S. No

Volume-3 Issue-2, May 2014, ISSN:  2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Mohammed Hussein Baqir

Paper Title:

System Efficiency Using PWM Switching Strategies

Abstract:   Pulse Width Modulation (PWM) is the technique of using switching devices to produce the effect of a continuously varying analogue signal; this PWM conversion generally has very high electrical efficiency. In controlling either a three-phase synchronous motor or a three-phase induction motor it is desirable to create three perfectly sinusoidal current waveforms in the motor windings, with relative phase displacements of 120°.  The production of sinewave power via a linear amplifier system would have low efficiency, at best 64%. If instead of the linear circuitry, fast electronic switching devices are used, and then the efficiency can be greater than 95%, depending on the characteristics of the semiconductor power switching.

Keywords: fast electronic switching devices are used, and then the efficiency can be greater than 95%,

References:
1.     . S.R., and Midoun, A. " Generalized Techniques of Harmonic Elimination and Voltage Control in Thyristor Inverters: part II- voltage Control Technique", IEEE Trans., 1974, Vpl. 1A-10, P.P. 666-673.
2.     N. Mohan, T- Underland, W. Robbins, " Power electronics Converters Application and Design ", Jone Wiley and Sons, 2008.
3.     S. Yeralan, "Programming and Interfacing the 8051 Microcontroller ", rigel corporation 2009. 
4.     K. E. Addoweesh and W. Shepherd, "Induction Motor Speed Control Using a Microprocessor Based PWM Inverter ", IEEE. Trans. Ind. Electron. Vol. 36, No. 4, Nov.1989.
5.     P. V. Enjeti, P. D. Ziogas and J. F. Lindsay, "Programmed PWM Techniques To Eliminate Harmonics A Critical Evaluation ", IEEE. Trans. Ind. Appl. Vol. 26, No. 2, MAR/APR. 1990.
6.     Richard A. Pear man, " Power Electronic Solid State Motor Control ", Print in 2003.
7.     B. Szabados and P. Lindon, "Pulse Width Modulation Inverter Drive Wth Fast Response to Frequency and Amplitude Controls ", IEEE. Trans. Ind. Electron , Vol. IECI-28, No. 4, NOV. 1981.
8.     J. You Lee and Y. Yih Sun, "Adaptive Harmonic Control in PWM Inverter With Fluctuating Input Voltage ", IEEE. Trans. Ind. Electron, Vol. IE-33, No. 1, FEB, 1986.

1-6

2.

Authors:

Junaid Maste, P. J. Salunke, N. G. Gore

Paper Title:

Dynamic Analysis of Laterally Loaded Piles (Effect of Spacing & Diameters

Abstract: In this study the finite element model (FEM) analysis of group of piles in cohesionless soil with the diameter from 0.5m to 2m and spacing between the piles varied from 2D to 3D by means of the FB-multipier software. Hence by developing a finite element model soil structure interaction study is carried out considering nonlinear soil behavior in time domain analysis with the help of Newmark’s beta method.       

Keywords:   Laterally loaded piles, Dynamic analysis, p-y curves, Newmark’s beta method, FB-multipier 

References:
1.        Milos Novak, “Dynamic stiffness and damping of piles,” Canadian geotechnical journal, June (1974), pp.575-598 
2.        Georgiadis, M., Anagnostopoulos, C. and Saflekou, S. (1992), “Cyclic lateral loading of piles in soft clay”, Geotech. Eng., 23(1), 47-60.
3.        Ashish Mehta et al., “Behavior of laterally loaded Pile,” International Journal of Engineering Science and Technology,(2010),pp.7252-7254 
4.        Sri Dewi et al., “Analysis on laterally loaded group piles by PLAXIS 3D foundation,” Journal of Engineering, March(2011),pp.1-5 
5.        K. Rajagopal et al., “Influence of combined vertical and lateral loading on the lateral response of piles,” International Association for Computer Methods and Advances in Geomechanics, October(2008),pp.3272-3282 
6.        Zamri H. Chik et al., “Lateral behavior of single pile in cohesionless soil subjected to  both vertical and horizontal loads,” European Journal of Scientific Research,(2009),pp. 194-205 
7.        K. B. Ladhane and V. A. Sawant., “Dynamic analysis of pile group with 3-piles in series arrangement.” Indian Geotechnical Conference, December(2011),pp.955-958 
8.        Christina J et al., “Dynamic experiments and analyses of a pile group supported structure,” Journal of Geotechnical and Geo-environmental Engineering, July(2001),pp.585-596 
9.        Mohamad Ahangar et al., “Dynamic nonlinear behavior of fixed offshore jacket piles,” International Journal of Civil and Structural Engineering, September(2011),pp.260-269 
10.     Kiran B. Ladhane and V. A. Sawant., “ Dynamic response of 2 piles in series and parallel arrangement,” Engineering Journal, July (2012),pp.1-10 
11.     Mohammad M. Ahmadi et al., “Dynamic analysis of piles in sand based on soil-pile-interaction,” World Conference on Earthquake Engineering, October(2008),pp.1-8
12.     Vishwas A. Sawant et al., “Finite element analysis for laterally loaded piles in sloping ground,” Coupled Systems Mechanics, (2012), pp.59-78 
13.     Murugan M et al., “Behavior of laterally loaded piles in cohesionless soils,” International Journal of Earth Sciences and Engineering, October (2011), pp.104-106 
14.     P.K. Basudhar et al., “Flexural analysis of laterally loaded piles using cpt and pmt results: a comparative study,(2009),pp.718-722

7-9

3.

Authors:

V. D. Shinde, Anand S. Shivade

Paper Title:

Parametric Optimization of Surface Roughness in Wire Electric Discharge Machining (WEDM) using Taguchi Method

Abstract:   Wire electrical discharge machining (WEDM) is widely used in machining of conductive materials when precision is of primary significance. Wire-cut electric discharge machining of AISI D3 tool steel has been considered in the present work. Experimentation has been completed by using Taguchi’s L9orthogonal array with different levels of input parameters. Optimal combination of parameters was obtained by this technique. The Taguchi technique was used for design of experiment so that with minimum number of experiments, the complete problem can be solved as compared to full factorial design. Experimental results make obvious that the machining model is proper and the Taguchi’s method satisfies the practical requirements. The results obtained are analyzed for the selection of an optimal combination of WEDM parameters for proper machining of AISI D3 tool steel to achieve better surface finish. Different analysis was made on the data obtained from the experiments.

Keywords:  ANOVA, D3 tool steel, Design of experiments, Surface roughness, Taguchi method, Wire electrical discharge machining (WEDM).

References:
1.     S. Kalpakjian and S. Schmid, “Manufacturing process for engineering materials”, Pearson education, South Asia, 2009.
2.     Lee S.H., Li X.P. (2001), “Study of the effect of machining parameters on the machining characteristics in electrical discharge machining of tungsten carbide”, Journal of Material Processing Technolology, 115, 344-358.
3.     Nihat Tosun (2003), “The effect of the cutting parameters on performance of WEDM”, KSME international journal, 17(6)816- 824.
4.     Chiang K.T., Chang, F.P. (2006), “Optimization of the WEDM process of particle-reinforced material with multiple performance characteristics using grey relational analysis”, Journal of Materials Processing Technology, 180, 96-101.
5.     Kanlaya siria K., Boonmung S. (2007), “Effects of wire-EDM machining variables on surface roughness of newly developed DC 53 die steel: design of experiments and regression model”, Journal of Materials Processing Technology, 459-464. 
6.     U. Esme, A. Sagbas and F. Kahraman (2009), “Prediction of surface roughness in wire electrical discharge machining using design of experiments and neural networks”, Iranian journal of science & technology, transaction b, engineering, 33, 231-240.
7.     Muthu Kumar V, Suresh Babu A , Venkatasamy R  and Raajenthiren M (2010),“Optimization of the WEDM Parameters on Machining Incoloy800 Super alloy with Multiple Quality Characteristics”, International Journal of Engineering Science and Technology,2(6), 1538-1547.
8.     Vamsi Krishna Pasam (2010), “Optimizing Surface Finish in WEDM Using the Taguchi Parameter Design Method”, J. of the Braz. Soc. of Mech. Sci. & Eng, 32(2), 107-113.
9.     Pujari Srinivasa Rao, Koona Ramji and Beela Satyanarayana (2011), “Effect of WEDM conditions on surface roughness:  a parametric optimization using Taguchi method”, International journal of advanced engineering sciences and technologies, 6(1), 41-48.
10.  Anish Kumar , Vinod Kumar and Jatinder Kumar (2012),“Prediction of Surface Roughness in Wire Electric Discharge Machining (WEDM) Process based on Response Surface Methodology”, International Journal of Engineering and Technology,2(4),708-719.
11.  Atul Kumar and Dr.D.K.Singh (2012), “Strategic optimization and investigation effect of process parameters on performance of wire electric discharge machine (WEDM)”, International journal of engineering science and technology, 4(06), 2766-2772.
12.  Dharmender, Rajeev Kumar and Anmol Bhatia (2012), “Investigation of the effect of Process Parameters on Surface Roughness in Wire Electric Discharge Machining of En31 Tool Steel”, Proceedings of the National Conference on Trends and Advances in Mechanical Engineering, YMCA University of Science & Technology,
Faridabad, Haryana,417-423.
13.  G. Rajyalakshmi and P.Venkata Ramaiah (2012), “A parametric optimization using Taguchi method: effect of WEDM parameters on surface roughness machining on Inconel 825”, Elixir Mech. Engg., 43, 6669-6674.
14.  Maneesh K. Yadav, ShaileshM.Pandey, Sumit Chaudhary and Qasim Murtaza (2012), “Effects of machining variables on surface roughness in wire-EDM of AISI D3”, International journal of engineering sciences, 1(3), 2277-9698.
15.  Navjot Singh, Parlad Kumar and Khushdeeep Goyal (2014), “Experimental Investigation of WEDM Variables on Surface Roughness of AISI D3 Die Steel By Using Two Cryogenically Treated Different Wires”, Manufacturing Science and Technology, 2(1),20-25.
16.  M.S.Phadke, “Quality engineering using robust design”, Pearson education, South Asia, 2012.
17.  G.Taguchi, S.Chowdhury and Y.Wu, “Taguchi’s Quality Engineering Handbook”, John Wiley & Sons, Inc., 2005.
18.  P.J.Ross, “Taguchi technique for quality engineering”, Tata McGraw-Hill Edition. , 2005.

