|
S. No
|
Volume-4 Issue-2, May 2015, ISSN: 2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.
|
Page No.
|
|
1.
|
Authors:
|
Mahima Jacob, Saurabh Mitra
|
|
Paper Title:
|
Video Watermarking Techniques: A Review
|
|
Abstract: Digital watermarking is meant to protect the digital information from unauthorized agencies or person. Internet has opened a new door to share their thoughts, text , images and video. This makes it possible to manipulate and redistribute these information illegally. Video watermarking is another variant of digital watermarking which is used for video authentication and for other purpose. This paper presents a review work in video watermarking research field.
Keywords: DCT (Discrete Cosine Transform), DWT (Discrete wavelet Transform), LSB (Least significant Bit), contourlet Transform (CT).
References:
1. T. Jayamalar, Dr. V. Radha, “Survey on Digital Video Watermarking Techniques and Attacks on Watermarks,” International Journal of Engineering Science and Technology, vol. 12, 6963- 6967, 2010.
2. E. Ganic and A. M. Eskicioglu, “Secure DWT-SVD Domain Image Watermarking: Embedding Data in All Frequencies,” ACM Multimedia and Security Workshop 2004.
3. P.W. Chan and M. Lyu, ”A DWT-based Digital Video Watermarking Scheme with Error Correcting Code,” Proceedings Fifth International Conference on Information and Communications Security (ICICS2003), Lecture Notes in Computer Science, Springer, Vol. 2836, pp. 202-213, Huhehaote City, Inner-Mongolia, China, Oct. 10-13, 2003.
4. P.W. Chan, M.R. Lyu and R.T. Chin “A Novel Scheme for Hybrid Digital VideoWatermarking: Approach, Evaluation and Experimentation,” submitted to IEEE Transactions on Circuits and Systems for Video Technology.
5. Vassaux, P. Nguyen, S. Baudry, P. Bas, and J. Chassery, “Scrambling technique for video object watermarking resisting to mpeg-4,” Proceedings Video/Image Processing and Multimedia Communications 4th EURASIP-IEEE Region 8 International Symposium on VIPromCom, pp. 239-244,2002 .
6. M. Swanson, B. Zhu, B. Chau, and A. Tewfik, ”Object- Based Transparent Video Watermarking,” Proceedings IEEE Signal Processing Society 1997 Workshop on Multimedia Signal Processing, Princeton, New Jersey, USA, Jun.23-25, 1997.
7. B. Mobasseri, ”Direct sequence watermarking of digital video using m-frames,” Proceedings International Conference on Image Processing (ICIP-98), Vol. 3, pp. 399-403, Chicago, Illinois, Oct. 4-7, 1998.
8. K. Su, D. Kundur and D. Hatzinakos, “A novel approach to collusion-resistant video watermarking”, Proceedings of the SPIE, vol. 4675, pp. 491-502.
9. B. G. Mobasseri, “Exploring CDMA for watermarking of digital video”, (1999) proceedings of of the SPIE, vol. 3675, pp. 96-102.
10. G. C. Langelaar, R. L. Lagendijk, and J. Biemond, “Realtime labeling of MPEG-2 compressed video,” (1998) journal of visual communication and image representation, vol. 9, pp. 256-270.
11. R. B. Wolfgang, C. I. Podilchuk and E. J. Delp, “Perceptual watermarks for digital images and video”, Proceedings of the IEEE, vol. 87, pp. 1108-1126, (1999).
12. M. M. Reid, R. J. Millar and N. D. Black, “Second-generation image coding: An overview”, ACM Computing Surveys, vol. 29, pp. 3-29.
13. F. Deguillaume, G. Csurka, J. Ruanaidh, and T. Pun, ”Robust 3D DFT video watermarking,” Proceedings Electronic Imaging’ 99: Security and Watermarking of Multimedia Contents, Vol. 3657, San Jose, CA, Jan. 1999.
14. Chris Shoemaker, “Hidden Bits: A Survey of Techniques for Digital Watermarking”, Independent Study, 2002.
15. http://www.vu.union.edu/~shoemakc/watermarking/watermarking.html .
16. Mahesh R. Sanghavi, Dr. Mrs. Archana M. Rajurkar, Prof. Dr. Rajeev Mathur ,Kainjan S. Kotecha “A Robust Scheme for Digital Video Watermarking based on Scrambling of Watermark”, International Journal of Computer Applications (0975 – 8887) Volume 35– No.2, December 2011
17. Tamanna Tabassum, S.M. Mohidul Islam “A Digital Video Watermarking Technique Based on Identical Frame Extraction in 3-Level DWT” in 2012 IEEE, PP-101-106
18. Sonjoy Deb Roy, Xin Li, Yonatan Shoshan, Alexander Fish and Orly Yadid-Pecht ”Hardware Implementation of a Digital Watermarking System for Video Authentication”, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 23, NO. 2, FEBRUARY 2013, Pg-289-301
|
1-4
|
|
2.
|
Authors:
|
R. Muthucumaraswamy, P. Sivakumar
|
|
Paper Title:
|
Unsteady Parabolic MHD Flow past an Infinite Vertical Plate with Variable Temperature in the Presence of Thermal Radiation and Chemical Reaction
|
|
Abstract: In this paper we analyse the effect of chemical reaction and thermal radiation on parabolic MHD flow past an infinite vertical plate with variable temperature a uniform magnetic field with variable temperature The non-dimensional equations governing the above flow characteristics are solved by using Laplace Transformation and the effect of different physical parameters on the velocity profile, temperature profile and concentration profile are illustrated graphically
Keywords: MHD, Chemical reaction, vertical plate, radiation, heat transfer, mass transfer, temperature, velocity Laplace transform method,
References:
1. A.S .Gupta, I. Pop and V.M. Soundalgekar 1979, Free convection effects on the flow past an accelerated vertical plate in an incompressible dissipative fluid. Rev. Roum. Sci. Techn. -Mec. Apl. 24: pp.561-568.
2. N.G. Kafousias and A.A. Raptis. 1981, Mass transfer and free convection effects on the flow past an accelerated vertical infinite plate with variable suction or injection. Rev. Roum. Sci. Techn.- Mec. Apl 26: pp.11-22.
3. A.K .Singh and N.Kumar 1984. Free convection flow past an exponentially accelerated vertical plate. Astrophysics and Space science. 98:pp. 245-258.4. M.A. Hossain and L.K. Shayo 1986, The Skin friction in the unsteady free convection flow past an accelerated plate. Astrophysics and Space Science. 125: pp. 315-324.
5. B.K. Jha (1991) MHD free-convection and mass transform flow through a porous medium. Astrophysics and Space science 175: 283-289
6. B.K .Jha, R. Prasad. and S. Rai 1991. Mass transfer effects on the flow past an exponentially accelerated vertical plate with constant heat flux. Astrophysics and Space Science. 181:pp.125-134.
7. R. Muthucumaraswamy, K.E. Sathappan and R. Natarajan 2008. Mass transfer effects on exponentially accelerated isothermal vertical plate. Int. J. of Appl. Math. and Mech. 4(6): 19-25.
8. V.M. Soundalgekar , S.K. Gupta and N.S. Birajdar , Effects of mass transfer and free convection currents on MHD Stokes problem for a vertical plate, Nuclear Eng. Des. 53(1979), 339-346.
9. V.M.Soundalgekar, M.R.Patil and M.D. Jahagirdar, MHD Stokes problem for a vertical plate with variable temperature, Nuclear Eng. Des. 64(1981), 39-42.
