 2012. [Online]. Available: https:/ /www. dataplus. ru/news /arcreview/ detail.php?ID=7436& SECTION_ID=251
  2. Ya. Omelchenko, V. O. Tanich, A. S. Maklakov, E. A. Karyakina, “A brief overview and prospects for the use of the Arduino microprocessor platform,” ES and K, vol.21, 2013. [Online]. Available: https:// cyberleninka .ru/article/n /kratkiy-obzor-i-perspektivy-primeneniya-mikroprotsessornoy-platformy-arduino
  3. Mazhar Rathore , Awais Ahmad , Anand Paul , Seungmin Rho, “Urban planning and building smart cities based on the Internet of Things using Big Data analytics,” Computer Network, vol. 10, no. 5, pp. 63-80, 2015.
  4. Ibrahim Abaker Targio Hashem , Victor Chang , Nor Badrul Anuar, Kayode Adewole, Ibrar Yaqoo, Abdullah Gani, Ejaz Ahmed , Haruna Chiroma., “The role of big data in smart city,” International Journal of Information Management, vol. 36, no. 5, pp. 748-758, 2016.

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11.

Authors:

Karthik K, S Jena, T Venu Gopal

Paper Title:

Performance Index - A Metric to Analyze and Evaluate Performance of Hypercube Interconnection Networks

Abstract: A Multiprocessor is a computing machine which has at least two central processors, to process the tasks simultaneously. An Interconnection network that links multiple processors greatly influences the performing capability of the entire system. Various network scales to evaluate interconnection networks are: degree, speed, node coverage, reliability, scalability, diameter, connectivity, throughput, packet loss, and network cost etc. Interconnection Network like a Hypercube can be considered as an graph with undirected edges, where a vertex indicates a processor and an undirected edge denotes a communication medium among the processors. Some of the variants of Hypercube Interconnection Networks are Hypercube Network, Folded Hypercube Network, Multiple Reduced Hypercube, Multiply Twisted Cube, Recursive Circulant, Exchanged Crossed Cube Network, Half Hypercube Network etc. The vital purpose of this paper is to investigate different variants of hypercube interconnection networks and to analyze their properties to summarize the differences in their performance. It is also discussed how to analyze and evaluate the performance of Hypercube Networks and identify the changes in Performance Index based on the variations in their properties

Keywords: Multiprocessor, Interconnection Network, Hypercube, Performance Index.

References:

  1. N S Murthy Sharma, Karthik kovuri, komira Yakaiah, B Srinivas: Analysis of multiple reduced hypercube interconnection network properties of both diameter and network cost. International Journal of Computer Applications in Engineering, Technology and Sciences.
  2. Harary, F., Hayes, J. P., Wu, H.-J.: A Survey of the Theory of Hypercube Graphs.Comput. Math. Appl. 15.
  3. Akers, S. B., Krishnamurthy, B.: A Group-Theoretic Model for Symmertric Interconnection Network. IEEE. Trans. Computers 38(4), 555{565 (1989).
  4. Tucker, L. W., Robertson, G. G Architecture and Application of the Connection Machine. IEEE. Trans. Computers 21(8), 26{38 (1988).
  5. Park, K.-Y. Chwa, Recursive circulant: A new topology for multicomputer networks, in: Proc. Internat. Symp. Parallel Architectures, Algorithms and Networks (ISPAN’94), Kanazawa, Japan, December 1994, pp. 73–80.
  6. Anirudha S. Vaidya, P.S. Nagendra Rao, and S. Ravi Shankar “A Class of Hypercube like Networks," 1063-6374/93$03.00©1993 IEEE.
  7. Nibedita Adhikari, and Dr. C. R. Thripathy “The Folded Cross Cube: A new Interconnection Network for Parallel Systems," in International Journal of Computer Applications (0975-8887) Volume 4- No. 3, July 2010.
  8. Qiang Zhu, Jun-Ming Xu, Xinmin Hou, and Min Xu “On reliability of folded hypercubes", in Science Direct Information Sciences 177, 1782-1788©2006 Elsevier.
  9. Agrawal, C.P. Ravi Kumar “Fault-tolerant routing in multiply twisted cube topology", Proc. Accepted 6 March 1996.
  10. Sun-Yuan Hsieh, and Chang-Jen Tu “Constructing edge-disjoint spanning trees in locally twisted cubes",  in theoretical computer Science 410 (2009) 926-932©2008 Elsevier doi:10.1016/j.tcs.2008.12.025
  11. Jung-Heum Park, and Kyung-Yong Chwa “Recursive circulants and their embeddings among hypercubes", in Theoretical computer Science 244, 35-62©2000 Elsevier.
  12. Jung-Heum Park, and Kyung-Yong Chwa “Recursive Circulant: A New Topology for Multicomputer Networks", 0-8186-6507/94$4.00©1994 IEEE.
  13. Hyun sim, Jae-chul Oh, and Hyeong-Ok Lee “Multiple Reduced Hypercube (MRH): A New Interconnection Network Reducing both Diameter and Edge of Hypercube” in International Journal of Grid and Distributed Computing Vol.3, No.1, March 2010.
  14. Keqiu Li, Yuangping Mu, Keqin Li, and Geyong Min “Exchanged Crossed Cube: A Novel Interconnection Network for Parallel Computation” in IEEE Transactions on Parallel and distributed Systems, Vol.24, No.11, November 2013.
  15. Hong-Chun Hsu, and Shin-Pei Hsu “Cube connected Crossed Cube: A New Interconnection Topology” in The 31st Workshop on Combinatorial Mathematics and computation theory
  16. Xuding Zhu “The Z-cubes: a hypercube variant with small diameter”, Grant Number: CNSF11571319 arXiv: 1509.06884v1 [math.CO] 23 Sep 2015.
  17. Ali Karci, and Burhan selcuk “A new hypercube variant: Fractal Cubic Network Graph”, 2215-0986©2015 Elsevier.
  18. Zaki Ahmed khan, Jamshed Siddiqui, and Abdus Samad “Topological Evaluation of Variants Hypercube Network” in Asian Journal of Computer Science and Information Technology 3: 9 (2013) 125-128, ISSN: 2249-5126.
  19. Mahfooz Alam, and Ankur K. Varshney “A Comparative Study of Interconnection Network” in International Journal of Computer applications (0975-8887), Volume 127-No.4, October 2015.
  20. P. Bertsekas, C. Ozveren, G.D. Stamoulis, P. Tseng, and J.N. Tsitsiklis “Optimal Communication Algorithms for Hypercubes” in Journal of Parallel and Distributed Computing 11, 263-275.

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12.

Authors:

M. Venkata Subbarao, P. Samundiswary

Paper Title:

Automatic Modulation Recognition in Cognitive Radio Receivers using Multi-Order Cumulants and Decision Trees

Abstract: Design of intelligent receiver is a major footstep in the implementation of Cognitive Radio (CR). Automatic Modulation Recognition (AMR) of the received signal decides the performance of the intelligent receiver. This paper proposes new classification algorithms for AMR using supervised Decision Tree (DT). DT Classifiers (DTC’s) are non-parametric classifiers which provide high speed and low complex solutions in classification. Fine Tree (FT), Medium Tree (MT) and Coarse Tree (CT) classifiers are implemented in this paper which is trained with multi-order cumulants to achieve optimum classification accuracy. Performance of DTC’s is compared with other classifiers stated in literature to prove their superiority in modulation classification.

Keywords: Modulation Classification, Cognitive Radio, Moments, Cumulants, Binary Trees

References:

  1. A Dobre, A Abdi, Y Bar-Ness, W Su, “Survey of automatic modulation classification techniques: classical approaches and new trends”, IET Communications, vol. 1, no. 2, pp. 137–156, Apr. 2007.
  2. W Wei, JM Mendel, “Maximum-likelihood classification for digital amplitude-phase modulations”, IEEE Transactions on Communications, vol. 48, no. 2, pp. 189–193, 2000.
  3. Choqueuse, S. Azou, K. Yao, L. Collin, and G. Burel, “Blind modulation recognition for MIMO systems”, MTA Rev., vol. 19, no. 2, pp. 183–196, Jun. 2009.
  4. C. Headley, J. D. Reed, and C. R. C. M. da Silva, “Distributed cyclic spectrum feature-based modulation classification”, in Proceedings of IEEE Wireless Communication Network Conference, Las Vegas, NV, pp. 1200–1204, Apr. 2008.
  5. A. Dobre, M. Oner, S. Rajan, and R. Inkol, “Cyclostationarity-based robust algorithms for QAM signal identification”, IEEE Communication Letters, vol.16, no. 1, pp. 12–15, Jan. 2012.
  6. Wei and J. M. Mendel, “Maximum-likelihood classification for digital amplitude-phase modulations,” IEEE Transaction on Communication, vol. 48, no. 2, pp. 189–193, Feb. 2000.
  7. Panagiotou, A. Anastasopoulos, and A. Polydoros, “Likelihood ratio tests for modulation classification,” in Proceedings of IEEE Military Communication Conference., Los Angeles, CA, vol. 2, pp. 670–674, Oct. 2000.
  8. C. Wu, M. Saquib, and Z. Yun, “Novel automatic modulation classification using cumulant features for communications via multipath channels,” IEEE Trans. Wireless Communication., vol. 7, no. 8, pp. 3098–3105, Aug. 2008.
  9. L. Barrera, F. E. Hernandez, “Classification of MPSK Signals through Eighth- Order Statistical Signal Processing”, IEEE Latin America Transactions, vol. 15, no. 9, pp. 1601-1607, Sep. 2017.
  10. Liu and P. L. Shui, “A new cumulant estimator in multipath fading channels for digital modulation classification,” IET Communication, vol. 8, no. 16, pp. 2814–2824, Aug. 2014.
  11. C. Chang and P. K. Shih, “Cumulants-based modulation classification technique in multipath fading channels”, IET Communication, vol. 9, no. 6, pp. 828–835, Apr. 2015.
  12. Wu, S. Zhou, Z. Yin, B. Ma and Z. Yang, “Robust Automatic Modulation Classification Under Varying Noise Conditions,” in IEEE Access, vol. 5, pp. 19733-19741, 2017.
  13. Mohannad Abu-Romoh, Ahmed Aboutaleb, Zouheir Rezki, “Automatic Modulation Classification using Moments and Likelihood Maximization”, IEEE Communication Letters, vol. 22, no. 5, pp. 938-941, May 2018.
  14. Zhenyu Zhang, Zhong Hua, Yingzhe Liu, “Modulation classification in multipath fading channels using sixth-order cumulants and stacked convolutional auto-encoders”, IET Communications, vol. 11, no. 6, pp. 910-915, June 2017.
  15. W. Aslam, Z. Zhu and A. K. Nandi, "Automatic Modulation Classification Using Combination of Genetic Programming and KNN," IEEE Transactions on Wireless Communications, vol. 11, no. 8, pp. 2742-2750, August 2012.
  16. Lubing H, Zan Li, OA Dobre, “Low complexity automatic modulation classification based on order-statistics,” IEEE Transactions on Wireless Communications, vol. 16, no. 1, pp. 400-411, Jan. 2017.
  17. Zhang, E. L. Xu, Z. Feng and P. Zhang, "A Dictionary Learning Based Automatic Modulation Classification Method," in IEEE Access, vol. 6, pp. 5607-5617, 2018.
  18. Loh WY, “Fifty years of classification and regression trees”, International Statistical Review, vol. 82, no. 3, pp. 329–348, June 2014.
  19. Song Y, Lu Y, “Decision tree methods: applications for classification and prediction”, Shanghai Archives of Psychiatry, vol. 27, no. 2, pp. 130-135, Feb. 2015.
  20. Shan, Z. Xin and W. Ying, "Improved modulation classification of MPSK signals based on high order cumulants," 2nd International Conference on Future Computer and Communication, Wuhan, pp. V2-444-V2-448, 2010.

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13.

Authors:

Mohammed Abdul Azeem, Khaleel-ur-Rahman Khan

Paper Title:

A Multi Order key Sharing and Dual Channel Based Secure Routing for WSN

Abstract: Growth in the remote monitoring and automation in maintenance for all fields of industrialization in motivating the sensor researches more and more. The major challenge faced by the practitioners and the researchers are to keep up with the advancements of the data accumulation and analytic demands as the resource capabilities of sensors, especially the wireless sensors, are limited in terms of battery or energy, processing capacity and security. A number of wireless sensor networks collect mission critical and sensitive data for the processing. Also, the feedback systems through the same sensor networks are also important and sensitive. Due to the fragile structure of the network, often it is vulnerable to the attacks. A number of studies have demonstrated the types of the attacks and their effect on the network. The identified attacks are highly versatile in nature, thus leaving a less scope for a single solution to prevent the attacks. Numerous research attempts are presented till date to find the most effective method of securing the wireless sensor networks. Nevertheless, all these solutions are criticised for neglecting one or the other possible threats. It is been observed that, the majority of the attacks happen during the data transmission time and the new node registration time. The transmissions of the data in the network are managed by the routing protocols and the registrations of the new node into the network are managed by node registration algorithms or strategies. Thus, these two are the highly vulnerable situations for any wireless sensor networks life cycle. Hence, this work addresses two unique solutions for these two situations, which is again mutually exclusive. The major outcome of this work is to secure the routing using randomize channels and node registration process using multi order key in order to avoid majority of the attacks on the network. Also, during the transmission or the routing of the data through the network channels, it is often recommended that the data must be encrypted. Nonetheless, the encryption and decryption of the data is a significant load on the limited processing capabilities of the sensor nodes. Thus this highly recommended process is habitually ignored, compromising the threats. Yet another outcome from this work, is to separate the header and the content part of the data packets to reduce the network loads.

Keywords: Secure Routing, Dual Channel, Multi-Order Key, Random Function, Trust Management.

References:

  1. Ozel, K. Tutuncuoglu, J. Yang, S. Ulukus, and A. Yener,``Transmission with energy harvesting nodes in fading wireless channels: Optimal policies,'' IEEE J. Sel. Areas Commun., vol. 29, no. 8, pp. 17321743, Sep. 2011.
  2. Marlon, C. Jose, A. B. Campelo, O. Rafael, V. C. Juan, and J. S. Juan, ``Active low intrusion hybrid monitor for wireless sensor networks,'' Sensors, vol. 15, no. 3, pp. 2392723952, 2015.
  3. Ottman, A. Bhatt, H. Hofmann, and G. Lesieutre, ``Adaptive piezoelectric energy harvesting circuit for wireless, remote power supply,'' IEEE Trans. Power Electron., vol. 17, no. 5, pp. 669676, Sep. 2002.
  4. K. A. Mohammad and S. Gadadhar, ``Enhancing cooperation in MANET using neighborhood compressive sensing model,'' Egyptian Informat. J., vol. 6, no. 1, pp. 115, 2016.
  5. G. Uttam and D. Raja, ``SDRP: Secure and dynamic routing protocol for mobile ad-hoc networks,'' IET Netw., vol. 3, no. 2, pp. 235243, 2014.
  6. K. K. Chin and K. L. A. Yau, ``Trust and reputation scheme for clustering in cognitive radio networks,'' in Proc. Int. Conf. Frontiers Commun.,Netw. Appl. (ICFCNA), Kuala Lumpur, Malaysia, Nov. 2014.
  7. Gao, H. W. Chris, J. J. Duan, and J. R. Chou, ``A novel energy aware distributed clustering algorithm for heterogeneous wireless sensor networks in the mobile environment,'' Sensors, vol. 15, no. 10, pp. 3110831124, 2015.
  8. G. Choi and S. Bahk, ``Cell-throughput analysis of the proportional fair scheduler in the single-cell environment,'' IEEE Trans. Veh. Technol.,vol. 56, no. 2, pp. 766778, Mar. 2007.
  9. B. Sourav and M. K. Pabitra, ``SIR: A secure and intelligent routing protocol for vehicular ad hoc network,'' IET Netw., vol. 4, no. 6, pp. 185194, 2015.
  10. Adel, K. Abdellatif, and E. Mohammed, ``A new trust model to secure routing protocols against DoS attacks in MANETs,'' in Proc. 10th Int. Conf. Intell. Syst. Theories Appl. (SITA), Taipei, Taiwan, Oct. 2015, pp. 16.
  11. M. Chang, T. Po-Chun,W. G. Isaac, C. C. Han, and C. F. Lai, ``Defending against collaborative attacks by malicious nodes in MANETs: A cooperative bait detection approach,'' IEEE Syst. J., vol. 9, no. 6, pp. 6575,Jun. 2015.
  12. G. Fernando, M. C. A. Rossana, T. O. Carina, and J. N. Souza,``EPMOSt: An energy-efcient passive monitoring system for wireles ssensor networks,'' Sensors, vol. 14, no. 3, pp. 1080410828, 2015.
  13. Du and H. H. Chen, ``Security in wireless sensor networks,'' IEEE Wireless Commun., vol. 15, no. 4, pp. 6066, Aug. 2008.
  14. Lin, W. Yu, N. Zhang, X. Yang, H. Zhang, and W. Zhao, ``A survey on Internet of Things: Architecture, enabling technologies, security and privacy, and applications,'' IEEE Internet Things J., 2017.
  15. Kurosawa, H. Nakayama, N. Kato, A. Jamalipour, and Y. Nemoto, ``Detecting blackhole attack on AODV-based mobile ad hoc networks by dynamic learning method,'' Int. J. Netw. Secur., vol. 5, no. 9, pp. 1421, 2007.
  16. Zhu, X. Yang, W. Yu, and X. Fu, ``Network coding vs. Traditional routing in adversarial wireless networks,'' Int. J. Ad Hoc Netw., vol. 20, no. 2, pp. 119131, 2014.
  17. Zhao, X. Yang, W. Yu, and X. Fu, ``A loose virtual clustering based routing for power heterogeneous MANETs,'' IEEE Trans. Veh. Technol., vol. 62, no. 5, pp. 22902302, Sep. 2013.
  18. Yu and J. Lee, ``Efcient energy sensitive routing protocols in mobile ad-hoc networks,'' in Proc. Process. Int. Conf. Wireless Netw., Shanghai,China, Jun. 2002, pp. 39.
  19. Morsi, D. S. Michalopoulos, and R. Schober, ``Multiuser scheduling schemes for simultaneous wireless information and power transfer over fading channels,'' IEEE Trans. Wireless Commun., vol. 14, no. 4, pp. 19501964, Apr. 2015.
  20. Yao, S. Feng, X. Zhou, and Y. Liu, ``Secure routing in multihop wireless ad-hoc networks with decode-and-forward relaying,'' IEEE Trans. Commun., vol. 64, no. 2, pp. 753764, Feb. 2016.
  21. Paramasivan, M. J. V. Prakash, and M. Kaliappan, ``Development of a secure routing protocol using game theory model in mobile ad hoc networks,'' J. Commun. Netw., vol. 17, no. 1, pp. 7583, Feb. 2015.
  22. Krikidis, S. Timotheou, S. Nikolaou, and G. Zheng, ``Simultaneous wireless information and power transfer in modern communication systems,''IEEE Commun. Mag., vol. 52, no. 11, pp. 1642416450, Nov. 2014.
  23. Vosoughi, R. C. Joseph, and A. Marshall, ``Trust-aware consensusinspired distributed cooperative spectrum sensing for cognitive radio adhoc networks,'' IEEE Trans. Cognit. Commun. Netw., vol. 2, no. 3,pp. 2437, Sep. 2016.
  24. Cornejo, S. Viqar, and J. L. Welch, ``Reliable neighbor discovery for mobile ad hoc networks,'' Ad Hoc Netw., vol. 12, no. 6, pp. 259277, 2014.
  25. Sun, Z. Han, and K. J. R. Liu, ``Defense of trust management vulnerabilities in distributed networks,'' IEEE J. Mag., vol. 46, no. 2, pp. 112-119,Feb. 2008.
  26. Anuj Kumar Singh ; Anshika Bhalla ; Pramod Kumar ; Manju Kaushik, Hierarchical routing protocols in WSN: A brief survey, (ICACCA) (Fall), 2017 3rd International Conference on, April 2018.

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14.

Authors:

Mohan Allam, M. Nandhini

Paper Title:

Feature Optimization using Teaching Learning Based Optimization for Breast Disease Diagnosis

Abstract: Disease diagnosis is a significant challenge in the field of medical science because most of the medical datasets contain irrelevant and redundant attributes which are not mandatory to obtain an accurate estimate of the disease diagnosis. In this work, we have used Teaching Learning Based Optimization (TLBO) algorithm for feature Optimization in automatic breast disease diagnosis. We have used a naive Bayes classifier for finding the fitness of individual and Multilayer Perceptron (MLP), J48, random forest, logistic regression algorithms for estimating the effectiveness of the proposed system. The results confirmed that the expected scheme produced higher accuracy on Wisconsin diagnosis breast cancer (WDBC) data set to classify the malignant and benign tumors. In short, the proposed TLBO variant presents an efficient technique to optimize the features for sustaining data-based decision making systems.

Keywords: Feature Optimization, Teaching Learning based Optimization, Breast Cancer.

References:

  1. Shuihua Wang, Ravipudi Venkata Rao, Peng Chen, “Abnormal Breast Detection in Mammogram Images by Feed-forward Neural Network Trained by Jaya Algorithm”, FundamentaInformaticae, vol. 151, no. 1-4, pp. 191-211, 2017.
  2. Sasikala, S.Appavu and S.Geetha, “A Novel Feature Selection Technique for ImprovedSurvivabilityDiagnosis of Breast Cancer“, 2nd International Symposium on Big Data and Cloud Computing (ISBCC’15), pp. 16-23, 2015.
  3. EminaAlicKovic,Abdulhamit Subasi, “Breast cancer diagnosis using GA feature selection and Rotation Forest”,Neural Computing and Applications, vol. 28(4), pp. 753–763, 2017.
  4. Hasmarina Hasan, Nooritawati Md Tahir, “Feature Selection of Breast Cancer Based on Principal Component Analysis”, 6th International Colloquium on Signal Processing & Its Applications (CSPA), IEEE, 2010.
  5. Noel Pérez1, Miguel A. Guevara, Augusto Silva, “Evaluation of Features Selection methods for breast cancer classification”, 15th International Conference on Experimental Mechanics, 2012.
  6. ShokoufehAalaei, Hadi Shahraki, Alireza Rowhanimanesh, and Saeid Eslami, “Feature selection using genetic algorithm for breast cancer diagnosis: experiment on three different datasets”, Iranian Journal of Basic Medical Sciences, vol. 19(5), pp. 476-482, 2016.
  7. Li-Yeh Chuang a, Sheng-Wei Tsai b, Cheng-Hong Yang, “Improved binary particle swarm optimization using catfish effect for feature selection”, Expert Systems with Applications, Vol. 38,pp. 12699–12707, 2011.
  8. Bichen ZhengSang WonYoon, Sarah S.Lam, “Breast cancer diagnosis based on feature extraction using a hybrid of K-means and support vector machine algorithms”, Expert Systems with Applications, Volume 41, Issue 4, pp. 1476-1482, 2014.
  9. Sridevi, A.Murugan, “A Novel Feature Selection Method for Effective Breast Cancer Diagnosis and Prognosis”, International Journal of Computer Applications, vol. 88(11), pp. 0975 – 8887, 2014.
  10. Vartika Agrawal, Satish Chandra, “Feature Selection using Artificial Bee Colony Algorithm for Medical Image Classification”, International Conference on Contemporary Computing (IC3), IEEE, pp. 171-176, 2015.
  11. Mohan Allam, M. Nandhini, “A Study on Optimization Techniques in Feature Selection for Medical Image Analysis”, International Journal on Computer Science and Engineering (IJCSE), vol. 9 (3), pp. 75-82, 2017.
  12. Zhi Chen, Tao Lin, Ningjiu Tang, and Xin Xia, “A Parallel Genetic Algorithm Based Feature Selection and Parameter Optimization for Support Vector Machine”, Volume 2016 (2016), Article ID 2739621.
  13. Saleh Shahbeig, Mohammad SadeghHelfroush, Akbar Rahideh, “A Fuzzy Multi-Objective Hybrid TLBO-PSO Approach to Select the Associated Genes with Breast Cancer”, Signal Processing, vol. 131, pp. 58-65, 2016.
  14. Jung IS, Thapa D, Wang GN, “Neural Network Based Algorithms for Diagnosis and Classification of Breast Cancer Tumor”, Computational Intelligence and Security, Lecture Notes in Computer Science, vol. 380, pp. 107–114, Springer, 2005.
  15. HtetThazin Tike Thein, Khin Mo Tun, “An Approach for Breast Cancer Diagnosis Classification using Neural network”, Advanced Computing: An International Journal (ACIJ), vol. 6, no.1, 2015.
  16. Paul R. Harper, “A review and comparison of classification algorithms for medical decision making Classification”, Elsevier, vol. 71, pp. 315–331, 205.
  17. V.Rao, V.J.Savsani, D.P.Vakharia, “Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems”,Computer-Aided Design, Science Direct, vol. 43(3), pp. 303-315, 2011.
  18. Venkata Rao, “Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems”, Decision Science Letters, vol. 5, pp. 1-30, 2016.
  19. Shikha Agrawal, Shraddha Sharma, Sanjay Silakari, “Teaching Learning Based Optimization Based Improved Iris Recognition System”, Advances in Intelligent Systems and Computing, vol. 366, pp. 735-740, 2015.
  20. GulaveSukdev Madhav, Surendra Vishwakarma,“Improve the Performance of Face Recognition Using Feature Based and Teacher Learning Based Optimization Techniques”, International Journal of Master of Engineering Research and Technology vol. 2, no. 10, 2015.
  21. AbhilashaWakde, Virendra Shrivastava, “The Improved Performance of Face Detection Based on Partial Feature and TLBO”, International Journal of Emerging Technology and Advanced Engineering, vol. 6, no. 9, 2016.
  22. Chereddy Srinivasa Rao, KanadamKarteeka Pavan1, Allam AppaRao, “An Automatic Medical Image Segmentation using Teaching Learning Based Optimization”, Proc. of Int. Conf. on Advances in Computer Science, AETACS, 2013.
  23. Baljit Singh Khehra, Amar Partap Singh Pharwaha, “Image Segmentation using Teaching-Learning based Optimization Algorithm and Fuzzy Entropy”, 15th International Conference on Computational Science and Its Applications, 2015.
  24. Naga Srinivasu, G. Srinivas,and T. Srinivas Rao, “An automated Brain MRI image segmentation using Generic Algorithm and TLBO”, IJCTA, 9(32), pp. 233-241, 2016.
  25. Panda M, Elephant search optimization combined with deep neural network for microarray data analysis. Journal of King Saud University – Computer and Information Sciences (2017), https://doi.org/10.1016/j.jksuci.2017.12.002
  26. Suresh C. Satapathy, Anima Naik, Parvathi K, “Rough set and teaching learning based optimization technique for optimal features selection”, Central European Journal of Computer Science, vol. 3, no. 1, pp. 27-42, 2013.
  27. Kapil Verma, Akash Mittal, Yogendra Kumar Jain, “A Hybrid method of face detection based on Feature Extraction using PIFR and Feature Optimization using TLBO”, Journal of Engineering Research and Applications, vol. 6, Issue 1, pp.145-150, 2016.
  28. Malkhede Seema Krishna, Surendra Vishwakarma,“ Improve the Performance of Fingerprint Recognition Using Feature Selection and Teacher Learning Based Optimization (TLBO)”, International Journal of Master of Engineering Research and Technology, vol. 2, no.10, 2015.
  29. UCI Machine Learning Repository: Breast Cancer Wisconsin (Diagnostic) Data Set (2012) Retrieved 15 Mar 2012 http://archive.ics.uci.edu/ml/datasets/Breast+ Cancer+Wisconsin+(Diagnostic)
  30. Chee Kau Lim, Chee Seng Chan, “A weighted inference engine based on interval-valued fuzzy relationaltheory”, Expert Systemswith Applications, vol. 42, pp. 3410-3419, 2015.
  31. Mantas C. J, Abellan. J, “Credal-C4.5: Decision tree based on imprecise probabilities to classify noisy data”, ExpertSystems with Applications, vol. 41, no. 10, pp. 4625–4637, 2014.
  32. Pacheco J, Alfaro E, Casado S, Gamez M, & Garcia N,“A GRASP method for building classification trees, Expert Systems with Applications”, 39(3),3241–3248, 2012.
  33. Michel Ballings,Dirk Van den Poel, “Kernel Factory: An ensemble of kernel machines”, Expert Systems with Applications, vol. 40,pp. 2904–2913, 2013.
  34. Ying Huang, Kechadi T, “An effective hybrid learning system for telecommunication churn prediction”, Expert Systems with Applications, 40(14), 5635–5647, 2013.
  35. David Koloseni,JouniLampinen, PasiLuukka , “Differential evolution based nearest prototype classifier with optimized distance measures for the features in the data sets”, Expert Systems with Applications, vol. 40,pp.4075–4082, 2013.
  36. Astudillo, B. John Oommen, “On achieving semi-supervised pattern recognition by utilizing tree-based SOMs”, Pattern Recognition, Vol (46), pg. 293-304, 2013.
  37. SinaTabakhi, Parham Moradi, “Relevance-redundancy feature selection based on ant colony optimization”, Pattern Recognition, Volume 48, Issue 9, Pages 2798-2811, 2015.
  38. José A.Sáez, JoaquínDerrac , “Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers”, Pattern Recognition, Volume 47, Issue 12, pp. 3941-3948, 2014.
  39. V.Rao, "Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems", International Journal of Industrial Engineering Computations, vol. 7, no. 1, pp. 19-34, 2016.
  40. V.Rao, “Teaching Learning Based Optimization Algorithm And Its Engineering Applications”, Springer International Publishing, 2016
  41. Danasingh Asir Antony Gnana Singh, Subramanian Appavu Alias Balamurugan, Epiphany Jebamalar Leavline. An Unsupervised Feature Selection Algorithm with Feature Ranking for Maximizing Performance of the Classifiers[J]. International Journal of Automation and Computing, vol. 12, no. 5, pp. 511-517, 2015

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15.

Authors:

Nita Kakhandaki, S. B. Kulkarni

Paper Title:

A Novel Framework for Detection and Classification of Brain Hemorrhage

Abstract: The proposed work focuses on detecting the correct location and type of the hemorrhage in MR Brain image. The Gradient Recalled Echo MR Images are considered as the input image. Then a region and structure specific Multi level Set evolution algorithm is implemented to segment the hemorrhagic region. An enhanced Local Tetra pattern based feature extraction algorithm is used to extract sharpened tetra features and the features are optimized by applying an enhanced Grey Wolf Optimization algorithm. Finally, a Relevance Vector Machine based Classifier is designed to classify the types of the hemorrhages. The proposed framework is compared with the existing techniques on the scale of accuracy, sensitivity, specificity, precision, Jaccard, Dice and kappa coefficient and proved to be outperforming.