10-15

4.

Authors:

Bhavin Mehta, Milind Soni, Kandarp Changela

Paper Title:

Review of Parametric Investigation of Cryogenic Heat Pipe

Abstract:   with the advancement in cryogenics, applications like optical sensors, electronic circuitry are devised to operate at very low temperature and thereby efficient heat transfer devices are required to transfer heat through a very low temperature gradient. In such cases even high conducting materials, like copper fail to transfer heat at the required levels as the temperature gradient is not sufficient. Cryogenic heat pipes stand out as a prominent heat transfer device in such low temperature gradient heat transfer without any external power. Heat pipe consists of basic three components, like container, working fluid and wick structure. The various working fluids which can be used in cryogenic heat pipe are nitrogen, oxygen, argon, helium, neon and propylene. Many types of heat pipes are available and the operation of a particular heat pipe for an application is constrained by a number of parameters. The paper deals with the review of various parameters like heat load, use of various working fluids, use of various wick structures, tilt angle and its effect on the performance of heat pipe at cryogenic temperature range.

Keywords:   Heat Pipe, Cryogenics, Working fluid, Wick structure.

References:
1.        Chandratilleke R, Hatakeyama H and Nakagome H, Development of      cryogenic loop heat pipes, 1998, Cryogenics vol- 38, 263–269.
2.        Mo Q, Liang J.T, A novel design and experimental study of a cryogenic loop heat pipe with high heat transfer capability, 2006, International Journal of Heat and Mass Transfer vol-49, 770–776.
3.        Kwon D. W, Sedwick R.J, Cryogenic heat pipe for cooling high temperature superconductors, 2009, Cryogenics vol-49, 514–523.
4.        Abdel-Samad S, Abdel-Bary M, Kilian K, Ritman J, Cryogenic target with very thin ‘‘gold finger’’ heat pipe, 2006, Nuclear Instruments and Methods in Physics Research Vol 556, 20–23.
5.        Abdel-Samad S, Abdel-Bary M, Kilian K, Ritman J, Deuteriu heat pipes—cryogenic targets for COSY experiments, 2005, Nuclear Instruments and Methods in Physics Research A 550, 61–69.  
6.        Jiao A, Maa H. B, Critser J. K, Experimental investigations of cryogenic oscillating heat pipes, 2009, International Journal of Heat and Mass Transfer, Volume 52, 3504-3509.
7.        Bai L, Lin G, Zhang H, Miao J, Wen D, Experimental study of a nitrogen-charged cryogenic loop heat pipe, 2012,  Cryogenics, Article in press.
8.        Zhao Y, Yan T, Liang J, Experimental study on a cryogenic loop heat pipe with high heat capacity, 2011, International Journal of Heat and Mass Transfer 54, 3304–3308.
9.        Mo Q, Liang J, Operational performance of a cryogenic loop heat pipe with insufficient working fluid inventory, 2006, International Journal of Refrigeration 29, 519–527.
10.     Abdel-Bary M, Abdel-Samad S, Kilian K, 2m heat pipe-cryogenic targets   for COSY-TOF experiment, 2005, Nuclear Instruments and Methods in Physics Research A 551, 236–244.
11.     Abdel-Bary M, Abdel-Samad S, Elawadi G. A, Kilian K, Ritman J, A thin  gold coated hydrogen heat pipe-cryogenic target for external experiments at COSY, 2009, Cryogenics 49, 192–197.
12.     Natsume K, Mito T, Yanagi M, Tamura H, Tamada T, Shikimachi K,  Hirano N, Nagaya S, Heat transfer performance of cryogenic oscillating  heat pipes for effective cooling of superconducting magnets, 2011,  Cryogenics 51, 309–314.
13.     El-Awadi G, Abdel-Samad S, Abdel-Bary M, Ritman J, Improving the performance of the cryogenic heat pipe-target system for the COSY-TOF experiment, 2009, Vacuum 83, 1321–1325.
14.     Muniappan S and Arumugam S, Experimental investigation on an axial grooved cryogenic heat pipe, 2012, Thermal science, vol 16, 133-138.
15.     Senthil Kumar M, Senthil Kumar A, Investigation on Start-Up  Characteristics of  Cryogenic Heat Pipes, 2011, ARPN Journal of Engineering & Applied science, Vol 6 (6), 58-61. 
16.     Namac P, Caja A, Malcho M, Thermal Performance measurement of heat pipe, 2011, Global Journal of Technology & Optimization, Vol 2, 104-110.
17.     Korn F, Heat Pipe & its application, 2008, Heat & Mass Transport, project report.
18.     Chi S. W, Heat Pipe Theory & Practice, 1976, Hemisphere Publishing Corporation.
19.     Faghri A, Heat Pipe Science and Technology, 1995, Taylor & Francis publishers.
20.     Barron R F, Cryogenic systems, 1985, Oxford University Pres

16-19

5.

Authors:

Ankita R Suvagia

Paper Title:

A Review on Microstrip Antenna Optimization using Bio-Inspired Optimization Techniques

Abstract:     Soft computing techniques like neural network, genetic and other optimization techniques proved to be an effective way to solve the problem of getting optimum value of antenna parameters for a particular frequency band. It provides a solution for high dimension problems with multiple local optima. Parameters like gain, return loss and directivity are optimized for a microstrip antenna. This paper highlights the implementation of neural network and other bio-inspired optimization techniques like Particle –Swarm Optimization (PSO), Differential Evolution (DE) Techniques and Genetic Algorithm on Microstrip antenna Dimensions which results in better Performance.

Keywords: Optimization, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Biogeographic – Based Optimization (BBO).

References:
1.     Yahya Rahmat- Shamii, Joshua M. Kovitz, Harish Rajagopalan, “Nature –  Inspired Optimization Techniques In Communication Antenna Design”, Proceeding Of The IEEE | Vol.100 | No.7, July 2012.
2.     Satvir Singh, Shelja Tayal, Gagan Sachdev, “Evolutionary Performance of BBO and PSO Algorithm For Yagi-Uda Antenna Design Optimization”, IEEE 2012, ISBN: 978-1-4673-4805-8.
3.     Dan Simon, “Biogeographic Based Optimization”, IEEE Transactions on Evolutionary Computation, Vol. 12, No. 6, Ieee2008, Isbn: 1089-778 X.
4.     M.R.Lohokare, S.S.Pattanaik, B.K.Panigrahi, S.Das, M.K.Bakwad, “Parameter Calculation of Rectangular Microstrip Antenna Using Biogeographic- Based Optimization”, 978-1-4244-4819-7/09/$25.00 ©2009 IEEE.

20-22

6.

Authors:

Mohammed Jassim

Paper Title:

Design of High Performance Middleware for Dynamic Peer-To-Peer Networks

Abstract: This paper deals with a specially designed middleware (P2P Messaging System) that release the advantages of peer-to-peer networks to a broad spectrum of applications. The goal of this paper is to design a middleware for p2p networks that focuses on high-performance group communication based on a publish/subscribe model and its performance is compared with the JXTA technology. The P2P Messaging System considers the heterogeneous and dynamic character of peer-to-peer networks by an augmented topology and its supporting features. This paper gives a solution for an efficient group communication that is established by creating an Overlay networks to overcome topological limitations, implementing the Multi-ring topology to provide scalability, heterogeneity of Peers and decentralization, creation of Dual mode links to allow multiple message sources and to avoid message collisions and creation of Backup links to increase robustness.

Keywords:  Peer-to-Peer, Domain Name Server, World Wide Web, Over lay networks

References:
1.     A. Rowstron and P. Druschel, “Pastry: Scalable, Distributed Object   Location and Routing for Large-Scale Peer-to-Peer Systems,” Proc. IFIP/ACM Int’l. Conf.  Distrib. Sys. Platforms (Middleware), Heidelberg, Germany, Nov.2001, pp. 329–50.
2.     M.O.Junginger,“A High Performance Messaging System for Peer- to-Peer Networks,”Master’sthesis, Univ. of MO-Kansas City, 2003; http://www.junginger.biz/thesis 11
3.     M. O. Junginger and Y. Lee, “The Multi-Ring topology-High-Performance Group Communication in Peer-to-Peer Networks,” Proc. 2nd Int’l. Conf. Peer to-Peer Comp., 2002, pp. 49–56.                                    
4.     A.W.Loo,“The Future of Peer-to-Peer Computing,” Commun. ACM, vol. 46,no. 9, pp. 57–61,September 2003.                                           
5.     W.W.Terpstra et al.,“A Peer-to-Peer Approach to Content-Based   Publish/Subscribe,” 2nd Int’l. Wksp. Distrib. Event-Based Sys., San  Diego,CA, June 8, 2003.
6.     I.Stoica et al.,“Chord:A Scalable Peer-to-Peer Lookup Protocol for Internet Applications,” IEEE/ ACM Trans. Net., vol. 11, no. 1,Feb.2003,pp.17–32.forInternetApplications,”IEEE/ACM Trans. Net., vol. 11, no. 1, Feb. 2003, pp. 17–32.
7.     G.Mühl, “Large-Scale Content-Based Publish/ Subscribe Systems,”Ph.D.thesis,Univ.of Technology Darmstadt, 2002.
8.     P. R. Pietzuch and J. Bacon, “Peer-to-Peer Overlay Broker Networks    in an Event-Based Middleware,” 2nd Int’l. Wksp. Distrib. Event-Based Sys, San Diego, CA, June 8, 2003.
9.     Sun Microsystems (2003). Project JXTA    Home page.  Available at: http://www.jxta.org
10.  Daswani, N., Garcia-Molina, H. and Yang, B. (2003) Open Problems in Data-Sharing Peer to-Peer Systems. Proceedings of the 9th International Conference on Database Theory, pp.1-15. Springer-Verlag, eidelberg, Germany

23-27

7.