10. V.M. Soundalgekar and H.S. Takhar, Radiation effects on free convection flow past a semi-infinite vertical plate , Model. Measure.Comrol (1993), 31-40. 11. M. A. Hossain and H. S. Takhar, Radiation effect on mixed Convection along a vertical plate with uniform surface temperature, Heat Mass Trans. 31(1996), 243-248.
12. Raptis and C. Perdikis, Radiation and free convection flow past a moving plate, Int. J.Appl Mech. Eng. 4(1999), 817-821.
13. U. N. Das, R.K. Deka and V.M. Soundalgekar , Radiation effects on flow past an impulsively started vertical infinite plate, J.theo. Mech 1(1996), 111-115
14. R. Muthucumaraswamy and B. Janakiraman, MHD and radiation effects on moving isothermal vertical plate with variable mass diffusion, Theo. Appl. Mech. 33(1) (2006), 17-29.
|
5-10
|
|
3.
|
Authors:
|
R. Ravikumar, U. Sundhar
|
|
Paper Title:
|
A Novel Approach for Improved Personalized Web Search with Privacy Protection
|
|
Abstract: Personalized web search is a promising way to improve search quality by customizing search results for people with individual information goals. However, users are uncomfortable with exposing private information to search engines. Thus, a balance must be struck between search quality and privacy protection. The proposed system presents a scalable way for users to automatically build rich user profiles. These profiles summarize user’s interests into a hierarchical organization according to specific interests. The system proposes a Personalized Web (PWS) framework called User customizable Privacy-preserving Search (UPS) that can adaptively generalize profiles by queries while respecting user specified privacy requirements. The runtime generalization aims at striking a balance between two predictive metrics that evaluate the utility of personalization and the privacy risk of exposing the generalized profile. The system presents two greedy algorithms, namely Greedy DP and Greedy IL, for runtime generalization. It also provides an online prediction mechanism for deciding whether personalizing a query is beneficial.
Keywords: Privacy-preserving Search, Privacy-preserving Search, Greedy DP and Greedy IL.
References:
1. Baeza-Yates R and Ribeiro-Neto B (1999), Modern Information Retrieval Addison Wesley Longman.
2. Breese J.S, Heckerman D, and Kadie C.M (1998), “Empirical Analysis of Predictive Algorithms for Collaborative Filtering,” Proc. 14th Conf. Uncertainty in Artificial Intelligence (UAI), pp. 43-52.
3. Chirita P.A, Nejdl W, Paiu R, and Kohlschutter C (2005), “Using ODP Metadata to Personalize Search,” Proc. 28th Ann. Int’l ACM SIGIR Conf. Research and Development Information Retrieval (SIGIR).
4. Dou. Z, Song R, and Wen J.-R (2007), “A Large-Scale Evaluation and Analysis of Personalized Search Strategies,” Proc. Int’l Conf. World Wide Web (WWW), pp. 581-590.
5. Gabrilovich E and Markovich S (2006), “Overcoming the Brittleness Bottleneck Using Wikipedia: Enhancing Text Categorization with Encyclopedic Knowledge,” Proc. 21st Nat’l Conf. Artificial Intelligence (AAAI).
6. Hafner K (2006), Researchers Yearn to Use AOL Logs, but They Hesitate, New York Times.
7. Ja¨rvelin K and Keka¨la¨inen J(2000), “IR Evaluation Methods forRetrieving Highly Relevant Documents,” Proc. 23rd Ann. Int’lACM SIGIR Conf. Research and Development Information Retrieval (SIGIR), pp. 41-48.
8. Krause A and Horvitz E (2010), “A Utility-Theoretic Approach to Privacy in Online Services,” J. Artificial Intelligence Research, vol. 39, pp. 633-662.
9. Pitkow J, Schu H ¨tze, Cass T, Cooley R, Turnbull V, Edmonds, A, Adar E, and Breuel T(2002), “Personalized Search,” Comm. ACM, vol. 45, no. 9, pp. 50-55.
10. Pretschner A and Gauch S (1999), “Ontology-Based Personalized Search and Browsing,” Proc. IEEE 11th Int’l Conf. Tools with Artificial Intelligence (ICTAI ’99).11. Ramanathan K, Giraudi J, and Gupta A (2008), “Creating Hierarchical User Profiles Using Wikipedia,” HP Labs.
12. Shen X, Tan B, and Zhai C (2005), “Implicit User Modeling for Personalized Search,” Proc. 14th ACM Int’l Conf. Information and Knowledge Management (CIKM).
13. Shen X,Tan B, and Zhai C(2005), “Context-Sensitive Information Retrieval Using Implicit Feedback,” Proc. 28th Ann. Int’l ACM SIGIR Conf. Research and Development Information Retrieval (SIGIR).
14. Shen X, Tan B, and Zhai C (2007), “Privacy Protection in Personalized Search,” SIGIR Forum, vol. 41, no. 1, pp. 4-17.
15. Spertta M. and Gach S (2005), “Personalizing Search Based on User Search Histories,” Proc. IEEE/WIC/ACM Int’l Conf. Web Intelligence (WI).
16. Sugiyama K, Hatano K, and Yoshikawa M (2004), “Adaptive Web Search Based on User Profile Constructed without any Effort from Users,” Proc. 13th Int’l Conf. World Wide Web (WWW).
17. Tan B, Shen X, and Zhai C (2006), “Mining Long-Term Search History to Improve Search Accuracy,” Proc. ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining (KDD).
18. Teevan. J, Dumais S.T, and Horvitz E (2005), “Personalizing Search via Automated Analysis of Interests and Activities,” Proc. 28th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), pp. 449-456.
19. Qiu F and Cho J (2006), “Automatic Identification of User Interest for Personalized Search,” Proc. 15th Int’l Conf. World Wide Web (WWW), pp. 727-736.
20. Xu Y, Wang K, Zhang B, and Chen Z (2007), “Privacy-Enhancing Personalized Web Search,” Proc. 16th Int’l Conf. World Wide Web (WWW), pp. 591-600.
|
11-14
|
|
4.
|
Authors:
|
Sangeetha N, Premchand Ravella, Vangala Mourya Sashidhar Reddy
|
|
Paper Title:
|
Analysis of 3D Laser Range Finder for Defense Applications
|
|
Abstract: In this paper, we are analyzing reliable, lightweight 3D laser range finder for the fast acquiring of 3D images of the target on defense applications. For scanning the target, we use algorithms such as LENCOMP , HOUGH & LINMER for line and surface detection of the data. So that the 3D image of the target can be retrieved. The optimum distance and angle by which the range finder could find the target is also analyzed.
Keywords: Laser range finder, Tanker, Triangulation method.
References:
1. http://upload.wikimedia.org/wikipedia/commons/2/22/M1_Abrams-TUSK.svg
2. https://shaneormonde.wordpress.com/2014/01/25/webcam-laser-rangefinder
3. Hartmut Surmann, Kai Lingemann, Andreas N¨uchter and Joachim Hertzberg-”Fast acquiring and analysis of three dimensional laser range data”
4. Sebastian Thrun, Dieter Fox, and Wolfram Burgard, “A real-time algorithm for mobile robot mapping with applications to multirobot and 3d mapping,” in IEEE International Conference on Robotics and Automation, San Francisco, 2000.