Keywords: Brain Hemorrhage, Multi-Level Set algorithm, Local Tetra Pattern, Grey Wolf Optimizer, Relevance Vector Machine.

References:

  1. H. Suryawanshi and K. Jadhao, "Smart Brain Hemorrhage Diagnosis Using Artificial Neural Networks," International Journal of Scientific & Technology Research, vol. 4, pp. 267-271, 2015.
  2. Davis and S. Devane, "Diagnosis of Brain Hemorrhage Using Artificial Neural Network," 2017.
  3. Tsai, R. Lasky, S. John, P. Evans, and K. Kennedy, "Predictors of neurodevelopmental outcomes in preterm infants with intraparenchymal hemorrhage," Journal of Perinatology, vol. 34, p. 399, 2014.
  4. Mahmoudzadeh, G. Dehaene-Lambertz, G. Kongolo, M. Fournier, S. Goudjil, and F. Wallois, "Consequence of intraventricular hemorrhage on neurovascular coupling evoked by speech syllables in preterm neonates," Developmental cognitive neuroscience, 2018.
  5. D. Phong, H. N. Duong, H. T. Nguyen, N. T. Trong, V. H. Nguyen, T. Van Hoa, et al., "Brain Hemorrhage Diagnosis by Using Deep Learning," in Proceedings of the 2017 International Conference on Machine Learning and Soft Computing, 2017, pp. 34-39.
  6. H. Ali, S. I. Abdulsalam, and I. S. Nema, "Detection and Segmentation of Hemorrhage Stroke using Textural Analysis on Brain CT Images," International Journal of Soft Computing and Engineering (IJSCE), ISSN, pp. 2231-2307, 2015.
  7. Kleindorfer, J. Khoury, K. Alwell, C. J. Moomaw, D. Woo, M. L. Flaherty, et al., "The impact of Magnetic Resonance Imaging (MRI) on ischemic stroke detection and incidence: minimal impact within a population-based study," BMC neurology, vol. 15, p. 175, 2015.
  8. Lee, H. Bae, U. Yun, I. Hwang, and S. M. Kim, "Atypical Hemorrhagic Brain Metastases Mimicking Cerebral Microbleeds," Journal of Neurocritical Care, vol. 10, pp. 129-131, 2017.
  9. Roy, S. Nag, S. K. Bandyopadhyay, D. Bhattacharyya, and T.-H. Kim, "Automated brain hemorrhage lesion segmentation and classification from MR image using an innovative composite method," Journal of Theoretical and Applied Information Technology, vol. 78, p. 34, 2015.
  10. V. Kumar and V. J. R. Krishniah, "An automated framework for stroke and hemorrhage detection using decision tree classifier," in Communication and Electronics Systems (ICCES), International Conference on, 2016, pp. 1-6.
  11. Dou, H. Chen, L. Yu, L. Zhao, J. Qin, D. Wang, et al., "Automatic detection of cerebral microbleeds from MR images via 3D convolutional neural networks," IEEE transactions on medical imaging, vol. 35, pp. 1182-1195, 2016.
  12. -C. Phan, V.-Q. Vo, and T.-C. Phan, "Automatic Detection and Classification of Brain Hemorrhages," in Asian Conference on Intelligent Information and Database Systems, 2018, pp. 417-427.
  13. Roy, P. Ghosh, and S. K. Bandyopadhyay, "Contour Extraction and Segmentation of Cerebral Hemorrhage from MRI of Brain by Gamma Transformation Approach," in Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014, 2015, pp. 383-394.
  14. Shah and N. Chauhan, "Classification of brain MRI images using computational intelligent techniques," International journal of computer applications, vol. 124, 2015.
  15. Wang, H. Xu, S. N. Ahmed, and M. Mandai, "Computer aided detection of cavernous malformation in T2-weighted brain MR images," in Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT), 2016 IEEE, 2016, pp. 101-104.
  16. Ferdian, A. Boers, L. Beenen, B. Cornelissen, I. Jansen, K. Treurniet, et al., "Automated Ventricular System Segmentation in CT Images of Deformed Brains Due to Ischemic and Subarachnoid Hemorrhagic Stroke," in Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment, ed: Springer, 2017, pp. 149-157.
  17. Qiu, J. Yuan, M. Rajchl, J. Kishimoto, Y. Chen, S. de Ribaupierre, et al., "3D MR ventricle segmentation in pre-term infants with post-hemorrhagic ventricle dilatation (PHVD) using multi-phase geodesic level-sets," NeuroImage, vol. 118, pp. 13-25, 2015.
  18. Snehkunj, A. N. Jani, and N. N. Jani, "Brain MRI/CT Images Feature Extraction to Enhance Abnormalities Quantification," Indian Journal of Science and Technology, vol. 11, 2018.
  19. Yang, Y. Zhang, J. Yang, G. Ji, Z. Dong, S. Wang, et al., "Automated classification of brain images using wavelet-energy and biogeography-based optimization," Multimedia Tools and Applications, vol. 75, pp. 15601-15617, 2016.
  20. Zhang, S. Wang, Z. Dong, P. Phillip, G. Ji, and J. Yang, "Pathological brain detection in magnetic resonance imaging scanning by wavelet entropy and hybridization of biogeography-based optimization and particle swarm optimization," Progress In Electromagnetics Research, vol. 152, pp. 41-58, 2015.
  21. Roy, D. Bhattacharyya, S. K. Bandyopadhyay, and T.-H. Kim, "An Iterative Implementation of Level Set for Precise Segmentation of Brain Tissues and Abnormality Detection from MR Images," IETE Journal of Research, vol. 63, pp. 769-783, 2017.
  22. R. Nayak, R. Dash, and B. Majhi, "Classification of brain MR images using discrete wavelet transform and random forests," in Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), 2015 Fifth National Conference on, 2015, pp. 1-4.

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16.

Authors:

P. Nagabushanam, S. Satheesh Kumar, J. Sunitha Kumar, S. Thomas George

Paper Title:

Brain Mri Image Segmentation using Improved Sobel Method

Abstract: Health care applications need correct segmentation on medical images which helps for correct diagnosis. Good quality segmentation can be done only by an efficient method. In this paper we have studied and evaluated three different segmentation techniques. We have presented an improved edge segmentation method for brain MRI images. The improved sobel algorithm makes use of sobel method with closed contour algorithm which will combinely help in maintaining uniformity in the regions. Image dependent method of thresholding helps in closed contour to fix up clear boundaries of different regions in an image. The algorithm is implemented in Matlab and performance is measured subjectively as well as objectively. For comparative analysis, we have used entrophy, correlation and energy of the three segmentations which show improved sobel method is better compared to watershed segmentation and sobel segmentation.

Keywords: Sobel segmentation, Watershed Segmentation, Improved Sobel Segmentation.

References:

  1. Asra Aslam, Ekram Khan, M.M. Sufyan Beg, “Improved Edge Detection Algorithm for Brain Tumor Segmentation”, Procedia Computer Science 58, 430 – 437, doi: 10.1016 /j.procs.2015.08.057,  Elsevier, 
  2. Siti Noraini Sulaiman, Noreliani Awang Non, Iza Sazanita Isa, Norhazimi Hamzah, “Segmentation of Brain MRI Image Based on Clustering Algorithm”, Energy, Environment, Biology and Biomedicine, ISBN: 978-1-61804-232-3.
  3. S. Cover, W.G. Herrera, M.P. Bento, S. Appenzeller, L. Rittner, “Computational methods for corpus callosum segmentation on MRI: A systematic literature review” Computer Methods and Programs in Biomedicine, https://doi.org/10.1016/j.cmpb.2017.10.025 0169-2607, Elsevier, 2017.
  4. Mamta K. Date, Mr. S.P. Akarte, “Brain Image Segmentation Algorithm using K-Means Clustering” International Journal Of Computer Science And Applications Vol. 6, No.2, ISSN: 0974-1011, Apr 2013.
  5. Yuehua Liu, Feilong Cao , Jianwei Zhao, and Jianjun Chu’, ‘Segmentation of White Blood Cells Image Using Adaptive Location and Iteration”, IEEE Journal of Biomedical and Health Informatics, 2168-2194, Vol. 21, No. 6, November, 2017.
  6. Elizˆangela de S. Rebouc¸as, Alan M. Braga, R´oger Moura Sarmento, Regis C. P. Marques and Pedro P. Rebouc¸as Filho, “Level set based on brain radiological densities for stroke segmentation in CT images” 2017 IEEE 30th International Symposium on Computer-Based Medical Systems, 1063-7125/17, DOI 10.1109/CBMS.2017.172, 391, 2017 IEEE 30th International Symposium on Computer-Based Medical Systems, IEEE, 2017.
  7. Xintao Dinga, Liping Suna, Yonglong Luo, “Shell histogram equalization of color images”, Optik 125, 3350–3354, http://dx.doi.org/10.1016/j.ijleo.2013.12.071 0030-4026, Elsevier, 2014.
  8. Euijoon Ahn , Jinman Kim , Lei Bi, Ashnil Kumar , Changyang Li, Michael Fulham, and David Dagan Feng,” Saliency-Based Lesion Segmentation Via Background Detection in Dermoscopic Images”, IEEE Journal of Biomedical and Health Informatics, 2168-2194, Vol. 21, No. 6, IEEE, November 2017.
  9. Xiaoxia Zhang, Degang Chen, E.C.C. Tsang “Generalized dominance rough set models for the dominance intuitionistic fuzzy information systems” • Information Sciences, Volume 378, Pages 1-25, February 2017.
  10. Anupama Namburu , Srinivas Kumar Samayamantula, Srinivasa Reddy Edara, “Generalised rough intuitionistic fuzzy cmeans for magnetic resonance brain image segmentation” IET Image Process., 2017, Vol. 11 Iss. 9, pp. 777-785, The Institution of Engineering and Technology 2017.
  11. Mohamed Abd El Aziz, Ahmed A. Ewees, Aboul Ella Hassanien, “Whale Optimization Algorithm and Moth-Flame Optimization for multilevel thresholding image segmentation” 242–256, Expert Systems With Applications 83, 2017.
  12. XiaoliZhanga, HaiyingZhao, XiongfeiLia, YuncongFeng, HongpengLi, “A multi-scale 3D Otsu thresholding algorithm for medical image segmentation” http://dx.doi.org/10.1016/j.dsp.2016.08.003, 1051-2004, Digital Signal Processing , Elsevier, 2016.
  13. S.R. Naidu, P. Rajesh Kumar, K. Chiranjeevi, “Shannon and Fuzzy entropy based evolutionary image thresholding for image segmentation” Alexandria Engineering Journal, http://dx.doi.org/10.1016/j.aej.2017.05.024, 1110-0168, Elsevier, 2017.
  14. Xiaoxia Zhang, Degang Chen, E.C.C. Tsang, “Generalized dominance rough set models for the dominance intuitionistic fuzzy information systems” Information Sciences 378, 1–25, 0020-0255, Elsevier, 2016.
  15. Jennifer Ranjani, S.J. Thiruvengadam, “Fast threshold selection algorithm for segmentation of synthetic aperture radar images” IET Radar Sonar Navig., 2012, Vol. 6, Iss. 8, pp. 788–795, The Institution of Engineering and Technology 2012.
  16. Garg, S. Urooj, and R. Vijay, “Detection of cervical cancer by using thresholding & watershed segmentation,” in Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on. IEEE, 2015, pp. 555–559.
  17. Masoumi, A. Behrad, M. A. Pourmina, and A. Roosta, “Automatic liver segmentation in MRI images using an iterative watershed algorithm and artificial neural network,”Biomedical Signal Processing and Control, vol. 7, no. 5, pp. 429–437, 2012.
  18. Beare, J. Chen, C. L. Adamson, T. Silk, D. K. Thompson, J. Y. M. Yang, V. A. Anderson, M. L. Seal, and A. G. Wood, “Brain extraction using the watershed transform from markers,” Frontiers in Neuroinformatics, vol. 7, p. 32, 2013.
  19. Sridhar, K. Reddy, and A. Prasad, “Automated medical image segmentation for detection of abnormal masses using watershed transform and markov random fields,” International Journal on Signal and Image Processing, vol. 4, no. 3, p. 56, 2013.
  20. M. Sarmento, R. F. Pereira, P. P. de Arajo Coimbra, A. C. N. de Macˆedo, and P. P. Rebouc¸as Filho, “Segmentac¸ ˜ao de acidente vascular cerebral em imagens de tomografia computadorizada: Um estudo comparativo,” in VII Simpsio de Instrumentao e Imagens Mdicas (SIIM). UNICAMP: SIIM, Outubro 2015.
  21. Benson, V. Lajish, and K. Rajamani, “Brain tumor extraction from MRI brain images using marker based watershed algorithm,” in Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on, Aug 2015, pp. 318–323.
  22. Yung-Chieh Lin, Yu-Pao Tsai, Yi-Ping Hung, and Zen-Chung Shih, “Comparison Between Immersion-Based and Toboggan-Based Watershed Image Segmentation” IEEE Transactions on Image Processing, Vol. 15, No. 3, March 2006.
  23. Shaheera Rashwan, Amany Sarhan, Muhamed Talaat Faheem, Bayumy A. Youssef “Fuzzy watershed segmentation algorithm: an enhanced algorithm for 2D gel electrophoresis image segmentation” Int. J. Data Mining and Bioinformatics, Vol. 12, No. 3, 2015.
  24. Hassan Masoumia, Alireza Behradb, Mohammad Ali Pourminaa, Alireza Roosta “Automatic liver segmentation in MRI images using an iterative watershed algorithm and artificial neural network” Biomedical Signal Processing and Control 7, 429– 437, 2012.
  25. Weng Kin Laia*, Imran M. Khanb, Geong Sen Poh, “Weighted Entropy-based Measure for Image Segmentation” International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012), Elsevier, 2012.
  26. Pamela Juneja, Ramgopal Kashyap, “Energy based Methods for Medical Image Segmentation” International Journal of Computer Applications (0975 – 8887) Volume 146,No.6,July,2016

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17.

Authors:

S. Radha, D. S. Shylu, P. Nagabushanam, J. Sunitha Kumari

Paper Title:

Design of RF LNA with Resistive Feedback and Gain Peaking for Multi-Standard Application

Abstract: Low Noise Amplifier (LNA) for 2.4 GHz is the leading block in RF to enhance the performance of the receiver. LNA used in video applications, satellite communications at RF front end of the receiver. Linearity is one of the key requirements for designing LNA, because LNA must exhibit linear operation in the presence of large interfering signals. Some of the existing techniques which improves linearity are Noise cancellation, Derivative superposition, Modified DS technique, body biasing, optimum gate biasing, MGTR, feed forward. The existing challenge in designing a LNA circuit is to achieve high gain, low noise figure and with low power usage without affecting its linearity. This paper analyses variety of linearization techniques that are used for CMOS Low Noise Amplifier (LNA). The LNA methods include (1) single ended LNA (2) PD-LNA (3) capacitive feedback (4) Current-Reuse. We also proposed a Resistive feedback & Gain Peaking technique for LNA using gated inductor at transistor to obtain high gain with low power consumption. Using variety of linearization techniques, the LNA circuits had been designed at 90nm CMOS technology in cadence virtuoso. The resistive feedback and gain peaking LNA gives a gain of 25.4dB with low power consumption of 3.4mv which is better compared to other existing linearization techniques.

Keywords: low noise amplifier (LNA), noise figure (NF), single ended LNA, resistive feedback, capacitive feedback, post distortion linearization technique (PD-LNA), current reuse technique.

References:

  1. Chun-Hsiang Chang, Marvin Onabajo, “A 0.77Mw 2.4GHz RF Front-End with -4.5dBm In-Band IIP3 Through Inherent Filtering”, IEEE Microwave and wireless communication, VOL.26, NO.5,PP.352-354,May 2016.
  2. BehzadRazavi, “A 2.4-GHz CMOS Receiver for IEEE 802.11 Wireless LAN’s”, IEEE Journal of solid state circuits,VOL. 34, NO. 10,PP.1382-1385,Oct. 1999.
  3. Wheeler, “Commercial applications of wireless sensor networks using Zig Bee”, IEEE Communication magazine, PP 70-77,April 2007.
  4. Razavi, “CMOS technology characterization for analogm and RFdesign”, IEEE J. Solid-State Circuits, VOL. 34, NO.3, PP. 268–276, Mar. 1999.
  5. Bonkee Kim, Jin-Su Ko,” A New Linearization Technique for MOSFET RF Amplifier Using Multiple Gated Transistors,” IEEE Microwave and Guided Wave Letters, Vol. 10, no. 9, pp. 371-373,Sep. 2000.
  6. Heng Zhang, Edgar Sánchez-Sinencio, “Linearization Techniques for CMOS Low Noise Amplifiers: A Tutorial” IEEE Transactions on circuits and systems,VOL. 58, NO. 1,PP.22-36, Jan. 2011.
  7. Prameela and Asha Elizabeth Daniel,” Design of Low Noise Amplifier for IEEE Standard 802.11b Using Cascode and Modified Cascode Techniques,” Procedia Technology, Vol. 25, 2016, PP.443-449.
  8. H. Misran and ,M.A. MeorSaid,” Design of Low Noise Amplifier using Feedback and Balanced Technique for WLAN Application,” Procedia Engineering, Volume 53, 2013, PP. 323-331.
  9. Udaya shankar and M. Davidson Kamala dhas,” Design and Performance Measure of 5.4 GHZ CMOS Low Noise Amplifier Using Current Reuse Technique in 0.18μm Technology,” Procedia Computer Science,Vol.  47, 2015, Pages 135-143.
  10. Mohammed K. Salama, Ahmed M. Soliman,” 0.7 V, 5.745 GHz CMOS RF low noise amplifier for IEEE 802.11a wireless LAN,” Int. J. Electron. Commun. (AEU), 1434-8411, Vol. 64, PP. 29 – 35, Elsevier, 2010.
  11. Bastos, L.B. Oliveira,” Noise canceling LNA with gain enhancement by using double feedback,” Integration, the VLSI Journal,Vol. 52, January 2016, PP. 309–315.
  12. Jun Chen, Benqing Guo,” An inductorless wideband common-gate LNA with dual capacitor cross-coupled feedback and negative impedance techniques,“Integration, the VLSI Journal,Vol. 56, January 2017, PP. 53–60.
  13. Atiyeh Karimlou, Roya Jafarnejad,” An Inductor-less Sub-mW Low Noise Amplifier for Wireless Sensor Network Applications,” Integration, the VLSI Journal,Vol. 52, January 2016, PP. 316–322.
  14. San-Fu Wang, Yuh-Shyan Hwang,” A new CMOS wideband low noise amplifier with gain control,” Integration, the VLSI Journal,Vol. 44, Issue 2, March 2011, PP. 136–143.
  15. Li and K.K. O, “Packaged single-ended CMOS low noise amplifier with 2.3 dB noise figure and 64dBm IIP2,”Electronics Lett., vol. 40, no. 10, 2004, pp. 712–713,.
  16. Benqing Guo and Xiaolei Li,”A 1.6–9.7 GHz CMOS LNA Linearised by Post Distortion Technique,”IEEE Microwave and wireless components letters,vol.23, no. 11,Nov. 2013, pp.608-610.
  17. Kim, V. Aparin, K. Barnett, and C. Persico, “A cellular-band CDMA CMOS LNA linearized using active post-distortion,”IEEE J. Solid-State Circuits, vol. 41, no. 7,Jul. 2006, pp. 1530–1534.
  18. Abolfazl Zokaei, Amir Amirabadi,” A 0.13μm  dual-band common-gate LNA using active post distortion for mobile Wimax,” Microelectronics Journal 45 (2014) 921–929.
  19. -T. Chien and Y.-J.Chan, “Bandwidth enhancement of transimpedance amplifier by a capacitive-peaking design,” IEEE J.Solid-State Circuits, vol. 34, no. 8,Aug. 1999, pp. 1167–1170.
  20. Lin, H. Chen, T. Wang, Y. Lin and S. Lu, “3-10GHz Ultra-Wideband Low-Noise Amplifier Utilising Miller Effect and Inductive Shunt-Shunt Feedback Technique,” IEEE Transactions on Microwave Theory and Techniques, Vol. 55, No. 9, Sep. 2007,pp. 1832–1843.
  21. Fadi Riad Shahroury , Chung-Yu Wu,” A 1-V RF-CMOS LNA design utilizing the technique of capacitive feedback matching network,” Integration, the VLSI Journal, Vol. 42, Issue 1, Pages 83–88, Jan.
  22. Muhammad Khurram and S. M. RezaulHasan,“A 3–5 GHz Current-Reuse gmBoosted CG LNA for Ultrawideband in 130 nm CMOS,”IEEE Techniques, vol. 52, no. 5, May 2004, pp. 1433-1442.
  23. Selvakumar, M. Zargham, and A. Liscidini,“Sub-mW current reuse receiver front-end for wireless sensor network applications,” IEEEJ. Solid-State Circuits, vol. 50, no. 12, Dec. 2015, pp. 2965–2974.
  24. Hyouk-Kyu Cha, M. KumarasamyRaja,”A CMOS MedRadio Receiver RF Front-End With a Complementary Current-Reuse LNA,”IEEE Transactions on Microwave Theory and Techniques, vol. 59, no. 7, July 2011,pp.1846-1854.
  25. Udayashankar ,M.Davidson Kamala dhas,” Design and Performance Measure of 5.4 GHZ CMOS Low Noise Amplifier using Current Reuse Technique in 0.18μm Technology,” Procedia Computer Science,vol.47,2015,pp.135 – 143.
  26. Chang, J. Chen, L. A. Rigge, and J. Lin, “ESD-protected sideband CMOS LNAs using modified resistive feedback techniques with chip-on-board packaging,”IEEE Trans. Microw. Theory Tech, vol. 56,no. 5, Aug. 2008, pp. 1817–1826.
  27. K. Shaeffer and T. H. Lee, “A 1.5-V, 1.5-GHz CMOS low noise amplifier,” IEEE J. Solid-State Circuits, vol. 32, no. 5, May 1997, pp. 745–759.
  28. -K. Chen, D.-C.Chang, Y.-Z.Juang, and S.-S. Lu, “A compact wideband CMOS low-noise amplifier using shunt resistive-feedback and series inductive-peaking techniques ,”IEEE Microw. Wireless Compon.Lett.,vol. 17, no. 8,Aug. 2007, pp. 616–618.
  29. Amir Nakhlestani, Ahmad Hakimi,” A novel configuration for UWB LNA suitable for low-power and low-voltage applications,” Microelectronics Journal, Vol. 43, Issue 7 , July 2012, pp. 444–451.
  30. Tae Hwan Jin, Hong Gul Han, Tae Wook Kim, “A 0.7‐dB NF, +8.2‐dBm IIP3 CMOS low noise amplifier using frequency selective feedback”, International Journal of Circuit Theory and Applications, Volume 44, Issue 1, January 2015.
  31. Zahra Haddad Derafshi, Javad Frounchi, “Low‐noise low‐power front‐end logarithmic amplifier for neural recording system” International Journal of Circuit Theory and Applications, Volume 42, Issue 5, April 2014.
  32. Gino Giusi ,Gianluca Cannatà, Graziella Scandurra, Carmine Ciofi, “Ultra‐low‐noise large‐bandwidth transimpedance amplifier” International Journal of Circuit Theory and Applications, Volume 43, Issue 10, August 2014.
  33. Jhen-Ji Wang, Duan-Yu Chen, San-Fu Wang, Rong-Shan Wei, “A multi-band low noise amplifier with wide-band interferencerejection improvement”, International Journal of Electronics and Communications (AEÜ), 1434-8411, Elsevier, ,2015.
  34. Qiuzhen Wan, Qingdi Wang, Zhiwei Zheng, “Design and analysis of a 3.1–10.6 GHz UWB low noise amplifier withforward body bias technique”, International Journal of Electronics and Communications (AEÜ), 1434-8411, Elsevier, 2014.
  35. I.A. Galala,∗, R. Pokharelb, H. Kanayaa, K. Yoshida, ” High linearity technique for ultra-wideband low noise amplifier in 0.18 m CMOS technology”, International Journal of Electronics and Communications (AEÜ), 1434-8411, Elsevier, 2012
  36. Chun-Yi Lin , Ching-Piao Liang, Jenn-Hwan Tarng, Shyh-Jong Chung,” Compact composite noise-reduction LNA for UWB WPAN and WBAN applications”, The Institution of Engineering and Technology 2017, ISSN 1751-8725, Vol. 12 Iss. 6, pp. 903-908, IET Microwaves, Antennas & Propagation, 2018.
  37. Ramya Vijay, Thipparaju Rama Rao, “Design of penta-band antenna with integrated LNA circuit for vehicular communications”, The Institution of Engineering and Technology 2017, ISSN 1751-858X, Vol. 12 Iss. 3, pp. 221-225, IET Circuits, Devices & Systems, 2018.
  38. Muyeon Lee, Ickjin Kwon, “3–10 GHz noise-cancelling CMOS LNA using gm-boosting technique”, The Institution of Engineering and Technology 2017, ISSN 1751-858X, Vol. 12 Iss. 1, pp. 12-16, IET Circuits Devices Syst., 2018.
  39. Eskandari, A. Ebrahimi, J. Sobhi, “A wideband noise cancelling balun LNA employing current reuse technique”, Microelectronics Journal, 0026-2692, Elsevier, 2018.
  40. AliSahafi, JafarSobhi, ZiaddinDaeiKoozehkanani, “Linearity improvement of gm-boosted common gate LNA: Analysis to design”, Microelectronics Journal, 0026-2692, Elsevier, 2016.
  41. Guoxiao Cheng, Zhiqun Li, Lei Luo, Zengqi Wang, Xiaodong He, Boyong He, “A low power and high gain current-reused LNA using cascaded L-type input matching network”, Microelectronics Journal, 0026-2692, Elsevier, 2018.

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18.

Authors:

S. Veerendra Prasad, B. V. R. Ravi Kumar, V. V. Subba Rao

Paper Title:

Optimisation of Process Parameters in Hard Turning of Aisi 5150 Steel by Anova

Abstract: In the present study, an attempt has been made to hard turn AISI 5150 steel using uncoated TiC inserts. Round bar stock of AISI 5150 steel was hardened to 48 HRC by oil quenching. Three different process parameters Speed, feed and depth cut were chosen at three different levels. The parameter combinations were chosen according to L9 orthogonal array to limit the number of experiments to nine instead of twenty seven. ANOVA is performed on the results of surface finish obtained for 9 experiments parameter combination chosen. The percentage contribution of the factor feed towards the response i.e., surface roughness is 51.19%, followed by depth of cut 24.07% and finally by speed 15.01%.The main effect plots for means were generated between process parameters and surface roughness an optimum process parameters were chosen and confirmation experiment was performed on the selected optimum process parameters.

Keywords: AISI 5150 steel, ANOVA, Hard turning, Surface roughness.

References:

  1. With Grzesik, Krzysztof Zak, Piotr Kiszka, “Comparison of surface textures generated in hard turning and grinding operations” 2nd CIRP Coference on Surface Integrrity (CSI), Procedia CIRP 13 (2014), 84 – 89.
  2. Uhlmann, H. Riemer, D. Schroter, S. Henze, F. Sammler, F. Barthelma, H. Frank, “Investigation of wear resistance of coated PcBN turning tools for hard turning,” International Journal of Refractory Metals and Hard Materials, Volume 72, April 2018, Pages 270 – 275.
  3. Pay Jun Liew, Ainusyafiqah Shaaroni, Nor Azwadi Che Sidik, Jiwang Yan, “An overview of current status of cutting fluids and cooling techniques of turning hard steel,” International Journal of Heat and Mass Transfer, 114 (2017), Pages 380 – 394.
  4. Mozammel Mia, Prithbey R.Dey, Mohammad S. Hossain, Md T. Arafat, Md Asaduzzaman, Md Shoriat Ullah, S. M. Tareq Zobaer, “Taguchi S/N based optimization of machining parameters for surface roughness, tool wear and material removal rate in hard turning under MQL cutting condition”, Measurement, Volume 122 July 2018, Pages 380 – 391.
  5. Ilhan Asilturk, Harun Akkus, “Determining the effect of cutting parameters on the surface roughness in hard turning using the Taguchi method”, Measurement, Volume 44, July 2011, Pages 1697 – 1704.
  6. Dipti Kanta Das, Ashok Kumar Sahoo, Ratnakar Das, B. C. Routara, “Investigations on hard turning using coated carbide insert: Grey based Taguchi and regression methodology”, Procedia Materials Science 6 (2014), Pages 1351 – 1358.
  7. Phillip J. Ross, "Taguchi Techniques for quality Engineering", Mc Graw Hill Education, 2017, Pages 329.

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19.

Authors:

S. Praveen Kumar, Y Srinivas, M. Vamsi Krishna

Paper Title:

A Data Leakage Identification System Based on Truncated Skew Symetric Gaussian Mixture Model

Abstract: Data transfer from source to destination has become more essential as the organizations working under a frame need to exchange the data for processing the information and solving the necessary tasks. This concept of data transfer has become a most tricky task with the advent of hackers, intruders and other guilt agents who try to steal the sensitive data for unethical means. The present article addresses the issue of identifying such data leakages and also provides a platform for data preventing from such issues.

Keywords: Truncated skew Gaussian Mixture, Hackers, Intruders, Guilt agent, Data Leakage.