Authors:

Neha Sobti, Ketki Arora

Paper Title:

Implementation of Data Mining Decision Tree Algorithms on Mobile Computing Environment

Abstract:  The idea of complex activity for characterizing the continuously changing complex behavior patterns of mobile users. For the purpose of data management, a complex activity is modeled as a sequence of location movement, service requests, the co-occurrence of location and service, or the interleaving of all above. An activity may be composed of sub activities. We, therefore, propose new methods for complex activity mining, incremental maintenance, online detection and proactive data management based on user activities. In particular, we devise prefetching and pushing techniques with cost-sensitive control to facilitate predictive data allocation. Preliminary implementation and simulation results demonstrate that the proposed framework and techniques can significantly increase local availability, conserve execution cost, reduce response time, and improve cache utilization. Different activities may exhibit dependencies that affect user behaviors. We argue that the complex activity concept provides a more precise, rich, and detail description of user behavioral patterns which are invaluable for data management in mobile environments. Proper exploration of user activities has the potential of providing much higher quality and personalized services to individual user at the right place on the right time. With the help of data mining algorithms, we will try to reduce execution time, find correctly classified instance, reduce error rate and improve accuracy.

Keywords:   ID3, DTNA, Mobile environment, data mining algorithms

References:
1.       Xiang Lian, Student Member, IEEE, and Lei Chen, Member, IEEE, “Ranked Query Processing in Uncertain Databases”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 22, NO.3, MARCH 2010.
2.       Stavroula G. Mougiakakou, Member, IEEE, “SMARTDIAB: A Communication and Information Technology Approach for the Intelligent Monitoring, Management and  ollow-up of Type 1 Diabetes Patients”, IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 14, NO. 3, MAY 2010.
3.       Eric Hsueh-Chan Lu, Vincent S. Tseng, Member, IEEE, “Mining Cluster-Based Temporal Mobile Sequential Patterns in Location-Based Service Environments” , IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 23, NO. 6, JUNE 2011.
4.       Mark N. Gasson, EleniKosta, Denis Royer, Martin Meints, and Kevin Warwick, “Normality Mining: Privacy Implications of Behavioral Profiles Drawn From GPS Enabled Mobile Phones”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C: APPLICATIONS AND REVIEWS, VOL. 41, NO. 2, MARCH 2011.
5.       Tzung-Shi Chen, Member, IEEE, Yen-Ssu Chou, and Tzung-Cheng Chen, “Mining User Movement Behavior Patterns in a Mobile Service Environment”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 42, NO. 1, JANUARY 2012.
6.       R. Agrawal, T. Imielinski, and A. Swami, “Mining Associations between Sets of Items in Massive Databases,” Proc. ACM SIGMOD, pp. 207-216, May 1993.
7.       R. Agrawal and J. Shafer, “Parallel Mining of Association Rules,” IEEE Trans. Knowledge and Data Eng, vol. 8, no. 6, pp. 866-883, Dec. 1996.
8.       R. Agrawal and R. Srikant, “Mining Sequential Patterns,” Proc. 11th Int’l Conf. Data Eng., pp. 3-14, Mar. 1995.
9.       B. Bruegge and B. Bennington, “Applications of Mobile Computing and Communication,” IEEE Personal Comm., pp. 64-71, Feb. 1996.
10.    M.-S. Chen, J. Han, and P.S. Yu, “Data Mining: An Overview from Database Perspective,” IEEE Trans. Knowledge and Data Eng., vol. 8, no 6, pp. 866-883, Dec. 1996..
11.    M.-S. Chen, J.-S.Park, and P.S. Yu, “Efficient Data Mining for Path Traversal Patterns,” IEEE Trans. Knowledge and Data Eng., vol. 10, no. 2, pp. 209-221, Apr. 1998.
12.    D.W. Cheung, V.T. Ng, W. Fu, and Y. Fu, “Efficient Mining Association Rules in Distributed Databases,” IEEE Trans. Knowledge and Data Eng., vol. 8, no. 6, pp. 911-922, Dec. 1996.
13.    T.H. Cormen, C.E. Leiserson, and R.L. Rivest, Introduction to Algorithm. MIT Press, 1989.
14.    SouptikDatta, Chris R. Giannella, and HillolKargupta, Senior Member, IEEE, “Approximate Distributed K-Means Clustering over a Peer-to-Peer Network” , IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 21, NO. 10, OCTOBER 2009.
15.    Kwong-Sak Leung, Kin Hong Lee, Jin-Feng Wang, “Data Mining on DNA Sequences   of Hepatitis B Virus”, IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, VOL. 8, NO. 2, MARCH/APRIL 
16.    Shady Shehata, Member, IEEE, FakhriKarray, Senior Member, IEEE, and Mohamed S. Kamel, Fellow, IEEE, “An Efficient Concept-Based Mining Model for Enhancing Text Clustering”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 22, NO. 10, OCTOBER. 
17.    Lijun Wang, ManjeetRege, Ming Dong, Member, IEEE, and Yongsheng Ding, Senior Member, IEEE, “Low-Rank Kernel Matrix Factorization for Large-Scale Evolutionary Clustering” , IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 24, NO. 6, JUNE 2012
18.    Eghbal G. Mansoori, “FRBC: A Fuzzy Rule-Based Clustering Algorithm”, IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 19, NO. 5, OCTOBER.
19.    Ji Dan, QiuJianlin, “A Synthesized Data Mining Algorithm Based on Clustering and Decision Tree”, 2010 10th IEEE International Conference on Computer and Information Technology (CIT 2010).

28-31

8.

Authors:

Manisha Patil, Manjusha Deshmukh

Paper Title:

Comparative Study of Relative Radiometric Normalization using No Change Set

Abstract:   Satellite images involves radiometric errors as well as geometric errors, these errors should be normalized. For radiometric correction of satellite images there two main methods are useful, absolute radiometric normalization and relative radiometric normalization. Relative radiometric correction has number of applications in weather and climate studies, crop studies, detection and removal of cloud, change detection and so on. The image distortion due to cloud cover is a classical problem of remote sensing imagery. Especially, for non-stationary satellite, it is commonly found in the earth resource observation application. Removing cloud cover from satellite imagery is very useful for assisting image interpretation. Hence cloud detection and removal is very vital in processing of satellite imagery. For detection and removal of cloud relative radiometric normalization using no change set (NC) technique is proposed here in spatial domain as well as in frequency domain. The cloudy image is radiometrically normalized by using reference image of same area, acquired at different date. The visual appearance results, statistical results and histogram results are discussed.

Keywords:  Normalization, No Change Set, Radiometric, Relative. 