5. Calibration of Laser Range Finder with a Genetic Algorithm Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems San Diego, CA, USA, Oct 29 - Nov 2, 2007
6. http://homepages.inf.ed.ac.uk/rbf/HIPR2/hough.htm
7. Calibration of Laser Range Finder with a Genetic Algorithm Masamitsu Kurisu and Hiroki Muroi,Yasuyoshi Yokokohji
8. A Low-Cost PC-Based Range Finder System S. M. A. Motakabber and Muhammad I. Ibrahimy
|
15-19
|
|
5.
|
Authors:
|
Mayank J. Patel, Brijesh N. Shah
|
|
Paper Title:
|
Robotic Arm Movement Using Image Processing
|
|
Abstract: Nowadays there is an increasing need to create artificial arms for different in human situations where human interaction is difficult or impossible.. Here I propose to build a robotic arm controlled by MATLAB. A human hand can handle various objects by his hand, with better capacity and precision. In some hostile conditions, a need arises to replicate the human arm movements by some sophisticated manipulator. This report illustrates the controlling of the movements of robotic arm, in accordance with the movements of RGB color strip (attached to human arm) using real time image processing.
Keywords: Matlab, Image Processing, Atmega16, Servo Motor
References:
1. Robotic arm movements wirelessly synchronized with human arm movements using real time image processing, Abdullah Shaikh, Gandhar Khaladkar, Rhutuja Jage, Tripti Pathak Javed Taili M. H. Saboo Siddik College of Engineering, Mumbai-08
2. Practical Applications for Robotic Arms Using Image Processing Mihai Dragusu, Anca Nicoleta Mihalache and Razvan Solea, member, IEEE
3. G. Dougherty, Digital Image Processing for Medical Applications, Cambridge University Press, 2009.4. Wearable Robot Control Interface based on Measurement of Human Body Motion using a Camera and Inertial Sensors Junichi Sugiyama and Jun Miura
5. Design of Automatic Cotton Picking Robot with Machine Vision Using Image Processing Algorithms USN Rao School of Electronics Vignan University Vadlamudi,Guntur, India
6. Digital Image Processing Using Matlab By Rafael C. Gonzalez, Richard Eugene Woods, Steven L. Eddins
7. http://www.atmel.com/Images/2466s.pdf
8. http://www.bpesolutions.com/bpemanuals/servo.info.pdf
9. http://www.engineersgarage.com/embedded/avr-microcontroller-projects/serial-communication-atmega16-usart
10. http://www.engineersgarage.com/electronic-components/16x2-lcd-module-datasheet
11. www.mathworks.in/products/matlab/
12. http://www.mcselec.com/?option=com_content&task=view&id=14&Itemid=4113. robokits.co.in/.../USB%20Programmer%20documentation
14. Robotic arm control through human arm movement using accelerometers by ashutosh pattnaik, rajiv ranjan, Department of electronics and communication
engineering, National institute of technology, Rourkela
15. http://www.bpesolutions.com/bpemanuals/servo.info.pdf
|
20-22
|
|
6.
|
Authors:
|
Omaima N. Ahmad AL-Allaf, Shahlla A. AbdAlKader
|
|
Paper Title:
|
Performance Analysis of Different Feature Extraction Algorithms Used with Particle Swarm Optimization for Gait Recognition System
|
|
Abstract: Recently, person identification systems based on gait recognition had been gained growing large interest from researchers in the fields of artificial intelligence and image processing Thus, a gait recognition system based on particle swarm optimization (PSO) has been suggested in this work to recognize any person at a distance who performing the movement. Three feature extraction and dimension reduction algorithms were used to increase the recognition performance of PSO algorithm. These algorithms are: Liner Discriminant Analysis (LDA); Discrete Fourier Transform (DFT); and Discrete Cosine Transform (DCT). Many experiments were conducted for PSO with the three algorithms using different: swarm size, block dimension and number of iterations. Best results obtained when selecting swarm size equal 40, feature block size 70×70 and 100 number of iterations. At the same time best results of: recognition rate (97%), MSE (0.0027) and PSNR (38) where obtained when adopting LDA algorithm in comparison with DFT and DCT. And also the results obtained from DFT are better than the results obtained from using DCT. The time required for executing the LDA is lowest than the time required for executing DFT and DCT. DCT require more time than the other used feature extraction algorithms.
Keywords: Gait Recognition, Practical Swarm Optimization (PSO), Liner Discriminant Analysis (LDA), Discrete Cosine Transform (DCT), Discrete Fourier Transform (DFT)
References:
1. Sruthy Sebastian, Activity Based Person Identification Using Particle Swarm Optimization Algorithm, International Journal of Computer Science and Mobile Computing, Vol.2, Issue.7, pp:1-6, Jul2013.
2. A. K. Jain, A. Ross, S. Prabhakar, "An Introduction to Biometric Recognition", IEEE Trans. on Circuits and Systems for Video Technology, Vol.14, No.1, pp 4-19, Jan2004.
3. Gajanan P. K., et al. Human Computer Interpreting with Biometric Recognition System, International Journal of Advanced Research in Computer Science and Software Engineering, Vol.2, Issue.12, pp:140-147, Dec2012.
4. Adam Świtoński, et al. Human Identification Based on the Reduced Kinematic Data of the Gait, 7th International Symposium on Image and Signal Processing and Analysis (ISPA), IEEE, pp:650–655, Dubrovnik,4-6 Sep2011.
5. M.Tistarelli, J.Bigun, and E.Grosso, Biometric Gait Recognition, Biometrics School 2003, LNCS 3161, pp: 19–42, 2005.
6. Liang Wang, et al. Silhouette Analysis-Based Gait Recognition for Human Identification, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol.25, No.12, pp:1-14, Dec2003.
7. Liang Wang, , et al, Fusion of Static and Dynamic Body Biometrics for Gait Recognition, Proceedings of the Ninth IEEE International Conference on Computer Vision (ICCV 2003), Vol.2.
8. Chiraz BenAbdelkader, et al. EigenGait: Motion-based Recognition of People using Image Self-Similarity, Lecture Notes in Computer Science Volume 2091, pp:284-294, 2001.
9. Payam Saisan and Swarup Medasani and Yuri Owechko, Multi-View Classifier Swarms for Pedestrian Detection and Tracking, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR Workshops, San Diego, CA, USA, 25-25Jun2005.
10. Qiong C., Bo F., and Hui C., Gait Recognition Based on PCA and LDA, Proceedings of the Second Symposium International Computer Science and Computational Technology(ISCSCT ’09), Huangshan, P. R. China, pp:124-127, 26-28Dec2009.
11. Ra´ul M. and Tao Xiang, Gait Recognition by Ranking, A. Fitzgibbon et al. (Eds.): ECCV 2012, Part I, LNCS 7572, pp:328–341, Springer-Verlag Berlin Heidelberg,2012.
12. Mohamed Rafi, et al. A Model Based Approach for Gait Recognition System, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Vol.3, Issue.5, pp:223-228, Nov 2013
13. Bogdan Kwolek, et al. 3D Gait Recognition Using Spatio-Temporal Motion Descriptors, DOI: 10.1007/978-3-319-05458-2_61 In book: Intelligent Information and Database Systems, Publisher: Springer International Publishing, Editors: Nguyen, NgocThanh and Attachoo, Boonwat and Trawiński, Bogdan and Somboonviwat,
Kulwadee, pp.595-604, 2014.
14. Rong Z., Christian V. and Dimitris M., Human Gait Recognition, Conference on Computer Vision and Pattern Recognition Workshop, 27-02Jun2004. CVPRW '04.