References:

  1. http://www.istf.jucc.edu.hk/newsletter/IT_03/IT3_Cloud_Computing.pdf
  2. http://www.buyya.com/papers/AnekaMagazineArticle1.pdf
  3. https://cloudsecurityalliance.org/topthreats/csathreat s.v1.0.pdf
  4. http://www.isaca.org/Groups/ProfessionalEnglish/security-trend/GroupDocuments/DLP-WP14Sept2010pdf
  5. http://www.istf.jucc.edu.hk/newsletter/General_01/Gen2_Data_leakage.pdf
  6. Philip K. Chan, Matthew V. Mahoney, Muhammad H.Arshad,” Learning Rules and Clusters for Anomaly Detection in Network Traffic”, Managing Cyber Threats Massive Computing Volume 5, 2005, pp 81-99
  7. Forrest, S. Hofmeyr, and A. Somayaji. Computer immunology. Comm. ACM, 4(10):88-96, 1997. IJCA International Journal of Computer Applications (0975 – 8887) .Volume 110 – No. 6, January 2015
  8. Varun Chandola, Arindam Banerjee, and Vipin Kumar, Outlier Detection – A Survey, Technical Report TR0717, University of Minnesota
  9. Xuan-Hui Wang; Zheng Chen; Hongjun Lu; Wei-Ying Ma, “CBC: Clustering Based Text Classification Requiring Minimal Labeled Data”, Proceedings of the Third IEEE International Conference on Data Mining, ICDM '03.
  10. Kyriakopoulou, A., Kalamboukis, and T.: Using clustering to enhance text classification. In: 30th annual international ACM SIGIR conference on Research and development in information retrieval (2007)
  11. Raskutti, B., Ferr, H., Kowalczyk, A.: Using unlabeled data for text classification through addition of cluster parameters. In: 9th International Conference on Machine Learning (2002)
  12. Zeng, H. J., Wang, X.H., Chen, Z., Lu, H., and Ma, W. Y.: CBC: Clustering based text classification requiring minimal labeled data. In: Third IEEE International Conference on Data Mining (2003)
  13. Hassan H. Malik,John R. Kender, “Classification by Pattern-Based Hierarchical Clustering”, ECML/PKDD08 Workshop 15 September 2008, Antwerp, Belgium
  14. Yoshida, T.; Xijin Tang, “Text Classification Using Semi supervised Clustering”, International Conference on Business Intelligence and Financial Engineering, 2009.
  15. Bekkerman, R. El-Yaniv, and Y.Winter,” Distributional word clusters vs. words for text categorization. Journal of Machine Learning Research”, 3:1183-1208, 2003.

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20.

Authors:

V. Pradeep Kumar, M. Gopichand, N. Srinivasu

Paper Title:

On the Viability of Adaptive Paris Metro Pricing in Agent Based Model for Federated Clouds

Abstract: Federated Clouds provides efficient resource pricing using static and dynamic methods. Most of these pricing models are analyzed based on cloud service provider perspective to maximize their revenue. Need of pricing model to prioritize the users request for allocating resources according to their demands and provide maximum utility within optimal price. This paper analyzes the viability of Adaptive Paris metro pricing (APMP) in agent based model for federated clouds to achieve equilibrium between provider and users of cloud in gaining maximum revenue with optimal price. Further APMP achieving strategy proof is analyzed with simulation support for federated clouds.

Keywords: Federated Clouds, Cloud resource pricing, Adaptive Paris Metro Pricing, Agent based model.

References:

  1. Jain, Kamal, Tung Mai, and Vijay V. Vazirani. "A Performance-Based Scheme for Pricing Resources in the Cloud." In International Conference on Web and Internet Economics, Springer, Cham, pp. 281-293,2017.
  2. Zhang, Hong, Hongbo Jiang, Bo Li, Fangming Liu, Athanasios V. Vasilakos, and Jiangchuan Liu. "A framework for truthful online auctions in cloud computing with heterogeneous user demands." IEEE Transactions on Computers ,Issue 65,vol. 3, pp: 805-818, 2016.
  3. Passas, Virgilios, Vasileios Miliotis, Nikos Makris, Thanasis Korakis, and Leandros Tassiulas. "Paris metro pricing for 5g hetnets." In Global Communications Conference (GLOBECOM), 2016 IEEE, pp. 1-6. IEEE, 2016.
  4. Huang, Huai‐Sheng, Shu‐Chiung Hu, Po‐Han Lee, and Yu‐Chee Tseng. "An adaptive Paris Metro Pricing scheme for mobile data networks." International Journal of Network Management Issue 26, vol.no. 6 ,pp: 422-434,2016.
  5. Hussin, A. Abdullah, R. Latip, "Agent-Based Pricing Determination for Cloud Services in Multi-Tenant Environment", International Journal of Computer and Communication Engineering, vol. 3, pp. 454-459, 2014
  6. Chau, Chi-Kin, Qian Wang, and Dah-Ming Chiu. "Economic viability of paris metro pricing for digital services." ACM Transactions on Internet Technology (TOIT) Issue14, vol. 2-3, pp: 12-33, 2014
  7. Xu, Hong, and Baochun Li. "Dynamic cloud pricing for revenue maximization." IEEE Transactions on Cloud Computing ,Issue 1,vol. 2, pp: 158-171 , 2013.
  8. Puspita, Fitri Maya, Kamaruzzaman Seman, and Bachok M. Taib. "Optimization of Internet Pricing Under Multiple QoS Networks." 2012.
  9. Mihailescu and Y. M. Teo, “Dynamic resource pricing on federated clouds,” in Proc. 10th IEEE/ACM Int. Conf. Cluster, Cloud Grid Comput., 2010, pp. 513–517,2010.
  10. Mihailescu, Marian, and Yong Meng Teo. "Strategy-proof dynamic resource pricing of multiple resource types on federated clouds." In International Conference on Algorithms and Architectures for Parallel Processing, Springer, Berlin, Heidelberg, pp. 337-350, 2010,  
  11. Ros, David, and Bruno Tuffin. "A mathematical model of the Paris metro pricing scheme for charging packet networks." Computer Networks ,Issue 46, vol no. 1 ,pp: 73-85,2004
  12. Dube, Parijat, Vivek S. Borkar, and D. Manjunath. "Differential join prices for parallel queues: Social optimality, dynamic pricing algorithms and application to internet pricing." In INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, vol. 1, pp. 276-283. 2002.
  13. Jain, Ravi, Tracy Mullen, and Robert Hausman. "Analysis of Paris Metro pricing strategy for QoS with a single service provider." In International Workshop on Quality of Service, pp. 44-58. Springer, Berlin, Heidelberg, 2001.
  14. Odlyzko, Andrew. "Paris metro pricing for the internet." In Proceedings of the 1st ACM conference on Electronic commerce, pp. 140-147. ACM, 1999.
  15. Marbach, Peter. "Pricing priority classes in a differentiated services network." In Proccedings of the Annual Allerton Conference on Communication Control and Computing, vol. 37, pp. 1075-1084. 1998.

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21.

Authors:

Srinivasa Akhil V, Sai Ajay V, Lakshmi Deepthi V, P.Saipriya

Paper Title:

Water Quality Parameter Guidelines and the Selection of Microcontroller for the Monitoring of Aquaculture System: A Review

Abstract: Aquaculture is known as the suitable method for cultivating fish and aquatic animals but there is negative impact on the Aquaculture. This is due to the lack of knowledge on the parameters regarding water quality and the use of manual and traditional fish farming. The aim of this research paper is to provide the proper guidelines for the maintenance of the Aquaculture system to attain the optimum yield. Firstly, the significance, desired limits and the remedies if they deviate from the tolerable limits of particular parameter are mentioned for the set of different parameters. Secondly, the required microcontroller is selected by comparing with the market's best microcontrollers to measure and monitor the parameters, this reduces the time and human intervention in the aqua farming and results in high yields. Subsequently, to mention the desired sensor for the particular parameter that works efficiently and effectively.

Keywords: Aquaculture, Hardness, Microcontroller, Plankton, Temperature, Turbidity. 

References:

  1. Fisheries, F. (2011). Aquaculture Department. 2013. Global Aquaculture Production Statistics for the year. C. Boyd, "Guidelines for aquaculture effluent management at the farm-level", Aquaculture, vol. 226, no. 1-4, pp. 101-112, 2003.
  2. Bartley, E. Hallerman, "A global perspective on the utilization of genetically modified organisms in aquaculture and fisheries", Aquaculture, vol. 137, no. 1-4, pp. 1-7, 1995.
  3. W. Creswell, J. D. Creswell, "Research design: qualitative quantitative and mixed methods approaches", Los Angeles: SAGE, 2018.
  4. Holmer, "Environmental issues of fish farming in offshore waters: perspectives concerns and research needs", Aquaculture Environment Interactions, vol. 1, no. 1, pp. 57-70, 2010.
  5. Cembella et al., "Population dynamics and spatial distribution of phycotoxic microalgae associated with shellfish aquaculture sites in Nova Scotia,"OCEANS '97. MTS/IEEE Conference Proceedings, Halifax, NS, Canada, 1997, pp. 557 vol.1-.
  6. Kobayashi, S. Msangi, M. Batka, S. Vannuccini, M. Dey, J. Anderson, "Fish to 2030: The Role and Opportunity for Aquaculture", Aquaculture Economics & Management, vol. 19, no. 3, pp. 282-300, 2015.
  7. H. Primavera, “Overcoming the impacts of aquaculture on the coastal zone,” Ocean Coastal Manage., vol. 49, nos. 9–10, pp. 531–545, 2006.
  8. Postolache, P. S. Girão, and J. M. D. Pereira, “Water quality monitoring and associated distributed measurement systems: An overview,” in Water Quality Monitoring and Assessment. Rijeka, Croatia: InTech, 2012.
  9. Tokhtuev, C. Owen, A. Skirda, V. Slobodyan, and J. Goin, “Turbidity sensor,” U.S. Patent 6842243, Jan. 11, 2005.
  10. Wang, S. M. S. M. Rajib, C. Collins and B. Grieve, "Low-Cost Turbidity Sensor for Low-Power Wireless Monitoring of Fresh-Water Courses," in IEEE Sensors Journal, vol. 18, no. 11, pp. 4689-4696, June1, 1 2018.
  11. Chanson, M. Takeuchi, and M. Trevethan, “Using turbidity and acoustic backscatter intensity as surrogate measures of suspended sediment concentration in a small subtropical estuary,” J. Environ. Manage., vol. 88, no. 4, pp. 1406–1416, 2008.
  12. Liu, Y. Liu, X. Gong and H. Zhang, "Design of Intelligent Dissolved Oxygen Detecting System Based on CAN Bus and Embedded USB Host," 2009 International Conference on Measuring Technology and Mechatronics Automation, Zhangjiajie, Hunan, 2009, pp. 85-88.
  13. Garcia, E. M. Trambulo, J. Pajarillo, M. R. B. Apsay, J. E. Tenorio and M. G. Chua, "Development of dissolved oxygen monitoring system for fish ponds," 2013 IEEE 3rd International Conference on System Engineering and Technology, Shah Alam, 2013, pp. 83-88.
  14. Wei, D. Changhui, L. Xiangjun and G. Jun, "Soft-sensor software design of dissolved oxygen in aquaculture,"2017 Chinese Automation Congress (CAC), Jinan, 2017, pp. 5413-5417.
  15. -H. Lee, T.-S. Lim, Y. Seo, P. L. Bishop, and I. Papautsky, “Needletype dissolved oxygen microelectrode array sensors for in situ measurements,” Sens. Actuators B, Chem., vol. 128, no. 1, pp. 179–185, 2007.
  16. Sosna, G. Denuault, R. W. Pascal, R. D. Prien, and M. Mowlem, “Field assessment of a new membrane-free microelectrode dissolved oxygen sensor for water column profiling,” Limnol. Oceanogr. Methods, vol. 6, no. 4, pp. 180–189, 2008.
  17. Bhattacharjee, H. Jiang and N. Behdad, "Sensor design for water hardness detection," 2013 IEEE SENSORS, Baltimore, MD, 2013, pp. 1-4.
  18. Maier and A. Uhl, "Areamap and Gabor filter based Vickers hardness indentation measurement,"21st European Signal Processing Conference (EUSIPCO 2013), Marrakech, 2013, pp. 1-5.
  19. Nasser, A. Zaman, L. Karim and N. Khan, "CPWS: An efficient routing protocol for RGB sensor-based fish pond monitoring system," 2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Barcelona, 2012, pp. 7-11.
  20. Y. Chung, C. L. Chen and J. b. Chen, "Design and Implementation of Low Power Wireless Sensor System for Water Quality Monitoring,"2011 5th International Conference on Bioinformatics and Biomedical Engineering, Wuhan, 2011, pp. 1-4.
  21. Baranyuk, "The comparative analysis of means for measuring pH," The Experience of Designing and Application of CAD Systems in Microelectronics, 2003. CADSM 2003. Proceedings of the 7th International Conference., 2003, pp. 398-399.
  22. López, J. M. Gómez, J. Sabater and A. Herms, "IEEE 802.15.4 based wireless monitoring of pH and temperature in a fish farm," Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference, Valletta, 2010, pp. 575-580.
  23. Bosma, R. Izett and R. Izett, "Challenges with collecting data for measured pH and dissolved inorganic carbon (DIC) in coastal waters,"OCEANS 2016 MTS/IEEE Monterey, Monterey, CA, 2016, pp. 1-5.
  24. Postolache, J. M. D. Pereira, and P. S. Girao, “An intelligent turbidity and temperature sensing unit for water quality assessment,” in Proc. Can. Conf. Elect. Comput. Eng., Winnipeg, MB, Canada, May 2002, pp. 494–499.
  25. Albert, V., & Ransangan, J. (2013). Effect of water temperature on susceptibility of culture marine fish species to vibriosis. International Journal of Research in Pure and Applied Microbiology, 3(3), 48-52.
  26. Wang, X. Xu, and P. Kestemont, “Effect of temperature and feeding frequency on growth performances, feed efficiency and body composition of pikeperch juveniles (Sander lucioperca),” Aquaculture, vol. 289, nos. 1–2, pp. 70–73, 2009.
  27. M. Africa, J. C. C. A. Aguilar, C. M. S. Lim, P. A. A. Pacheco and S. E. C. Rodrin, "Automated aquaculture system that regulates Ph, temperature and ammonia," 2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), Manila, 2017, pp. 1-6.
  28. V. Ramesh et al., "Water quality monitoring and waste management using IoT," 2017 IEEE Global Humanitarian Technology Conference (GHTC), San Jose, CA, 2017, pp. 1-7.
  29. J. Matuszewski, R. M. Lopes and R. M. Cesar, "Visual Rhythm-Based Method for Continuous Plankton Monitoring," 2013 IEEE 9th International Conference on e-Science, Beijing, 2013, pp. 204-211.
  30. M. M. Asad, I. A. Marouf and H. M. Enshasy, "An effective way to program microcontrollers for high speed control operations," 2017 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), Srivilliputhur, 2017, pp. 1-4.
  31. N. Mamatha and S. N. Namratha, "Design & implementation of indoor farming using automated aquaponics system," 2017 IEEE International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), Chennai, 2017, pp. 396-401

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22.

Authors:

Korakrich Montian, Nanthi Suthikarnnarunai

Paper Title:

Factors Influencing Purchase Intention towards Electric Vehicles in Bangkok Metropolis

Abstract: Electric Vehicles (EVs) is the modern vehicle technology with a rapid development which will alleviate the problems of energy, air pollution and global warming that are becoming more severe. This paper was aimed at the study the relationships between individual factors and factors influencing purchase intention toward EVs in Bangkok Metropolis. The questionnaires distributed to 50 respondents were collected by online survey in Bangkok Metropolis which descriptive data were analyzed and inferential information by used a statistic: means, percentage, standard deviation and chi-squared test. According to the results obtained of the questionnaires show that Infrastructure factor and Financial factor were very important with the averages of 4.60 and 4.50 respectively, and the factors that were fairly important were Performance, Government Support, Market Efficiency Awareness, Environmental Impact and Information Awareness with the averages of 0.47, 4.06, 4.02, 4.00 and 3.68 respectively from most to least. Furthermore, the correlations between the demographic variables and purchase intention towards EVs in the future shown that the variables of gender, age, occupation, education highest and monthly income are all no significantly different for purchase intention towards EVs in the future. The results of the present research can help the researchers to continue create a new model forecasting toward EVs adoption in the future.

Keywords: Electric Vehicles, Factors influencing, Purchase intention.

References:

  1. International Energy Agency (IEA), “Energy Technology Perspective 2010: Scenarios & Strategies to 2050,” IEA Publications, Paris, France, 2010.
  2. UNFCCC, U N,“Paris declaration on electro-mobility and climate change & call to action”. New York, 2015.
  3. International Energy Agency (IEA), “Global EV outlook 2017,” BP, Energy Outlook-2017.
  4. International Organization of Motor Vehicle Manufacturers (OICA), 2017.
  5. Energy Policy and Planning Office, “To study of preparing future for electric vehicles in Thailand,” 2016.
  6. Krungsri Research, "Thailand with technology development EVs". Research Intelligence, 2017.
  7. Nissan-commissioned study by Frost & Sullivan, “Future of Electric Vehicles in Southeast Asia,” 2018.
  8. Power, J.D., “While Many New-Vehicle Buyers Express Concern for The Environment, Few Are Willing to Pay More for An Environmentally Friendly Vehicle,” Available online: https://www.finanzen.net/nachricht/ aktien/j-d-power-and-associates-reports-while-many-new-vehicle-buyers-express-concern-for-theenvironment-few-are-willing-to-pay-more-for-an-environmentally-friendly-vehicle-651084 (accessed on 15 June 2018).
  9. Hidrue, M.K., Parsons, G.R., Kempton, W., Gardner, M.P., “Intention to pay for electric vehicles and their attributes,” Resource and Energy Economics 333, 686-705, 2011.
  10. Ozaki, R., Sevastyanova, K., “Going hybrid:An analysis of consumer purchase motivations. Energy Policy 395,” 2217-2227, 2010.
  11. Brownstone D, Bunch DS, Train K., “Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles,” 2000:315–338.
  12. Lai, I. K., Liu, Y., Sun, X., Zhang, H., & Xu, W., “Factors influencing the behavioural intention towards full electric vehicles: An empirical study in Macau,” Sustainability, 7(9), 12564-12585, 2015.
  13. Liao, F., Molin, E., & van Wee, B., “Consumer preferences for electric vehicles: a literature review,” Transport Reviews, 37(3), 252-275.
  14. Constantinides, E. “Influencing the online consumer's behavior,” Internet research, 14(2), 111-126, 2004.
  15. Wang, N., & Liu, Y., “Key factors influencing consumers’purchase intention electric vehicles in China,” 2015.
  16. Nie, Y., Wang, E., Guo, Q., Shen, J., “Examining Shanghai Consumer Preferences for Electric Vehicles and Their Attributes,” Sustainability 2018, 10, 203.
  17. Yong, T., & Park, C., “A qualitative comparative analysis on factors affecting the deployment of electric vehicles,” Energy Procedia, 128, 497-503, 2017.
  18. Degirmenci, K., Breitner, M.H., “Consumer purchase intentions for electric vehicles: Is green more important than price and range?”, Transportation Research Part D 51, 250–260, 2017.
  19. Krungsri Research, "Thailand with technology development EVs," Research Intelligence, May 2017.

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23.

Authors:

Taha Bensiradj, Samira Moussaoui

Paper Title:

Deployment Model of Wireless Sensors Networks in the Framework of Hybrid Sensors and Vehicular Networks for Road Safety

Abstract: Hybrid Sensors and Vehicular Networks (HSVN) represent an architecture which creates a framework of collaboration between Wireless Sensors Networks (WSN) and Vehicular Ad Hoc Networks (VANET). The goal of this collaboration is the improvement of the road safety. The coverage and connectivity problems (deployment models) of wireless sensors networks represent a big challenges studied by many searchers. The environment and application requirements have a relationship with the aspects used to create a deployment model. In this paper, we have proposed a deployment model of WSN used in HSVN basing on the roads network and application of road safety. This model uses an algorithm which has for purpose ensuring the sensing of any road event and allows the connectivity between sensors. The results proven that our proposition is more reliable than others works.

Keywords: Coverage, Connectivity, Deployment models HSVN, VANET, WSN.

References:

  1. VAA, Torgeir, PENTTINEN, Merja, and SPYROPOULOU, Intelligent transport systems and effects on road traffic accidents: state of the art. IET Intelligent Transport Systems, 2007, vol. 1, no 2, p. 81-88.
  2. SJOBERG, P.ANDRES and T.BUBURUZAN. Cooperative intelligent transport systems in Europe: current deployment status and outlook. IEEE Vehicular Technology Magazine, 2017, vol. 12, no 2, p. 89-97.
  3. SADOU and L. BOUALLOUCHE-MEDJKOUNE, Hybrid sensor and vehicular networks: a survey. International Journal of Vehicle Information and Communication Systems, 2017, vol. 3, no 3, p. 204-229.
  4. LU, JianFeng and HUANG, Jianglong. A RESTful information service method in hybrid sensor and vehicular networks. In: IET Conference Proceedings. The Institution of Engineering & Technology, 2012.
  5. Victor Krebss and Boris Tsilker, ‘Coverage evaluation approaches for intelligent transportation systems based on anisotropic sensor networks’, Proceedings of the 10th International Conference “Reliability and Statistics in Transportation and Communication” (RelStat’10), 20–23 October 2010, Riga, Latvia, p. 199-206. ISBN 978-9984-818-34-4 Transport and Telecommunication, Institute, Lomonosova 1, LV-1019, Riga, Latvia.
  6. KHOUFI, Ines, MINET, Pascale, LAOUITI, Anis, and Saoucene Mahfoudh. Survey of deployment algorithms in wireless sensor networks: coverage and connectivity issues and challenges. International Journal of Autonomous and Adaptive Communications Systems, 2017, vol. 10, no 4, p. 341-390.
  7. Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (WPANs); IEEE Std 802.15.4; IEEE: New York, NY, USA, 2006.OMNeT++ community-www.omnetpp.org 2001-2015.

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24.

Authors:

Ifrat Jahan, Md. Lizur Rahman, Ahmed Wasif Reza, Surajit Das Barman

Paper Title:

Systolic Blood Pressure Measurement from Heart Rate using IoT

Abstract: Hybrid Sensors and Vehicular Networks (HSVN) represent an architecture which creates a framework of collaboration between Wireless Sensors Networks (WSN) and Vehicular Ad Hoc Networks (VANET). The goal of this collaboration is the improvement of the road safety. The coverage and connectivity problems (deployment models) of wireless sensors networks represent a big challenges studied by many searchers. The environment and application requirements have a relationship with the aspects used to create a deployment model. In this paper, we have proposed a deployment model of WSN used in HSVN basing on the roads network and application of road safety. This model uses an algorithm which has for purpose ensuring the sensing of any road event and allows the connectivity between sensors. The results proven that our proposition is more reliable than others works.

Keywords: Coverage, Connectivity, Deployment models HSVN, VANET, WSN.

References:

  1. Christofaro, D.G.D., Casonatto, J., Vanderlei, L.C.M., Cucato, G.G. and Dias, R.M.R. (2017). Relationship between Resting Heart Rate, Blood Pressure and Pulse Pressure in Adolescents. Arquivos brasileiros de cardiologia, 108(5), 405-410.
  2. Pierce, G. L., Zhu, H., Darracott, K., Edet, I., Bhagatwala, J., Huang, Y., & Dong, Y. (2012). Arterial stiffness and pulse-pressure amplification in overweight/obese African-American adolescents: relation with higher systolic and pulse pressure. American journal of hypertension, 26(1), 20-26.
  3. Hassan, M. K. B. A., Mashor, M. Y., Nasir, N. M., & Mohamed, S. (2008). Measuring of systolic blood pressure based on heart rate. In 4th Kuala Lumpur International Conference on Biomedical Engineering 2008 (pp. 595-598). Springer, Berlin, Heidelberg.
  4. O'brien, E., Pickering, T., Asmar, R., Myers, M., Parati, G., Staessen, J., ... & Gerin, W. (2002). Working Group on Blood Pressure Monitoring of the European Society of Hypertension International Protocol for validation of blood pressure measuring devices in adults. Blood pressure monitoring, 7(1), 3-17.
  5. Ramsey, M. (1991). Blood pressure monitoring: automated oscillometric devices. Journal of clinical monitoring, 7(1), 56-67.
  6. Pickering, T. G., Coats, A., Mallion, J. M., Mancia, G., & Verdecchia, P. (1999). Blood Pressure Monitoring. Task force V: White-coat hypertension. Blood pressure monitoring, 4(6), 333-341.
  7. Afonso, V. X., Tompkins, W. J., Nguyen, T. Q., & Luo, S. (1999). ECG beat detection using filter banks. IEEE transactions on biomedical engineering, 46(2), 192-202.
  8. De Chazal, P., O'Dwyer, M., & Reilly, R. B. (2004). Automatic classification of heartbeats using ECG morphology and heartbeat interval features. IEEE transactions on biomedical engineering, 51(7), 1196-1206.

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25.

Authors:

G. Reddy Babu, Pala Gireesh Kumar

Paper Title:

Effect of Sulfates on Cement and Fly Ash Mortar Made With Treated Domestic Wastewater

Abstract: Investigative studies were carried out, to evaluate the effects of sulfates on cement and fly ash mortar made with treated domestic wastewater in the laboratory. Treated domestic wastewater (TDWW) from a treatment plant which is in Vishnu Educational Society, Bhimavaram, A.P, India, was used in the present research work. A combination of (70% Portland cement + 30% fly ash) was arrived based on number of trials where the best compressive strength was obtained. This combination was used throughout the research work. 90 days age of reference specimens, cast and cured in Potable water (PW), and 90 days age of test specimens cast and cured in treated domestic wastewater (TDWW) were immersed in sodium sulfate (Na2SO4) and magnesium sulfate (MgSO4) solutions. When compered test specimens with reference specimens, Loss of compression strength in test specimens was almost same as that of reference specimens. But MgSO4 was more vulnerable than the Na2SO4.

Keywords: Cement, Fly ash, TDWW, Compression Strength, Durability, sulfates

References:

  1. K. Mehta, J.M. Paulo Monteiro, Concrete: Microstructure, Properties, and Materials, 3rd ed. McGraw-Hill Professional; 2006.
  2. E.Wallah and B.V. Rangan, Low-Calcium Fly Ash-Based Geopolymer Concrete Long-term Properties , Res.report- GC2, Curtin University, Australia, 2006: 76-80.
  3. B. Polder, Effects of slag and fly ash on reinforcement corrosion in concrete in chloride environment- Research from the Netherlands, Heron 2012:57: 197.
  4. M. Malhotra and P.K. Mehta, High-performance, high-volume fly ash concrete materials, mixture proportioning, properties, construction practice, and case histories; 2002.
  5. Siddique, Performance characteristics of high-volume ` class F fly ash concrete, CemConcr Res 2004;34(3):487–93.
  6. H. Zhang and J. Islam, Use of nano-silica to reduce setting time and increase early strength of concretes with high volume fly ash or slag, Construct Build Mater 2012; 29:573–80.
  7. M. Hossain, M.R. Karim, M. Hasan, and M.F.M. Zain, Durability of mortar and concrete made up of pozzolans as a partial replacement of cement: A review, Construction and Building Materials, 2016;116:128-140.
  8. H. Tay and W.K. Yip, Use of reclaimed water for cement mixing, J. Environ. Engg 1987: 113:5: 1156-60.
  9. Z. Cebeci and A.M. Saatci. Domestic sewage as mixing water in concrete, ACI Material Journal, 1989: 86:503 -506.
  10. A. El-Nawawy and S. Ahmed, Use of treated effluent in concrete mixing in an arid limate, Cement Concrete Composites, 1991; 13:2:137-41.
  11. Nan, Wu. Yeong-Hwa and Mar. Chung-Yo, Effect of magnetic water on engineering properties of concrete containing granulated blast furnace slag, Cement and Concrete Research, 2000:599-605.
  12. V. Ramana Reddy, N.R.S Prasad Reddy, G. Reddy Babu, B. Kotaiah and P. Chiranjeevi, Effect of biological contaminated water on cement mortar properties, The Indian Concrete Journal, 2006: 80:13-19.
  13. S Al-jabri, A.H. Al-saidy, R. Taha, A.J. Al- Kemyandi, The effect of using wastewater on the properties of high strength concrete, in; The twelfth east-Pacific conference engineering and construction, proceedia engineering, Vol.14, 2011,pp.370-378.
  14. Asadollahfardi, M. Delnavaz, V. Rashnoiee and N. Ghonabadi, Use of treated domestic wastewater before chlorination to produce and cure concrete, Construction and Building Materials, 2016:105:253-261.
  15. Standard Methods for the Examination of Water and Wastewater: APHA, AWWA, WEF, Washington, Dc, USA.1998.
  16. S.B. Al-Amoudi, Rasheeduzzafar, M. Maslehuddin and S.N. Abduljawad, Influence of chloride ions on sulfate deterioration in plain and blended cements, Mag.Concr Res. 1994: 46:167:113-123.

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26.

Authors:

G. Durga Rama Naidu, G. Tirupathi Naidu, Duvvada Hariprasad

Paper Title:

Behaviour of Multistoried Composite Structures with Different Wind Velocities and Structure Heights

Abstract: In India concrete and rolled steel sections are used in construction activities, steel composites are often being used based on their advantages in heavy structure like multistoried structures and also in offshore structures. In this study we tried four composite structure models G+5, G+10, G+20, G+30 are considering with varying wind velocities 33,39,44,47,50,55m/s, as per IS875-part-3 and structure foundation depth is considered 2m below foundation level and the base conditions are fixed at the bottom or at the supports/footings. The structures modeled in ETABS structural analysis and design software by considering various loads and load combinations by their relative occurrence are considered the material properties considered are M30 concrete grade & FE415 reinforcing steel.

Keywords: Composite Structures, Wind Speeds, RCC, Multistoried Structures, Varying Heights

References:

  1. Mahesh Suresh Kumawat and L G Kalurkar “analysis and design of multistory building use composite structure” international journal of structural and civil engineering research ISSN 2319 – 6009 page 125-137 Vol. 3, No. 2, May 2014.
  2. Mohd Amir Khan “comparative study of R.C.C & structural steel –concrete composite frame for linear and non-linear analysis” international research journal of engineering and technology (IRJET) vol. 3, No. 2, May 2014  p-ISSN: 2395-0072  volume: 04 Issue: 07  July -2017
  3. D. R. Panchal “investigated advanced design of composite steel-concrete structural element journal of engineering research and applications “ISSN : 2248-9622, Vol. 4, Issue 7 ( version 2), July 2014, pp.124-138
  4. Datta” steel-concrete composite construction – new trend in India” IOSR journal of mechanical and civil engineering e-ISSN: 2278-1684, p-ISSN: 2320–334X
  5. Vinay Damam “design of steel concrete composite structure as comparative with reinforced concrete structure by adapting STAAD. ProV8I” international journal of engineering sciences & management research :January, 2016,  ISSN 2349-6193
  6. Mario D’Aniello “Nonlinear behavior, design and analysis of steel structures: recent findings and new trends for the next generation of European design standards” the open civil engineering journal, 2017, 11, (Suppl-1, M1) 315-318
  7. 1893(Part1):2002,"Criteria for earthquake resistant design of structures -general provisions and buildings", bureau of indian standards, New Delhi, India.
  8. IS 456: 2000,"Plain reinforced concrete-code of practice", bureau of indian standards, New Delhi, India.
  9. IS 875-3 (1987): Code of practice for design loads (other than earthquake) for buildings and structures, Part 3: wind loads

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27.