References:
1.     Yang, X.J., and C.P. Lo. "Relative Radiometric Normalization Performance for Change Detection From Multi-Date Satellite Images." Photogrammetric Engineering and Remote Sensing, Vol. 66, No. 8, pp. 967-980, 2000.
2.     www.ncl.ak.uk/tcmweb/bilko/module7/lesson3.pdf.
3.     M. Caprioli, B. Figorito, E. Tarantino, "Radiometric Calibration Methods For Change Detection Analysis Of Satellite Data Aimed At Environmental Risk Monitoring". DVT- Polytechnic University of Bari -Italy E-mail: m.caprioli@poliba.it;benedetto1980@libero.it; e.tarantino@poliba.it. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B8. Beijing 2008
4.     Todd A. Schroeder a, Warren B. Cohen b, Conghe Song c, Morton J. Canty d, Zhiqiang Yang , "Radiometric Correction of Multi-Temporal Landsat Data for Characterization of Early Successional Forest Patterns in Western Oregon" Department of Forest Science, Oregon State University, Corvallis, OR 97331, United States Forestry Sciences Laboratory, Pacific Northwest Research Station, USDA Forest Service, 3200 SW Jefferson Way, Corvallis, OR 97331, United States c Department of Geography, University of North Carolina, Chapel Hill, NC, 27599, United States Systems Analysis and Technology Evaluation, Jülich Research Center, D-52425 Jülich, Germany Received 2 November 2005; received in revised form 10 March 2006; accepted 11March 2006
5.     Xuexia Chen, Lee Vierling, Don Deering ,"A Simple and E_ective Radiometric Correction Method to Improve Landscape Change Detection Across Sensors and Across Time" , Remote Sensing of Environment ,May 2005
6.     Munmun Baisantr , Dr.D.S.Negi, O.P.Manocha, "Automatic Relative Radiometric Normalization for Change Detection of Satellite Imagery", ACEEE Int. J. on Information Technology, Vol. 02, No. 02, April 2012.
7.     R.N. Sahoo, R.K.Tomar, "Radiometric Scene Correction of Temporal Multi-Spectral Satellite for Crop Discrimination." Indian Journal of radio and Space Physics Vol. 35, April 2006,pp. 116-121
8.     Seema Biday, Udhav Bhosle _Relative Radiometric Correction of Cloudy Multitemporal Satellite Imagery_ International Journal of Civil and Environmental Engineering 2:3 2010
9.     Seema Gore Biday and Udhav Bhosle "Radiometric Correction of Multitemporal Satellite Imagery", Journal of Computer Science 6 (9): 1027-1036, 2010 ISSN 1549-3636
10.  Gang Hong, Yun Zhang, "Radiometric Normalization Of Ikonos Image sing Quick bird Image For Urban Area Change Detection", Department of Geodesy and Geometrics Engineering, University of New Brunswick, 2002
11.  John Rogana, DongMei Chen "Remote Sensing Technology for Mapping and Monitoring Land-Cover and Land-Use Change."  61 (2004) PP. 301_325,43
12.  J Yuan, D. and Elvidge, C.D., 1996, "Comparison of Relative Radiometric Normalization Techniques", ISPRS Journal of Photogrammetry and Remote Sensing, vol. 51, pp. 117-126.
13.  Dr. Mohamed Mansoor Roomi, R.Bhargavi, T.M.Hajira Rahima Banu "Automatic Deintification Of Cloud Cove Regions Using Surf ", International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.2, April 2012
14.  Ruhul Amin, Richard Gould, Weilin Houa, Zhongping Leeb and Robert Arnone "Automated Detection and Removal of Cloud Shadows on HICO Images" ,Ocean Sensing and Monitoring III, edited by Weilin W. Hou, Robert Arnone, Proc. of SPIE Vol. 8030,803004, 2011
15.  Salem Saleh Al-Amri, N. V. Kalyankar and Khamitkar S.D. "Image Segmentation By Using Threshold Techniques", Jornal of computing, Vol.2, issue 5, May 2010, ISSN 2151-9617
16.  Tracey A. Dorian, " Tracey A. Dorian National Weather Center Research Experiences for Undergraduates Program & Pennsylvania State University" MICHAEL W. DOUGLASNOAA's Office of Oceanic and Atmospheric Research & National Severe Storms Laboratory Corresponding author address, 1409 Allan Lane West Chester , PA 19380, tad240@psu.edu
17.  El Mamoun Haroun. Osman, "Demonstrating an Efficient Algorithm for Cloud Detecting and Removal for Satellite", College of Natural Resources and Environmental Studies, Department of Forestry, University of Bahri. Khartoum- Sudan, December 27, 2012
18.  Tracey A. Dorian, Michael W. Douglas, "Choosing the Most Accurate Thresholds in a Cloud Detection Algorithm for Modis Imagery", National Weather Center Research Experiences for Undergraduates Program & Pennsylvania State University, NOAA's Office of Oceanic and Atmospheric Research & National Severe Storms Laboratory
19.  Gary Jedlovec, "Automated Detection of Clouds in Satellite Imagery", NASA Marshall Space Flight Center USA.
20.  E. Zaunick K. Janschek J. Levenhagen, "GEO Satellite Image Navigation with Cloud Detection using Multispectral Payload Image Data", Institute of Automation, Technische Universitat Dresden, Dresden, Germany Tel.: +49 351 463 31913, Fax: +49 351 463 37039, e-mail: edgar.zaunick@tu-dresden.de. Institute of Automation, Technische Universitat Dresden, Dresden, Germany e-mail: klaus.janschek@tu-dresden.de. EADS Astrium GmbH, Friedrichshafen, Germany email: jens.levenhagen@astrium.eads.net.
21.  E.H. Helmer and B. Ruefenacht, "Cloud-Free Satellite Image Mosaics with RegressionTrees and Histogram Matching", Photogrammetric Engineering & Remote Sensing, Vol. 71, No. 9, September 2005, pp. 1079_1089. 0099-1112/05/7109_1079/$3.00/0© 2005 American Society for Photogrammetry and Remote Sensing.

32-36

9.

Authors:

M. Balasubba Reddy, Y.P. Obulesh, S.Sivanaga Raju, Venkata Suresh

Paper Title:

Optimal Power Flow in the Presence of Generalized Interline Power Flow Controller

Abstract:  In this paper a novel non-linear optimization problem is formulated to minimize the generation fuel cost and transmission power losses in the presence of generalized interline power flow controller (GIPFC). This paper presents a methodology to optimally allocate the device in a give power system by minimizing the system severity system buses and total transmission line power flows in order to maximize the system security. The formulated objectives are optimized individually while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on cuckoo search algorithm and genetic algorithm cross over operations is proposed to test the effectiveness on IEEE-14 bus system, and the detailed analysis is carried out.

Keywords:  Optimal power flow, Generalized interline power flow controller, Power injection model, Practical constraints, HCSA.

References:
1.        R.Leon Vasquez-Arnez, Luiz Cera Zanetta Jr., “A Novel Approach for modeling the steady-state VSC-Based Multiline FACTS Controllers and their operational constraints”, IEEE Trans. on Pwr. Del., 2008, Vol.23, No.1, pp. 457-464.
2.        R.Leon Vasquez-Arnez, Luiz Cera Zanetta Jr., “Unified Power Flow Controller (UPFC): its versatility in handling power flow and interaction with the network”, in Proc. IEEE/PES Transmission & Distribution Conference, 2002, Asia Pacific, Yokohama, Japan, 2002, Vol.2, pp.1338-1343.
3.        R.Leon Vasquez-Arnez, Luiz Cera Zanetta Jr., “Multi-Line Power Flow Control: An Evaluation of the GIPFC (Generalized Interline Power Flow Controller)”, International Conference on Power Systems Transients (IPST’05) in Montreal, Canada, June 19-23, 2005. 
4.        C. R. Fuerte-Esquivel and E. Acha, “Unified power flow controller: a critical comparison of Newton-Raphson UPFC algorithms in power flow studies,” IEE Proc.-Gener. Transm. Distrib., Vol.144, No. 5, Sept. 1997, PP. 437–444.[10]
5.        M. Noroozian, L. Angquist, M. Ghandhari, and G. Andersson, “Use of UPFC for optimal power flow control,” IEEE Trans. Power Del., Vol.12, No. 4, Oct. 1997, PP. 1629–1634.
6.        L. Gyugyi, K. K. Sen, and C. D. Schauder, “The interline power flow controller concept a new approach to power flow management in transmission systems,” IEEE Trans. Power Del., Vol. 14, No. 3, Jul. 1999,PP.1115–1123
7.        X.P.Zhang, "Advanced modeling of the multicontrol functional static synchronous series compensator (SSSC) in Newton power flow," IEEE Trans. Power Syst., Vol.18, No.4, Nov.2003, PP.1410–1416.
8.        X. P. Zhang, “Modeling of the interline power flow controller and the generalized unified power flow controller in Newton power flow,” IEE Proc.-Gener. Transm. Distrib., Vol. 150, No. 3, May 2003, PP. 268–274.
9.        S. Teerathana, A. Yokoyama, Y. Nakachi, and M. Yasumatsu, "An optimal power flow control method of power system by interline power flow controller (IPFC)," Proc. of 7th Int. Power Engg. Conf, Singapore, 2005, PP. 1-6.
10.     Jun Zhang and Akihiko Yokoyama, "Optimal power flow control for congestion management by interline power flow controller (IPFC)," IEEE Int. Conf. on Power System Technology, Chongqing, China, Oct.2006.
11.     Vinkovic A and Mihalic R, “A current-based model of SSSC for Newton–Raphson power flow,” Electric Power Syst. Res., Vol.78, 2008, PP.  1806 –1813.
12.     Vinkovic A and Mihalic R, “A current-based model of an IPFC for Newton–Raphson power flow,” Electric Power Syst. Res., Vol. 79, 2009,PP.  1247–1254. 
13.     Ramin Rajabioun, “Cuckoo Optimization Algorithm,” Applied soft computing, Vol.11, 2011, PP. 550821-5518
14.     Xin-She Yang, Suash Deb., “Cuckoo Search via Levy Flights”, in: Proc. of World Congree on Nature & Biologically Inspired Computing (NaBIC 2009), India, IEEE Publications, USA, pp.210-214.

37-42

10.

Authors:

Prachi Agrawal

Paper Title:

Radio Frequency based Automatic Meter Reading System

Abstract:  This paper specifies a practical model of Pulse Detection and Electric Metering System based on the Radio Frequency (RF). The supporting device transmitter works on 98.5 MHz operating frequency and 200.5 MHz carrier frequency and receiver works on same.. This project works within the range of 50 meters. This Radio Frequency (RF) based Pulse Detection and Electric Metering System is used for clear and accurate billing based on actual consumption rather than on an estimate based on previous consumption.

Keywords:   Automatic Meter Reading, Digital Power Meter, Radio Frequency, Short Messaging System..