15. Adam S., Andrzej P., Konrad W., Human Identification Based on Gait Paths, book chapter: Advanced Concepts for Intelligent Vision Systems, 13th International Conference, ACIVS 2011, Ghent, Belgium, August 22-25, 2011. Proceedings DOI: 10.1007/978-3-642-23687-7_48, pp 531-542, 2011.
16. Qinghai Bai, Analysis of Particle Swarm Optimization Algorithm, Computer and Information Science, Vol.3, No.1, 2010.
17. Kennedy, J. and Eberhart, R. (1995), Particle swarm optimization, Proceedings of IEEE International Conference on Neural Networks, Perth, WA, 1942-1948.
18. H. Kuo, J. Chang and C. Liu, Particle Swarm Optimization For Global Optimization Problems, Journal of Marine Science and Technology, Vol. 14, No. 3, pp:170-181,
2006.
19. Dian P.R., Siti M.S. and Siti S.Y., Particle Swarm Optimization: Technique, System and Challenges, International Journal of Computer Applications, Vol.14, No.1, pp:19-27, Jan2011
20. Satyobroto Talukder, Mathematical Modelling and Applications of Particle Swarm Optimization, Master’s Thesis, Mathematical Modelling and Simulation, School of Engineering at Blekinge Institute of Technology,Master of Science, Feb 2011.
21. Voratas K., Comparison of Three Evolutionary Algorithms: GA, PSO, and DE, Industrial Engineering & Management Systems, Vol.11, No.3, pp.215-223, Sep2012.
22. Daniel Bratton and James Kennedy, Defining a Standard for Particle Swarm Optimization, Proceedings of the 2007 IEEE Swarm Intelligence Symposium (SIS 2007).
23. Davoud S. and Ellips M., Particle Swarm Optimization Methods, Taxonomy and Applications, International Journal of Computer Theory and Engineering, Vol. 1, No. 5, pp: 486-502, Dec 2009.
24. M. Peyvandi, M. Zafarani and E. Nasr, Comparison of Particle Swarm Optimization and the Genetic Algorithm in the Improvement of Power System Stability by an SSSC-based Controller, Journal of Electrical Engineering & Technology Vol. 6, No. 2, pp:182-191, 2011.
25. Bijayalaxmi Panda, Soumya Sahoo, Sovan Kumar Patnaik, A Comparative Study of Hard and Soft Clustering Using Swarm Optimization, International Journal of Scientific & Engineering Research, Vol.4, Issue.10, pp:785-790, Oct-2013 ISSN 2229-5518
26. Rania Hassan, Babak Cohanim, Olivier de Weck, A Copmarison Of Particle Swarm Optimization And The Genetic Algorithm, American Institute of Aeronautics and Astronautics, 46th Aiaa/Asme/Asce/Ahs/Asc Structures, Structural Dynamics And Materials Conference, 2005.
27. R. M. Ramadan and R. F. AbdelKader, Face Recognition Using Particle Swarm Optimization-Based Selected Features, International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol.2, No.2, pp:51-66, Jun2009.
28. P.V. Shinde, B.L. Gunjal and R. G. Ghule, Face Recognition Using Particle Swarm Optimization, Emerging Trends in Computer Science and Information Technology -2012(ETCSIT2012) Proceedings published in International Journal of Computer Applications® (IJCA), pp:11-13.
29. M. Arunkumar And S. Valarmathy, Palmprint And Face Based Multimodal Recognition Using Pso Dependent Feature Level Fusion, Journal of Theoretical and Applied Information Technology,Vol.57, No.3, pp:337-346, 30th November 2013.
30. K. Krishneswari and S. Arumugam, Intramodal Feature Fusion Based On Pso For Palmprint Authentication, Ictact Journal On Image And Video Processing, May 2012, Vol.2, Issue: 04, pp:435-440.
31. Ola M. Aly, et al., A Multimodal Biometric Recognition system using feature fusion based on PSO, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 2, Issue.11, pp: 4336-4343, Nov2013.
32. Ola M. Aly, et al., An Adaptive Multimodal Biometrics System using PSO, International Journal of Advanced Computer Science and Applications, Vol. 4, No.7, pp:158-165,2013
33. S. Ivekovic, E. Trucco and Y. R. Petillot, Human Body Pose Estimation With Particle Swarm Optimisation, Evolutionary Computation, Vol.16, No.4, pp: 509-528.
34. Ricardo Gutierrez-Osuna, CSCE 666 Pattern Analysis, L10: Linear discriminants analysis, CSE@TAMU.
35. C.R. Rao, Linear Statistical Inference and Its Applications, second ed.Wiley Interscience, 2002.
36. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed San Diego, CA: Academic, 1990.
37. T. Hastie, R. Tibshirani, and J. H. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer-Verlag, 2001.
38. A. M. Martinez and M. Zhu, “Where are linear feature extraction methods applicable?,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 12, pp. 1934–1944, Dec. 2005.
39. Shuiwang Ji and Jieping Ye, Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection, IEEE Transactions On Neural Networks, Vol.19, No.10, pp:1768-1782. Oct2008.
40. M. Ahmad, T. Natarajan and K. R. Rao, Discrete Cosine Transform, IEEE Trans. Computers, 1974, pp:90-94.
41. Aman R. C., Pallavi P. V. and M. M. Roja, Face Recognition Using Discrete Cosine Transform for Global and Local Features, Proceedings of the 2011 International Conference on Recent Advancements in Electrical, Electronics and Control Engineering IEEE Xplore:CFP1153R-ART; ISBN: 978-1-4577-2149-6
42. Ziad M. Hafed and Martin D. Levine, Face Recognition Using the Discrete Cosine Transform, International Journal of Computer Vision , Vol.43, No.3, pp:167–188, 2001 Kluwer Academic Publishers. Manufactured in The Netherlands.
43. C. Podilchuk and X. Zhang, “Face Recognition Using DCT-Based Feature Vectors,” Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 4, pp. 2144-2147, May 1996.
44. Z. Yankun and L. Chongqing, “Efficient Face Recognition Method based on DCT and LDA,” Journal of Systems Engineering and Electronics, vol. 15, no. 2, pp. 211-216, 2004.
45. F. M. Matos, L. V. Batista, and J. Poel, “Face Recognition Using DCT Coefficients Selection,” Proc. of the 2008 ACM Symposium on Applied Computing, (SAC’08),pp. 1753-1757, March 2008.
46. Z. Pan and H. Bolouri, “High Speed Face Recognition Based on Discrete Cosine Transform and Neural Networks,” Technical Report, Science and Technology Research Center (STRC), University of Hertfordshire.
47. Virendra P. Vishwakarma, Sujata Pandey Member IEEE, and M. N. Gupta , A Novel Approach for Face Recognition Using DCT Coefficients Re-scaling for Illumination Normalization, 15th International Conference on Advanced Computing and Communications, IEEE Computer Sociaety, pp:535-539.
48. [Signal Processing Toolbox™ User's Guide, R2015a, The MathWorks, Inc., 1988–2015.
49. Image Processing Toolbox For Use with MATLAB, User’s Guide Version 2, The MathWorks, Inc. 1993 – 1998.
50. Kazuyuki Miyazawa, et al. A Phase-Based Iris Recognition Algorithm. D. Zhang and A.K. Jain (Eds.): ICB 2006, LNCS 3832, pp. 356–365, 2005, Springer-Verlag Berlin Heidelberg 2005.
51. Poulami Das, et al. Person Identification through IRIS Recognition, International Journal of Security and its Applications Vol. 3, No. 1, January, 2009, pp:129-148.