Authors:

G. Ramakrishna Reddy, Debjyoti Pal, A. K. Sinha, A. K. Choudhary

Paper Title:

Improvement in Swelling, Strength and Deformation Characteristics of Expansive Soil using Lime and Brick Dust

Abstract: In India concrete and rolled steel sections are used in construction activities, steel composites are often being used based on their advantages in heavy structure like multistoried structures and also in offshore structures. In this study we tried four composite structure models G+5, G+10, G+20, G+30 are considering with varying wind velocities 33,39,44,47,50,55m/s, as per IS875-part-3 and structure foundation depth is considered 2m below foundation level and the base conditions are fixed at the bottom or at the supports/footings. The structures modeled in ETABS structural analysis and design software by considering various loads and load combinations by their relative occurrence are considered the material properties considered are M30 concrete grade & FE415 reinforcing steel.

Keywords: Composite Structures, Wind Speeds, RCC, Multistoried Structures, Varying Heights

References:

  1. Bhavsar Sachin N.et al.5 (2014),Stabilization of expansive soil using lime and brick dust”, International Journal of Research in Engineering and Technology, volume 3, Issue 4, 435-441.
  2. Harish, G.R., et al.3 (2017),Stabilization of expansive soil using lime”, International Research Journal of Engineering and Technology (IRJET), e-ISSN: 2395 -0056, Volume: 04 Issue: 06, June -2017, 1725-1727.
  3. Kumar Ajay, kumar Ashok and Praksah Ved3(2014),Stabilization of expansive soil using lime and brick dust”, International Journal of All Research Education and Scientific Methods, ISSN: 2455-6211, Volume 4, Issue 9, September- 2016.
  4. Kumar Vijay et al.5 (2011),Stabilization of expansive soil using lime and brick dust”, Indian Journal of Research, Volume 5, Issue no 5, 23-26.
  5. Kumar Vinoth M. and kumaran Muthu K.2(2015), studied the “Effect of vertical sand drains on embankment construction”. 50th geotechnical conference, 17th-19th December 2015.
  6. Nadgouda K.A., and Hedge R.A., et al.2 (2010),Stabilization of expansive soil using lime ”, Indian Geotechnical Conference – 2010, GEOtrendz, December 16–18, 2010, IGS Mumbai Chapter & IIT Bombay, 513-514.
  7. Pokale Kunal R., Borker Yogesh R and Jichkar Rahul R 3 (2015), Stabilization of expansive soil using brick dust”, International Research Journal of Engineering and Technology (IRJET), e-ISSN: 2395-0056, Volume: 02 Issue: 05 , Aug-2015, 726-728.

146-150

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28.

Authors:

Ganzi Suresh, K. L. Narayana, M. Kedar Mallik

Paper Title:

Characterization and Wear Properties of Co-Cr-W alloy Deposited with Laser Engineered Net Shaping

Abstract: Commercially available Co-Cr-W alloy, known as Stellite 6, samples are deposited using Laser Engineered Net Shaping process using L9 orthogonal array of Taguchi method with three different process parameters, each at three levels. All the samples are tested for the microstructure analysis with ESEM and wear resistance. The EPMA mapping is also presented for analysis. The wear testing results reveal that the samples fabricated with 350W laser power, 7.5g/min powder feed rate and 15mm/s laser scan speed have exhibited highest wear resistance at 30N load and 300rpm.

Keywords: Additive Manufacturing; Laser Engineered Net Shaping (LENS); Co-Cr-W Alloy; Wear Resistance; Micro Structure

References:

  1. Chua, C.K., Teh, S.H. and Gay, R.K.L. (1999). ‘Rapid Prototyping Versus Virtual Prototyping in Product Design and Manufacturing’, Int. J. Adv. Manufac. Technol., vol. 15, pp. 597-603.
  2. Ganzi Suresh, K L Narayana and M. Kedar Mallik. Laser Engineered Net Shaping process in Development of Bio-Compatible Implants: An Overview. Journal of Advanced Research in Dynamical and Control Systems, Vol. 9. Sp–14 / 2017.
  3. Ganzi Suresh and K L Narayana. A Review on Fabricating Procedures in Rapid Manufacturing. International Journal of Manufacturing, Materials, and Mechanical Engineering, 6.2 (2016): Web. 24 Mar 2016.
  4. Ganzi Suresh, K L Narayana and M. Kedar Mallik., A Review on Development of Medical Implants by Rapid Prototyping Technology. International Journal of Pure and Applied Mathematics, Volume 117 No. 21 2017, pp.257-276
  5. Khan, W., Muntimadugu, E., Jaffe, M. and Domb, A.J., 2014. Implantable medical devices. In Focal controlled drug delivery (pp. 33-59). Springer, Boston, MA
  6. Yoo J.S., Oh Y.R., Kim K.T., Kim J.G., Influences of passivating elements on the corrosion and biocompatibility of super stainless steels, J Biomed Mater Res B ApplBiomater 86B (2008), 310–20.
  7. Balla V. K., Banerjee S., Bose S., Bandyopadhyay A., Direct laser processing of a tantalum coating on titanium for bone replacement structures, Acta Biomater., 6 (6) (2010), 2329–2334.
  8. Nag S, Banerjee R, Fraser HL. Mater Sci Eng C 2005; 25:357–62
  9. Mantrala Kedar Mallik, Chalamalasetty Srinivasa Rao, Vaddi Venkata Sundara Kesava Rao, “Effect of heat treatment on hardness and wear behaviour of weld deposited Co-Cr-Mo alloy” Revista Materia, Vol.20, No.2, 2015, pp 544-549
  10. Yamanaka, K., Mori, M., Kuramoto, K. and Chiba, A., 2014. Development of new Co–Cr–W-based biomedical alloys: effects of microalloying and thermomechanical processing on microstructures and mechanical properties. Materials & Design, 55, pp.987-998.
  11. Walke, W., Paszenda, Z. and Tyrlik-Held, J., 2006. Corrosion resistance and chemical composition investigations of passive layer on the implants surface of Co-Cr-W-Ni alloy. Journal of Achievements in Materials and Manufacturing Engineering, 16(1-2), pp.74-79.
  12. Ganzi Suresh, K L Narayana, M. Kedar Mallik and V. Srinivas., Electro Chemical Corrosion Behaviour of LENSTM Deposited Co-Cr-W Alloy for Bio-Medical Applications. International Journal of Mechanical and Production Engineering Research and Development, Special Issue, Jun 2018, pp.41-52.
  13. Ganzi Suresh, K L Narayana, M. Kedar Mallik and V. Srinivas., Processing & Characterization of LENSTM Deposited Co-Cr-W Alloy for Bio-Medical Applications. International Journal of Pharmaceutical Research (IJPR) Volume 10 (1), 2018, pp.276-285

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29.

Authors:

J. Thrisul Kumar, Y. Mallikarjuna Reddy, B. Prabhakara Rao

Paper Title:

Change Detection in Sarimages Based on Artificial Bee Colony Optimization With fuzzy C - Means Clustering

Abstract: Synthetic aperture radar (SAR)generates images with high resolution in all weather conditions for a given application. An Artificial Bee Colony (ABC), optimization algorithm is proposed to detect changes in multitemporal SAR images which are captured at same area in various times. It is well- known fact that the speckle noiseis existed in SAR images.In order to reduce the speckle noise in the co-registered images, a novelAdaptive Median filter is implemented in this paper. Afterthe minimization of speckle noise, discrete wavelet (DWT) fusion is exploited for further image segmentation. Also, an Artificial Bee Colony (ABC) optimization technique is adopted for effective smoothing the image to make decisiveimage classification. Using fuzzy c -means clustering classificationwe can detect changed pixels and unchanged pixels.Finally, theresults are comparedwith DWT-FCM (without optimization), GeneticAlgorithm (GA)optimizationand proposed ABC optimizationAlgorithm. The performance of proposed technique iscomparedin terms ofaccuracy, sensitivity, precision and F1 – score.

Keywords: SAR, Optimization, ABC algorithm, GA algorithm and Fuzzy – C means clustering.

References:

  1. Speckle Noise Reduction in SAR Imagery Using a Local Adaptive Median Filter Fang Qiua , Judith Berglund b , John R. Jensen b ,Pathik Thakkar a &Dianwei Ren. GIScience & Remote SensingGIScience and Remote Sensing, 2004, volume No. 3, pp. 244-266.
  2. Robin, L. Moisan, and S. Le Hegarat-Mascle, “An a-contrarioapproach for subpixel change detection in satellite imagery”, IEEETrans. Pattern Anal. Mach. Intell., vol. 32, no. 11, pp. 1977-1993, Nov. 2010.
  3. A Genetic Algorithm-Based Low Voltage Ride-Through Control Strategy for Grid Connected Doubly Fed Induction Wind Generators TheodorosD. Vrionis, XanthiI.Koutiva, and Nicholas. ieee transactions on power systems, vol.29, no.3, may2014.pp 1325-1334
  4. Rey, G. Subsol, H. Delingette, and N. Ayache, “Automatic detection and segmentation of evolving processes in 3-D medical images: Application to multiple sclerosis”, Med. Image Anal., vol. 6, no. 2, pp. 163-179, Jun. 2002.
  5. Bollingerbands approach on boosting ABC Algorithm and its varients by basic kocer, Applieds of Computing, Elsevier, volume no 49,2016.pp-292-312
  6. ‘A global best artificial bee colony algorithm for global optimization’ By Weifeng GaoSanyang Liu Lling Huang journal of computational and ppliedmathematics.W.Gaoetal./Journal of Computationaland Applied Mathematics, volume236, 2012. pp-2741–2753
  7. Hame, I. Heiler, and J. S. Miguel-Ayanz, “An unsupervised change detection and recognition system for forestry”, Int. J. Remote Sens., vol. 19, 1998.pp. 1079-1099.
  8. R., Merril, and L., Jiajun. “A Comparisonof Four Algorithms for Change Detection in an Urban Environment”. Remote Sens. Environments,Volume 63 (2), 1998, pp. 95-100.
  9. S Rajkumar, S Kavitha,“Redundancy Discrete Wavelet Transform and Contourlet Transform for Multimodality Medical Image Fusion with Quantitative Analysis”,Third International Conference on Emerging Trends in Engineering and Technology, volume 05,2010.pp. 134-139.
  10. ‘Unsupervised change detection in SAR images based on frequency difference and a modified fuzzy c-means clustering’ Weidong Yan, Shaojun Shi, Lulu Pan, Gang Zhang linternational journal of remote sensing, 2018 VOL. 39, NO. 10, 3055–3075.
  11. ’Synthetic aperture radar image change detection based on improved bilateral filtering and fuzzy C means’ Ronghua Shang Ailing Wen Yongkun Liu Licheng Jiao Rustam Stolk Journal of Applied Remote Sensing 046017-1 Oct–Dec 2016 • Vol. 10(4)
  12. Application of Genetic Algorithm for Image Enhancement and Segmentation. Miss. Komal R. Hole, Prof. Vijay S. Gulhane, Prof. Nitin D. Shellokar. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 2, Issue 4, April 2013 pp-1342-1346
  13. Unsupervised Change Detection of Remotely Sensed Images using Fuzzy Clustering.sushmitaghosh et all volume 82, 2009. IEEE conference on Advances in Pattern Recognition. pp-383-388
  14. Change Detection in Synthetic Aperture Radar Images by Sangeetha R Revathy, International Journal of Science and Research (IJSR).Volume 5 Issue 12, December 2016.pp-1681-1686
  15. Image Fusion on Ratio Images for Change Detection in SAR Images Using DWT and PCA P. Sanjay Krishnamal et al Int. Journal of Engineering Research and Applications ISSN: 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.1242-1246
  16. Change Detection Of Remote Sensing Images By Dt-Cwt And MrfShida OuYanga, KuikuiFana,b, HuibingWanga, and Zhongyuan Wang b.The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-1/W1, 2017.pp.3-10
  17. Unsupervised Change Detection in SAR Image Based on Gauss-Log Ratio Image Fusion and Compressed Projection Biao Hou, Member, IEEE, Qian Wei, Yaoguo Zheng, and Shuang Wang, Member, IEEE.Volume:7, issue 8, Aug. 2014.pp-3297 - 3317
  18. Speckle Noise Reduction of Medical Ultrasound Images using Bayesshrink Wavelet Threshold by k.karthikeayan, International Journal of Computer Applications (0975 – 8887) Volume 22– No.9, May 2011.
  19. Change Detection in Synthetic Aperture Radar Images Using a Multiscale-Driven Approach Olaniyi A. Ajadi, Franz J. Meyer and Peter W. Webley, Remote Sens. 2016, 8, 482. pp.1-27
  20. Importance of Statistical Measures in Digital Image Processing Vijay Kumar1, Priyanka Gupta2, International Journal of Emerging Technology and Advanced Engineering ISSN 2250-2459, Volume 2, Issue 8, August 2012. pp.130-145

156-160

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30.

Authors:

K. NagaRajesh, B. Girish Kumar, G. Jagadeesh, R. Srinivasa Rao

Paper Title:

A Study on Asphalt Pavements by using RAP, Sand & UFS Mixtures as Replacements

Abstract: The centre of this study is concentrated on introducing the lean ideas in asphalt pavement construction particularly in the Quality control (QC) process in HMA. HMA comprises of nearly 95% of aggregate, gravel or sand, filler and these ingredients are binding together with bitumen a by-product from crude oil industry. The aim of the present study is to compare the strength in terms of stability and flow value of Conventional & Non-conventional mix by Marshal Stability test. The present study relates Usage of RAP to reduce the fresh aggregate in the proposed Mix without influencing the properties of mix, from the test results we are adopting 10 % RAP with 90 % fresh aggregate for NCM mixes.VG 30 grade bitumen is used as binder and Maximum aggregate size (MAS) 23.0 mm and Nominal Maximum Aggregate size (NMAS) 19.0 mm. Cement is used as filler for conventional mixes, while UFS, Sand is used as filler for NCM-II and NCM-III respectively. And finally, 1 % lime in the weight of bitumen used as antistripping agent to minimise moisture susceptibility or to increase the resistance to moisture sensitivity of the proposed mix. From this study we are observed NCM –II shows better results than other Non-conventional mixes, the stability values are slightly lesser than conventional mix, other Marshall properties are far better than conventional ones. The optimum binder content (OBC) is 5.68 for NCM – II, which is lesser than Conventional mix 5.72

Keywords: Bituminous concrete, Reclaimed Asphalt Pavement (RAP), Optimum Binder Content (OBC), Used Foundry Sand (UFS), Non-Conventional Mix (NCM).

References:

  1. Tambak,et.al.,(2014) “Laboratory investigation on hot mix asphalt using reclaimed asphalt pavement (rap) for bituminous concrete mix” International Journal of Research in Engineering and Technology Volume: 03
  2. “Ministry of Road Transport and Highways (MoRT&H)” (2012) Specification for Roads and Bridge work. Government of India, Indian Roads Congress, 5th revision, New Delhi, India,.
  3. Brajesh Mishra et.al., (2015)“A Study on Use of Reclaimed Asphalt Pavement (RAP) Materials in Flexible Pavements” IJIRSET Vol. 4
  4. Roshan Karki, Prof. Gautam Bir SinghTamrakar “Comparative Study of Asphalt Concrete Using Sand and Stone Dust” Journal of Transportation Systems Volume 3 Issue 1 Page 1-20.
  5. Hasan Hamodi Joni Hussein Hamel Zghair (2016) “Effect of Adding Used-Foundry Sand on Hot Asphalt Mixtures Performance” Eng & Tech. journal Vol.34 Part (A) no 6.
  6. Dipu Sutradhar, et.al, (2015) “Effect of Using Waste Material as Filler in Bituminous Mix Design,” American Journal of Civil Engineering 3(3): 88-94
  7. Sunil S et.al ( 2014 )“Experimental Investigations on the Performance of Bituminous Mixes With Reclaimed Asphalt Pavement (Rap) Materials (Case Study Tumkur To Chitradurga-Nh4)”, International Journal of Research in Engineering and Technology, Volume: 03 Special Issue.
  8. Bekir Aktas, Sevket Aslan (2017) “comparative Evaluation of Replacement Foundry Sand with Mineral Fine Aggregates on HMA Properties”, The Online Journal of Science and Technology Volume 7, Issue 3.
  9. D D M Huwae (2017) et.al “The use of natural sand from lampusatu beachkabupatenmerauke, papua for mixed asphalt Concrete” IOP Conf. Ser.: Mater. Sci. Eng. 204,.
  10. Suji D, et.al (2016) “Experimental Study on Partial Replacement of Waste Foundry Sand in Flexible Pavements”, International Journal of Civil and Structural Engineering Research Vol. 4, Issue 1, pp: (188-197),
  11. Saud A. Sultan, Zhongyin Guo, (2017) “Evaluating the performance of sustainable perpetual pavements using recycled asphalt pavement in China”, International Journal of Transportation Science and Technology.
  12. Cory Patrick Shannon, (2012)“Fractionation of recycled asphalt pavement materials: improvement of volumetric mix design criteria for High-RAP content surface mixtures”, University of Iowa, Iowa Research Online .
  13. Prithvi Singh Kandhal, et.al, (2010)“Guidelines for Long Lasting Bituminous Pavements In India”, Journal of the Indian Roads Congress, Paper No. 564 Volume 71-3, .
  14. Pramukh N, et al. 2015 “Influence of combined flakiness and elongation indices of coarse aggregates on the bituminous concrete mixture with nmas of 12.5mm”, International Journal of Research in Engineering and Technology, Volume: 04 Special Issue.
  15. Bradley J et.al., ( 2006)  “Department  of  Civil  Engineering Clemson University Laboratory Evaluation of Anti-Strip Additives in Hot Mix Asphalt”, Report No. FHWA-SC-06-07.
  16. F. Kallas, et.al., (1961) “Mineral Fillers in Asphalt Paving Mixtures”, The Asphalt Institute, College Park, Maryland, Proc., Assoc. of Asphalt Paving Technologists, Vol. 30
  17. Feipeng Xiao,et. Al., (2015) “Moisture Susceptibility and Rut Resistance of RAP Asphalt Mixtures with High Percentage of Natural Sand”, American Society of Civil Engineers J. Mater. Civ. Eng., 27(7)
  18. “Reclaimed Asphalt Pavements in Asphalt Mixtures”: State of the practice Publication No:FHWA- HRT-11-21 2011
  19. Michael Mamlouk, and Mena I.Souliman, (2017) “Simple Approach for Designing Sustainable Pavement with Self-Healing Fatigue Cracking”, American Society of Civil Engineers Volume 143(2),.
  20. Dallas N. Little and Jon A. Epps (2001) “The Benefits of Hydrated Lime in Hot Mix Asphalt” Prepared for National lime association,
  21. Willway, Baldachin et al, “The effect of climate change on Highway Pavements and how to minimise them: Technical Report”.
  22. “Virginia department of transportation”, volume.1 2011.
  23. “Binder selection guidelines for RAP mixtures”, AASHTO M 323
  24. Aboelkasim Diab and Zhanping “Bitumen-Based Prototype to Predict the Workability of Asphalt Concrete Mixtures”
  25. Federal Highway Administration. Foundry sand facts for civil engineers. Federal Highway Administration (FHWA); 2004 May 2004. Report nr FHWA-IF-04-004.
  26. Naga Rajesh, R Srinivas Rao (Nov2017) “Effect on Replacement of Conventional Sand with Used Foundry Sand in Flyash Bricks”, Page No.16701679, Volume No 5,International Journal for Research in Applied Science & Engineering Technology.

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31.

Authors:

Pankaj Choudhary, Upasna Singh

Paper Title:

Ranking Terrorist Organizations Network in India Using Combined Sna-Ahp Approach

Abstract: Terrorism is one of the major concern Worldwide. Many countries over the globe are developing strategies to fight with terrorism, either kinetically or non-kinetically. Terrorist Networks are often covert in nature, that’s why also called Dark Networks. In this effort, Social Network Analysis (SNA) is a well-known technique among researchers analyzing these Dark Terrorist Networks. Various centrality measures of SNA have been evolved over time for targeting the key players in terrorist or covert networks and finding their ranking. On the other hand, Analytical Hierarchy Process (AHP), a multi-criteria decision making technique, enables subjective as well as objective choices of the decision makers over available criteria and makes decisions over various alternatives. Often, centrality measures of SNA result in different ranking and different set of key players, which makes terrorist targeting very tough. To deal with it, we propose a combined SNA-AHP approach for obtaining the consolidated/final/overall ranking of nodes in various terrorist networks. We consider a case study of a Network of various Terrorist Organizations involved in terrorist activities in India from 2000 to 2003. Final ranking of these terrorist organization is obtained using combined SNA-AHP approach. These rankings are compared with other rankings obtained from existing centrality approaches. To assess the robustness of our approach, sensitivity analysis is proposed and recommended. The results of this study show that the combined SNA-AHP approach delivers promising results in ranking and targeting dark/covert/terrorist networks.

Keywords: Terrorist Network, Analytical Hierarchy Process (AHP), Social Network Analysis (SNA), Centrality Measures, Key Players, Ranking Terrorist Network, Terrorist Targeting, Dark Networks 

References:

  1. Krebs, V. E. (2002). Mapping networks of terrorist cells. Connections, 24(3), 43-52.
  2. Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social networks, 1(3), 215-239.
  3. Choudhary, P., & Singh, U. (2015). A Survey on Social Network Analysis for Counter-Terrorism. International Journal of Computer Applications, 112(9).
  4. Choudhary, P., & Singh, U. (2016). Ranking Terrorist Nodes of 26/11 Mumbai Attack using Analytical Hierarchy Process with Social Network Analysis. In 11th Annual Symposium on Information Assurnace (ASIA’16) (pp. 46-51).
  5. Choudhary, P., & Singh, U. (2016). Ranking Terrorist Nodes of 9/11 Network using Analytical Hierarchy Process with Social Network Analysis. In International Symposium on the Analytic Hierarchy Process (ISAHP’16) (pp. 46-51).
  6. Choudhary, P., & Singh, U., Ranking in Terrorist Networks: A Decision Maker’s Outlook using combined SNA-AHP Approach. In Decision Support System, in press.
  7. Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical Modelling, 9(3), 161-176.
  8. Saaty, T. L. (2000). Decision Making for Leaders; The Analytical Hierarchy Process for Decisions in a Complex World, Belmont, CA: Wadsworth. Pittsburgh: RWS Publications.
  9. Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International journal of services sciences, 1(1), 83-98.
  10. Fox, W. P., & Everton, S. F. (2014). Using data envelopment analysis and the analytical hierarchy process to find node influences in a social network. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology.
  11. Basu, A. (2005, June). Social network analysis of terrorist organizations in India. In North American Association for Computational Social and Organizational Science (NAACSOS) Conference (pp. 26-28). NAACSOS.
  12. Saxena, S., Santhanam, K., & Basu, A. (2004). Application of social network analysis (SNA) to terrorist networks in Jammu & Kashmir. Strategic Analysis, 28(1), 84-101.

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32.

Authors:

Hadi, M.I, Dankaka, N.M, Aladodo, M.A, Yakubu, A.I

Paper Title:

Design and Fabrication of Compressed Air Vehicle

Abstract: Increase in the energy consumption rate in this present day’s pose to cause a great number of hazards to man and his environment. With the aim of curbing this, researchers, engineers, scientist, and environmentalist around the world have taken great steps, but not all the steps have been applied to our physical environment. One of the least explored is compressed air powered vehicle, which can help in reducing a great deal of the hazards. Compressed air engines offer advantages of no pollution, light weight, reduced cost of maintenance and production over others engines using fossil fuels. The compressed air engine project involves modification of an internal combustion engine to operate on compressed air. A single cylinder four-stroke engine (Lifan 110 motorcycle) was selected alongside the designed frame considering design results. Air induction transmission systems were also designed. Several estimations of theoretical power were made along with estimated run time. The engine was fully assembled and incorporated into the frame. Although there were no measuring instruments within our capability to test for the flow rate giving the output power of the engine. The theoretical computations showed that efficiency of the engine running at a given pressure would be lower than that of engine running on fossil fuels. It was concluded that, while this type of engine may run on compressed air, it is likely that more powerful modified internal combustion engines would be more promising for accomplishing the project’s goal of an efficient compressed air engine.

Keywords: Compressed air, Lifan 100, Fossil fuel, IC-engines.

References:

  1. Abhishek L., (2012). Design and Dynamic Analysis of single stroke compressed air Engine.
  2. Jalandhar Delhi. G.T Punjab india. Archer M., and Bell G., Advanced Electronic Fuel Injection Systems – An Emissions Solution for both 2- and4-stroke Small Vehicle Engines. SAE, 2001, Paper 2001-01-0010
  3. Bhandari V., (2010). Design of Machine Elements. McGraw Hill.
  4. Dhyeya O., (2010). Development of Compressed air Charged Vehicle Retrieved from http://www.researchpublish.com.
  5. Gordon P. (1996). Design and Simulation of Two-stroke engines. 2nd ed. Society of Automotive Engineers, Inc.,
  6. Haliburton M., (2008). Pure Energy Systems News, Engine air’s Ultra- Efficient Rotary Compressed-Air Motor, Retrieved from http:// pesn.com /2006/05 /11/ 9500269_ Engineair_ Compressed- Air_ Motor.pdf
  7. Harold A., (2004). Cam design handbook, 1st edition. McGraw Hill companies, Inc.
  8. Hamilton T., (2008). The Air Car Preps for Market. Retrieved From: http://www.technologyreview.com/Energy/20071
  9. ISO-Standards – ICS 27.020: internal combustion Engine.
  10. ISO- Standards Power Engines ISO/TC 22/SC 34 Power shaft.
  11. Jadpati B., Gupta M., …& Sharma M., (2014). Design of compressed air engine. Amit school of Engineering and technology
  12. John A., (2013). Chain and sprocket. Retrieved http://grabcad.com/library/chain
  13. Khabbab M. and Ahmed M., (2014) Modification of a single cylinder petrol engine to run on compressed air. Khartoum University.
  14. Kumar N. and Bank U., (2013). Compressed air Retrofit for Existing Motor Vehicle, Delhi Technical University India
  15. Khurmi S. and Gupta J., (2008). A Textbook of Machine Design. Eurasia Publishing House (PVT.) Ltd. RAM NAGAR, NEW DELHI-110055.
  16. Larson E. and Kenward A., (2011). A Roadmap to Climate-Friendly Cars. Retrived :http:/ /www. climatecentral.org/wgts/leafapp/Climate_Friendly_Cars_2012.pdf
  17. Manish M. and Prawn R., (2014). study and Development of compressed air engine. University of Agriculture and technology, Elawa.
  18. Patel B., Barot R.,& Sharma, V.(2016). Air Powered Engine. National Conference on recent trends in Engineering & Technology.
  19. Rajput K., (2011). Engineering Thermodynamics 3rd Edition. Laxmi Publication LTD New Delhi
  20. Reimpel D. and Stoll D., (2001) The Automotive chassis, 2nd edition. Butterwatz-Heinmann.
  21. Robert L. (2012). Internal Combustion Engine. Mc Graw- hill compony ibc. New York.
  22. Stone R. and Ball J., Automotive engineering fundamentals. Warrendale, Pa: SAE – International, 2004.
  23. Thipse D., (2008). Compressed air car. Engine development laboratory automotive research association of India.

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33.

Authors:

Manish Jain, Dinesh Gopalani

Paper Title:

AOP Approach for Testing Program Invariants

Abstract: Mankind is becoming increasingly dependent on software technology which intensifies the need for thorough software testing and development of automated software testing techniques. We have proposed Aspect Oriented Programming (AOP) as a potential methodology for performing various types of automated software testing. In this paper, we have particularly demonstrated the use of AOP for performing testing of invariants in software artifacts. Invariants are assertions about the state of a program that are expected to be true each time control reaches a particular point in the program. If an assertion is found not to be true, then such condition corresponds to a bug discovery. In this paper, adherence to run time as well as compile time invariants in Java applications has been tested using AspectJ, which has become the de-facto standard for AOP. We established that our AOP approach for testing invariants has got several advantages like faster test execution, no test-code scattering etc.

Keywords: Aspect oriented programming, AspectJ, aspects, crosscutting, invariant testing, software testing.

References:

  1. Hussain, A. Razak, and E. Mkpojiogu, “The perceived usability of automated testing tools for mobile applications,” Journal of Engineering Science and Technology, vol. 12, pp. 89–97, 04 2017.
  2. S. Kochhar, F. Thung, N. Nagappan, T. Zimmermann, and D. Lo, “Understanding the test automation culture of app developers,” in 2015 IEEE 8th International Conference on Software Testing, Verification and Validation (ICST), April 2015, pp. 1–10.
  3. Jain and D. Gopalani, “Use of aspects for testing software applications,” in 2015 IEEE International Advance Computing Conference, June 2015, pp. 282–285.
  4. Jain and D. Gopalani, “Memory leakage testing using aspects,” in 2015 International Conference on Applied and Theoretical Computing and Communication Technology, Oct 2015, pp. 436–440.
  5. Jain and D. Gopalani, “Aspect oriented programming and types of software testing,” in 2016 Second International Conference on Computational Intelligence Communication Technology, Feb 2016, pp. 64–69.
  6. Jain and D. Gopalani, “Testing application security with aspects,” in 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), March 2016, pp. 3161–3165.
  7. Duclos, S. L. Digabel, Y. G. Gueheneuc, and B. Adams, “Acre: An automated aspect creator for testing C++ applications,” in IEEE 7th European Conference on Software Maintenance and Reengineering, 2013, pp. 121–130.
  8. Sioud, “Gestion de cycle de vie des objets par aspects pour C++,” Master’s thesis, UQaC, 2006.
  9. Sokenou and S. Herrmann, “Aspects for testing aspects?” in 1st Workshop on Testing Aspect-Oriented Programs, 2005.
  10. Copty and S. Ur, “Multi-threaded testing with AOP is easy, and it finds bugs!” Lecture Notes in Computer Science, vol. 3648, pp. 740–749, 2005.
  11. B. Daszczuk, “Invariant testing technique for debugging a structured operating system,” Microprocess. Microsyst., vol. 11, no. 4, pp. 205–208, May 1987. [Online]. Available: http://dx.doi.org/10.1016/ 0141-9331(87)90339 5
  12. D. Ernst, J. H. Perkins, P. J. Guo, S. McCamant, C. Pacheco, M. S. Tschantz, and C. Xiao, “The Daikon system for dynamic detection of likely invariants,” Sci. Comput. Program., vol. 69, no. 1-3, pp. 35–45, December 2007.
  13. Hangal and M. S. Lam, “Tracking down software bugs using automatic anomaly detection,” in Proceedings of the 24th International Conference on Software Engineering. ICSE 2002, May 2002, pp. 291–301.
  14. D. Ernst, J. Cockrell, W. G. Griswold, and D. Notkin, “Dynamically discovering likely program invariants to support program evolution,” in IEEE transactions on software engineering, vol. 27, 2001, pp. 99–123.
  15. R. Kuhn and V. Okun, “Pseudo exhaustive testing for software,” in 30th Annual IEEE Software Engineering Workshop, 2006, pp. 153–158.
  16. Rafi, K. Moses, K. Petersen, and M. Mantyla, “Testing non-functional requirements with aspects,” in IEEE 7th International Workshop on Automation of Software Test AST, 2012, pp. 36–42.