References:
1.        H. G. Rodney Tan, C.H. Lee, “Automatic Power  Meter Reading System using GSM network”, 978-981-05-9423-7 c_2007 GPRS.
2.        Irfan Quazi, Sachin Kumar Gupta and Rajendra   Prasad, “Pre Paid Energy Meter based on AVR Microcontroller”, IJERA, Vol-1, pp.   1879 1884.                                            
3.        Shoeb S.Sheikh “Design and Implementation of “Wireless AutomaticMeter Reading System” IJEST, Vol-3 pp. 2329-2334.
4.        Rob van Gerwen, Saskia Jaarsma and Rob Wilhite, KEMA, “Smart   Metering” July 2006.
5.        T.H.Lee, “Design of CMOS Radio Frequency Integrated Circuits”, second edition, CUP, 2004.
6.        Li Yujin, “Remote Automatic Meter Reading System based on GPRS   Technology” IEEE 2010.
7.        Litting Cao, Wei Jiang, Zhaoli Zhang, “Automatic Meter Reading    System based on wireless Mesh Networks and SOPC Technology” IEEE Nov. 3, 2009.
8.        Liting Cao, Jingwen Tian and Dahang Zhang, “Networked Remote Meter-Reading System Based on Wireless CommunicationTechnology” in International Conference on Information
9.        Acquisition, 2006 IEEE.
10.     Richa Shrivastava and Nipun Kumar Mishra, "An Embedded System for Wireless Prepaid Billing of Digital Energy eter,"          International Journal of Advances in Electronics Engineering, pp. 322-324.
11.     Amit Jain, Mohnish Bagree “A prepaid meter using mobile communication” International Journal of Engineering, Science  and Technology, Vol. 3, No. 3, 2011, pp. 160-166. 
12.     Md. Mejbaul Haque1, Md. Kamal Hossain, Md. Mortuza Ali, Md. Rafiqul Islam Sheikh “Microcontroller Based Single Phase Digital Prepaid Energy Meter for Improved Metering and Billing System” International Journal of Power Electronics and Drive System (IJPEDS) Vol.1, No.2, December 2011, pp. 139~147 ISSN: 2088-8694.
13.     http://www.seminarprojects.com/Thread-     automatic-meter- reading-amr#ixzzle7T3VMcj.International Standards for all electrical, electronic and related  technologies available at- http://www.iec.ch.

43-45

11.

Authors:

Vithya KP, Premkumar R

Paper Title:

Secured ECG Distribution using Compression and RSA Algorithm for Telemedicine Application

Abstract:   The detailed condition of a cardiac patient can be better understood from his ECG. For treatment of the patient over the internet both the security and the bandwidth issues plays a very vital role. A new approach which combines RSA for transmission and SPHIT (Set Partioning in Hierarchical Trees) for image compression which enables uploading of important coefficients of ECG signal. This technique not only provides security but also provides doctor to patient interaction. The simulation results indicate that the proposed method enhances the security for data transmission over the internet with a compression ratio of 2.5. The idea for choosing the SPHIT is it is lossless algorithm and much of importance is to be given to the patient details to provide perfect treatment by all means.

Keywords:  Image compression, Image encryption, discrete wavelet transform, RSA Encryption, SPHIT, ECG 

References:
1.        Biel L, Peterson O, Philips on LWide P. Ecg analysis: a new approach in human identification. IEEE Transaction on Instrumentation and measurement at 2001.
2.        W. Lee and C. Lee, “A cryptographic key management solution for hipaa privacy/security regulations,” IEEE Transactions on InformationTechnology in Biomedicine,, vol. 12, no. 1, pp. 34–41, 2008.
3.        Shashikala Channalli et al, “Steganography An Art of Hiding Data”, International Journal on Computer Science and Engineering Vol.1(3), 2009, 137-141 137. 
4.        Chunlin Song, Sud Sudirman, Madjid Merabti, “Recent Advances and Classification of WatermarkingTechniques in Digital Images”International Conference, Oct. 2009.
5.        Ayman Ibaida, Ibrahim Khalil “Wavelet Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Sys-tems” IEEE Transactions On Biomedical Engineering. 
6.        Ibaida, A. ; Sch. of Comput. Sci. & IT, RMIT Univ., Melbourne, VIC, Australia ; Khalil, I. Al-Shammary, D. , “Embedding patients confidential data in ECG signal for healthcare information systems”, Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. 
7.        M. Engin, Y. Yamaner, E. Z. Engin, “A biotelemetric system for human ECG measurements”, Elsevier Measurement, Article in Press, accepted 7 April, 2005. 
8.        Chiaraluce F, Ciccarelli L, et al. A new RSA algorithm for video encryption. IEEE Trans Consum Electron 2002; 48:838–43. 
9.        Sufi F, Khalil I. A new feature detection mechanism and its application in secured ecg transmission with noise Masking. Journal of Medical Systems 2009; 33(3):121–132. 
10.     S. Jayaraman, S. Esakkirajan, and T. Veerakumar. Digital Image Processing. McGraw-Hill, 2009. 
11.     K. Zheng and X. Qian, “Reversible Data Hiding for Electrocardiogram Signal Based on Wavelet Transforms,” in International Conference on Computational Intelligence and Security, 2008. CIS’08, vol. 1, 2008. 
12.     A. Al-Fahoum, “Quality assessment of ECG compression techniques using a wavelet-based diagnostic measure,” IEEE Transactions on Information Technology in Biomedicine, vol. 10, no. 1, 2006.

46-48

12.

Authors:

Manoj Sharadrao Awakhare

Paper Title:

A CMOS Class-E Cascode Power Amplifier for GSM Application

Abstract:    The design of A 2.4-GHz CMOS Class E cascode power amplifier (PA) for GSM applications in TSMC 0.18-μm CMOS technology present in this paper. Proposed Class E cascode PA topology is a single-stage topology in order to minimize the device stress problem. A parallel capacitor is connected across the transistors for efficiency enrichment also for dominating the effect of parasitic capacitances at the drain node. The simulation results point to that the PA delivers 12 dBm output power with 43.6% and 46.6% of power added efficiency (PAE) and drain efficiency (DE) respectively with 2.5-Volt power supply into a 50-Ω load.

Keywords:   Class E, CMOS power amplifier, power added efficiency, switching amplifier

References:
1.           N. O. Sokal and A. D. Sokal, “Class E—A new class of high-efficiency tuned single-ended switching power amplifiers,” IEEE J. Solid-State Circuits, vol. SC-10, no. 6, pp. 168–176, Jun. 1975.
2.           F. H. Raab, “Idealized operation of the class E tuned power amplifier”, IEEE Trans. Circuits Syst., vol. CAS-24, no. 12, pp. 725–735, Dec.1977.
3.           N.  Kumar, C. Prakash, A. Grebennikov, and A. Mediano, “High-efficiency broadband parallel-circuit class E RF power amplifier with reactance-compensation technique,” IEEE Trans. Microw. Theory Tech. .,vol. 56, no. 3, pp. 604–612, Mar. 2008.
4.           M. Kazimierczuk and K. Puczko, “Exact analysis of class E tuned power amplifier at any and switch duty cycle,” IEEE Trans. Circuits Syst., vol. CAS-34, no. 2, pp. 149–158, Feb. 1987.
5.           V. Grebennikov, “Class E high-efficiency power amplifiers: Historical aspect and future prospect,” Appl. Microw. Wireless, vol.14, no. 72, pp. 64–71,  Jul.–Aug. 2002.
6.           C.-H. Li and Y.-O. Yam, “Maximum frequency and optimum performance of class E power amplifiers,” Proc. Inst. Elect. Eng.—Circuits Devices Syst., vol. 141, pp. 174–184, Jun. 1994.
7.           J. Wilkinson and K. A. Everard, “Transmission line load network topology for class E power amplifiers,” IEEE Trans. Microw. Theory Tech., vol. 49, no. 6, pp. 1202–1210, Jun. 2001.
8.           T.Tuetsugu and M. L. Kazimierczuk, “Analysis and design of class E amplifier with shunt capacitance composed of nonlinear and linear capacitances,”IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 51, no. 7, pp. 1261–1268, Jul. 2004.
9.           P.Alinikula, K. Choi, and I. Long, “Design of class E power amplifier with nonlinear parasitic output capacitance,” IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process., vol. 46, no. 2, pp. 114–119, Feb.1999.
10.        Mediano, P. Molina-Gaudó, and C. Bernal, “Design of class E amplifier with nonlinear and linear shunt capacitances for any duty cycle,”IEEE Trans. Microw. Theory Tech., vol. 55, no. 3, pp. 484–492, Mar. 2007.
11.        J. Jeon, J. Kim, and Y. Kwon, “Temperature compensating bias circuit for GaAs HBT RF power amplifiers with a stage bypassarchitecture,”Electron. Lett., vol. 44, no. 19, pp. 1141–1143, Sep. 2008.
12.        S. Gao, H. Xu, S. Heikman, U. K. Mishra, and R. A. York, “Two-stage quasi-class-E power amplifier in GaN HEMT technology,” IEEE Microw. Wireless Compon. Lett., vol. 16, no. 1, pp. 28–30, Jan. 2006.13.        P.Watson et al., “An indium phosphide_-band class-E power MMIC with 40% bandwidth,” in IEEE Compound Semiconduct. Integr. Crcuits. Symp., Palm Springs, CA, Nov. 2005, pp. 220–223.
14.        K.-C. Tsai and P. R. Gray, “A 1.9-GHz, 1-W CMOS class-E power amplifier for wireless communications,” IEEE J. Solid-State Circuit, vol. 34, no. 7, pp. 962–970, Jul.
1999.
15.        C. Yoo and Q. Huang, “A common-gate switched 0.9-W class-E power amplifier with 41% PAE in 0.25-_m CMOS,” IEEE J. Solid-State Circuits, vol. 36, no. 5, pp. 823–830, May 2001.
16.        J.Jang, C. Park, H. Kim, and S. Hong, “A CMOS RF power amplifier using an off-chip transmission line transformer with 62% PAE,”IEEE Microw. Wireless Compon. Lett., vol. 17, no. 5, pp. 385–387,May 2007.
17.        R. Brama, L. Larcher, A. Mazzanti, and F. Svelto, “A 30.5 dBm 48% PAE CMOS class-E PA with integrated balun for RF applications,”IEEE J. Solid-State Circuits., vol. 43, no. 8, pp. 1755–1762, Aug. 2008.
18.        K. L. R. Mertens and M. S. J. Steyaert, “A 700-MHz, 1-W fully differential CMOS class-E power amplifier,” IEEE J. Solid-State Circuits,vol. 37, no. 1, pp. 137–141, Jan.
2006.
19.        R.  Negra and W. Bächtold, “Lumped-element load-network design for class-E power amplifiers,” IEEE Trans. Microw. Theory Tech., vol. 54,no. 6, pp. 2684–2690, Jun. 2006.
20.        M. Apostolidou et al., “A 65 nm CMOS 30 dBm class-E RF power amplifier with 60% power added efficiency,” in IEEE Radio Freq. Integr.Circuits Symp. Dig., Jun. 2008, pp. 141–144.
21.        Mazzanti, L. Larcher, R. Brama, and F. Svelto, “Analysis of reliability and power efficiency in cascode class-E PAs,” IEEE J. Solid-StateCircuits., vol. 41, no. 5, pp. 1222–1229, May 2006.
22.        C.-C. Ho, C.-W. Kuo, C.-C. Hsiao, and Y.-J. Chan,“A fully integrated class-E CMOS amplifier with a class-F driver stage,” in IEEE RadioFreq. Integr. Circuits Symp. Dig., Jun. 2003, pp. 211–214.
23.        E. Cipriani, P. Colantonio, F. Giannini, and R. Giofrè, “Optimization of class-E power amplifier design above theoretical maximum frequency,”in Proc. 38th Eur. Microw. Conf., Oct. 2008, pp. 1541–1544.
24.        Grebennikov and N. O. Sokal, Switchmode RF Power Amplifiers. Burlington, MA: Newnes, 2007, pp. 186–190.
25.        F. H. Raab, “Effects of circuit variations on the class E tuned power amplifier,” IEEE J. Solid-State Circuits, vol. SSC-13, no. 4, pp. 239–247,Apr. 1978.
26.        N. O. Sokal, “Class E high efficiency switching-mode power amplifiers, from HF to microwave,” in IEEE MTT-S Int. Microw. Symp. Dig.,Jun. 1998, pp. 1109–1112.
27.        N. O. Sokal, “Class-E power amplifiers,” QEX/Commun. Quart., pp.9–20, Jan./Feb. 2001.
28.        M. Kazimierczuk, “Collector amplitude modulation of the class E tuned power amplifier,” IEEE Trans. Circuits Syst., vol. CAS-31, no.6, pp. 543–549, Jun. 1984.
29.        F. H. Raab and N. O. Sokal, “Transistor power losses in the class E tuned power amplifier,” IEEE J. Solid-State Circuits, vol. SSC-13, no.6, pp. 912–914, Dec. 1978.
30.        International Technology Roadmap for Semiconductors, System Drivers, 2005.
31.        Andrea Mazzanti, Associate Member, IEEE, Luca Larcher, Member, IEEE, Riccardo Brama, Student Member, IEEE, and Francesco Svelto, Member, IEEE,  “Analysis of
Reliability and Power Efficiency in Cascode Class-E PAs”, IEEE JOURNAL OF SOLID STATE CIRCUITS, VOL. 41, NO. 5, MAY 2006.
32.        “Optimised class –E rf power amplifier design in bulk cmos”, thesis by tao wang, university of Texas.