52. Jaydeep K., Nilesh G. Pardeshi and Vikas N., Improved Iris Recognition using Discrete Fourier Transform, International Journal of Computer Applications (0975 – 8887) International Conference on Recent Trends in engineering & Technology - 2013(ICRTET'2013), pp:33-38.
53. Ahmed Mostayed, et al. Abnormal Gait Detection Using Discrete Fourier Transform, International Journal of Hybrid Information Technology Vol.3, No.2, April, 2010, pp:1-8.
54. K Manikantan and S Ramachandran, DFT domain Feature Extraction using Edge-based Scale Normalization for Enhanced Face Recognition, Journal of Advanced Computer Science and Technology, Vol.1, No.3, 2012, pp:134-166, Science Publishing Corporation,
55. CASIA Gait Database, http:// www.sinobiometrics.com, 2006. CASIA Gait Database collected by Institute of Automation, Chinese Academy of Sciences" and a citation to "CASIA Gait Database.
|
23-30
|
|
7.
|
Authors:
|
Mohamed H. Almeer
|
|
Paper Title:
|
Implementing Hashing for Virus Recognition Using ANN (HASH-ANN)
|
|
Abstract: In this paper, we propose an intelligent first-warning system for virus code detection based on Artificial Neural Networks (ANNs). The proposed system operates in accordance with the basic principles of ANNs to conduct pattern matching of 32-bit hash signatures and detect virus signatures by means of the hashing applied to the byte content of executable code. The proposed system can accurately detect virus code in accordance with information it has learned, and gives false positive ratios within acceptable ranges. The results of experiments conducted show that the combination of 32-bit hashing and neural networks results in a low false positive rate. This paper also discusses the key ideas and approaches, along with the necessary adaptations and adjustments undertaken in the neural network model underlying the proposed early warning virus detection system.
Keywords: Hashing, Hash code, BKDR hash function, ANN, Neural Networks, Virus detection.
References:
1. K. Tan, “The application of neural networks to UNIX computer security,” Proceedings of the IEEE International Conference on Neural Networks, vol. 1, 1995.
2. C. James and M. James, “The application of artificial neural networks to misuse detection: Initial results,” Proceedings RAID98, Louvain-la-Neuve, Belgium, pp. 14-16, 1998.
3. W. Arnold and G. Tesauro, “Automatically generated Win32 heuristic virus detection,” Virus Bulletin Conference, pp. 51-60, September 2000
4. G. J. Tesauro, O. J. Kephart, and B. G. Sorkin, “Neural networks for computer virus recognition,” IEEE Expert Magazine, pp. 5-6, 1996.
5. W.A. Salameh, “Detection of intrusion using neural networks: A customized study,” Studies in Informatics and Control, vol. 13, no. 2 pp. 135-143, 2004.
6. G.E. Dahl, et al. “Large-scale malware classification using random projections and neural networks,” Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
7. S. Shah, et al. “Virus detection using artificial neural networks,” International Journal of Computer Applications, vol. 84, 2013.
8. V. Golovko and S. Bezobrazov, “Neural network artificial immune system for malicious code detection,” ICNNAI'2010, pp. 147-153, June 2010.
9. S. Lian, J. Sun, and Z. Wang, “One-way hash function based on neural network,” arXiv preprint arXiv:0707.4032, 2007.
10. O. Haddadi, Z. Abbasi, and H. TooToonchy, “The Hamming code performance analysis using RBF neural network,” Proceedings of the World Congress on Engineering and Computer Science, vol. 2, 2014.
11. B.W. Kernighan and D.M. Ritchie, The C Programming Language, Prentice Hall Professional Technical Reference, 1988, ISBN:0131103709.
12. Neural Network Toolbox User Guide.
13. Clam AV, www.clamav.org.
14. A.V. Aho and M.J. Corasick, “Efficient string matching: An aid to bibliographic search,” Communications of the ACM, vol. 18, no. 6, pp. 333-340, 1975.
15. S. Wu and U. Manber, “A fast algorithm for multi-pattern searching,” Technical Report TR-94-17. University of Arizona, 1994.
16. R.S. Boyer and J.S. Moore, “A fast string searching algorithm,” Communications of the ACM, vol. 20, no. 10, pp. 762-772, 1977.
17. M.H. Almeer, “N-grams and neural networks in early virus warning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), vol. 4, no. 4, pp. 1-5, April 2015.
|
31-35
|
|
8.
|
Authors:
|
A. A. Shaikh, P. S. Shinde, S. R. Singh, S. Chandra, R. A. Khan
|
|
Paper Title:
|
Thy Ensemble: A Virtual Dressing Room for e-shopping using Augmented Reality
|
|
Abstract: Augmented Reality combined with new algorithms and social media technologies have started a revolutionary shift away from the classic desktop paradigm and into the direction of intuitive, “natural interaction” where people interface with the technological world through hand gestures, speech and body language. The virtual dressing room will make use of Human Computer Interface and Augmented Reality and it will be used for online shopping. This will facilitate the shopping experience by letting customers to try-on the apparels without being physically present in the retail shop. These platforms are not only powerful decision tools for the on-line shopper, but also contribute to the fun factor of in-store shopping. The system gets the data of custom body sizes to construct virtual fitting model through photos already uploaded. The model then tries on different costumes and the system shows the fitting effect. Augmented Reality virtual dressing room works by superimposing the model or picture of a garment or accessory within the live video feed of the customer. In addition, omnipresent social networking features allow sending photos or videos of the shopper wearing the apparel for quick feedback. The proposed project can achieve real-time, high-fidelity cloth simulation and provide encouraging online virtual fitting experiences.[1
Keywords: Augmented Reality, Superimposition, Computer Vision, Gesture recognition, Human-Computer Interaction, Motion tracking.
References:
A. A. Shaikh, P. S. Shinde, S. R. Singh, S. Chandra, R. A. Khan, “A Review on Virtual Dressing Room for e-shopping using Augmented Reality” International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307,Volume-4, Issue-5,November 2014.
1. http://indianonlineseller.com/2014/12/indian-e-commerce-in-a-nutshell-important-trends-in-the-industry/
2. http://www.statista.com/statistics/289770/india-retail-e-commerce-sales/
3. http://www.digihooks.com/the-future-of-ecommerce-in-india/
4. http://globalnews.ca/news/1991610/interactive-shelves-to-virtual-dressing-shopping-gets-high-tech/
5. Ronald Azuma, “A Survey of Augmented Reality,” In Presence: Teleoperators and Virtual Environments 6, 4 (August 1997), 355-385.
6. R. Gonzales and R. Woods, Digital Image Processing, Addison Wesley, 1992, pp 47 - 51, 185 - 187.7. Foley, James D., Andries van Dam, Steven K. Feiner, and John F. Hughes, Computer Graphics: Principles and Practice (2nd edition). Addison-Wesley (1990).
8. http://en.wikipedia.org/wiki/Image_subtraction#cite_note-1
9. http://en.wikipedia.org/wiki/Thresholding_(image_processing)
10. S. Mitra and T. Acharya, “Gesture Recognition: A Survey,” IEEE Transactions On Systems, Man, And Cybernetics—Part C: Applications And Reviews, Vol. 37, No. 3, May 2007.
11. V. I. Pavlovic, R. Sharma, and T. S. Huang, “Visual interpretation of hand gestures for human computer interaction,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 677–695, Jul. 1997.