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34.

Authors:

V. Suma Deepthi, M. Maheswari, M. Vibhavari, K. Prasanth Kumar

Paper Title:

Penalty Quoted Cost Approach for Loss Allocation in a Transmission line by Considering the Mutual Inductance

Abstract: In deregulated electricity market, there is a significance of Loss and Cost Allocation due to transmission. The real power loss from the generators and its associated cost is allocated to the concerned parties in a fair manner by Independent System Operator (ISO). In the cost allocation process there is a participation of generators and loads. The effective part of the paper is there is an impact of mutual inductance (MI) which involves in transmission line in transmission cost/loss allocation phenomena for multilateral contracts is illustrated using a test bus system. To determine the effect of mutual inductance penalized quoted cost (PQC) based approach has discussed. Effect of mutual inductance is tested on an IEEE-4bus system. The simulation results are obtained using MATLAB R2014a. The result shows that there is a significant impact on transmission loss due to mutual inductance which cannot be neglected in the Allocation of loss process.

Keywords: penalized quoted cost, loss/cost allocation, multilateral contracts, mutual inductance and independent system operator.

References:

  1. John Grainger, William Stevenson, "Power System Analysis", Tata McGraw Hill Publisher, India, 1994
  2. Kusic GL, "Computer aided power system analysis", Englewood Cliffs - N.J : Prentice-Hall, 1986.
  3. Pai MA, "Computer techniques in power system analysis", Tata/McGraw-Hill, New Delhi, 1979.
  4. Stagg GW, El-Abiad AH, "Computer methods in power system analysis", New York: McGraw-Hill, 1968.
  5. Pai MA, "Computer techniques in power system analysis",Tata/McGraw-Hill, New Delhi, 1979.
  6. John Grainger, William Stevenson, "Power System Analysis", Tata McGraw Hill Publisher, India, 1994.
  7. C. Schweppe, M. Caramanis, R. Taboras and R. Bohn, “Spot Pricing of Electricity”, Kluwer Academic Publishers, Boston, 1998.

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35.

Authors:

Vikas Pandey, M.V Padmavati, Ramesh Kumar

Paper Title:

Rule Based Parts of Speech Tagger for Chhattisgarhi Language

Abstract: There is an increasing demand for machine translation systems for various regional languages of India. Chhattisgarhi being the language of the young Chhattisgarh state requires automatic languages translating system. Various types of natural language processing (NLP) tools are required for developing Chhattisgarhi to Hindi machine translation (MT) system. In this paper, we are presenting rule based parts of speech tagger for Chhattisgarhi language. Parts of Speech tagging is a procedure in which each word of sentence is assigned a tag from tag set. The Parts of Speech tagger is based on rule base which is formed by taken into consideration the grammatical structure of Chhattisgarhi language. The system is constructed over corpus size of 40,000 words with tag set consists of 30 different parts of speech tags. The corpus is taken from various Chhattisgarhi stories. The system achieves an accuracy of 78%.

Keywords: Chhattisgarhi, Machine Translation, Natural Language Processing, Parts of Speech tagger, Rule Based System.

References:

  1. Agrawal, R., Ambati, B., & Singh, A.Singh.(2012). A GUI to Detect and Correct Errors in Hindi Dependency Treebank.  In Proc.of Eighth International Conference on Language Resources and Evaluation, Istanbul, Turkey, 1907-1911.  
  2. Hasan, M., F.,Uzzaman, N., & Khan, M.(2006 ). Comparison of Different POS Tagging Techniques (n- grams, HMM and Brill’s Tagger) for Bangla. International Conference on Systems, Computing Scienc and Software Engineering (SCS2 06) of International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering.
  3. Kumawat, D., & Jain,V. (2015). POS Tagging Approaches: A Comparison. International Journal of Computer Applications ,vol 118,32-38    
  4. Antony, P.,J.(2011). Parts Of Speech Tagging for Indian Languages: A Literature Survey. International Journal of Computer Applications, Vol 34, 22-29.
  5. Ekbal, A., Haque, R, & Bandhopadha, ( 2007). Bengali part of speech tagging using Conditional Random  Field. In Proc. of SPSAL2007. 131-136.
  6. Shrivastav, , & Bhattacharyya, P. ( 2008). Hindi POS Tagger Using Naive Stemming: Harnessing Morphological Information without Extensive Linguistic Knowledge. In Proc.of ICON, 1-6
  7. Sharia, , Das, D., Sharma U. , Kalita, J. (2009). Part of Speech Tagger for Assamese Text  . In Proc. of the ACL-IJCNLP, 33-36.
  8. Joshi, , Darbari,  H., & Mathur, I. (2013). HMM Based POS Tagger For Hindi. In Proc.of CCSIT, SIPP, AISC, PDCTA, 341-349

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36.

Authors:

S. Aruna Mastani, Patra Suresh Reddy

Paper Title:

On Timing Closure: Hold-Violation Removal using Insertion of Buffers, Inverters and Delay Cells

Abstract: Timing closure plays a major role in the Physical design synthesis. In the process of timing optimization, buffers, inverters, delay cells are used as delay elements inorder to speedup the circuit. Given with the violated path proper selection of combination of delay elements is to be made to meet the hold requirement of the path. Here, in this work a standard industrial design is taken having 5241 violated paths. For these paths, hold time is computed as per the linear programming optimization. Timing closure is done by various combinations of buffers, inverters and delay cells. Discrete buffers, Complex timing constraints and accurate timing models/analysis make time consuming and problem difficult to solve. The linear programming-based methodology is presented to model the setup and hold-time constraints. Then based on the solution to the linear programming optimization, buffers, inverters and delay cells are inserted as delay elements to solve hold violations. The implemented approach where delay cells, buffers, inverters are used as delay elements for optimization and using only buffers as delay elements in optimization process are tested on industrial design together with the industrial hold optimization flow, and better results achieved in terms of minimum hold slack, hold violations and utilization are reported.¬¬ Compared to the delay insertion using buffers only, the implemented approach can obtain 31% worst hold slack reductions and better utilization for the industrial circuit level design. Analysis of timing paths and removal of hold violation problem in physical design flow is implemented using TCL and PERL scripts in cadence encounter tool.

Keywords: Delay Insertion, Hold Violation, Physical Design, Utilization.

References:

  1. Pei-Ci Wu ; Martin D. F. Wong ; Ivailo Nedelchev ; Sarvesh Bhardwaj ; Vidyamani Parkhe on timing closure: buffer insertion for hold violation removal 51st ACM/EDAC/IEEE Design Automation Conference (DAC) Pages:1 – 6,2014
  2. -H. Huang, C.-H. Cheng, C.-M. Chang, and Y.-T. Nieh. Clock period minimization with minimum delay insertion. InDesign Automation Conference, 2007. DAC’07. 44th ACM/IEEE, pages 970–975. IEEE, 2007.
  3. -H. Huang, G.-Y. Jhuo, and W.-L. Huang. Minimum buffer insertions for clock period minimization. In Computer Communication Control and Automation (3CA), 2010 International Symposium on, volume 1, pages 426–429.IEEE, 2010.
  4. B. Kahng, J. Lienig, I. L. Markov, and J. Hu. VLSI Physical Design: From Graph Partitioning to Timing Closure. 2011..
  5. Lin and H. Zhou. Clock skew scheduling with delay padding for prescribed skew domains. In Design AutomationConference, 2007. ASP-DAC’07. Asia and South Pacific,pages 541–546. IEEE, 2007
  6. M. Ozdal, S. Burns, and J. Hu. Gate sizing and device technology selection algorithms for high-performance industrial designs. In Proceedings of the InternationalConference on Computer-Aided Design, pages 724–731.IEEE Press, 2010.
  7. V. Shenoy, R. K. Brayton, and A. L. Sangiovanni-Vincentelli. Minimum padding to satisfy short path constraints. In Computer-Aided Design, 1993.ICCAD-93. Digest of Technical Papers., 1993 IEEE/ACM International Conference on, pages 156–161. IEEE, 1993.
  8. -P. Tu, C.-H. Chou, S.-H. Huang, S.-C. Chang, Y.-T. Nieh, and C.-Y. Chou. Low-power timing closure methodology for ultra-low voltage designs. In Proc. Int.Conf. on Computer-Aided Design, pages 697–704, 2013.

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37.

Authors:

Md. Lizur Rahman, Ifrat Jahan, Akash Saha, Md. Nawab Yousuf Ali

Paper Title:

Efficient Recognition of Bangla Handwritten Digits Based on Deep Neural Network

Abstract: Nw-a-days world has started to move into machine based technologies. Recognition of various features, shapes, images etc., has become extremely excited topics over recent years. Many authors proposed various techniques to recognition of handwritten digits on different languages. This paper presents a new technique based on deep neural network for the purpose of efficiently recognition of handwritten digits for Bangla language. Two datasets are used in this paper including CMATERDB 3.1.1 dataset and ISI (Indian Statistical Institute) dataset. About 24500 samples are used for training purpose and 4800 samples are used for testing purpose and the proposed technique achieves 98.70 percent accuracy. This paper also presents detailed overview on artificial neurons, and deep neural network. In addition, the efficiency of proposed method shown by comparing the results with other existing techniques.

Keywords: Handwritten Digit Recognition; Perceptron; Sigmoid Neuron; Dropout; Deep Neural Network; Artificial Neuron; Bangla Digit.

References:

  1. Blakemore, C., & Campbell, F. W. (1969). On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images. The Journal of physiology, 203(1), 237-260.
  2. Sutskever, I., Vinyals, O., & Le, Q. V. (2014). Sequence to sequence learning with neural networks. In Advances in neural information processing systems (pp. 3104-3112).
  3. Belongie, S., Malik, J., & Puzicha, J. (2002). Shape matching and object recognition using shape contexts. CALIFORNIA UNIV SAN DIEGO LA JOLLA DEPT OF COMPUTER SCIENCE AND ENGINEERING.
  4. Soltanzadeh, H., & Rahmati, M. (2004). Recognition of Persian handwritten digits using image profiles of multiple orientations. Pattern Recognition Letters, 25(14), 1569-1576.
  5. Ashiquzzaman, A., & Tushar, A. K. (2017). Handwritten Arabic numeral recognition using deep learning neural networks. arXiv preprint arXiv:1702.04663.
  6. Parvin, H., Alizadeh, H., Moshki, M., Minaei-Bidgoli, B., & Mozayani, N. (2008, November). Divide & conquer classification and optimization by genetic algorithm. In Convergence and Hybrid Information Technology, 2008. ICCIT'08. Third International Conference on (Vol. 2, pp. 858-863). IEEE.
  7. Rahman, L., Sarowar, G., & Kamal, S. (2018). Teenagers Sentiment Analysis from Social Network Data. In Social Networks Science: Design, Implementation, Security, and Challenges (pp. 3-23). Springer, Cham.
  8. Kiani, K., & Korayem, E. M. (2015, November). Classification of Persian handwritten digits using spiking neural networks. In Knowledge-Based Engineering and Innovation (KBEI), 2015 2nd International Conference on (pp. 1113-1116). IEEE.
  9. Gardner, M. W., & Dorling, S. R. (1998). Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences. Atmospheric environment, 32(14-15), 2627-2636.
  10. Glorot, X., Bordes, A., & Bengio, Y. (2011, June). Deep sparse rectifier neural networks. In Proceedings of the fourteenth international conference on artificial intelligence and statistics (pp. 315-323).
  11. Hagan, M. T., Demuth, H. B., Beale, M. H., & De Jesús, O. (1996). Neural network design (Vol. 20). Boston: Pws Pub..
  12. M. Hawkins, “The problem of overfitting,” Journal of chemical information and computer sciences, vol. 44, no. 1, pp. 1–12, 2004.
  13. Srivastava, G. E. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: a simple way to prevent neural networks from overfitting.” Journal of Machine Learning Research, vol. 15, no. 1, pp. 1929–1958, 2014.
  14. Shopon, M., Mohammed, N., & Abedin, M. A. (2017, February). Image augmentation by blocky artifact in Deep Convolutional Neural Network for handwritten digit recognition. In Imaging, Vision & Pattern Recognition (icIVPR), 2017 IEEE International Conference on (pp. 1-6). IEEE.
  15. Bhattacharya, U., and Chaudhuri, B. B., Handwritten numeral databases of indian scripts and multistage recognition of mixed numerals, In IEEE transactions on pattern analysis and machine intelligence, 31(3) on pp.444-457. IEEE,2009.
  16. Das, N., Reddy, J. M., Sarkar, R., Basu, S., Kundu, M., Nasipuri, M., & Basu, D. K. (2012). A statistical–topological feature combination for recognition of handwritten numerals. Applied Soft Computing, 12(8), 2486-2495.

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38.

Authors:

T. Lakshmi Praveena, N. V. Muthu Lakshmi

Paper Title:

Sentiment Analysis on Autism Spectrum Disorder using Twitter Data

Abstract: Autism is the behavioral disorder; it leads to developmental disorder and repetitive disorder. Autism Spectrum Disorder (ASD) is one of the disorders of autism. ASD diagnosed based on assessing social behavior and clinical tests of autistic children. The assessment process is conducted by multi disciplinary team of doctors based on the universal standard questionnaire. The objective of this paper is to predict analytical values from semi structured data posted in twitter by individuals, caregivers of autistic children. The different Natural Language Processing and Topic Modeling algorithms are applied to analyze autism based on tweets collected. Approximately 10k tweets dataset is used for this analysis. NLP and topic modeling are reliable and efficient methods to perform text analysis with 50% less time and the results are 90% accurate compared to regular text processing methods. The analysis performed for genetic analysis, effect of vaccination analysis and behavior analysis. The analytical results are used to learn the genetic impact on ASD, vaccination effect on ASD. And also used learn the behavior changes and population of autistic children. Results are useful for the parents, caregivers, individuals and other researchers to learn about ASD.

Keywords: ASD, Sentiment Analysis, Twitter, Natural language processing

References:

  1. Yerys, B.E., Pennington, B.F., 2011. How do we establish a biological marker for a behaviorally defined disorder? Autism as a test case. Autism Res. 4 (4), 239–241. http://dx.doi.org/10.1002/aur.20421710504.
  2. Anibal Sólon Heinsfelda, Alexandre Rosa Francob,c,d, R. Cameron Craddockf,g, Augusto Buchweitzb,d,e, Felipe Meneguzzia,b,*,Identification of autism spectrum disorder using deep learning and the ABIDE dataset, http://dx.doi.org/10.1016/j.nicl.2017.08.017
  3. Glen Coppersmith, Ryan Leary, Patrick Crutchley and Alex Fine, Natural language Processing of Social Media as Screening for Suicide Risk, Biomedical  informatics Insights Volume 10: 1–11.
  4. Ashish Bindra,SocialLDA:Scalable Topic Modeling in Social Networks, A thesis submitted in partial ful_llment of the requirements for the egree of Master of Science University of Washington 2012.
  5. Charu Virmani Research Scholar, YMCAUST, India. Dr. Anuradha Pillai Ymcaust, Faridabad, India. Extracting information from Social Network using NLP,  International Journal of Computational Intelligence Research ISSN 0973-1873 Volume 13, Number 4 (2017), pp. 621-630.
  6. Michael J. Paul1*, Mark Dredze1,2, Discovering Health Topics in Social Media Using Topic Models, PLOS ONE | www.plosone.org  August 2014 | Volume 9 | Issue 8 | e103408
  7. Benton A, Coppersmith G, Dredze M. Ethical research protocols for social media health research. Paper presented at: Proceedings of the First Workshop on Ethics in Natural Language Processing; April 4, 2017; Valencia, Spain:94–102. New York, NY: ACL.
  8. Sap M, Park G, Eichstaedt JC, et al. Developing age and gender predictive lexica over social media. Paper presented at: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP); October 25–29, 2014; Doha, Qatar:1146–1151. New York, NY: ACL.
  9. Kim Y, Jernite Y, Sontag D, Rush AM. Character-aware neural language models, 2015.http://arxiv.org/abs/1508.06615.
  10. Kim Y. Convolutional neural networks for sentence classification, 2014. http://arxiv.org/abs/1408.5882.
  11. Yang Z, Yang D, Dyer C, He X, Smola AJ, Hovy EH. Hierarchical attention networks for document classification. Paper presented at: HLT-NAACL; June 12–17, 2016; San Diego, CA.
  12. Pennington J, Socher R, Manning CD. GloVe: global vectors for word representation. Paper presented at: Empirical Methods in Natural Language Processing (EMNLP); October 25–29, 2014; Doha, Qatar:1532–1543. New York, NY: ACL.
  13. Bahdanau D, Cho K, Bengio Y. Neural machine translation by jointly learning to align and translate, 2014. https://arxiv.org/abs/1409.0473.
  14. Mikal J, Hurst S, Conway M. Ethical issues in using twitter for population-level depression monitoring: a qualitative study. BMC Med Ethics. 2016;17:22. [PMC free article] [PubMed]
  15. Hsin H, Torous J, Roberts L. An adjuvant role for mobile health in psychiatry. JAMA Psychiatry. 2016;73:103–104. [PubMed]

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39.

Authors:

Shivani Jain, Seeja.K.R, Rajni Jindal

Paper Title:

A New Method for Semantic Similarity Assessment using Fuzzy Formal Concept Analysis & Fuzzy Set Similarity Measure

Abstract: Measuring the accurate semantic similarity between the words is a major issue in various applications of artificial intelligence and computational linguistics areas such as natural language processing, text-mining, information retrieval and for development of semantic web. In the past, many approaches have been proposed and adopted to evaluate similarity by using the knowledge based systems such as Word Net and MeSH ontology. In this paper we have proposed a new method; based on hybridization approach in knowledge based system. In this we have used feature based method and fuzzy Set theory. In feature based approach, properties or features are used for measuring the similarity as compare to edge and content information approaches. Our approach is investigated on standard dataset like R&G, M&C and 353-TC, which shows prominent improvement in the judgment of semantic similarity score between the words. This approach can be further used among cross ontology and fuzzy ontology as it is based on the feature based measure and fuzzy set theory.

Keywords: Semantic Similarity Measures, Formal concept Analysis, Fuzzy Formal Concept Analysis, Word Net

References:

  1. Farrar and T. Langendoen, “A Linguistic Ontology for the Semantic Web,” pp. 1–7, 2001.
  2. Hliaoutakis, G. Varelas, E. Voutsakis, E. G. M. Petrakis, and E. Milios, “Information Retrieval by Semantic Similarity,” Int. J. Semant. Web Inf. Syst., vol. 2, no. 3, pp. 55–73, 2006.
  3. R. Gruber, “A translation approach to portable ontology specifications,” Knowl. Acquis., vol. 5, no. 2, pp. 199–220, 1993.
  4. Dutta, U. Chatterjee, and D. P. Madalli, “YAMO : Yet Another Methodology for large-scale faceted Ontology construction,” 2015.
  5. A. Miller and W. G. Charles, “Language and Cognitive Processes Contextual correlates of semantic similarity Contextual Correlates of Semantic Similarity,” Lang. Cogn. Process., vol. 6, no. 1, pp. 1–28, 1991.
  6. Martinez-Gil, “An overview of textual semantic similarity measures based on web intelligence,” Artif. Intell. Rev., vol. 42, no. 4, pp. 935–943, 2012.
  7. Collobert, J. Weston, L. Bottou, M. Karlen, K. Kavukcuoglu, and P. Kuksa, “Natural Language Processing (Almost) from Scratch,” J. Mach. Learn. Res., vol. 12, pp. 2493–2537, 2011.
  8. J. Jiang and D. W. Conrath, “Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy,” Proc. Int. Conf. Res. Comput. Linguist., 1997.
  9. a. Miller, “WordNet: a lexical database for English,” Commun. ACM, vol. 38, no. 11, pp. 39–41, 1995.
  10. Budanitsky and G. Hirst, “Evaluating WordNet-based Measures of Lexical Semantic Relatedness,” Comput. Linguist., vol. 32, no. 1, pp. 13–47, 2006.
  11. Naik and P. A. Kharwar, “Knowledge Discovery of Weighted RFM Sequential Patterns With Multi Time Interval From Customer Sequence Database.”
  12. R. Curran, “From Distributional to Semantic Similarity Doctor of Philosophy,” p. 177, 2003.
  13. Mihalcea, C. Corley, and C. Strapparava, “Corpus-based and knowledge-based measures of text semantic similarity,” Proc. 21st Natl. Conf. Artif. Intell., vol. 1, pp. 775–780, 2006.
  14. Aamodt et al., “Requirements Engineering,” Requir. Eng., vol. 19, no. 1, pp. 35–46, 2013.
  15. Xue, C. Fu, and Z. Shaobin, “A study on sentiment computing and classification of sina weibo with Word2vec,” Proc. - 2014 IEEE Int. Congr. Big Data, BigData Congr. 2014, no. 2013, pp. 358–363, 2014.
  16. Hliaoutakis, “Semantic Similarity Measures in MeSH Ontology and their application to Information Retrieval on Medline,” Interface, pp. 1–79, 2005.
  17. Wang and X. Liu, “Knowledge-Based Systems A new model of evaluating concept similarity q,” Knowledge-Based Syst., vol. 21, no. 8, pp. 842–846, 2008.
  18. Saruladha, G. Aghila, and S. Raj, “A Survey of Semantic Similarity Methods for Ontology Based Information Retrieval,” 2010 Second Int. Conf. Mach. Learn. Comput., pp. 297–301, 2010.
  19. Lin and E. Hovy, “From Single to Multi-document Summarization: A Prototype System and its Evaluation,” Comput. Linguist., no. July, pp. 457–464, 2002.
  20. B. Gao, B. W. Zhang, and X. H. Chen, “A WordNet-based semantic similarity measurement combining edge-counting and information content theory,” Eng. Appl. Artif. Intell., vol. 39, pp. 80–88, 2015.
  21. Gao, B. Zhang, and X. Chen, “Engineering Applications of Arti fi cial Intelligence A WordNet-based semantic similarity measurement combining edge-counting and information content theory,” Eng. Appl. Artif. Intell., vol. 39, pp. 80–88, 2015.
  22. Pesquita, D. Faria, A. O. Falcão, P. Lord, and F. M. Couto, “Semantic similarity in biomedical ontologies,” PLoS Comput. Biol., vol. 5, no. 7, 2009.
  23. Resnik, “Using Information Content to Evaluate Semantic Similarity in a Taxonomy,” vol. 1, 1995.
  24. Formica, “Concept similarity in Formal Concept Analysis : An information content approach,” vol. 21, pp. 80–87, 2008.
  25. Banu, S. S. Fatima, K. Ur, and R. Khan, “Information Content Based Semantic Similarity Measure for Concepts Subsumed By Multiple Concepts,” vol. 7, no. 3, pp. 85–94.
  26. Tversky, “Features of similarity. - 1977 - Tversky.pdf.”
  27. J. Egenhofer, “Determining Semantic Similarity Among Entity Classes from Different Ontologies M. Andrea Rodríguez and Max J. Egenhofer IEEE Transactions on Knowledge and Data Engineering,” no. 1.
  28. Jiang, X. Zhang, Y. Tang, and R. Nie, “Feature-based approaches to semantic similarity assessment of concepts using Wikipedia,” Inf. Process. Manag., vol. 51, no. 3, pp. 215–234, 2015.
  29. A. Zadeh, “Fuzzy Sets,” Inf. Control, no. 8, pp. 338–353, 1965.
  30. Priss, “Linguistic Applications of Formal Concept Analysis,” no. 1996, pp. 149–160, 2005.
  31. Hernández, F. Prieto, M. Laguna, and Y. Crespo, “Formal concept analysis support for conceptual abstraction in database reengineering,” Database Manag. Reengineering, no. 34, 2002.
  32. Priss and L. J. Old, “Modelling lexical databases with formal concept analysis.,” J. Univers. Comput. Sci., vol. 10, no. 8, pp. 1–19, 2004.
  33. T. Quan, S. C. Hui, and T. H. Cao, “FOGA : A Fuzzy Ontology Generation Framework for Scholarly Semantic Web,” Knowl. Discov. Ontol., 2004.
  34. C. Chen, C. T. Bau, and C. J. Yeh, “Merging domain ontologies based on the WordNet system and Fuzzy Formal Concept Analysis techniques,” Appl. Soft Comput. J., vol. 11, no. 2, pp. 1908–1923, 2011.
  35. Cross, “Fuzzy semantic distance measures between ontological concepts,” IEEE Annu. Meet. Fuzzy Information, 2004. Process. NAFIPS ’04., vol. 2, pp. 1–6, 2004.
  36. Joshi, A. Verma, A. Kandpal, S. Garg, R. Chauhan, and R. H. Goudar, “Ontology based fuzzy classification of web documents for semantic information retrieval,” 2013 Sixth Int. Conf. Contemp. Comput., pp. 1–5, 2013.
  37. Tunde, J. Rancz, V. Varga, and J. Puskas, “A software tool for data analysis based on formal concept analysis,” vol. LIII, no. 2, pp. 67–78, 2008.
  38. Rubenstein and J. B. Goodenough, “Contextual correlates of synonymy,” Commun. ACM, vol. 8, no. 10, pp. 627–633, 1965.
  39. Budanitsky and G. Hirst, “Semantic distance in WordNet : An experimental , application-oriented evaluation of five measures,” Work. WordNet Other Lex. Resour. Second Meet. North Am. Chapter Assoc. Comput. Linguist., vol. 2, no. 12, pp. 29–34, 2001.
  40. Rada, H. Mili, E. Bicknell, and M. Blettner, “Development and Application of a Metric on Semantic Nets,” IEEE Trans. Syst. Man Cybern., vol. 19, no. 1, pp. 17–30, 1989.
  41. Wu and M. Palmer, “Verb Semantics and Lexical Selection,” 1994.

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Authors:

Shikha Pandey, Arpana Rawal

Paper Title:

An NLP Based Plagiarism Detection Approach for Short Sentences

Abstract: The notable issue in the fields of plagiarism detection is, to assess the semantic similarity between obfuscated sentences, and it becomes more completed in case of short sentences (only 4-8 words). An innovative approach, typed dependencies relationship (TDR), based on Natural Language processing is presented for detecting plagiarism on short sentences. In this study proposed approach performed on previous datasets of short sentences and compared results with 3 state-of-art methods. The investigation shows that the proposed calculation has exceptional execution in taking care of sentences with complex linguistic structure.

Keywords: Type Dependencies Relationship, Plagiarism Detection, Sentence Similarity, Syntactic and Semantic Similarity

References:

  1. Gomaa Wael H. & Fahmy A. (2013) A Survey of Text Similarity Approaches, International Journal of Computer Applications (0975 – 8887)
  2. Hall, P. A. V. & Dowling, G. R. (1980) Approximate string matching, Comput. Surveys, 12:381-402.
  3. Peterson, J. L. (1980). Computer programs for detecting and correcting spelling errors, Comm. Assoc. Comput. Mach., 23:676-687.
  4. Jaro, M. A. (1989). Advances in record linkage methodology as applied to the 1985 census of Tampa Florida, Journal of the American Statistical Society, vol. 84, 406, pp 414-420.
  5. Jaro, M. A. (1995). Probabilistic linkage of large public health data file, Statistics in Medicine 14 (5-7), 491-8.
  6. Winkler W. E. (1990). String Comparator Metrics and Enhanced Decision Rules in the Fellegi-Sunter Model of Record Linkage, Proceedings of the Section on Survey Research Methods, American Statistical Association, 354–359.
  7. Needleman, B. S. & Wunsch, D. C.(1970). A general method applicable to the search for similarities in the amino acid sequence of two proteins", Journal of Molecular Biology 48(3): 443–53.
  8. Smith, F. T. & Waterman, S. M. (1981). Identification of Common Molecular Sub sequences, Journal of Molecular Biology 147: 195–197.
  9. Alberto, B., Paolo, R., Eneko A. & Gorka L. (2010). Plagiarism Detection across Distant Language Pairs, In Proceedings of the 23rd International Conference on Computational Linguistics, pages 37–45.
  10. Eugene F. K. (1987). Taxicab Geometry, Dover. ISBN 0-486-25202-7.
  11. Dice, L. (1945). Measures of the amount of ecologic association between species. Ecology, 26(3).
  12. Jaccard, P. (1901). Étude comparative de la distribution florale dans une portion des Alpes et des Jura. Bulletin de la Société Vaudoise des Sciences Naturelles 37, 547-579.
  13. Lund, K., Burgess, C. & Atchley, R. A. (1995). Semantic and associative priming in a high-dimensional semantic space. Cognitive Science Proceedings (LEA), 660-665.
  14. Lund, K. & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments & Computers, 28(2),203-208.
  15. Landauer, T.K. & Dumais, S.T. (1997). A solution to plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge", Psychological Review, 104.
  16. Matveeva, I., Levow, G., Farahat, A. & Royer, C. (2005). Generalized latent semantic analysis for term representation. In Proc. of RANLP.
  17. Gabrilovich E. & Markovitch, S. (2007). Computing Semantic Relatedness using Wikipedia-based Explicit Semantic Analysis, Proceedings of the 20th International Joint Conference on Artificial Intelligence, pages 6–12.
  18. Martin, P., Benno, S. & Maik, A.(2008). A Wikipedia-based multilingual retrieval model. Proceedings of the 30th European Conference on IR Research (ECIR), pp. 522-530.
  19. Turney, P. (2001). Mining the web for synonyms: PMI-IR versus LSA on TOEFL. In Proceedings of the Twelfth European Conference on Machine Learning (ECML).
  20. Mihalcea, R., Corley, C. & Strapparava, C. (2006). Corpus based and knowledge-based measures of text semantic similarity. In Proceedings of the American Association for Artificial Intelligence.(Boston, MA).
  21. Miller, G.A., Beckwith, R., Fellbaum, C.D., Gross, D. & Miller, K. (1990). WordNet: An online lexical database. Int. J. Lexicograph. 3, 4, pp. 235–244.
  22. Resnik, R. (1995). Using information content to evaluate semantic similarity. In Proceedings of the 14th International Joint Conference on Artificial Intelligence, Montreal, Canada.
  23. Lin, D. (1998b). Extracting Collocations from Text Corpora. In Workshop on Computational Terminology , Montreal, Kanada, 57–63.
  24. Jiang, J. & Conrath, D. (1997). Semantic similarity based on corpus statistics and lexical taxonomy. In Proceedings of the International Conference on Research in Computational Linguistics, Taiwan.
  25. Leacock, C. & Chodorow, M. (1998). Combining local context and WordNet sense similarity for word sense identification. In WordNet, An Electronic Lexical Database. The MIT Press.
  26. Wu, Z.& Palmer, M. (1994). Verb semantics and lexical selection. In Proceedings of the 32nd Annual Meeting of International Journal of Computer Applications (0975 – 8887) Volume 68– No.13, April 2013 18 the Association for Computational Linguistics, Las Cruces, New Mexico.
  27. Li, Y., McLean, D., Bandar, Z.A., O’Shea, J.D., Crockett, K., 2006. Sentence similarity based on semantic nets and corpus statistics. IEEE Trans. Knowledge Data Eng. 18, 1138–1150.
  28. Ercan Canhasi 2013, measuring the sentence level similarity, ISCIM 2013, pp. 35-42 © 2013 Authors
  29. Lee, M.C., 2011. A novel sentence similarity measure for semanticbased expert systems. Expert Syst. Appl. 38, 6392–6399.
  30. Alzahrani, S. M., Naomie Salim, Vasile Palade(2015) ,:Uncovering highly obfuscated plagiarism cases using fuzzy semantic-based similarity model, Journal of King Saud University – Computer and Information Sciences  27, 248–268(2015).
  31. Marie-Catherine de, Marneffe, Bill MacCartney, Christopher D. Manning . In LREC (2006).
  32. Sebastian Schuster and Christopher D. Manning2016. In LREC 2016.