49-53

13.

Authors:

Gayathri M, A. Sudha

Paper Title:

Software Defect Prediction System using Multilayer Perceptron Neural Network with Data Mining

Abstract:  Fault prediction in software systems is crucial for any software organization to produce quality and reliable software.  Faults (defects) or fault-proneness of software modules are to be predicted in the early stages of software life cycle, so that more testing efforts can be put on faulty modules.  Various metrics in software like Cyclomatic complexity, Lines of Code have been calculated and effectively used for predicting faults.  Techniques like statistical methods, data mining, machine learning, and mixed algorithms, which were based on software metrics associated with the software, have also been used to predict software defects.  Many works have been carried out in the prediction of faults and fault-proneness of software systems using varied techniques.  In this paper, an enhanced Multilayer Perceptron Neural Network based machine learning technique is explored and a comparative analysis is performed for the modeling of fault-proneness prediction in software systems.  The data set of software metrics used for this research is acquired from NASA’s Metrics Data Program (MDP).

Keywords:    Faults, Fault-proneness, Software Metrics, Software Defect Prediction, Multilayer Perceptron Neural Network.

References:
1.       Sunghun Kim, Hongyu Zhang, Rongxin Wu and Liang Gong, ‘Dealing with Noise in Defect Prediction’, CSE’11, Waikiki, Honolulu, HI, USA, ACM 978-1-4503-0445-0/11/05, 2011.
2.       Rachna Ratra, Navneet Singh Randhawa, Parneet Kaur, and Dr. Gurdev Singh, 'Early Prediction of       Fault Prone Modules using Clustering Based vs. Neural Network Approach in Software Systems', IJECT Vol. 2, Issue 4, Oct. - Dec. 2011
3.       Naheed Azeem and Shazia Usmani, 'Analysis of Data Mining    Based Software Defect PredictioTechniques', Global Journal of Computer Science and Technology Volume 11 Issue 16 Version 1.0 September 2011
4.       Qinbao Song, Zihan Jia, Martin Shepperd, Shi Ying, and Jin Liu, 'A General Software Defect-Proneness Prediction Framework', IEEE Transactions on Software Engineering, Vol. 37, No. 3, May/June 2011
5.       Yi (Cathy) Liu, Member, IEEE Computer Soceity, Taghi M. Khoshgoftaar, Member, IEEE, and Naeem Seliya, Member, IEEE, 'Evolutionary Optimization of Software Quality Modeling with Multiple Repositories', IEEE Transactions On Software Engineering, Vol. 36, No. 6, November/December 2010, pp 852-864
6.       Ebru Ardil, Erdem Ucar, and Parvinder S. Sandhu, ‘Software Maintenance Severity Prediction with Soft Computing Approach’, Proceedings of World Academy of Science, Engineering and Technology (2009), 38, pp. 139-143.
7.       Stefan Lessmann, Bart Baesens, Christophe Mues, and Swantje Pietsch, 'Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings', IEEE Transactions On Software Engineering, Vol. 34, No. 4, July/August 2008 pg : 485
8.       Cagatay Catal and Banu Diri, ‘Software Defect Predicition Using Artificial Immune Recognition System’, Proceedings of the 25th IASTED International Multi – Conference Software  Engineering (2007), Innsbruck, Austria, ISBN Hardcopy:978-0-88986-641- 61/CD:978-0-88986-643-0.
9.       Venkata U.B. Challagulla, Farokh B. Bastani, I-Ling Yen, and Raymond A. Paul, 'Empirical Assessment of Machine Learning based Software Defect Prediction Techniques', Proceedings of the 10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems (2005).
10.    Fenton N.E. and Neil M., 'A critique of software defect prediction models', IEEE Transactions on Software Engineering, Volume: 25 Issue: 5, Sept. - Oct. 1999, Page(s): 675 -689.
11.    Hongjun Lu, Member, IEEE Computer Society, Rudy Setiono and Huan Liu, Member, IEEE, 'Effective Data Mining Using Neural Networks', IEEE Transactions on Knowledge and Data Engineering, Vol. 8, No. 6, December 1996

54-59

14.

Authors:

Sharad D. Pawar, Abhay Utpat

Paper Title:

Analysis of Composite Laminate for Maximum Stiffness

Abstract:   The purpose of this study is to develop optimization procedure to maximize the stiffness and minimize the weight of composite laminate subjected to in-plane loading .The design variables for optimization problem are fiber orientation angles, thickness of lamina and number of laminas. Maximum stress failure criteria are used to determine whether load bearing capacity is exceeded for a configuration generated during optimization process. In a recent year, the application of Fiber reinforced composite material has increased with increasing need of low weight, high strength, high stiffness etc. in aerospace industry, automobile industry, sporting equipment, civil industry etc. In the case of Fiber Reinforcement Plastic composite structural design, the requirements of certain application can be achieved not only by sizing the cross sectional areas and thickness of components but by changing the material system design i.e. optimizing the material system itself such as fiber orientation angle, ply thickness, stacking sequence etc. The optimization techniques are being used to assist the designer in finding an optimized solution. Carefully designed individual composite parts at present, are about 20-30% lighter than their conventional metal parts.