12. Deering, Michael, “High Resolution Virtual Reality,” Proceedings of SIGGRAPH '92 (Chicago, IL, 26-31 July 1992). In Computer Graphics 26, 2 (July 1992), 195-202.
13. http://internetretailing.net/2013/01/fashion-retailers-opt-for-virtual-fitting-rooms/
14. http://made-to-measure-suits.bgfashion.net/article/10575/58/Futuristic-dressing-room-innovative-retail-and-marketing-solution
|
36-40
|
|
9.
|
Authors:
|
Shobha Sharma, Amita Dev
|
|
Paper Title:
|
High Speed EX-OR Gate at 22nm High K Metal Gate Strained SI Technology Node
|
|
Abstract: Four transistor exor gate is chosen and made to work with reverse body bias in all the four transistor. In an another setup, the same exor gate is made to work with forward body bias of 0.45V in all the transistors of the ex_OR gate. The propagation delay is observed to be reduced by 25.146% in the case of all transistors forward body bias. The propagation delay in the normal reverse body bias is 26.096X10-12 sec whereas in the all transistor forward body bias, it is 19.534X10-12 Sec. This high speed Ex-OR gate finds it’s application where power penalty is acceptable.
Keywords: exor gate, ex_OR, Ex-OR, transistor,
References:
1. Sung Mo Kang & Yusuf ,”cmos digital integrated circuits-analysis and design”,3rd ed.,Tata McGraw-Hill Ed.
2. Parminder Kaur & Balwinder Singh Dhaliwal,”Design of fault tolerant full adder/subtractor using reversible gates”, International Conference CCI-2012,Coimbatore , India
3. G Reddy et al,”A novel power aware and high performance full adder cell for ultra low power design”,ICCTPCT2014,pp1121-1126.
4. Deepa et al,Analysis of low power 1bit adder cell using different x-or,x-nor gates.
5. B.Calhoun,Y Cao et al,”digital circuit design challenges & opportunities in the era of nanoscale CMOS”, proceeding of IEEE,vol96,issue2,pp343-365,Feb2008
6. Small C, ”shrinking devices put the squeeze on system packaging,EDN39, 4Feb1994,pp41-46.
7. Krishnendu et al, design of low power, high speed and energy efficient 3 transistor xor gate in 45nm technology “,ICCICCT2014pp66-69
8. Liqong Wei et al, ”Mixed Vth CMOS circuit design methodology for low power applications, ”design automation conference,36th proceeding,430-435-1999
|
41-42
|
|
10.
|
Authors:
|
A Rajalakshmi Devi, S. Ramesh, V. Periasamy
|
|
Paper Title:
|
Self Assembled Monolayers (Sams) of Methimazole on Copper in Corrosion Protection
|
|
Abstract: Self assembled monolayers (SAMs) are formed on copper using Methimazole, under suitable conditions. Corrosion behaviour of copper is studied in neutral medium of 300 ppm aqueous sodium chloride solution using weight loss followed by electrochemical (impedance, potentiodynamic polarization), cyclic voltammetric studies. With the high charger transfer resistance, an efficiency of 95% is observed. The protective film formed on the surface is characterised by water contact angle measurements, FT-IR, SEM/EDX, and AFM studies. Potentiodynamic polarization studies have shown that SAMs control both anodic and cathodic reactions, but cathodic reactions more predominantly and behave as a mixed inhibitor. The surface film formed is found to be stable. The presence of nitrogen and sulphur in the inhibitor molecules on the metal surface due to chemisorption is analysed using EDX.
Keywords: Corrosion inhibition, SAMs, Methimazole.
References:
1. H. Kondoh, N. Saito, F. Matsui, T.Yokoyama, T. Ohta, H. Kuroda, J. Phy. Chem. Soc. B 105 (2001) 12870.
2. S. Pathak, A.S. Khanna, Indian Journal of Chem. Tech., Vol.14 Jan.2007 pp. 5-15.
3. Ulman. Chem Rev. 96 (1996) 1533.
4. P. E. Laibins & Whitesides J Am Chem Soc, 117(1995) 12009.
5. R G Nuzzo & D C Allara, J Am Chem Soc, 105 (1983) 4481.
6. Z. Quan, X. Wu, S. Chen, S. Zhao, H. Ma, Corrosion 57 (2001) 195.
7. Miki Ishibashi, Miki IToh, Kiroshi Nishihara, Kunnitsugu Aramaki, Electrochim. Acta 41 (1996) 241.
8. M. Yadav, D. P. Sharma, Indian Journal of Chem, Tech., Vol.17 March 2020, pp 95-101.
9. El-sayed M. Sherif, Int, J. Electrochem. Sci., 7 (2012) 1884-1887.
10. B.V. Apparao, Md.Iqbal, B.Sreedhar, Indian Journal of Chem. Tech., Vol.16 Jan.2009 pp.25-31.
B. Brzoska, N. Shahidzadeh. F. Rondelez, Nature 360 (1992) 719.
11. O. E. Barcia, O. R. Mattos, N. Pebere, B. Tribollet, J. Electrochem. Soc. 140 (1993) 2825.
12. Y. Feng, W. K. Teo, K. S. Siow, K. L. Tan, A. K. Heish, Corros. Sci. 38 (1996) 369.
13. X. Wu, H. Ma, S. Chen, Z. Xu, A. Sui, J.Electrochem. Soc. 146 (1999) 1847.
14. C.T. Wang, S. H. Chen, h. Y. Ma, L. Hua, N. X. Wang, J. Serb. Chem. Soc. 67 (10) (2002) 685.
15. H. Y. Ma, C. Yang, S. H. Chen, Y. L. Jiao, S. X. Huang, D. G. Li, J. L. Luo, Electrochim. Acta 48 (2003) 4277.
16. V. Appa Rao, Md. Yakub Iqbal, B. Sreedhar, Corrosion Science 51 (2009) 1441-1452.
17. Guiyan Li, Houyi Ma,Yongli Jiao, Shenhao Chen, J. Serb. Chem. Soc. 69 (10) (2004) 791.
18. C.T. Wang, S. H. Chen, h. Y. Ma, L. Hua, N. X. Wang, J. Serb. Chem. Soc. 67 (10) (2002) 685.
19. T. M. Nahir, E. F. Bowden, Electrochim Acta 39 (1994) 2347.
20. F. P. Zamborini, R. M. Crooks, Langmuir 14 (1998) 3279.
21. Sun, R. M. Crooks, Langmuir 9 (1993) 1951.
22. O. Chailapakel, L.Sun, C. Xu, R. M. Crooks, J. Am. Chem. Soc. 115 (1993) 12459.
23. X. M. Zhao, J. L. Wilbur, G. M. Whitesides, Langmuir 12 (1996) 3257.
24. Lalitha. S. Ramesh, S. Rajeswari, Electrochim Acta 51 (2005) 47.
25. H. Baba, T. Kodama, K. Mori, H. Hirahara, Corros. Sci. 39 (1997) 555.
26. Chun-Tao Wang, Shen-Hao Chen, Hou-Yi Ma, lan Hua & Nai-Xing Wang, J. Serb. Chem. Soc. 67 (10) 685-696 (2002).
27. H. P. Lee, K. Nobe, J. Electrochem.Soc. 133 (1986) 2035.
28. Deslouis, B. Tribollet, G. Mengoli, M. M. Musiani, J. Appl. Electrochem. 18 (1988) 374.
|
43-54
|
|
11.
|
Authors:
|
Takaaki Wajima, Zar Zar Hlaing, Akiko Saito, Hideki Nakagome
|
|
Paper Title:
|
Removal of Halogens from Pyrolysis Oils Produced by Plastics Containing Flame Retardants
|
|
Abstract: Plastics containing brominated flame retardants are commonly used in electrical and electronic products, and disposal or recycle of these products is difficult because of their halogen content. In this study, brominated acrylonitrile butadiene styrene (Br-ABS) was pyrolyzed at 450 °C. The halogen content in the product oil was reduced by addition of sodium hydroxide (NaOH) and pine charcoal. The mass fraction of bromine in the oil obtained without the NaOH or charcoal was 3.2 %, whereas those in the oils obtained with NaOH and charcoal were 1.74 % and 1.25 %, respectively. Using both NaOH and charcoal, the bromine mass fraction in the oil was reduced to 0.6 %. Combustion tests were used to determine the colorific values of pyrolysis oils with various bromine contents, and any corrosion that could limit their use as an alternative fuel was evaluated after these tests. Pyrolysis oil with a bromine content of less than 2000 mg/L could be used as fuel without corrosion.