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Authors:

Prashant A. Athavale, H. D. Kattimani, P. S. Puttaswamy

Paper Title:

Segmentation of the Lungs from Chest X-Rays: A Simplified Computer Aided Approach

Abstract: The lungs reflect the health condition of a person, and hence it has been imaged and analysed by diagnosticians for over a century, and it requires knowledge and experience. The human observer’s time and effort could be used productively if the lung image analysis is automated. This is especially true in case of screening of the lung chest x-rays. The lung segmentation is by default the first of a series of steps to analyse and interpret the images using a computer. One of the traditional approaches to segmentation of the lungs has been the use of statistical models, and the other is the rule based approach. This paper proposes a fusion method to segment the lungs on chest x-rays, as this modality of imaging is low cost, easy to operate, and gives first-hand information required for diagnosis. The results that are obtained are fast and promising accuracy has been documented. The entire approach can be extended to any organ on a medical image, or any object of interest in a general segmentation problem

Keywords: Lungs Segmentation, Active Shape Models, Computer Aided Diagnosis, Morphological Operation

References:

  1. Chunli Qin, Demin Yao, Yonghong Shi, Zhijian Song, Computer Aided detection in chest radiography based on artificial intelligence: A survey, BioMedical Engineering On line 2018.doi:10.1186/s12938-018-0544
  2. Story A, Aldridge RW, Abubakar I, Stagg HR, Lipman M, et al. (2012) Active case finding for pulmonary tuberculosis using mobile digital chest radiography: An Observational Study. International Journal of Tuberculosis and Lung Disesase 16: 1461–1467.
  3. Shi, Yonghong, Feihu Qi, Zhong Xue, Kyoko Ito, Hidenori Matsuo, and Dinggang Shen. "Segmenting lung fields in serial chest radiographs using both population and patient-specific shape statistics." In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 83-91. Springer, Berlin, Heidelberg, 2006.
  4. Shiraishi, S. Katsuragawa, J. Ikezoe, T. Matsumoto, T. Kobayashi, K. Komatsu, M. Matsui, H. Fujita, Y. Kodera, and K. Doi, "Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists' detection of pulmonary nodules", American Journal of Roentgenology, vol. 174, p. 71-74, 2000.
  5. Chaofeng Li, Guoce Zhu, Xiaojun Wu, Yuanquan Wang, ‘False-Positive Reduction on Lung Nodules Detection in Chest Radiographs by Ensemble of Convolutional Neural Networks’ IEEE Access, Vol-6, 2018. DOI: 10.1109/ACCESS.2018.2817023
  6. Seghers, Dieter ‘Image segmentation using local shape and gray-level appearance models’, Medical Imaging 2006: Image Processing. Vol. 6144. International Society for Optics and Photonics, 2006.
  7. Nagata, Ryoichi, Tsuyoshi Kawaguchi, and Hidetoshi Miyake. "A Rule-Based Algorithm for Detection of Ribcage Boundary in Chest Radio-graphs." In ITC-CSCC: International Technical Conference on Circuits Systems, Computers and Communications, pp. 1001-1004. 2009.
  8. Starcevic, Đorđe S., Vladimir S. Ostojic, and Vladimir S. Petrovic. ‘An open-source digital diagnostic radiography image annotation software’, In Telecommunications Forum (TELFOR), 2016 24th, pp. 1-4. IEEE, 2016.
  9. Zhennan Yan, Jing Zhang, Shaoting Zhang, and Dimitris N. Metaxas, ‘Automatic Rapid Segmentation of Human Lung from 2D Chest X-Ray Images’, MICCAI workshop on Sparsity Techniques in Medical Imaging, 2012.
  10. Prashant A. Athavale, P. S. Puttaswamy, ‘Median Values of Gray Levels for Detection of Lung Contours’, International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT-2015) PESCE, ISBN: 978-1-4673-9563-2
  11. Muyoyeta M, Maduskar P, Moyo M, Kasese N, Milimo D, Spooner R, ‘The Sensitivity and Specificity of Using a Computer Aided Diagnosis Program for Automatically Scoring Chest X-Rays of Presumptive TB Patients Compared with Xpert MTB/RIF in Lusaka Zambia’. PLoS ONE 9(4): e93757. (2014) https://doi.org/10.1371/journal.pone.0093757

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42.

Authors:

S. Phani Venkata Ramana, K. Anitha Reddy, K. Deepthi, K. Chetaswi

Paper Title:

Harmonic Emission of Grid Connected Back To Back Arrangement of Rectifiers in Distribution Networks

Abstract: Emission of Harmonics plays a potent role in distribution systems. The intention of this paper to inspect the harmonic level by the implementation of UPQC (Unified Power Quality Conditioner) at distribution system level. This system offers indirect power quality (PQ) pay of the voltage and also the supply current. The harmonic performance of small grid with respect to different power electronics and grid parameters. Latest studies suggest that the UPQC has high efficiency and better Power quality. This system is very simple and uncomplicated. The equipments used in this system always monitors the harmonic level on the source side by considering the voltage magnitude and supply current. By employing this system, the THD value is very low, injected voltages or currents gets nearer to sinusoidal. The execution of the planned system is simulated in MATLAB/Simulink surrounding

Keywords: Power Quality, UPQC, Active power filter, Sinusoidal, Harmonic content.

References:

  1. firuz zare, hamid soltani, dinesh kumar, pooya davari, hernan andres miranda delpino, and frede blaabjerg “Harmonic Emissions of Three-Phase Diode Rectifiers in Distribution Networks” Received January 3, 2017, accepted February 12, 2017, date of publication February 16, 2017, date of current version March 28, 2017.
  2. Banothu Raju, Fatima Azra “Power Quality Improvement Using D-STATCOM with PI and Fuzzy Logic Controller” International Journal of Computational Science, Mathematics and Engineering Volume 3, Issue.9, 2016
  3. Anitha Rani, Sivakumar.R “Improvement of Power Quality using DVR in Distribution Systems”, International Conference on Engineering Technology and Science-(ICETS’14) On 10th & 11th February Volume 3, Special Issue 1, January 2014
  4. Bhushan S. Rakhonde, Astt.Prof. C. M. Bobade “Harmonic Mitigation using Modified Synchronous Reference Frame Theory” , International Research Journal of Engineering and Technology  Volume: 04 Issue: 08 | Aug -2017
  5. Parag Datar, Vani Datar, S. B. Halbhavi, S G Kulkarni “Synchronous Reference Frame Theory For Nonlinear Loads using Mat-lab Simulink” JETIR (ISSN-2349-5162)  June 2016, Volume 3, Issue 6
  6. J.P.Sridhar, Ayan Sarkar, Nirupam Tarafdar, Nitesh Kumar, Pranav Verma “UPQC Based Power Quality Improvement in Distribution System Connected with PV Arrays” International Journal of Advanced Research in Electrical,Electronics and Instrumentation Engineering, Vol. 5, Issue 5, May 2016
  7. Rajiv Kumar sinku “Study of Unified Power Quality Conditioner for Power Quality Improvement” Department of Electrical Engineering National Institute of Technology, Rourkela May 2015
  8. Bhushan S. Rakhonde, Astt.Prof. C. M. Bobade “ Harmonic Mitigation using Modified Synchronous Reference Frame Theory” International Research Journal of Engineering and Technology (IRJET),  Volume: 04 Issue: 08 | Aug -2017
  9. Suleiman Musa, Mohd Amran Mohd Radzi , Hashim Hizam , Noor Izzri Abdul Wahab ,Yap Hoon and Muhammad Ammirrul Atiqi Mohd Zainuri “Modified Synchronous Reference Frame Based Shunt Active Power Filter with Fuzzy Logic Control Pulse Width Modulation Inverter” 29 May 2017
  10. Srinivasa Rao, H.J.Jayatheertha “Modeling And Simulation Of Various Srf Methods For Shunt Active Power Filter And Application To BLDC Drive” International Journal of Advanced Engineering Research and Studies E-ISSN2249–8974
  11. P Ananda Mohan , M Sandeep “Synchronous Reference Frame Theory (SRF) along with PI Controller Based Dynamic Voltage Restorer”, Volume 4, Issue 11 (November 2015), PP. 40-45
  12. Chandra Kishor Gupta, Mr.MihirB. Chaudhari “ Simulation of Synchronous Reference Frame Theory based Method for Harmonic Mitigation”, International Journal of Advance Engineering and Research Development Volume 2,Issue 3, March -2015
  13. Brijesh Kumar Sen, Seema Agrawal, Mahendra Kumar, R. K. Somani “Performance Analysis of Synchronous Reference Frame based Shunt Active Power Filter”, International Conference on Research Trends in Engineering, Applied Science and Management (ICRTESM-2017}, Sponsored by Institutions of Engineers Kota Center, Supported by RTU Kota, Rajasthan
  14. S. Wamane, J.R. Baviskar, S. R. Wagh, “A Comparative Study on Compensating Current Generation Algorithms for Shunt Active Filter under Non-linear Load Conditions”, International Journal of Scientific and Research publications volume 3,issue 6,June 2013

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43.

Authors:

Penki Ramu, Ram Kumar, B.A.V, Sandeep Reddy G, Praveen B.

Paper Title:

Road Maintenance through Community Contracting as an Instrument of Rural Development in India by Mobile Applications

Abstract: India has most of the rural-based road network with 70.23% and the total rural network of about 39.3 lakh Km’s for the year 2015-16. In countries like India 2/3rd of the population lives in rural areas and they contribute 46% to the gross national income. The rural road network has increased on an average of 1.55 times for the past seven decades. With increase in the road network rapidly, maintenance becomes complex and at the same time it is essential to maintain roads regularly for improving their serviceability. Maintaining these roads under community-based contracting by the local villagers will give an opportunity for employment and reduces their migration to urban areas. Road tracking and condition survey applications were used for preparing the database of the road network. Data collected was further imported into the computer system to prepare the maintenance plans, contract packages and tenders are called from the community. Contracts are allocated to group members in a community based on age, gender, interest, residence, ethnic group, poverty and leadership skills as well as other skills like reading, writing, and math skills. Community contracting is applicable for small works like bush clearing, clearing side drains, pothole patching and rejuvenate/fog spray. Giving these types of works to the local community will indirectly develop the social, economic and cultural ethics of the rural areas. It also helps in reducing the paper works and improves the quality of work as those works are done by local people.

Keywords: Community Contracting, Road Tracking, Condition Survey.

References:

  1. Paul, Satya, “Unemployment in India: Temporal and Regional Variation”, Oct. 30, 1993, JSTOR, pp. pp. 2407-2414.
  2. Tilak, V R K. “Unemployment Statistics in India “, THE ECONOMIC WEEKLY, January 2, 1965, Vol. 17 .
  3. MARTHA CHEN, JOANN VANEK, JAMES HEINTZ,” Informality, Gender and Poverty: A Global Picture,”. No. 21, Economic and Political Weekly & JSTOR, May 27 - Jun. 2, 2006, Vol. Vol. 41. pp. 2131-2139.
  4. Lesley A. Ross, a Erica L. Schmidt,a and Karlene Balla, “Interventions to Maintain Mobility: What Works, “ HHS, 2012 Oct 16. PMC3633644.
  5. Stankevich, Sally Burningham and Natalya, “Why road maintenance is important and how to get it done”, THE WORLD BANK, WASHINGTON, DC : Transport Note , June 2005 , Vols. Transport Note No. TRN-4 . 33925.
  6. De Silva, Samantha. “Community-based contracting : a review of stakeholder experience”. s.l. : World Bank, 2000/01/31. 20414.
  7. Soraut, Dr. A. C. Sama & R. K. “Socio-Economic Impact of Rural Roads and Parameters for Evaluation”. New Delhi: Compendium on CRRI Technologies - CRRI, 2012.
  8. Heggie, Ian G. “Management and Financing of Roads-an agenda for reform”. World Bank, 2002/10/22. 275.

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44.

Authors:

Pandiri Sivakumar, Doddi Madhav, Kalamulla Mohammad, Gurujala Venkata Naga Kaushik

Paper Title:

A Brief Study on Homogeneous Charge Compression Ignition Engine

Abstract: HCCI (Homogeneous Charge Compression Ignition Engine) is a new mode of combustion which leads to the development of ICE. HCCI engine is an alternative to the present day diesel engine with higher thermal efficiency. To reduce the effect of pollutants, the development of engines by improving the technology and by friendly combustion process, the engines are able to achieve/meet the future emission standards. The recent advancement in HCCI engine, has meet these standards by reducing the NOx and soot emissions up to 85-90% and also by increasing its thermal efficiency 10-15% more than the present day gasoline and diesel engine. HCCI engines are operated upon gasoline, diesel, natural and most other alternate fuels. HCCI engines incorporated with the best features of both spark ignition (SI) and compression ignition (CI) engines. However, HC and CO emissions are slightly higher as compared to CI engines. So, the usage of methods like EGR (Exhaust Gas Recirculation), variable fuel ratio, and by variation of induced gas temperature. The paper looks in to the ignition timing of the HCCI engine and the factors effecting (or) depending to increase efficiency. Also the methods to required characteristics of HCCI engine.

Keywords: HCCI engine, EGR (Exhaust Gas Recirculation), spark ignition (SI), compression ignition (CI).

References:

  1. 16 Olsson, J-O, Tunestål, P. and Johansson, B. Closed-Loop Control of an HCCI Engine. SAE Technical Paper 2001-01-1031, 2001
  2. Richter, M., Franke, A., Engström, J., Aldén, M., Hultqvist, A. and Johansson, B. The Influence of Charge Inhomogeneity on the HCCICombustion Process, SAE Technical Paper 2000-01-2868, 2000
  3. HomogeneousCharge Compression Ignition – the future of IC engines? Prof. Bengt Johansson Lund Institute of Technology at Lund University
  4. Nautilus Four Stroke, Six Cycle, Dynamic Multiphasic Combustion Engine, Nautilus Engineering, LLC Document - 00005R01V00 by Matthew Riley, Sina Davani, Shabbir Dalal, Fujian Yan, Fenil Desai.
  5. Fuel Requirements for HCCI engine operations by Tom Rayan, Andrew Matheaus from Southwest Research institution.
  6. Automotive HCCI Engine Research by Richard Steeper Sandia National Laboratories 2010 DOE Vehicle Technologies Annual Merit Review Washington, DC June 8, 2010.

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Authors:

P. V. Surendra Mohan Kumar, K. Jyothi Padmaja, D.V. Seshagirirao, Ch.Raghavendra

Paper Title:

Effect of Cabin Partitioning on the Fuel Consumption in Automobiles

Abstract: This paper deals with the effect of cabin separation on load on compressor in turn the fuel consumption in automobiles. It is a study to check reduction in working time of compressor in turn the fuel consumption when the cabin space is reduced to 45% by providing cabin partition. In present scenario people are using automobiles (cars) to reach their destinations irrespective of number of passengers. So, at minimum load conditions that is when only one or two persons travelling then there is no need to cool the entire space in the cabin so, the cabin space is reduced by providing a partition between Rear seats and front seats, the work done by compressor reduces which in turn increases the fuel economy, the load on the engine, compared to the non-partition of the cabin. Due to fuel economy, a micro level reduction in pollution and as a whole macro level.

Keywords: Due to Fuel Economy, The Load On The Engine, 

References:

  1. Design & Cooling Performances of an air conditioning system with two parallel refrigeration cycles for special purpose vehicles-Moo-Yeon Lee-Applied Sciences Feb-2017
  2. Air Conditioning Systems.com
  3. Howell, R.H.; Coad, W.J.; Sauer, H.J. Principles of Heating Ventilating and Air Conditioning, 6th ed.; ASHRAE: Atlanta, GA, USA, 2009.
  4. Md Shahid Imam, Dr.M.Shameer Basha, Dr.Md.Azizuddin, Dr. K.Vijaya Kumar Reddy ,2013,Design of Air Conditioning system in Automobile, International Journal of Innovative Research in Science, Engineering and TechnologyVol-2,Issue 12,ISSN 2319-8753.
  5. Automobile Air conditioning Testing Manual-Aria zone
  6. Air Conditioning in Automobile Vehicle by Audi-Volkswagen

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46.

Authors:

Nissankara Lakshmi Prasanna, Pujari Jeevana Jyothi, Nallamekala Rajeswari, R Tejaswini

Paper Title:

A Diagnosis System for Multi class Primary Headaches Using Ant Miner plus Algorithm

Abstract: This article proposes a diagnosis system for dealing with primary headache classification using variant of ant colony optimization algorithm for classification. The diagnosis system proposed is an expert system completely designed with information gathered from patients suffering from headaches. Randomly chosen patients who are visiting various hospitals in India are addressed to collect data for expert system. They are provided with detailed questionnaire about the symptoms to analyze the headache types. With help of neurologist the headaches are compared with the results of ant colony optimization algorithms for classification. Ant miner plus algorithm is enforced for better results. The algorithm is observed for its accuracy levels of classification and is analyzed. This article addresses 4 types of headaches as multi-class classification problem with an in detailed report of symptoms gathered from patients. This kind of expert system is useful to neurologists to track symptoms of their patients and to provide mediation.

Keywords: primary headaches, ant colony optimization, diagnosis system, ant miner plus algorithm, multi-class classification problem.

References:

  1. Freitas, Alex, and André Carvalho. "A tutorial on hierarchical classification with applications in bioinformatics." In Research and Trends in Data Mining Technologies and Applications, pp. 175-208. IGI Global, 2007.
  2. Duda, R. O., P. E. Hart, and D. G. Stork. "Pattern Classification, New York: Wiley Interscience." (2000).
  3. Pop, P. H. M., C. M. Gierveld, H. A. M. Karis, and H. G. M. Tiedink. "Epidemiological aspects of headache in a workplace setting and the impact on the economic loss." European journal of neurology 9, no. 2 (2002): 171-174.
  4. Lipton, Richard B., Walter F. Stewart, Seymour Diamond, Merle L. Diamond, and Michael Reed. "Prevalence and burden of migraine in the United States: data from the American Migraine Study II." Headache: The Journal of Head and Face Pain 41, no. 7 (2001): 646-657.
  5. Olesen, Jes, and T. J. Steiner. "The International classification of headache disorders, 2nd edn (ICDH-II)." (2004): 808-811.
  6. Headache Classification Committee of the International Headache Society (IHS). "The international classification of headache disorders, (beta version)." Cephalalgia 33, no. 9 (2013): 629-808.
  7. Scottish Intercollegiate Guidelines Network. Diagnosis and Management of Headache in Adults: A National Clinical Guide. Scottish Intercollegiate Guidelines Network, 2008.
  8. Ravishankar, K. "The art of history-taking in a headache patient." Annals of Indian Academy of Neurology 15, no. Suppl 1 (2012): S7.
  9. Kernick, David, Sally Stapley, and William Hamilton. "GPs' classification of headache: is primary headache underdiagnosed?." Br J Gen Pract 58, no. 547 (2008): 102-104.
  10. Morgan, Myfanwy, Linda Jenkins, and Leone Ridsdale. "Patient pressure for referral for headache: a qualitative study of GPs' referral behaviour." Br J Gen Pract 57, no. 534 (2007): 29-35.
  11. Al-Hajji, AhmadA. "Rule-Based expert system for diagnosis and symptom of neurological disorders “Neurologist Expert System (NES)”." In Proceedings of the 1st Taibah University International Conference on Computing and Information Technology, Al-Madinah Al-Munawwarah, Saudi Arabia, vol. 1214, p. 6772. 2012.
  12. Kinabalu, Kota. "2012 International Symposium on Computer Applications and Industrial Electronics (ISCAIE 2012)." (2012).
  13. Yin, Ziming, Zhao Dong, Shengyuan Yu, Xudong Lu, Guanjun Feng, and HuilongDuan. "A guideline-based decision support system for headache diagnosis." Studies in health technology and informatics 192 (2013): 1022-1022.
  14. Dong, Zhao, Ziming Yin, Mianwang He, Xiaoyan Chen, XudongLv, and Shengyuan Yu. "Validation of a guideline-based decision support system for the diagnosis of primary headache disorders based on ICHD-3 beta." The journal of headache and pain 15, no. 1 (2014): 40.
  15. Yin, Ziming, Zhao Dong, Xudong Lu, Shengyuan Yu, Xiaoyan Chen, and HuilongDuan. "A clinical decision support system for the diagnosis of probable migraine and probable tension-type headache based on case-based reasoning." The journal of headache and pain 16, no. 1 (2015): 29.
  16. Yin, Ziming, Lingtong Min, Xudong Lu, and HuilongDuan. "A clinical decision support system for primary headache disorder based on hybrid intelligent reasoning." In Biomedical Engineering and Informatics (BMEI), 2014 7th International Conference on, pp. 683-687. IEEE, 2014.
  17. Krawczyk, Bartosz, Dragan Simić, Svetlana Simić, and MichałWoźniak. "Automatic diagnosis of primary headaches by machine learning methods." Open Medicine 8, no. 2 (2013): 157-165..
  18. Mendes, Karina Borges, Ronald Moura Fiuza, M. Teresinha, and A. Steiner. "Diagnosis of headache using artificial neural networks." J. Comput. Sci 10, no. 7 (2010): 172-178.
  19. Celik, Ufuk, NiluferYurtay, EmineRabiaKoc, NerminTepe, HalilGulluoglu, and Mustafa Ertas. "Migraine, tension-type and cluster-type of headaches classification by using immunos algorithms." Journal of Medical Imaging and Health Informatics 6, no. 5 (2016): 1173-1177.
  20. Dorigo, Marco. "Optimization, learning and natural algorithms." PhD Thesis, Politecnico di Milano (1992).
  21. Świątnicki, Zbigniew. "Application of ant colony optimization algorithms for transportation problems using the example of the travelling salesman problem." In Advanced Logistics and Transport (ICALT), 2015 4th International Conference on, pp. 82-87. IEEE, 2015.
  22. Maniezzo, Vittorio. "Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem." INFORMS journal on computing 11, no. 4 (1999): 358-369.
  23. Maniezzo, Vittorio, and Alberto Colorni. "The ant system applied to the quadratic assignment problem." IEEE Transactions on Knowledge & Data Engineering 5 (1999): 769-778.
  24. Gambardella, Luca Maria, ÉricTaillard, and Giovanni Agazzi. "Macs-vrptw: A multiple colony system for vehicle routing problems with time windows." In New ideas in optimization. 1999.
  25. Blum, Christian, and Michael Sampels. "An ant colony optimization algorithm for shop scheduling problems." Journal of Mathematical Modelling and Algorithms 3, no. 3 (2004): 285-308.
  26. Den Besten, Matthijs, Thomas Stützle, and Marco Dorigo. "Ant colony optimization for the total weighted tardiness problem." In International Conference on Parallel Problem Solving from Nature, pp. 611-620. Springer, Berlin, Heidelberg, 2000.
  27. Gambardella, Luca Maria, and Marco Dorigo. "An ant colony system hybridized with a new local search for the sequential ordering problem." INFORMS Journal on Computing 12, no. 3 (2000): 237-255.
  28. Blum, Christian. "Beam-ACO—Hybridizing ant colony optimization with beam search: An application to open shop scheduling." Computers & Operations Research 32, no. 6 (2005): 1565-1591.
  29. Khan, Salabat, and Abdul Rauf Baig. "Ant colony optimization based hierarchical multi-label classification algorithm." Applied Soft Computing 55 (2017): 462-479.
  30. Stützle, Thomas, and Holger H. Hoos. "Improving the Ant System: A detailed report on the MAX–MIN Ant System." FG Intellektik, FB Informatik, TU Darmstadt, Germany, Tech. Rep. AIDA–96–12 (1996).

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47.

Authors:

Nirzari Patel, Mehul P Barot

Paper Title:

Observations on Anonymization Based Privacy Preserving Data Publishing

Abstract: Anonymization is a process of hiding the infor- mation such that an illegal user could not deduce anything from the records, on the other hand an analyzer will get necessary information[4].The term Data Privacy is related with data collection and distribution of data. Privacy issues arise in different area such as health care, Bank sector, social media data,etc.It is one of the challenging issues when sharing or publishing the data between one to many sources for research purpose and data analysis[2].Many organizations also release vast micro data. It excludes an individual’s direct identity marks like name, address and consist of specific information like gender, DOB, marital status, Pin-code, which can be combined with other public data to recognize a person[3]. This inference attack can be worked to obtain any sensitive information from social network platform, by that putting the privacy of a person in danger. To stop such attacks by changing micro data, K-anonymization is used. In this paper, we provide a computational disclosure technique for releasing information from a private table such that the identity of any individual to whom the released data refer cannot be definitively recognized[1]. It is based on the topic of generalization, from which stored values can be replaced with trustworthy but less specific alternatives, and of k-anonymity.

Keywords: Data publishing, privacy preserving, k- anonymization, classification.

References:

  1. Pierangela Samarati,  Latanya  Sweeney  ”Generalizing  Data  to  Provide Anonymity when Disclosing Information”.
  2. Mahesh,T.  Meyyappan  ”Anonymization  Technique  through  Record Elimination  to  Preserve  Privacy  of  Published  Data”Proceedings  of  the 2013  International  Conference  on  Pattern  Recognition,  Informatics  and Mobile Engineering, February 21-22
  3. Simi  M  S,  Mrs.  SankaraNayaki  K,  Dr.M.Sudheep  Elayidom  ”An Extensive   Study   on   Data   Anonymization   Algorithms   Based   on   K- Anonymity”  IOP  Conf.  Series:  Materials  Science  and  Engineering  225 (2017) 012279 doi:10. 1088/1757-899X/225/1/012279.
  4. S,Sarju.  S  ”A  Scalable  Approach  for  Anonymization  Using Top Down Specialization and Randomization for Security” 2017 Interna- tional Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT)
  5. Latanya Sweeney“Weaving  technology  and  policy  together  to  maintain confidentiality” Journal of Law, Medicine,   Ethics, 25(2(3):98110, 1997.
  6. Preet Chandan  Kaur,  Tushar  Ghorpade,  Vanita  Mane  ”Analysis  of  Data Security by using Anonymization Techniques” 978-1-4673-8203-8/16/in 2016 IEEE.
  7. Qingshan Jiang,  A  S  M  Touhidul  Hasan  ”A  General  Framework  for Privacy  Preserving  Sequential  Data  Publishing”  2017  31st  International Conference   on   Advanced   Information   Networking   and   Applications Workshops.
  8. Machanavajjhala ,  Kifer  D.,  Gehrke  J.,  Venkitasubramaniam  M.,”l- diversity:  Privacy  beyond  k-anonymity”  2007,  ACM  Transaction  on Knowledge Discovery in Data, 1, 18-27.
  9. Li, N., Li, T., and Venkatasubramanian, S.,”t-Closeness: Privacy beyond k-Anonymity and   l-Diversity”   2007,   Proceedings,   23rd   International Conference on Data Engineering, USA, 106-115.
  10. Sweeney, “Datafly: a system for providing anonymity in medical data. In Database Security”, XI: Status and Prospects, IFIP TC11 WG11.3 11th Int’l Conf. on Database Security, 356-381, 1998
  11. Bache and M. Lichman. UCI Machine Learning Repository, 2013.
  12.  Soria-Comas,   J.   Domingo-Ferrer,   D.   Sanchez,   and   S.   Martınez, ”Improving  the  Utility  of  Differentially  Private  Data  Releases  via  k- Anonymity”,  In  Proceedings  of  the  12th  IEEE  International  Conference on  Trust,  Security  and  Privacy  in  Computing  and  Communications, TRUSTCOM-13, pages 372–379, 2013.
  13. http://www.cs.waikato.ac.nz/ml/weka/
  14. http://www.nltk.org/
  15. https://opennlp.apache.org/
  16. UCI Machine Learning Repository http :// archive .ics .uci .edu /ml /datasets

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48.

Authors:

N. Swathi, S. Ramlal, G. Thirupathi Naidu

Paper Title:

Compartive Analysis of G + 9 Structure with Shear Wall at Corners, Central Bays and Alternate Bays

Abstract: Need of multi-storey buildings are increasing now-a-days because of rapidly growing population. But when natural calamities like earthquakes occur, there will be great loss to these structures, not only in terms of property but also in terms of causalities. In this paper, an attempt is being made to minimize the loss caused by lateral loads during earthquakes. Shear walls are the one of the most commonly used strategies for resisting the lateral loads. But placing a shear wall at every location is not economical. In this paper, comparison is made among multi-storied structure in different seismic zones by placing shear wall at different locations. Four different configurations viz.., a bay Frame without shear wall, a bay Frame with shear walls at corners, a bay Frame with shear walls at central exterior bays and a bay Frame with shear walls at alternate bays. These Frames are analyzed and results are compared in terms of deflection, bending moments and base shear. Based on the results best configuration is suggested. Analysis of these structures are carried out using STAAD. Pro V8i conforming to Indian codes i.e., IS456:2000, IS1893:2002, IS875 (PART1), IS875 (PART2), IS1343.

Keywords: Multi-storey building, Earthquakes, Seismic zones, lateral loads, shear wall configurations, deflection, bending moment, base shear.