Keywords:   Composite Material, FEA,Stiffness

References:
1.        Mustafa Akbulut, Fazil O. Sonmez, “Optimum Design of Composite Laminate  for Minimum Thickness”, Composite and Structures 2008;pp 1974-1982.
2.        G. NarayanaNaik, S. Gopalakrishnan , RanjanGanguli, “Design Optimization of Composites using Genetic Algorithms and Failure Mechanism Based Failure Criterion”, Composite Structures  2008 ; pp. 354–367.
3.        Jacob L. Pelletier, Senthil S. Vel, “Multi-objective Optimization of Fiber Reinforced Composite Laminate for Strength, Stiffness and Minimal Mass”, Composite and Structures 2006,pp 2065-2080.
4.        M. Walker, R.E. Smith, “A Technique for Multi-objective Optimization of Laminated Composite Structure using Genetic Algorithm and Finite Element Analysis”, Composite and Structures 2003, pp. 123-128.
5.        Rafael F. Silva, Iuri B. C. M. Rocha, EvandroParente Jr., Antonio M. C. MeloandAurea S. Holanda, “Optimization of Laminated Tubes using Finite Element Analysis’,Mechanica Computational Vol- XXIX, pages. 1761-1781.
6.        Chung Hae Park ,Abdelghani Saouab ,Joël Bréard ,Woo Suck Han, “An Integrated Optimisation for the Weight, the Structural Performance and the Cost of Composite Structures”, Composite Science Technology, 2009, pp 1101-1107.
7.        Sukrukarakaya,  Omer Soykasap, “Structural Optimization of Laminated Composite Plates for Maximum Buckling Load Capacity Using Genetic Algorithm”, Key Engineering Materials 2007, pp. 725-728.
8.        T. Rangaswamy, S.Vijayarangan, “Optimal Design and Analysis of Automotive CompositeDrive Shaft”, International Symposium of Research Students on Materials Science and Engineering, 2004.
9.        Avinash Ramsaroop and Krishnan Kanny, “Using MATLAB to Design and Analyse Composite Laminates”, Scientific Research Engineering, 2010, pp- 904-9.
10.     “Mechanics of Composite Materials”, Robert M. Jones, Taylor & Francis, Boca Raton, Fla, USA, 2nd edition, 1999.
11.     Rasoul Khandan, Siamak Noroozi, Philip Sewell, John Vinney, and Mehran Koohgilani, “Optimum Design of Fiber Orientation in Composite Laminate Plates for Out
Plane Stresses”, Advances in Materials Science and Engineering, 2012.

60-66

15.

Authors:

Brij Kishor Kushwaha, N. G. Gore, P.J. Salunke

Paper Title:

Optimization of PSC Slab Bridges

Abstract:  The objective of this study is to investigate the appropriate optimization method to find minimum weight and the minimum cost of a Railway PSC slabs. In view of achieving this objective it is decided to develop a computer code in MATLAB7. After validating this computer code by comparing the results with analytical results, it is planned to carry out the economical and safe design of PSC slab. For the minimum weight and cost design of the PSC slab unit the following design variables are chosen: 1-Depth of PSC slab unit at center, 2-Depth of PSC slab unit at end, 3-Eccentricity of prestressing cable at center, & 4-Total prestressing force.

Keywords:   Prestressed concrete slab, Railway bridges, Structural optimization, prestressing force, cost and weight optimisation.

References:
1.          M. Z. Colin, F. ASCE and A. J. MacRae, “Optimization of structural concrete beams,” Journal of Structural Engg, (1984),110, pp.1573-1588.
2.          Y.B. Miao & L.M.C. Simoes, “Multicriteria Optimum Design of prestressed Concrete Bridge Girders,” FUNDACAO ORIENTE Portugal,(1995), pp.8.
3.          Samuel HaileMichael WeldeHawariat, “Optimal Design for Prestressed Concrete Box Girder Bridge,” Thesis to MSc. In Structural Engineering, University of Addis Ababa Ethiopia, (2002), PP.135
4.          Samer Barakat , Ali Salem Al Harthy, Aouf R. Thamer, “Design of Prestressed Concrete Girder Bridges Using Optimization Techniques,” Information Technology Journal, (2002) Vol I, PP:193-201
5.          J. M. Sadeghi & A. Babaee, “Structural Optimization of B70 Railway Prestressed Concrete Sleepers,” Iranian Journal of Science & Technology, (2006) Vol. 30, No. B4, pp.461-473.
6.          Byeong Moo Jin, In Gyu Kim, Young Jin Kim, In Ho Yeo, Won Seok Chung, Jae Suk Moon, “Proposal of Maglev Guideway Girder by Structural Optimization,” Proceeding of International Conference on Electrical Machines and Systems, Seoul, Korea (2007), pp.1959-1962
7.          Myung-Seok Bang, Sung-Ho Han, “Optimal Design of PSC beam reinforcement for minimum life-cycle cost,” Journal of the KOSOS, (2008) Vol.23 no.5,PP.125-131
8.          Mostafa A. Hassanain and Robert E. Loov, “Cost optimization of concrete bridge infrastructure,” Canada Journal of Civil Eng. (2003) 30, pp. 841–849.
9.          S. Rana, R.Ahsan & S.N.Ghani, “Design of prestressed concrete I-girder bridge superstructure using optimization algorithm,” IABSE-JSCE conference Bangladesh, (2010), pp.211-223.
10.       Mamoun Alqedra, Mohammed Arafa and Mohammed Ismail, “Optimum Cost of Prestressed and Reinforced Concrete Beams using Genetic Algorithms,” Journal of Artificial Intelligence, (2011) 4, pp.76-88.11.       Raquib Ahsan; Shohel Rana; and Sayeed Nurul Ghani, “Cost Optimum Design of Post tensioned I-Girder Bridge using Global Optimization Algorithm,” Journal of Structural Engineering, (2012),138, pp,273-284.
12.       Byungik Chang, Kamal Mirtalaei, Seungyeol Lee, and Kenneth Leitch, “Optimization of Post-Tensioned Box Girder Bridges with Special Reference to Use of High-Strength Concrete Using AASHTO LRFD Method,” Advances in Civil Engineering, (2012), pp.8
13.       IS : 1343 – 1980: Indian Standard Code of Practice for Prestress Concrete
14.       BS 5400Part 4: Code of practice for design of concrete bridges
15.       Indian Railway Standard: Code of practice for Plain, Reinforced and Prestressed concrete for General Brige construction (Concrete Bridge code)
16.       IRC-18-2000:   Prestressed Concrete (Post -tensioned concrete).
17.       Research Design & Standards Organization, Indian Railways: Standard Drawings.
18.       S.S. Rao: Engineering Optimization Theory And Practice” New age international publication.

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16.

Authors:

P.Sukumar, K.S.Gayathri

Paper Title:

Semantic based Sentence Ordering Approach for Multi-Document Summarization

Abstract:   With the rapid growth of online information which is unstructured in nature poses a great challenge to the text mining algorithms to retrieve useful and meaningful information in an efficient way. However larger amount of data are readily available, it is very difficult to access the required information at the right time and also in the most appropriate form. Therefore a systematic approach called multi-document summarization is required to generate a summary about particular topic. The main focus of document summarization is sentence ordering and ranking. The existing system for sentence ordering deals with the measures such as chronology, topical, precedence and succedence experts. The main drawback of existing system is, it does not address the semantic relationship between the sentences in the summary which is necessary to create a meaningful summary. The proposed system addresses the semantic relationship between sentences in the summary using wordnet synsets. This system builds an entailment model whichinfer the logical relationship among the sentences when arranging the sentences in the summary. Graph method is used for ranking the sentences, where nodes represents the sentences and the edges represents the preference value of one sentence over another sentence. The proposed system provides an efficient summary which is considerably increases the meaningfulness of the final summary and also typically recovering the user from the information overload problem by giving quick and efficient access to required information.

Keywords: Multi-document summarization, sentence ordering, sentence ranking, semantic expert, text entailment expert.

References:
1.        similarity measures’, 10th International Conference on Data Warehousing and Knowledge Discovery 2008.
2.        Kogilavani, P. Balasubramanie. (2011), ‘Semantic summary generation from multiple documents using feature specific sentence ranking strategy’, Elixir Comp. Sci. Engg. Volume 40, pp. 5372-5375.
3.        Kogilavani, P. Balasubramanie. (2012), ‘Update Summary Generation based on Semantically Adapted Vector Space Model’, International Journal of Computer Applications (0975 – 8887), Vol 42, No.16.
4.        Bollegala D., Okazaki N. and Ishizuka M. (2010), ‘A bottom-up approach to sentence ordering for multi-document summarization’, Information Processing and Management, Vol.46, No.1, pp. 89–109.
5.        Bollegala D., Okazaki N. and Ishizuka M. (2012), ‘A preference learning approach to sentence ordering for multi-document summarization’, Information Science, pp. 78-95.
6.        Cai X. and Li W. (2013), ‘Ranking Through Clustering: An Integrated Approach to Multi-Document Summarization’, Vol.21, No.7, pp. 1424-1433.
7.        Castillo J J. (2010), 'An approach to Recognizing Textual Entailment and TE Search Task using SVM', Natural Language Processing, Vol. 44, pp. 139-145.
8.        D.O. Seaghdha, A. Korhonen. (2011), ‘Probabilistic models of similarity in syntactic context’, in: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP-11), Edinburgh, UK.
9.        F. Xia, T.-Y. Liu, J. Wang, W. Zhang, H. Li. (2008), ‘Listwise approach to learning to rank: theory and algorithm’, in: ICML 2008.
10.     Hobbs J. R. (1985). ‘Ontological promiscuity’, Proceedings of the 23rd annual meeting on Association for Computational Linguistics.
11.     J.J. Castillo. (2011), ‘A wordnet-based semantic approach to textual entailment and cross-lingual textual entailment’, International Journal of Machine Learning and Cybernetics 2, pp. 177–189.
12.     Liu Y. and Liang Y. (2013), 'A sentence semantic similarity calculating method based on segmented semantic comparison', Journal of Theoretical and Applied Information Technology, Vol. 48, No. 1, pp. 231-235.
13.     Miguel Angel Rios Gaona, Alexander Gelbukh, and Sivaji Bandyopadhyay (2011), ‘Recognizing Textual Entailment Using a Machine Learning Approach’.
14.     M. Lapata (2003), ‘Probabilistic text structuring: experiments with sentence ordering’, in: Proceedings of the Annual Meeting of ACL, 2003, pp. 545–52.
15.     P.Sukumar and K.S.Gayathri (2014) ‘An Effective Sentence Ordering Approach For Multi-Document Summarization Using Text Entailment’, in International Journal on Recent and Innovation Trends in Computing and Communication [IJRITCC], Vol.2, Issue.1, pp. 144-149.
16.     Partha P., Sivaji B. and Alexander G. (2011), 'Textual entailment using lexical and Syntactic similarity', International Journal of Artificial Intelligence & Applications, Vol. 2, No. 1, pp. 43-58.
17.     Peng G., He Y., Tian Y., Tian Y. and Wen W, 'Analysis of Sentence Ordering Based on Support Vector Machine', Pacific-Asia Conference on Knowledge Engineering and Software Engineering 2009.
18.     Peng G., He Y., Zhang W., Xiong N. and Tian Y., 'A Study for Sentence Ordering Based on Grey Model', IEEE Asia-Pacific Services Computing Conference 2010.
19.     Yogan J K. and Salim N. (2012), ‘Automatic Multi Document Summarization Approaches’, Journal of Computer Science, Vol.8, No.1, pp. 133–140.      