Keywords: charcoal, halogen, pyrolysis oil, sodium hydroxide,
References:
1. Tohka, and R. Zevenhoven. (2002). TMS Extraction and Processing Division. Meeting on Recycling and Waste Treatment in Mineral and Metal Processing: Technical and Economic Aspects, Lulea, Sweden.
2. Available: http://www.abo.fi/~rzevenho/tkk-eny-14.pdf.
3. W. Koch. (2010 April). Estimate absolute computer [News Article] USATodayvailable:http://content.usatoday.com/communities/greenhouse/post/2010/04/developing-world-will-produce-twice-the-e-waste-of-developed-countries-by-2016/1#.Uh1CNZCCjMw.
4. W. J. Hall, and P. T. Williams. (2006, July). Fast Pyrolysis of Halogenated Plastics Recovered from Waste Computers. Journal of Analytical and Applied Pyrolysis. 77(1), 75–82. Available: http://ac.els-cdn.com/S016523700600026X/1-s2.0-S016523700600026X-main.pdf?_tid=1ad8d580-0084-11e5-b76a-00000aacb35f&acdnat=1432300489_352ece8f3b0a83c9f52822591c1f1b67
|
55-59
|
|
12.
|
Authors:
|
Shobha Sharma, Amita Dev
|
|
Paper Title:
|
High Speed EX_NOR Gate At 22nm High K Metal Gate Strained Si Technology Node
|
|
Abstract: The propagation delay of the normal Ex_Nor circuit is calculated to be ---with reverse body bias. Also the propagation delay of the same exnor circuit is calculated with its body bias forward biased of Vdd/2. With forward body bias the propagation delay is reduced by 55.89% and this high speed Exnor circuit finds its application where power penalty is acceptable.
Keywords: 22nm, high speed, X-nor gate, X-or gate.
References:
1. A.P.Chandrashekharan et al,”low power cmos digital design”IEEE transaction on solid state circuits,Vol 27,no4,p473-483,1992
2. Yibin, K Roy et al,”power consumption in XOR based circuits”, IEEE conference 078035012x/99, 1999.
|
60-61
|
|
13.
|
Authors:
|
Dhandapani Anbarasu
|
|
Paper Title:
|
Wireless Communications - 5G Networks and Architecture
|
|
Abstract: The number of people using mobile phones In the world has exceeded 6 billion and this figure is continuing to grow. For the past several years, mobile data traffic such as Internet access, the downloading of music, and video communication has been nearly tripling every year. Hence, the search for new technology is always the main intention of the prime wireless communication giants to out innovate their competitors. In addition, the main purpose of the fifth generation wireless networks (5G Wireless networks) is planned to design the best wireless world that is free from limitations and hindrance of the previous generations. 5G technologies will change the way most high bandwidth users access their Mobile Radio Communication (MRC). So, this paper represents, great evolution of 1G to 4G yield 5G, introduction to 5G technologies, why there is a need for 5G, advantages of 5G networks technology, exceptional applications, Quality of Service (QoS), 5G network architecture-The Master Core as well as hardware and software for the 5G Master Core technology.
Keywords: 5G, Quality of Service, Architecture, Mobile Radio Communication
References:
1. Saddam Hossain, “5G wireless Communication systems” American Journal of Engineering Research (AJER).
2. Dr. Anwar M Mousa. "'Prospective of Fifth Generation Mobile Communications"' International Journal of Next-Generation Networks (IJNGN) Vol.4, No.3, September 2012
3. Sapana Singh & Pratap Singh. "Key Concepts and Network Architecture for 5G Mobile Technology" International Journal of Scientific Research Engineering & Technology (IJSRET) Volume 1 Issue 5 pp165-170 August 2012
4. T. Janevski. "Traffic Analysis and Design of Wireless IP Networks", Artech House Inc., Boston, USA. 2003.
5. Imthiyaz Ali, '5G the Nanocore " March 5, 2011
6. ITU-T. Y2173, ""Managemeiti of performance measurement for NGN", September 200S.
7. Chen, YP: Yang, YH (2007), "A new 4G architecture providing multimode terminals always best connected services, "IEEE Wireless Communications, Volume: 14 Issue: 2 pp. 36-41.
8. Xichun Li, AbudullaGani. RosliSalleh. Omar Zakaria 2009," Tlie Future of Mobile Wireless Communication Networks, "2009 Internationa! Conference on Communication Software and Networks
9. 3GPP TSG RAN TR 36.913 vS.0.0, Requirements for Further Advancements for E-LTRA(LTEAdvanced).
10. Emiolov V. et al. "Significance of Nanotechnology for future wireless devices and Communications",The 18th Annual IEEE International Symposium on PIMRC'07.
11. RK.Jain. Risal Singh, "Role of Nanotechnology in fiiture wireless mid communication systems". National seminar proceeding Academy of Business & Engineering Scietice Ghaziabad, pp-19-28, 16- 17th January 2009.
12. Engr. Muhammad Farooq. Engr. Muhammad Ishtiaq Ahmed, Engr. Usman M Al, "Future Generations of Mobile Communication Networks" Academy7 of Contemporary Research Journal VII (I), 15-21, ISSN:2305-865, January 2013
13. Theodore S. Rappaport, "Wireless Communications Principle and Practice," published by Pearson Education (Singapore) Pte. Ltd,. Second Edition, Chapter Two;
14. Vijay K. Garg and Joseph E. Wilkes, "Principles & Applications of GSM," Published by DoplingKindersley (India) Pvt. Ltd., licensees of Pearson Education in South Asia, First Impression, 2006;
|
62-67
|
|
14.
|
Authors:
|
Rubina Soni, Sarabjit Singh
|
|
Paper Title:
|
FPGA Implementation of Optimized The 64-BIT RC5 & RC6 Cryptography Encryption Algorithm
|
|
Abstract: In today's era there is a great demand for secure communications systems, which in turns demand for real-time implementation of cryptographic algorithms. In this paper we present a hardware implementation of the RC6 & RC5 algorithm using VHDL Hardware Description Language. We also explore the competence of RC6 & RC5 from the hardware implementation perspective with Field Programmable Gate Arrays (FPGAs) as the end technology. FPGAs are highly attractive options for hardware implementations of encryption algorithms as they provide cryptographic algorithm agility, physical security, and potentially much higher performance than software solutions. Our analysis and synthesis studies of the ciphers will suggest that RC5 & RC6 are fast block ciphers, developed by RSA Security, which exploits data rotation to achieve a high level of nonlinearity. 128 bit key and 12 rounds of operation in the design will provide great security to the user’s data. The optimization of area, timing and power is done during physical design process.