References:

  1. Akash Panchal and Ravi Dwivedi., Analysis and design of G+6 building in different seismic zones of India. International Journal of Innovative Research in Science, Engineering and Technology, 6(7), 14331-14338, (2017).
  2. Anjali, B.U. and Gopisiddappa., Effect and positioning and configuration on seismic performance of RC building resting on hilly and plain terrain. International Journal Research of Engineering and Technology, 4(6),  2501-2506, (2017).
  3. Anshul Sud and Poonam Dhiman., Effect of different shear wall configuration on seismic response of a moment-resisting Frame. European Scientific Journal, Special Edition, 139-145, (2014).
  4. Mohd Atif., Prof. Laxmikant Vairagade and Vikram Nair., Comparative study on seismic analysis of Multi-Storey building with Stiffened with bracing and shear wall. International Journal Research of Engineering and Technology, 2(5), 1158-1170, (2017).
  5. Narla Mohan and Mounika Vardhan A., Analysis of G+20 RC building in different seismic zones in E-tabs. International Journal of Professional Engineering Studies, 8(3), 180-192, (2017).
  6. Mishra R.S., Kushwaha V. and Kumar S. A., Comparative study of different configuration of shear wall location in soft storey building subjected to seismic load. International Research Journal of Engineering and Technology, 2(7), 513-519, (2015).
  7. Sachin Dyavappanavar P., Dr.Manjunath K. and Kavya N., Seismic Analysis of RC Multi-Storey structures with shear walls at different locations. International Research Journal of Engineering and Technology, 2(6), 214-219, (2015).
  8. Sanisha Santhosh and Linda Ann Mathew, Seismic Analysis of Multi-storeyed building with shear walls of different shapes. International Journal of Engineering and Technology, 6(6), 490-494, (2017).
  9. Abhinav, V. and Dr,Sreenath Reddy, S., Seismic analysis of multi-storeyed building using STAAD.Pro. International Journal of Innovative Technology and Research , 4(5), 3776-3779, (2016).

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49.

Authors:

D. Narendar Singh, B. Pavitra, M. Anusha

Paper Title:

IOT Based Cloud Integrated Parking, Trolley Identification and Outdoor Mapping System at Airport

Abstract: In every airport, it is mandatory to maintain the security system like parking area, left over trolley’s, outdoor mapping, etc., The proposed parking system consists of an deployment of an IOT module that is used to monitor the state of availability of each single parking space a mobile application is also provided that allows an user to check the availability of parking space and book a parking slot accordingly. And few passengers will left trolleys in parking area if they find of no use, in order to track leftover trolleys we integrate devices to trolleys and check the status in mobile app. And also new passengers can checking nearby places at airport, with the help of mobile app passengers can view airport outdoor mapping.

Keywords: ESP8266, ESP32, OLED, Keypad, Servo Motor, Mobile App, Cloud storage.

References:

  1. Wu He, Gongjun Yan, and Li Da Xu,Senior Member, IEEE “Developing Vehicular Data Cloud Services in the IoT Environment” IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 10, NO. 2, MAY 2014.
  2. Li, L. Xu, and X. Wang,“Compressed sensing signal and data acquisition in wireless sensor networks and internet of things,” IEEE Trans. Ind. Informat., vol. 9, no. 4, pp. 2177–2186, Nov. 2013.
  3. M. R. Tarouco, L. M. Bertholdo, L. Z. Granville, L. M. R. Arbiza, F. Carbone, M. Marottaet al., “Internet of Things in healthcare: Interoperatibility and security issues,”in Proc. IEEE Int. Conf. Commun.(ICC). Ottawa, ON, Canada, 2012, pp. 6121–6125.
  4. Boyi Xu, Li Da Xu,Senior Member, IEEE, Hongming Cai, Cheng Xie, Jingyuan Hu, and Fenglin Bu “Ubiquitous Data Accessing Method in IoT-Based Information System for Emergency Medical Services” IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 10, NO. 2, MAY 2014.
  5. Lumpkins, “The internet of things meets cloud computing,” IEEE Consum. Electron. Mag., vol. 2, no. 2, pp. 47–51, Apr. 2013
  6. Md Whaiduzzamana,n, Mehdi Sookhak , Abdullah Gani , Rajkumar Buyya “A survey on vehicular cloud computing”, ELSEVIERJournal of Network and Computer Applications 40 (2014) 325–344.
  7. A. Feki, F. Kawsar, M. Boussard, and L. Trappeniers,“The Internet of Things: The next technological revolution,” Computer, VOL. 46, NO. 2, pp. 24–25, 2013.
  8. Atzori, A. Iera, and G. Morabito, “The internet of things: A survey,” Comput. Netw., vol. 54, no. 15, pp. 2787–2805, 2010.
  9. An Internet of Things Example: Classrooms Access Control over Near Field Communication Sensors 2014, 14, 6998-7012; doi: 10.3390/s140406998.
  10. European Commission Information Society, Internet of Things in 2020:
  11. A Roadmap for the Future [Online]. Available: www.iotvisitthefuture.eu.

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50.

Authors:

L. Lakshmi Aparna, K. Sai Sravani, V. Sambasiva Rao, G. Chaitanya

Paper Title:

Evaluation and Damage Repair of Continuous GFRP Tensile Composite Laminate using FEA

Abstract: GFRP composites are replaced by metals in extreme domains due to high strength to weigth ratio. Presence of damage in a composite pannel reduces the structural integrity. The current research discusses about the criteria to improve the tensile strength of uni-directional glass fiber composite laminate using adhesively bonded patch repair over the damage area. The paper uses SIEMENS NX10 tool for modelling the samples and the structural analysis with and without patch work was done in ANSYS 19.1 work bench. The results are compared finally. 

Keywords: GFRP, Composite, Damage, Patch Repair

References:

  1. Hull, T.W. Clyne. An introduction to composite materials: Cambridge University Press, 1996.
  2. Vaxman, A.; Narkis, M.; Siegmann, A.; Kenig, S. (1989). "Void formation in short-fiber thermoplastic composites". Polymer Composites 10: 449–453.
  3. Agari Y, Ueda A and Nagsai S, (1991), Thermal conductivity of polyethylene filled with disoriented short-cut carbon fibers, Journal of polymer science 43(6), 1117-1124.
  4. Chin W K, Liu H T and Lee Y D (1988), “Effect of fiber length and orientation distribution on elastic modulus of short fiber reinforced thermoplastics”, Polymer Composite, 9(1), 27-35.
  5. Dunn M L, Taya M, Hatta H, Takei T and Nakajima Y (1991), “Thermal conductivity of hybrid short fibers”, Journal of composite materials, 27(15), 1493-1519.
  6. R. C. EADS Deutshland GmbH. The research requirements of the transport sectors to facilitate an increased usage of composite materials.
  7. RF Gibson, A review of recent research on mechanics of multifunctional composite materials and structures, Composite Structures, November 2010, 92(12), 2793-2810
  8. M. Ramji, Assistant professor, Department of Mechanical and Aerospace Engineering, Fiber reinforced plastics manufacturing (overview), characterization, Damage and Repair, Short course on FRP composites July10, 11 2014, Indian Institute of Technology (IIT) Hyderabad.
  9. P N Rao, Manufacturing Technology volume-1, third edition, The Mc Graw-Hill Companies.
  10. P.D Rajan, R.M. Pillai, B.C. Pai, K.G. Satyanarayana, P.K. Rohatgi, Proceedings of National Conference on: Recent Advances in Materials and Processing (RAMP-2001), India,     pp. 327-334.
  11. W. Clyne, P.J. Withers, An introduction to Metal Matrix Composites, Cambridge University Press, Cambridge, UK, 1993, pp. 166-217.
  12. Z. Jang, Advanced Polymer Composites: Principles and Applications, ASM International, OH, 1994, Page 22.
  13. G. Advani & E. Murat Sozer, Process Modeling in Composites Manufacturing,Marcel Dekker, Inc New York. (2003) , ISBN: 0-8247-0860-1
  14. Sanjay K. Mazumdar, Composites Manufacturing-Materials, Product, and Process Engineering, CRC Press, New York. (2002), ISBN: 0-8493-0585-3
  15. G. Advani & Kuang-Ting Hsiao, Manufacturing techniques for polymer matrix composites (PMCs), Woodhead Publishing Limited, 2012, ISBN:978-0-85709-067-6
  16. Krishan K. Chawla, Composite Materials- Science and Engineering, Springer 3rd Edition, (2013), ISBN: 978-0-387-74364-6
  17. K. Mallick, Fiber Reinforced Composites- Materials, Manufacturing, and Design, 3rd Edition CRC press Taylor & Francis Group, LLC (2007), ISBN: 978-0-8493-4205-9.

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51.

Authors:

L. Venkateswara Kiran, R. Bala Dinakar, P. Siva Prasad

Paper Title:

Blockchain Technology - A Sturdy Protective Shield

Abstract: Blockchain Technology, very popular buzz word after the tremendous success of Bitcoin. An immutable ledger in Blockchain makesthe transactions in decentralized manner. Blockchainapplications cover different fields like financial services, reputation system and Internet of Things and many more. Even though there are so many challenges forBlockchain technology like scalability and security to be overcome. This paper briefs an overview on Blockchain technology. We are providing an overview of Blockchain architecture, security, and technical challenges are precisely listed. We are also brief the future trends for Blockchain.

Keywords: We are also brief the future trends for Blockchain.

References:

  1. State of blockchain q1 2016: Blockchain fundingOvertakes bitcoin,” 2016. [Online]. available:http://www.coindesk.com/state- of-blockchain-q1-2016/
  2. Nakamoto, “Bitcoin: A peer-to-peer electronic cash system,” 2008. [Online].available: https://bitcoin.org/bitcoin.pdf
  3. Foroglou and A.-L. Tsilidou, “Further applications of theblockchain,” 2015.
  4. Kosba, A. Miller, E. Shi, Z. Wen, and C Papamanthou,“Hawk: The blockchain model of cryptography and privacy- preserving smartcontracts,” in Proceedings of IEEE Symposium on Security and Privacy (SP), SanJose, CA,USA, 2016, pp. 839–858.
  5. Sharples and J. Domingue, “The blockchain and kudos:a distributed system for educational record, reputation and   reward,” inProceedings of 11th European  Conference onTechnology Enhanced  Learning (EC- TEL2015), Lyon,France, 2015, pp. 490–496.
  6. Noyes, “Bitav: Fast anti-malware by Distributedblockchain consensus and feedforward scanning,” arXiv preprint arXiv:1601.01405, 2016.
  7. Eyal and E. G. Sirer, “Majority is not enough: Bitcoin mining is vulnerable,” in Proceedings of International Conference on Financial Cryptography and Data Security, Berlin, Heidelberg, 2014, pp. 436– 454.
  8. Tschorsch and B. Scheuermann, “Bitcoin and beyond: A technical survey on decentralized digital currencies,” IEEE Communications SurveysTutorials, vol. 18,  no.3, pp. 2084–2123, 2016.
  9. NRI, “Survey on blockchain technologies Andrelated services,” Tech.Rep., 2015.
  10. Buterin, “A next-generation smart ContractAnd decentralized application  platform,”white paper, 2014.
  11. Buterin, “On public and private blockchains,” 2015.[Online]. Available: https:// blog. ethereum. org/2015/08/07/ on-public-and-private-blockchains/
  12. King and S. Nadal, “Ppcoin: Peer-to-peer crypto-currency with proofof-stake,” Self- Published Paper, August, vol. 19, 2012.
  13. Schwartz, N. Youngs, and A. Britto, “The ripple protocol consensus algorithm,” Ripple Labs Inc White Paper, vol. 5, 2014.
  14. Kwon, “Tendermint: Consensus without mining,” URLhttp://tendermint . com/docs/tendermint { } v04. pdf, 2014.
  15. King, “Primecoin: Cryptocurrency with prime numberproof-ofwork,” July 7th,  2013.
  16. Wood, “Ethereum: A secure decentralized generalised transaction ledger,” Ethereum Project Yellow Paper, 2014.
  17. Mazieres, “The stellar consensus protocol:a federated model for internet-level consensus,” Stellar Development Foundation, 2015.
  18. “Antshares digital assets for everyone,”   [Online]Available: https://www.antshares.org
  19. Decker, J. Seidel, and R. Wattenhofer, “Bitcoin meets strong consistency,” in Proceedings of the 17th International Conference on Distributed Computing and Networking (ICDCN). Singapore, Singapore: ACM, 2016.
  20. Kraft, “Difficulty control for blockchain- basedconsensus systems,” Peer-to-Peer Networking and Applications, vol. 9, no. 2, Pp.397–413, 2016.
  21. A. Chepurnoy, M. Larangeira, and A Ojiganov, “Aprunableblockchain Consensusprotocol based on non-interactive  proofs ofpast states retrievability,” arXiv preprintarXiv:1603.07926, 2016.

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52.

Authors:

KSB Prasad, S. Naveen Kumar, D. SAravind Varma

Paper Title:

A Review on Present Trend in Speed Bump

Abstract: This technical paper deals about the reducing the over speeding vehicles by using smart speed bump. According to the Ministry of Road Transport and Highways of India on 2016 survey statistics 9583 road accidents are occurred on speed bump in which 3396 are killed. In order to reduce impact caused by conventional speed bump replaced by smart speed bump It is formed by flexible material made up several hollow slots or unique slot. Each slot is filled with impregnated Shear thickening fluid (Non- Newtonian Fluid)the main principle involves here is pressure acting on the Material strip then the fluid acts itself as resistance against the pressure. When the tire pressure act on strip with low speed then automatically the viscosity level in the strip reduces, strip easily deformed vehicle will moves smoothly And another side if vehicle moves with high speed than it required it will act as a Rigid obstacle for high speed .Due to change in viscosity due to sudden tire pressure act on the strip. Where as in conventional speed bump the vehicle has to slow down in order to prevent damage of the vehicle. However the smart speed bump is sensitive to the speed of the vehicle. Vehicle need not be halt down unless if the vehicle is coming at the high speed. It will give more pleasure and comfort to the driver.

Keywords: Non-Newtonian fluid, Speed bump, Reduce impact, Viscosity level

References:

  1. "Traffic Calming Measures – Speed Hump". Institute of Transportation Engineers
  2. Ding, Jie; Li, Weihua; Z. Shen, Shirley, “Research and Applications of Shear Thickening Fluids ” Recent Patents on Materials Science”, Volume 4, Number 1, January 2011, pp. 43-49(7) K. Subramanya , Tata McGraw-Hill Education, Hydraulic Machines
  3. W. McAllister , Pipeline Rules of Thumb Handbook kindle.worldlibrary.net/articles/Bicycle_reflector, Accessed on 23.2.2016 , 10.45 AM
  4. Numerical modeling of non-Newtonian fluid flow in fractures and porous media Variable Density Speed Hump Rajenderpal Singh Bhamrah1 International Journal of Students’ Research In Technology & Management Vol 4 (2) March-June 2016, pg 35-37 eISSN 2321-2543, doi: 10.18510/ijsrtm.2016.423.

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53.

Authors:

Krishnaiah Boyana, Venkateswara Rao Gurrala, G.V. Swamy

Paper Title:

Hierarchical Approach to Control Dynamic Data Transmission and Mobility Management in MANETs

Abstract: Autonomous addressing protocols require a distributed and self-managed mechanism to avoid address collisions in dynamic mobile ad hoc networks with fading channels, frequent partitions, and joining/leaving nodes. Random policy based adaption is the informative analysis in mobile ad hoc networks dynamism and node simulation in recent application framework with respect to the mobile ad hoc networks performance. Traditionally propose and analyze a lightweight protocol that configures mobile ad hoc nodes based on a distributed address database stored in filters that reduces the control load and makes the proposal robust to packet losses and mobile ad hoc networks partitions. The proposed framework addresses the mobility management issue from a new perspective through posing it as a problem of learning from current system behavior, while creating new policies at runtime in response to changing requirements. A hierarchical policy model i.e. Dynamic Position & Quorum based Opportunistic Energy Routing Protocol (DPQOERP) is used to capture users and administrators’ higher level goals into mobile ad hoc networks level objectives. Given sets of mobile ad hoc networks objectives and constraints, policies are assembled at runtime. The new approach gives more flexibility to users and applications to dynamically change their quality-of-service (QoS) requirements while maintaining a smooth delivery of QoS through mobile ad hoc networks monitors feedback. Our proposed approach compares with existing mobility models with respect to end-to end delay, packet delivery ration and other specifications present in ad hoc networks. Simulation results demonstrate the performance with traditional mobility model.

Keywords: Mobile ad hoc networks, Lightweight protocol, Energy Protocol, Quality of service, Mobility management and dynamic & position routing.

References:

  1. Kyungtae Woo and Chansu Yu Hee Yong Youn Ben Lee, “Non-Blocking, Localized Routing Algorithm for Balanced Energy Consumption in Mobile Ad Hoc Networks” IEEE Computer, Vol. 27, No. 4, pp. 38-47, Apr. 2016.
  2. Ya Xu, Solomon Bien, “Topology Control Protocols to Conserve Energy in Wireless Ad Hoc Networks”, In Proceedings of the ACM/IEEE International Conference on Mobile Computing and Networking, pages 85–97, October, 2014.
  3. Cerpa and D. Estrin. ASCENT: Adaptive self configuring sensor network topologies. In Twenty First International Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), June 2002.
  4. Chen, K. Jamieson, H. Balakrishnan, and R. Morris. Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. ACM Wireless Networks, 8(5), September 2002.
  5. R. Das, C. E. Perkins, and E. M. Royer. Performance comparison of two on-demand routing protocols for ad hoc networks. In Proceedings of the IEEE Infocom, pages 3–12, Tel Aviv, Israel, March 2000.
  6. -K. Toh, “Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks”, IEEE Communications Magazine • June 2001.
  7. Chansu Yu Ben Lee Hee Yong Youn, “Energy Efficient Routing Protocols forMobile Ad Hoc Networks”, Proceedings of European Wireless
  8. Doshi S, Brown TX. Minimum Energy Routing Schemes for a Wireless Ad Hoc Network. Proceedings of the Conference on Computer Communications (IEEE Infocom 2002)
  9. Banerjee S, Misra A. Minimum Energy Paths for Reliable Communication in Multi-hop Wireless Networks. Proceedings of Annual Workshop on Mobile Ad Hoc Networking & Computing (MobiHOC 2002)
  10. Narayanaswamy S, Kawadia V, Sreenivas RS, Kumar PR. Power Control in Ad-Hoc Networks: Theory, Architecture, Algorithm and Implementation of the COMPOWProtocol. Proceedings of European Wireless
  11. Woo K, Yu C, Youn HY, Lee B. Non-Blocking, Localized Routing Algorithm for Balanced Energy Consumption in Mobile Ad Hoc Networks. Proceedings of Int'l Symp. on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS 2001) 2001;117-124.
  12. Toh C-K. Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks. IEEE Communications
  13. Chen B, Jamieson K, Morris R, Balakrishnan H. Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks. Proceedings of Int’l Conf. on Mobile Computing and Networking (MobiCom’2001)
  14. Xu Y, Heidemann J, Estrin D. Geography-informed Energy Conservation for Ad Hoc Routing. Proceedings of Int’l Conf. on Mobile Computing and Networking (MobiCom’2001)
  15. Girling G., Wa J, Osborn P, Stefanova R. The Design and Implementation of a Low Power Ad Hoc Protocol Stack. Proceedings of IEEE Wireless Communications and Networking Conference
  16. Jones CE, Sivalingam KM, Agrawal P, Chen JC. A Survey of Energy Efficient Network Protocols for Wireless Networks. Wireless Networks 2001; 7(4): 343-358.
  17. Goldsmith AJ, Wicker SB. Design Challenges for Energy-Constrained Ad Hoc Wireless Networks. IEEE Wireless Communications 2002; 8-27.
  18. Ephremides A. Energy Concerns in Wireless Networks. IEEE Wireless Communications 2002; 48-59.
  19. Ferrari, M. Zimmerling, L. Mottola, and L. Thiele, “Low-power wireless bus,” in Proc. 10th ACM Conf. Embedded Netw. Sensor Syst., 2012, pp. 1–14.
  20. Misra and C. Mandal, “Minimum connected dominating set using a collaborative cover heuristic for ad hoc sensor networks,” IEEE Trans. Parallel Distrib. Syst., vol. 21, no. 3, pp. 292–302, Mar. 2010.
  21. D. Sarwate and A. G. Dimakis, “The impact of mobility on gossip algorithms,” IEEE Trans. Inf. Theory, vol. 58, no. 3, pp. 1731– 1742, Mar. 2012.
  22. Roysr. t? Mclliar-Smith. and L. Moscr. "An analysis of the optimum node densily fur ad hoc mobile networks." in Proc. oflCC. 2001.
  23. D. McDonald and T. E Znali. 'A mobihty-baed framework for adaptive clustering iii wireless ad hoc nclworki' IEEE MC. Sprcinl Issrrr on :WHm Nenwrks. Aug. 1999.
  24. Li. 1. C. Hou. and L. Shu. "Dcsipn and analysis of iln MST-based lopulogy control algorithm'' in Pmc. IEEE Ir$ocom. Mar./@(. 2003.
  25. Fa11 and K. Varadhan. "lkc ns nnnuul." Tke VlNT Project. UCB. LBL. LlSCnSl and Xarox PARC. hltp:llwww.isr.~dulns"~~"~/docl, Apr. 2002.
  26. Wu and E Dai. "Mobilily-sensitive lopology control in mobile ad hoc nctwurks:~ Oct. 2003. submiosd fur publication.
  27. An and S. Papvassiliou, "A mobility-based clustering approach lo support mobility management and multicast routing in mobile ad-hoc wireless nctworki." hlunralio~mal Jolusnznl of Ntlwork Mannsernmt. vol. 11. no. 6. pp. 387-395. Nor-Dec. 2001.

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54.

Authors:

D. Narendar Singh, G. Anil Kumar, K. Sowjanya

Paper Title:

IOT based Secured Railway Passengers Service Systems with QR Code and Unmanned Railway Crossing Alarm

Abstract: Railway is the most commonly used transportation vehicle. Most of the people choose this transportation mainly for the low cost and it gives comfort ability. To make more comfortable to the users our system gives many solutions and provide the greater facilitation to the users. Mainly our system creates an mobile app where the users can know the which seats are available or empty to reserve with the help of QR scanner. The passengers can order the food within the train and users can know the live tracking of a train using GPS. Our system also provides one alert system near unmanned gate to avoid accidents at the same time which train has come near to which station is also shown with the help of nRF in mobile app

Keywords: IOT, QR (Quick Response) scanner, Pantry System, GPS (Global Positioning System), Accident monitoring.

References:

  1. Semwal, N. S., S. S. Jha, and S. B. Nair, “Tartarus: A multi-agent platform for bridging the gap between cyber and physical systems (demonstration),” in Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems, ser. AAMAS ’16. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems, 2016.
  2. Catarinucci, D. De Donno, L. Mainetti, L. Palano, L. Patrono, M. L. Stefanizzi, and L. Tarricone, “An iot-aware architecture for smart healthcare systems,” Internet of Things Journal, IEEE, vol. 2, no. 6, pp. 515–526, 2015.
  3. Semwal, M. Bode, V. Singh, S. S. Jha, and S. B. Nair, “Tartarus: a multi-agent platform for integrating cyber-physical systems and robots,” in Proceedings of the 2015 Conference on Advances In Robotics. ACM, 2015.
  4. W. Godfrey, S. S. Jha, and S. B. Nair, “On a mobileagentframeworkforaninternetofthings,”inInternationalConferenceonCommunication Systems and Network Technologies (CSNT), 2013. IEEE, 2013.
  5. Niclota-Cristina Gaitan, Vasile Gheorghita Gaitan,Ioan Ungurean Ungurean;”A Survey on the Internet of things software Architecture”. International journal of advanced CSE Dec-2015.
  6. Ortiz, A. M., Hussein, D., Park, S., Han, S. N., & Crespi, N. (2014).The cluster between internet of things and social networks: Review and research challenges.
  7. Sandakan, Neha, Rane Dipti, and Sachin Pandey. "2013 Android Railway Ticketing with GPS as Ticket Checker." Proceedings of National Conference on New Horizons In IT-NCNHIT. 2013.
  8. S. Tey, L. Ferreira, A. Wallace, “Measuring Driver Responses at Railway Level Crossings” , Accident Analysis and Prevention, vol.43(6): p.2134-2141, 2011.
  9. Gao, K. He, H. Liu, F. Sun, “Design and Development of Autonomous Driving Train” IEEE, 2010.
  10. Dewang Chen and Rong Chen (2013), “Online Learning Algorithms for Train Automatic Stop Control Using Precise Location Data of Balises”, IEEE Transactions On Intelligent Transportation Systems, VOL. 14, NO. 3, September 2013.

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55.

Authors:

D. Narendar Singh, G. Ashwini, K.Uma Rani

Paper Title:

IOT Based Recommendations for Crop Growth Management System

Abstract: It is mandatory to maintain good crop growth in every area like cotton, rice, jute, maize, etc., the proposed system consists of an IOT module that is used to monitor the state of each crop to grow in a good condition by providing requirements to it generally crop may not grow due to temperature rainfall moisture and pressure there are the primary requirements for which a crop to grow healthy to overcome this problem we are using sensors like water temperature, soil moisture, BME280 and wind velocity, all this sensors are connected to ESP32 and will detect the present value according to the climate and soil condition and transform the data from sensor to the cloud in which I have already stored the values all the detected values, which are transformed from controller to cloud and through web app all the detected values like climate, soil condition are displayed whether in normal condition or not and if the detected values proceed and exceed it alert and gives suggestion to farmer. Good condition cloud after receiving data compare with the default values all the detected values which are transformed from controller to cloud and through web app all the detected values will be displayed and climate ,soil condition are displayed weather in normal condition or not and if the detected values proceed and exceed it alert and gives suggestion to farmer.

Keywords: BME280, Soil Moisture Sensor, Water temperature Sensor, Wind Velocity Sensor ESP32, Cloud, web application

References:

  1. Romeo Mawonike And Vinscent Nkomo. “Univariate Statistical Process Control Of Super Saver Beans: A Case Of Rmv Supermarket, Zimbabwe”. Journal Of Management And Science , Vol.5,PP.No 48-58, 2015.
  2. Haider Raza N, Girijeshprasad,Yuhuali . “Ewma Model Based Shift-Detection Methods For Detecting Covariate Shifts In Non-Stationary Environments”.Patternrecognition, Science Direct ,Vol.48, PP.No659–669,
  3. Liu Yumei, Zhang Changli , Zhu Ping. “The Temperature Humidity Monitoring System Of Soil  Based On Wireless Sensor Networks” Electric Information and control engineering (ICEICE), PP. No 1-4, 2011.
  4. Jeonghwan Hwang, Changsun Shin And Hyun Yoe . “Study On An Agricultural Environment Monitoring Server System Using Wireless Sensor Network”, IEEE Sensors 2010 Vol.10, PP.No11189-11211, 2010
  5. Carlone, J. Dong, S. Fenu, G. Rains, and F. Dellaert, “Towards 4D crop analysis in precision agriculture: Estimating plant height and crown radius over time via expectation-maximization,” in ICRA Workshop on Robotics in Agriculture, 2015.
  6. Chirima Justin, Chinofunga Peter Tinashe, Zvobgo Rungano Jonas ,Mufandaedza,Jonathan And Dambaza Marx. “Application Of Statistical Control Charts To Climate Change Detection In Masvingo City, Zimbabwe”. Journal
  7. Dae-Heon Park,Beom-Jin    Kang,Kyung-Ryong  Cho ,Chang-Sun Shin ,Sung-Eon Cho,Jang-Woo Park ,Won-Mo Yang. “A Study On Greenhouse Automatic Control System Based Onwireless Sensor Network”, Wireless Personal Communication Springer journal , Vol 56, PP.No 117–130, 2011.
  8. Agriinf
  9. Li, X. Fan, N. J. Mitra, D. Chamovitz, D. Cohen-Or, and B. Chen, “Analyzing growing plants from 4D point cloud data,” ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia, vol. 32, no. 6, p. 157, 2013.
  10. Wu, B. Clipp, X. Li, J.-M. Frahm, and M. Pollefeys, “3d model matching with viewpoint-invariant patches (VIP),” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 1–8, 2008.

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56.

Authors:

Bhanu Chander, Kumaravelan

Paper Title:

One class SVMs Outlier Detection for Wireless Sensor Networks in Harsh Environments: Analysis

Abstract: Outlier/Anomaly detection is renewed challenge in data mining, internet of things as well as machine learning communities. In present era Internet of things is emerging with its tremendous applications where wireless sensor nodes are incredibly well structured to accumulate huge amount of raw data from unsystematic sectors and hand over it to authoritative systems such as disaster monitoring, surveillances, green monitoring, and smart city applications etc,. However such authoritative and prediction systems truthfulness subject to reliability of sensor node. Unluckily, sensed data excellence and reliability influenced by circumstances such as sensor faults, intrusion and unusual events within others. As a result it obstructs authoritative decision making as well as prediction, hence there is need of effectual, real time abnormality detection mechanisms for consistent decisions. A key dispute is how to lessen energy consumption and communication overhead in network at the same time identifying anomalies in unsystematic environments. Even though a impressive number of studies, existing anomaly detection algorithms are there still Machine learning numerous appliances has captured massive importance in outlier detection especially for wireless sensor networks (WSNs), notably Support Vector Machine (SVM) based techniques provides effectual outlier detection and classification achievements in harsh environment. This work presents various one class SVM formulations eminently well instructed outlier detection in harsh environments, moreover formulations analyzed in terms of various characteristics include input data, dynamic topology, outlier types, Spatio temporal attribute correlations etc. Brief comparison and characteristics of distinctive one class SVM formulations are described.

Keywords: Wireless Sensor Networks, Outlier Detection, Classification, Support vector Machine, Event Detection.