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17.

Authors:

Trupti.Thite, Sharada.C.Sajjan

Paper Title:

Palmprint Texture Analysis using 1D Log-Gabor Filter

Abstract:  Biometrics is the study of automated methods for recognizing a person based on his physical or behavioral characteristic. Biometric systems can be divided into two categories- identification systems and verification systems. Identification systems tell “who you are?” and verification system tell “are you the one who you claim to be?” Security has become a paramount concern in today’s arena. Hence palmprint identification plays a very significant role to address issues of authentication .This involves image acquisition, preprocessing, feature extraction, and pattern matching. Here 1D Log-Gabor filter is used for texture analysis and feature extraction. Support Vector Machine (SVM) classifier is used in this project for pattern matching as against conventional hamming distance. By the incorporation of this SVM classifier the performance of the whole application has significantly increased duly yielding concise accurate results.

Keywords: CCD, SVM

References:
1.        D. Zhang and W. Shu, “Two novel characteristics in palmprint verification: datum point invariance and line feature matching,” Pattern Recognition, vol. 32, no. 4, pp. 691-702, 1999.
2.        N. Duta, A. K. Jain, and Kanti V. Mardia, "Matching of Palmprint", Pattern Recognition Letters, vol. 23, no. 4, pp. 477-485, 2002.
3.        D. Zhang, Automated Biometrics – Technologies and    Systems, Kluwer Academic Publishers, 2000.
4.        J. You, W. Li and D. Zhang, "Hierarchical pamlprint identification via multiple feature extraction", Pattern Recognition, vol. 35, no. 4, pp. 847-859, 2002.
5.        W. Shu and D. Zhang, “Automated personal identification by palmprint,” Optical Engineering, vol. 37 no. 8, pp.2,659-2,362, 1998.
6.        W. Li and D. Zhang, ″Palmprint identification by Fourier Transform″, To appear in International Journal of Pattern Recognition and Artificial Intelligence, 2002.
7.        J. Daugman, “High confidence visual recognition of persons by a test of statistical independence,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 11, pp. 1,148-1,161, 1993.
8.        P.S. Wu and M. Li. “Pyramid edge detection based on stack filter”, Pattern Recognition Letters, vol. 18, no. 4, pp. 239-248, 1997.
9.        Jain and G. Healey, “A multiscale representation including opponent color features for texture recognition,” IEEE Transactions on Image Processing,vol. 7, no. 1, pp. 124-128, 1998.
10.     D. Dunn and W.E. Higgins, “Optimal Gabor filters for texture segmentation,” IEEE Transactions on Image Processing, vol. 4, no. 4, pp. 947-964, 1995.
11.     A.K. Jain, S. Prabhakar, L. Hong and S. Pankanti, “Filterbank-based fingerprint matching,” IEEE Transactions on Image Processing, vol. 9, no. 5, pp. 846-859, 2000.
12.     B. Duc, S. Fischer and J. Bigun, “Face authentication with Gabor information on deformable graphs,” IEEE Transactions on Image Processing, vol. 8, no. 4, pp. 504- 516, 1999.
13.     D. Zhang (ed.), Biometrics Resolutions for Authentication in an E-World, Kluwer Academic Publishers, USA, 2002. 

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18.

Authors:

Dipika Gadriye, Gopichand Khandale, Rahul Nawkhare

Paper Title:

System for Diagnosis of Diabetic Retinopathy using Neural Network

Abstract:   The main cause of blindness for the working age population in western countries is Diabetic Retinopathy - a complication of diabetes mellitus - is a severe and wide- spread eye disease. Digital color fundus images are becoming increasingly important for the diagnosis of Diabetic Retinopathy. In order to facilitate and improve diagnosis in different ways, this fact opens the possibility of applying image processing techniques. An algorithm able to automatically detect the microaneurysms in fundus image captured is a necessary preprocessing step for a correct diagnosis as microaneurysms are earliest sign of DR. The key for low cost widespread screening is a system usable by operators with little training. Some methods that address this problem can be found in the literature but they have some drawbacks like accuracy or speed. The aim of this thesis is to develop and test a new method for detecting the microaneurysms in retina images. To do so preprocessing, gray level 2D feature based vessel extraction is done using neural network by using extra neurons which is evaluated on DRIVE database which is superior than rule based methods. Morphological opening and image enhancement are performed to identify microaneurysms in an image. The complete algorithm is developed by using a MATLAB implementation and the diagnosis in an image can be estimated with the better accuracy and in shorter time than previous techniques.

Keywords: Contrastnormalizationfundusmicroaneurysmsretinapixel classification,retina.

References:
1.        G. G. Gardner, D. Keating, T. H.Williamson, and A. T. Elliott, “Automatic detection of diabetic retinopathy using an artificial neural network: A screening tool,” Br. J. Ophthalmol., vol. 80, pp. 940–944, 1996.
2.        M. Niemeijer, J. Staal, B. v. Ginneken, M. Loog, and M. D. Abramoff, J. Fitzpatrick and M. Sonka, Eds., “Comparative study of retinal vessel segmentation methods on a new publicly available database,” in SPIE Med. Imag., 2004, vol. 5370, pp. 648–656.
3.        J. Staal, M. D. Abràmoff, M. Niemeijer, M. A. Viergever, and B. v. Ginneken, “Ridge based vessel segmentation in color images of the retina,” IEEE Trans. Med. Imag., vol. 23, no. 4, pp. 501–509, Apr. 2004.
4.        J. V. B. Soares, J. J. G. Leandro, R. M. Cesar, Jr., H. F. Jelinek, and M. J. Cree,  “Retinal vessel segmentation using the 2D Gabor wavelet and supervised classification,” IEEE Trans. Med. Imag., vol. 25, no. 9, pp.  1214–1222, Sep. 2006.
5.        E. Ricci and R. Perfetti, “Retinal blood vessel segmentation using line operators and  support vector classification,” IEEE Trans. Med. Imag., vol. 26, no. 10, pp.
1357–1365, Oct. 2007.
6.        G. G. Gardner, D. Keating, T. H.Williamson, and A. T. Elliott, “Automatic detection of diabetic retinopathy using an artificial neural network: A screening tool,” Br. J. Ophthalmol., vol. 80, pp. 940–944, 1996
7.        C. Sinthanayothin, J. F. Boyce, H. L. Cook, and T. H. Williamson, “Automated localisation of the optic disc, fovea and retinal blood vessels from digital colour fundus images,” Br. J. Ophtalmol., vol. 83, pp. 902–910, 1999.
8.        M. Niemeijer, J. Staal, B. v. Ginneken, M. Loog, and M. D. Abramoff, J. Fitzpatrick and M. Sonka, Eds., “Comparative study of retinal vessel segmentation methods on a new publicly available database,” in SPIE Med. Imag., 2004, vol. 5370, pp. 648–656.
9.        J. V. B. Soares, J. J. G. Leandro, R. M. Cesar, Jr., H. F. Jelinek, and M. J. Cree, “Retinal vessel segmentation using the 2D Gabor wavelet and supervised classification,” IEEE Trans. Med. Imag., vol. 25, no. 9, pp. 1214–1222, Sep. 2006.

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19.

Authors:

Umang Sardesai, Aakash Makwana, Sagar Haria

Paper Title:

Review Mining: A New Approach using Modified NLP

Abstract:    The Web has become an excellent source for gathering consumer opinions. There are now numerous Web sites containing such opinions, e.g., customer reviews of products, forums, discussion groups, and blogs. Nowadays we get all the technical specifications of a product on the Web, but what matters is what the customer feels about or what his opinions about the product are. This paper focuses on analyzing and summarizing online customer reviews of products. While analyzing we devise a new approach for NLP, by assigning a latent weight to each aspect/feature of a product. After extracting the sentiment in each sentence of the review, we summarize the opinions and express it graphically. This will not only help customers but also help the product manufacturers to get an indirect customer feedback.

Keywords: NLP, Sentiment Analysis, Opinion mining, Latent weight, Visualization

References:
1.        Hu, M., and Liu, B. 2004. Mining and summarizing customer reviews. KDD’04, 2004.
2.        B. Liu, M. Hu, and J. Cheng. Opinion observer: Analyzing and comparing opinions on the web. In WWW '05, pages 342{351, 2005.
3.        Hongning Wang, Yue Lu, Chengxiang Zhai. Latent Aspect Rating Analysis on Review Text Data: A Rating Regression Approach 2010.
4.        Bing Liu. Sentiment Analysis and Subjectivity. To appear in Handbook of Natural Language Processing, Second Edition, (editors: N. Indurkhya and F. J. Damerau), 2010.
5.        Bing Liu. Sentiment Analysis and Opinion Mining, Morgan & Claypool Publishers, May 2016

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