References:

  1. Xie M, Han S, “Anomaly detection in WSN: A survey,” Journal of computer Applications, 34(4),1302-1325, 2011.
  2. O’Reilly C, Gulhak, “Anomaly detection in WSN in a non stationary environment,” IEEE Communication survey tutor, 16(3), 1413-1432, 2014.
  3. Bhanu chander, “A Analysis of machine learning in WSN,” International journal of engineering and technology, 7(4.6), pp 185-192, 2018.
  4. N.Tan, “knowledge discovery from sensor data, 2006.
  5. Banarjee A, Burlina P, “ A Support vector machine for anomaly detection in hyper spectral imagenay” IEEE Remote, 44(8),2282-2291, 2006.
  6. Suthuran rajasegarar, Christopher Leckie, “Quarter sphere based distributed anomaly detection in wireless sensor networks” IEEE Trans. ICC 2007.
  7. D.Brown, and H.T.Davis, “Receiver operating characteristics curves and related decision measures: A tutorial,” chemetrics and intelligent laboratory systems, Vol 1, No 1, pp 24-38, 2006.
  8. Hao P, “A new maximal-marginal special structured mutli class classification,” intelligent application,30(2) pp-98-111, 2009
  9. Abe S, “Support vector machine for pattern classification,” Springer, 2010.
  10. Sutharan rajasegarar, “An iterative ellipsoid based anomaly detection in WSN,” IEEE proceedings, 2012.
  11. Hugo martins, Luis Palma, “A support vector machine based technique for detection of outlier in transient times,” IEEE trans. 2015
  12. Yang Zhang, Nirvana Meratnia, “Distributed online outlier detection in wireless sensor networks using ellipsoidal SVM,” Ad-hoc networks, Elsevier B.V all rights reserved, 2012.
  13. Yaswanth singh, Suma Saha, “Distributed event detection in wireless sensor networks,” IEEE 15th international conference on computer modeling and simulation, 2013
  14. Nauman shahid, Ijaz Haider Naqvi, “One class support vector machine: analysis of outlier detection for WSN in harsh environments,” Springer, Artificial intelligence reviews, 2013.
  15. Zhen Feng, Jingqi Fu, “A new approach of anomaly detection in wireless sensor networks using SVDD,” International journal of distributed sensor networks, Vol.3(1), 2017
  16. Raihan, Hossain, “A Novel anomaly detection algorithm for sensor data under uncertainty,” Springer, Soft computing, 2016
  17. Aditi chatterjee, Das, “ State estimation and anomaly detection in wireless sensor networs,” Springer, Emerging WSN technolohies, 2018
  18. Rajasegarar S, Leckie, “Hypersphereical cluster based distributed anomaly detection in wireless sensor networks” journal of parll distrb communications,74(1),1833-1847,2014
  19. Shaid, Naqvi, “Quarter sphere SVM: Spatio temporal outlier detection in WSN,” IEEE Communications, 2012.
  20. Zhu F and Wei JF, “ A New SVM reduction strategy of large scale training sample sets, ICMT-2013, pp 815-819, 2013
  21. Zhang, Mariena “ Adaptive online one class SVM based outlier detection for WSN,” WAINA-2009, PP 990-995, 2009.
  22. Van vuongntrinh. Anomaly detection in WSN via SVM description, 2017 4th NAFOSTED Conference on Information and Computer Science. 2017.
  23. Yang et al, “An online outlier detection in wsn Using unsupervised quarter sphere Support vector machine,” ISSNIP 2008, PP151-156,2008
  24. D.Wang, D.S Yung, “Structured one class classification,” IEEE Trans system man, cyber, 2006.

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57.

Authors:

Ch. Chandra Sekhar, Shiv Sankar Ch, G. Nageswara Rao

Paper Title:

Future Reality is Immersive Reality

Abstract: Reality is defined as set of all that is real and has existence unlike imaginary. Immersive Reality is a path breaking technology which bridges the gap between imagination and reality. Virtual Reality (VR), Augmented Reality (AR) and the latest Mixed Reality (MR) together are called as Immersive reality. It has been a quite a few years that way that people interact with content has not changed. Productivity across businesses is not in an encouraging position. This paper highlights how Immersive technologies are going to alter how we interact with content fundamentally. For example, Companies such as GE Renewable Energy and its technology partner Upskill worked together to develop head-mounted display (HMD) which helped employee to receive wiring installation instructions instead of reading a traditional paper manual. Using virtual reality headset, we can take ourselves to imaginary environment. Another development in this field is Microsoft HoloLens which is self-contained holographic computer, helps us in accessing digital content and interact with the holograms in the world around us. The design of all these products aim same goal – being part of human efforts to create better world for people to live in. These kinds of developments can transform the current entertainment, gaming, Education, Training, real estate, hospitality, shopping experience, healthcare, marketing experiences and travel communication businesses. As there are two sides for a coin, there are many issues which Immersive Reality must tackle before it makes global presence. This paper also focuses on the ethical dilemmas that Immersive reality faces.

Keywords: Immersive Reality, Virtual Reality, Augmented Reality, Mixed Reality.

References:

  1. Oliver Grau, "Virtual Art: From Illusion to Immersion" MIT-Press, Cambridge 2003
  2. Frank Popper, "From Technological to Virtual Art", MIT Press. ISBN0-262-16230-X.
  3. Adams, Ernest (July 9, 2004). "Postmodernism and the Three Types of Immersion"Gamasutra. Retrieved 2007-12-26.
  4. Tcha-Tokey, O. Christmann, E. Loup-Escande, and S. Richir, “Proposition and validation of a questionnaire to measure the user experience in immersive virtual environments,”International Journal of Virtual Reality, vol. 16, no. 1 ,pp. 33–48, 2016.
  5. Slater M., & Sanchez‐Vives M. V. (2016). Enhancing our lives with immersive virtual reality. Frontiers in Robotics and AI, 3, 74 10.3389/frobt.2016.00074 
  6. Garau M., Slater M., Vinayagamoorthy V., Brogni A., Steed A., & Sasse M. A. (2003). The impact of avatar realism and eye gaze control on perceived quality of communication in a shared immersive virtual environment. Proceedings of the conference on Human factors in computing systems – CHI ‘03 (p. 529). ACM Press, New York, NY: 10.1145/642611.642703.
  7. Joseph Nechvatal, Towards an Immersive Intelligence: Essays on the Work of Art in the Age of Computer Technology and Virtual Reality (1993–2006). Edgewise Press. New York, N.Y. 2009.
  8. Cobb SVG, Nichols S, Ramsey A, Wilson JR. Virtual Reality-Induced Symptoms and Effects (VRISE) Presence: Teleoperators and Virtual Environments. 1999;8:169–186.
  9. Roberts, J. (2016). What is HoloLens? Microsoft’s holographic headset explained. Retrieved from http://www.trustedreviews.com/opinion/hololens-release-date-news-and-price-2922378
  10. El Saddik et al., “Haptics Technologies: Computer Haptics” in Springer Series on Touch and Haptics Systems, Springer-Verlag Berlin Heidelberg, 2011, pp. 105-143.

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58.

Authors:

Devi Perla, Rajya Lakshmi Valluri

Paper Title:

Slotted Circular Shaped Wide Band Antenna for Wi-Max Application

Abstract: In this paper, Circular shaped Micro strip patch antenna is designed for wide band and to improve the performance of an antenna and applicable for Wi-MAX, a slot is placed on a circularly shaped microstrip patch antenna .FR4 substrate with a relative permittivity of 4.4 and strip line feed is used. When compared to conventional patch antenna, the slotted antenna has better return loss of -35dB and a gain of 5dB. HFSS ( High Frequency Structure simulator is used for designing and simulation of results.

Keywords:  Microstrip Patch antenna, Wi-MAX, HFSS, Wide Band.

References:

  1. Siva Sundara Pandian And C.D. Suriya kala, “ A New UWB Tri Band Antenna For Cognitive Radio” , International Conference 0n Communication, Computing And Security (ICCCS-2012)
  2. ReshmaLakshanan And Shinoj K. Sukumaran, “ FlexibleUWb Antenna For WBN Applications”, International Conference on Emerging Trends In Engineering, Science and Technology (ICETEST-2015)
  3. Awad and MohammesK.Abdelazeez, “ Multi Slot Microstrip Antenna For Ultra-Wide Band Applications”, Journal of King Saud University-Engineering Sciences,2016.
  4. Yashar Zenforoosh, Changiz Ghobadi And JavadNourinia, “ Antenna Design For Ultra Wide Band Application Using A New Multilayer Structure” , PIERS Online, Vol.2,No.6,2006.
  5. A .Hsseini, Z.Ztlasbaf and K.Forooraghi, “Two New Loaded Compact Planar Ultra Wide Band Antenna Using Defected Ground Plane” , Progress In Electromagnetic Research B, Vol.2,165-176,2008.
  6. ZuhuraJuma Ali, “ A Printed Microstrip Patch Antenna Design For Ultra Wideband Applications” , International Journal Of Science And Research (IJSR), ISSN (Online): 2319-7064.
  7. Merin Susan Philip,M.J. Jayashree, Satya Bhusan Shukla, “ Performance Evolution Of An Ultra Wideband Slot Antenna” , International JournalOf Engineering And Innovative TechnologyVol.3, Issues-1, July,2015Roberts, J. (2016).

310-312

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59.

Authors:

Dharma Pal Singh Chauhan

Paper Title:

Model Order Reduction of Continuous Interval Systems via Time Moment Matching and Pole Clustering Approaches

Abstract: In this manuscript, authors propose an algorithm for model order reduction of interval systems. Algorithm utilizes pole clustering and time-moment matching approaches for calculating denominator and numerator of model respectively. In pole clustering approach, poles of the high order system are considered for denominator calculation. According to order of the model, clusters of the poles are framed. Cluster centre of every cluster is determined using inverse distance criterion. Using these cluster centres, model denominator is deduced. Numerator is obtained by equating time moments of system and model. Proposed algorithm is applied on sixth order system and results are compared with other existing techniques which shows that proposed algorithm is superior to other techniques.

Keywords: Inverse Distance Criterion; Interval System; Model-order Reduction; Pole-Clustering; Time-Moment; Time Moment Matching.

References:

  1. Bandyopadhyay, et al., "Routh-Pade approximation for interval systems," IEEE Transactions on Automatic Control, vol. 39, pp. 2454-2456, 1994.
  2. Sastry, et al., "Large scale interval system modelling using Routh approximants," Electronics letters, vol. 36, pp. 768-769, 2000.
  3. Bhattacharyya, et al., "Robust control: the parametric approach," Upper Saddle River, 1995.
  4. Singh, et al., "On Time Moments and Markov Parameters of Continuous Interval Systems," Journal of Circuits, Systems and Computers, vol. 26, p. 1750038, 2017.
  5. Sastry and P. M. Rao, "A new method for modelling of large scale interval systems," IETE journal of research, vol. 49, pp. 423-430, 2003.
  6. Sastry and G. R. Rao, "Simplified polynomial derivative technique for the reduction of large-scale Interval systems," IETE journal of research, vol. 49, pp. 405-409, 2003.
  7. Bandyopadhyay, et al., "Stable γ− δ Routh approximation of interval systems using Kharitonov polynomials," international journal of information and systems sciences, vol. 4, pp. 348-361, 2008.
  8. Ismail, et al., "Discrete interval system reduction using Pade approximation to allow retention of dominant poles," IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 44, pp. 1075-1078, 1997.
  9. Singh and D. Chandra, "Model reduction of discrete interval system using clustering of poles," International Journal of Modelling, Identification and Control, vol. 17, pp. 116-123, 2012.
  10. Deif, "The interval eigenvalue problem," ZAMM‐Journal of Applied Mathematics and Mechanics/Zeitschrift für Angewandte Mathematik und Mechanik, vol. 71, pp. 61-64, 1991.

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60.

Authors:

Divya Sri, B. Purna Chandra Sekhar, D.V. Seshagirirao, P.V. Surendra Mohan Kumar

Paper Title:

Evaluation of Thermal Performance and Thickness of Carbon Phenolic Composite Structure under Aero-Thermal Loading

Abstract: Aerospace structures contain multilayer structures to sustain severe aerodynamic loading and heating. Hence they will be made with a carbon-epoxy internal layer(as a structural layer) whereas carbon phenolic external layer (as thermal protection layer) as a multi-layered component. Carbon-phenolic composites are meant or heat protection of the aerospace like aircraft skins, nozzles and heat shields during the aerodynamic loading conditions. In this paper, the behavior of the thermal protection system under aero-thermal load during re-entry at hypersonic speed through the earth atmosphere has been studied. Thermal performance of the carbon-phenolic components depends on the shape of the structure, velocity of the object, angle of attack and the heat flux experienced. The heat of reaction and pyrolysis process decides the structural integrity of the thermal layer. For various velocities, shapes and heat Flux conditions, the rate of ablation, surface temperature, residual thickness of the material has been evaluated. The heat of reaction and the volume of chemical species evolved under aerodynamic heating are measured by pyrolysis gas chromatography (Py-GC) and thermo-gravimetry (TG), which will be used as inputs or thermal evaluation of the structure. Modeling of the blunt body using CAD and imported to simulation software USIM to visualize different properties of the atmosphere and blunt body model.

Keywords: (as a Structural Layer), (as Thermal Protection Layer) (Py-GC) and Thermo-Gravimetry (TG),

References:

  1. Yaxi Chen, Ping Chen, Changqing Hong, Baoxi Zhang, David Hui 2013 Improved ablation resistance of carbon–phenolic composites by introducing zirconium diboride particles Composites Part B: Engineering. 47 320-325.
  2. Paglia, J.Tirillò, F.Marra, C.Bartuli, A.Simone, T.Valente, G.Pulci 2016 Carbon-phenolic ablative materials for re-entry space vehicles: plasma wind tunnel test and finite element modeling J. Materials & Design. 90 1170-1180.
  3. Hsi-Wu Wong, Jay Peck, James Assif, Francesco Panerai, Jean Lachaud, Nagi N.Mansour 2016 Detailed analysis of species production from the pyrolysis of the Phenolic Impregnated Carbon Ablator Journal of Analytical and Applied Pyrolysis 122. 258-267.
  4. James B.Scoggins, Jason Rabinovitch, Benjamin Barros-Fernandez, Alexandre Martin, Jean Lachaud, Richard L.Jaffe, Nagi N.Mansour, Guillaume Blanquart, Thierry E.Magin 2017 Thermodynamic properties of carbon–phenolic gas mixtures Aerospace Science and Technology. 66 177-192.
  5. Bernd Helber, Alessandro Turchi, James B.Scoggins, Annick Hubin, Thierry E.Magin 2016 Experimental investigation of ablation and pyrolysis processes of carbon-phenolic ablators in atmospheric entry plasmas International Journal of Heat and Mass Transfer. 100 810-824.
  6. Samire Sabagh, Ahmad Aref Azar, Ahmad Reza Bahramian 2017 High-temperature ablation and thermo-physical properties improvement of carbon fiber reinforced composite using graphene oxide nanopowder Composites Part A: Applied Science and Manufacturing 101. 326-333.
  7. Sanoj, Balasubramanian Kandasubramanian 2014 Hybrid Carbon-Carbon Ablative Composites for Thermal Protection in Aerospace J. Journal of Composites 825607. 15.
  8. Alexandre Martin, Iain D. Boyd 2010 Chemistry model for ablating carbon-phenolic material during atmospheric re-entry J. AIAA 2010-1175.
  9. Bianchi, D, Martelli, E, Onofri, M 2006 Practical Navier-Stokes Computation of Flowfields with Ablation Products Injection Thermal Protection Systems and Hot Structures 631. 15.
  10. S. Tate, S. Gaikwad, N. Theodoropoulou, E. Trevino, J. H. Koo 2013 Carbon/Phenolic Nanocomposites as Advanced Thermal Protection Material in Aerospace Applications J. Journal of Composites ID 403656. 9.

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61.

Authors:

G. Ramesh, Ch. Mallikarjuna Rao

Paper Title:

Code-Smells Identification by using PSO Approach

Abstract: Code-smell defines the smells which arise in coding part of the software development life cycle. It is very crucial to detect smells in software projects. If smells are detected earlier then the possibility of occurrence of errors, faults will be reduced. Hence, quality of the software is improved. The existing work used Bayesian approaches, manual approaches and search-based approaches to detect smells. These approaches lack in getting optimization solutions in detecting process. So, paper makes use of one of the popular optimization technique called Particle Swarm Optimization (PSO) for detecting the smells in programming part. The technique shows how intelligently the smells are detected and mainly concentrated on five types of smells namely Long Methods, Long Parameters, Large Classes, Duplicated Codes, and Primitive Obsessions. Implementation of this technique is, considering source-code of any software applications or programs and injecting PSO technique into the system. Here, PSO has trained to detect five types of smells whenever their appear in the source-code. Detecting the smells in initial stages of the project gives best performance of the software, and in other hand quality of the software is achieved. Experimental results are shown by using PSO technique, where searching time will be less consumed and accuracy of the system is gained.

Keywords: Code-Smells, Duplicated Codes, Software Quality, PSO. 

References:

  1. Wael Kessentini, Houari Sahraoui, Slim Bechikh, and Ali Ouni, “A Cooperative Parallel Search-Based Software Engineering Approach for Code-Smells Detection”, IEEE Transactions on Software Engineering 40(9):841-861 · September 2014.
  2. R. Chidamber and C. F. Kemerer, “A metrics suite for objectoriented design,” IEEE Trans. Softw. Eng., vol. 20, no. 6,pp. 293–318, Jun. 1994.
  3. Harman, S. A. Mansouri, and Y. Zhang, “Search-based software engineering: Trends, techniques and applications,” ACM Comput. Surv., vol. 45, no. 1, 61 pages.
  4. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA,USA: Addison Wesley, 1989.
  5. Tomassini and L. Vanneschi, “Guest editorial: Special issue on parallel and distributed evolutionary algorithms, part two,”Genetic Program. Evolvable Mach., vol. 11, no. 2, pp. 129–130, 2010.
  6. Fowler, K. Beck, J. Brant, W. Opdyke, and D. Roberts, Refactoring: Improving the Design of Existing Code. Reading, MA,USA:Addison Wesley, 1999.
  7. K, A. AnandaRao and Ramesh. G “Detection of Code-Smells by Using Particle Swarm Optimization Technique (PSO)”, South Asian Journal of Engineering and Technology Vol.2, No.28 Pp. 10–13, 2016.
  8. Eberhart & Dr. Kernnedy, “particle swarm optimization”, IEEE, pp. 1942-1948, 1995.
  9. Vignesh and P. Ramya, “Detection and Removal of Bad Smells instantly using a InsRefactor” , international Journal of Computer Science & Engineering Technology(IJCSET), Vol. 5 No. 04 Apr 2014.
  10. J. Brown, R. C. Malveau, W. H. Brown, and T. J. Mowbray, Anti Patterns: Refactoring Software, Architectures, and Projects in Crisis. Hoboken, NJ, USA: Wiley, 1998.

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62.

Authors:

M. Rajasekhar, T. Prasanth, M. Yasheel, N. Rufus

Paper Title:

Analysis of Defective Bearings

Abstract: Rolling element bearings are widely used as low friction joints between rotating machine components. A small defect either on raceway or the ball may occur while installation or any other process should be detected. If not detected in time, the defect forms a fatigue and increases upon working, decreasing the life time of bearing and leads to malfunctioning of the machine components. This research work is mainly focused on the frequency of vibrations produced by the bearings with different faults and gives the comparison between vibrational frequency of different faulty bearings and healthy bearing. The results of this experiment are interpreted to shoot out the defect in the bearing, which is helpful in finding the fault in the bearing element without dismantling the machine with reference to the frequency graphs.

Keywords: If Not Detected In Time, the Defect Forms A Fatigue And Increases Upon Working,

References:

  1. Sugumaran, K. I. Ramachandran, Fault diagnosis of roller bearing using fuzzy classifier and histogram features with focus on automatic rule learning, Expert Systems with Applications, Vol. 38, 2011, 4901- 4907.
  2. K. Kankar, S. C. Sharma, S. P. Harsha, Fault diagnosis of ball bearings using continuous wavelet transform, Applied Soft Computing, Vol. 11, 2011, 2300-2312.
  3. S. Patil, J. Mathew, P. K. Rajendra kumar, S. Desai, A theoretical model to predict the effect of localized defect on vibrations associated with ball bearing, International Journal of Mechanical Sciences, Vol. 52, 2010, 1193-1201.
  4. Debray, F. Bogard, Y.Q.Guo, Numerical vibration analysis on defect detection in revolving machines using two bearing models, Archive of Applied Mechanics, Vol. 74, 2004, 45-58
  5. Djebala, N. Ouelaa, N.Hamzaoui, Detection of rolling bearing defects using discrete wavelet analysis, Meccanica, Vol. 43, 2008, 339-348.
  6. Orhan, N. Akturk, V. Celik, Vibration monitoring for defect diagnosis of rolling element bearings as a predictive maintenance tool: Comprehensive case studies, NDT&E International, Vol. 39, 2006, 293-298.
  7. B. Randall, J. Antoni, Rolling element bearing diagnostics - A tutorial”, Mechanical Systems and Signal Processing, Vol 25, 2011, 485-520.
  8. Stepanic, I. V. Latinovic, Z.Djur, A new approach to detection of defects in rolling element bearings based on statistical pattern recognition, International Journal of Advanced Manufacturing Technology, Vol. 45, 2009, 91-100.
  9. Zotos, Th. Costopoulos, on the use of rolling element bearings models in precision maintenance, American Journal of Engineering and Applied Science, Vol. 6, 2009, 344-352.
  10. S. Patil, J. Mathew, P. K. Rajendrakumar, S. Desai, A theoretical model to predict the effect of localized defect on vibrations associated with ball bearing, International Journal of Mechanical Sciences, Vol. 52, 2010, 1193-1201.

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63.

Authors:

E. Srinivas, Lakkireddy Jhansi, N. Sharath Kumar

Paper Title:

A Low Power and High Resolution 2nd Order DT Sigma-Delta Modulator for Data Converters

Abstract: A 2nd order low power and High Resolution discrete time Sigma-Delta modulator presented in this paper for Analog-to-Digital converters (ADC), is developed using CMOS technology. This paper is specifically designed through which it accepts an input signal of frequency 1 KHz, an over sampling ratio (OSR) ≤512 and sampling frequency up to 2MHZ for a second order Sigma-Delta modulator. It is put in to practice in a standard 0.18 µm (180nm) CMOS technology. The design of the sigma-Delta modulator and the simulation of it is done by using CADENCE tools. To form Sigma-Delta modulator this paper essentially elaborates integrator, summer, comparator, D-Latch and Digital-to-Analog (DAC) converters which are integrated together. The key component used in the design is CMOS Operational Amplifier, the OP-AMP open loop gain is 86.8dB, unity gain frequency 5.41 MHz and power consumption is 35.6 microwatts. Finally using a ±1.8 v supply voltage a 2nd order Sigma-Delta modulator is realized.

Keywords: Analog-Digital Converters, Op-Amp, Operational Amplifier, Sigma-Delta Modulator.

References:

  1. Youngcheol Chae, Gunhee Han “Low Voltage, Low Power, Inverter-Based Switched-Capacitor Delta-Sigma Modulator” in IEEE JOURNAL OF SOLID-STATE CIRCUITS, VOL. 44, NO. 2, FEBRUARY 2009.
  2. Luca Bettini Thomas Christen, Thomas Burger, Qiuting Huang “A Reconfigurable DT ∑∆ Modulator for Multi-Standard 2G/3G/4G Wireless Receivers” IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, VOL. 5, NO. 4, DECEMBER 2015.
  3. Prakruthi T.G, Siva Yellampalli “Design and Implementation of Sample and Hold Circuit in 180nm CMOS Technology” in IEEE transactions 2015.
  4. “Methodology for designing switched capacitor sample and hold circuit used in data converters” IET circuits,Device and systems,28th Nov 2013
  5. Behzad Razavi,”Design of sample and hold amplifiers for high speed low voltage A/D converter”, Custom integrated circuit conference, IEEE 1997.
  6. Specification and architecture of sample and hold amplifier”, National semiconductor corporation,July 1998..
  7. Biao Li,”A high DC gain op-amp for sample and hold circuit”, proceedings of the 2nd international conference on computer science and electronic engineering, ICCSEE 2013.
  8. Yan Xiang,Fan xiangining ,”Design of sample and hold circuit for a reconfigurable ADC”,International conference on computer science and service system,2012southeast university,Nanjing,China.
  9. Razavi, “Design of Analog CMOS Integrated Circuits”, New York: Mc-Graw Hill,2001.
  10. Johns and Ken Martin “Analog Integrated Circuit Design”, Wiley India Pvt. Ltd, 1997.
  11. Boaz Shem-Tov, MucahitKozak, and EbyG.Friedman, “A High – Speed CMOS Op-Amp Design Techniques using Negative Miller Capacitance,” proceedings of the 11th IEEE International Conference on Electronics, circuit and systems, December 200.

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64.

Authors:

Manohar K. R. Dasannagari, Emanuel S. Grant

Paper Title:

Review of the use of Formal Specification Techniques in Safety Critical Systems

Abstract: In today’s world, computers permeate control systems on which most human lives depend. Thus, the need for software safety is vital. One best approach to ensure the correctness of such systems is to apply formal specification techniques. The use of these techniques helps in the increase of human confidence in safety critical systems. This paper focuses on the review of the use of formal specification techniques in the fields of aviation, and railways. The first section gives a brief description about safety critical systems and formal specification techniques. The second section provides background of the use of formal specification techniques in different areas. The application of formal specification techniques in the railway industry, its advantages and disadvantages will be discussed in third section. The next section provides an insight of application of formal specification techniques in the field of aviation, its pros and cons. The concluding section addresses future need of formal specification techniques usage in safety critical systems that can put human life at stake.

Keywords: Safety Critical Systems, Formal Specification Techniques, Aviation, Railways, Medical.

References:

  1. Bowen, Jonathan P., and Victoria Stavridou. "Formal methods and software safety." Safety of Computer Control Systems 1992 (SAFECOMP'92). 1992. 93-98.
  2. Singh, Monika, Ashok Kumar Sharma, and Ruhi Saxena. "Why Formal Methods Are Considered for Safety Critical Systems?" Journal of Software Engineering and Applications 8.10 (2015): 531.
  3. Lamsweerde, Axel van. "Formal specification: a roadmap." Proceedings of the Conference on the Future of Software Engineering. ACM, 2000.
  4. Bowen, Jonathan, and Victoria Stavridou. "Safety-critical systems, formal methods and standards." Software Engineering Journal 8.4 (1993): 189-209.
  5. Zafar, Nazir Ahmad, Sher Afzal Khan, and Keijiro Araki. "Towards the safety properties of moving block railway interlocking system." Int. J. Innovative Comput., Info & Control8.7 (2012): 5677-5690.
  6. Janota, Ales. "Using Z specification for railway interlocking safety." Periodica Polytechnica. Transportation Engineering28.1-2 (2000): 39.
  7. Jamal, Maryam, and Nazir Ahmad Zafar. "Requirements analysis of air traffic control system using formal methods." Information and Emerging Technologies, 2007. ICIET 2007. International Conference on. IEEE, 2007.
  8. Keenan, Peter. "Formal methods and air traffic control-opportunities and limitations." Software in Air Traffic Control Systems-The Future, IEE Colloquium on. IET, 1992.

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65.

Authors:

Enaul haq Shaik, Krishna Prasad Satamraju, Riyazuddien Shaik, Vasantha Lakshmi Movva

Paper Title:

Interference based All-optical 4 × 2 Encoder

Abstract: In this article, we propose the design of all-optical photonic crystal based 4 × 2 encoder by interconnecting cross-shaped waveguide dependent OR gate. Initially the design and operation of photonic crystal based OR gate using cross-shaped waveguide is discussed with an additional reference input. The phase of all the input light signals are maintained at zero in order to have constructive interference to perform OR function. Later, OR gates are interconnected to realize encoder in such a way that the light path from the input ports to cross-shaped waveguide junctions be same. The structure is numerically simulated using Finite Difference Time Domain (FDTD) method and observed that the contrast ratio is 7.98 dB. Also, the size of the proposed structure is quite smaller by 84.7% and 22.07% than self-collimation and resonance based designs existing in the literature so far. With the fair results obtained, it can be concluded that the proposed encoder is suitable as a basic component in future Photonic Integrated Circuits.

Keywords: Photonic Crystal, All-Optical 4×2 Encoder, Contrast ratio

References:

  1. Hamed A B, Farhad M, Somaye S, Mahdi H K, "A 2*4 all optical decoder switch based on photonic crystal ring resonators", Journal of Modern Optics, 2014, 62(6), pp: 430-434.
  2. Rani P, Yogita K, Sinha R K, "Realization of AND gate in Y-shaped photonic crystal waveguide", Optics Communications, 2013, 298–299, pp: 227-231.
  3. Wang J, Sun J, Sun Q, "Experimental observation of a 1.5 µm band wavelength conversion and logic NOT gate at 40 Gbit/s based on sum-frequency generation", Optics Letters, 2006, 311(11), pp: 1711–1713.
  4. Esmaeli S A, Cherri A K, "Photonic crystal based all-optical arithmetic circuits without SOA-based switches", Optik-International Journal for Light and Electron Optics, 2014, 125(14), pp: 3710-3713.
  5. Lee C L, Lee R K, Kao Y M, "Design of multichannel DWDM fiber Bragg grating filters by Lagrange multiplier constrained optimization", Optics Express, 2006, 14(23), pp: 11002-11011.
  6. Uthayakumar T, Jayakanta R, Porsezian K, "Realization of all-optical logic gates through three core photonic crystal fiber", Optics Communications, 2013, 296, pp: 124-131.
  7. Johnson S G, Joannopoulos J D. Introduction to Photonic Crystals: Bloch’s Theorem, Band Diagrams, and Gaps (But No Defects). Cambridge, MA, USA: MIT, 2003.
  8. Shaik E H, Rangaswamy N, "Design of photonic crystal-based all-optical AND gate using T-shaped waveguide", Journal of  Modern Optics, 2016, 63(10), pp: 941-949.
  9. Bao J, Xiao J, Fan L, Li X, Hai Y, Zhang T, Yang C, "All-optical NOR and NAND gates based on photonic crystal ring resonator", Optics Communications, 2014, 329, pp: 109-112.
  10. Christina X S, Kabilan A P, "Design of optical logic gates using self-collimated beams in 2D photonic crystal", Photonic Sensors, 2012, 2(2), pp: 173-179.
  11. Wu C J, Liu C P, Ouyang Z, "Compact and low-power optical logic NOT gate based on photonic crystal waveguides without optical amplifiers and nonlinear materials", Applied Optics, 2012, 51(5), pp: 680-685.
  12. Hadi G., Somaye M, "2-channel all optical demultiplexer based on photonic crystal ring resonator", Frontier of Optoelectronics, 2013, 6(2), pp: 224-227.
  13. Moniem T A, "All-optical digital 4 × 2 encoder based on 2D photonic crystal ring resonators", Journal of Modern Optics, 2015, 63(8), pp: 735-741.
  14. Alipour-Banaei H, Rabati M G, Abdollahzadeh-Badelbou P, Mehdizadeh F, "Application of self-collimated beams to realization of all optical photonic crystal encoder", Physica E, 2016, 75, pp: 77-85.
  15. Ouahab I, Naoum R "A novel all optical 4×2 encoder switch based on photonic crystal ring resonators", Optik-International Journal for Light and Electron Optics, 2016, 127, pp: 7835-7841.
  16. Jiang Y C, Liu S B, Zhang H F, Kong X K "Realization of all optical half-adder based on self-collimated beams by two-dimensional photonic crystals", Optics Communications, 2015, 348, pp:90-94.

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