Keywords: Cryptographic Algorithms, RC5, RC6,
References:
1. N. Sklavos, C. Machs, and O. Koufopavlou, “Area optimized architecture and VLSI implementation of RC5 encryption algorithm,” in Proc. 10th IEEE International Conference on Electronics, Circuits and Systems, vol. 1. December 2003.2. R.L. Rivest, M.J.B. Robshaw, R. Sidney, and Y.L.Yin, “The RC6 Block Cipher," available at website http://theory.csail.mit.edu/~rivest/rc6.pdf
3. M.Rahman, I.R.Rokon, "Efficient hardware implementation of RSA cryptography", Proc. of International Conference on Anti-counterfeiting, Security, and Identification in Communication, pp.316-319, 2009.
4. H.Rahaman, J.Mathew, A.Jabir, D.K.Pradhan, "Ctestable S-box implementation for secure advanced encryption standard", Proc .of IEEE International On-Line Testing Symposium, pp.210-211, 2009.
5. Olabisi, A. and Elkeelany, O. “Integrated design of RC5 algorithm.” In “The IEEE 39th Southeastern Symposium on System Theory,” , 2007.
6. Nimmagadda, S. and Elkeelany, O. “Performance evaluation of different hardware models of RC5 algorithm.” In “The IEEE 39th Southeastern Symposium on System Theory,”, 2007.
7. “XCV-1000 FPGA Board v. 1.0 User Manual,” Xess Coporation, available at website http://www.xess.com/manuals/xcv-1000-manual- 1_0.pdf. 2005.
8. Abdul Hamid M. Ragab, Nabil A. Ismail, Senior Member IEEE and Osama S. Farag Allah, “Enhancements and Implementation of RC6TM Block Cipher for Data Security”, IEEE Catalogue No. 01 CH37239-0-7803-7101-1/01
9. Asma Belhaj Mohamed, Ghada Zaibi, Abdennaceur Kachouri “IMPLEMENTATION OF RC5 AND RC6 BLOCK CIPHERS ON DIGITAL IMAGES”, 978-1-4577-0411-6/11
|
68-71
|
|
15.
|
Authors:
|
Mohammad Hossein Zaeimbashi Isaabadi, Ehsan Harirchian, Emad Kasra Kermanshahi, Ali Bagheri Fard
|
|
Paper Title:
|
Comparison of Different Project Management Systems in Terms of Project Life Cycle Assessment in The Construction Industry
|
|
Abstract: Assessment means to evaluate how effective a process is. For this, a proper framework has to be developed such that the process can be managed, its products can be measured and areas needing improvements can be identified. Such a framework will have to be developed for all processes that considerably affect the execution of a project. This paper proposes a comparison between Lean management, 5S process, Six-Sigma, Value Management and Value Engineering framework for the Construction project life cycle process in the construction industry, which will assist in assessment and finding improvement opportunities in the application of management system in managing the construction project life cycle.
Keywords: Project management, Construction industry, Project Life Cycle.
References:
1. Abdelhamid, T. S.; “Six Sigma in Lean Construction Systems: Opportunities and Challenges.” Proceedings IGLC-11, Aug. 2003, Blacksburg, Virginia. 2003.
2. Abdul-Kadir, M. R., & Price, A. D. F.; Conceptual phase of construction projects. International Journal of Project Management, 13(6), 387-393. 1995.
3. Banwell, G H the Placing and Management of Contract of Building and Civil Engineering Works HMSO, UK. 1964.
4. Breyfogle, F.W., Cupello, J.M., Meadows, B.; Managing Six Sigma: A Practical Guide to Understanding, Assessing, and Implementing the Strategy That Yields Bottom-Line Success. Wiley, NY. 2001.
5. Chang, S. &Ou, X., Zhang, X.; Scenario analysis of alternative fuel/vehicle for China’s future road transport: Life-cycle energy demand and GHG emissions. Energy Policy, 38 (8), 3943-3956. 2010.
6. Fard, A. B., Rad, K. G., Sabet, P. G. P., & Aadal, H.; Evaluating Effective Factors on Value Engineering Implementation in the Context of Iran. 2013.
7. Hunt, R. G., Franklin, W. E., & Hunt, R. G.; LCA—How it came about. The international journal of life cycle assessment, 1(1), 4-7. 1996.
8. Kobayashi, K., Nouchi, I., & Yoneyama, T. ; Enhanced UV‐B radiation has little effect on growth, δ13C values and pigments of pot‐grown rice (Oryza sativa) in the field. Physiological Plantarum, 96(1), 1-5. 1996.
9. Koskela, L; Application of the new production philosophy to construction (No. 72). Stanford, CA: Stanford University, 1992.
10. Latham, M; ‘Constructing the team’ in Joint Review of Procurement and Contractual Arrangements in the UK Construction Industry; Jul 1994.
11. Male, S., Kelly, J., Gronqvist, M., & Graham, D.; Managing value as a management style for projects.International Journal of Project Management, 25(2), 107-114. 2007.
12. Miles, L. D.; Techniques of value analysis and engineering (Vol. 4). New York: McGraw-hill. 1972
13. Naoum, S.; .Dissertation research and writing for construction students. Routledge. 2007
14. Norman, J., MacLean, H. L., & Kennedy, C. A.; Comparing high and low residential density: life-cycle analysis of energy use and greenhouse gas emissions. Journal of urban planning and development, 132(1), 10-21, 2006.
15. Oglesby, C.H., Parker, H.W. and Howell, G. A.; (Productivity Improvement in Construction, Mc Graw-Hill Inc., New York, N.Y. 1989.
16. Spoor, G., Jones, R. J. & Thomasson, A. J; Vulnerability of subsoils in Europe to compaction: a preliminary analysis. Soil and Tillage Research, 73(1), 131-143, 2003.
17. Zhang, X., Mao, X., &AbouRizk, S. M.; Developing a knowledge management system for improved value engineering practices in the construction industry. Automation in Construction, 18 (6), 777-789, 2009.
|
72-74
|
|
16.
|
Authors:
|
Lois Onyejere Nwobodo, Hyacinth C. Inyiama
|
|
Paper Title:
|
Evaluation of Organizational Intellectual Property Management Decision Structure using Organizational Risk Analyzer (ORA)
|
|
Abstract: The optimal exploitation of intellectual property (IP) as a strategy requires effective IP management structure. Many organizations have developed and implemented Intellectual Property Management System (IPMS). However the issue remains the problem of evaluating the effectiveness of the organizations IP management mechanism. The evaluation enables the benchmarking of the performance of the organizations IP management structure and provides the basis and information for possible re-engineering of such management architecture. The simplicity of the balanced scorecard does not allow it to factor in the complex interaction that exists in the organization which impact on effective IP management. This paper proposes the Organizational Risk Analyzer for the evaluation of the performance of IP management structure. The ORA metrics (ORA measures) is presented to indicate how its evaluation enables the assessment of the efficiency of an organizations IP management decision structure.
Keywords: IPM, decision structure, organization structure, ORA, decision structure evaluation.
References:
1. Karuna Jaint and Varadana Sharma “Intellectual property management system: An organizational perspective” Journal of intellectual property weights vol. 11 Sept. 2006 Pp 330-332.
2. Joe Dury “protecting and managing your intellectual property” View point Calypso 2013, www.kalpso.com.
3. Miresi, Cela, “intellectual property management and strategy in business Mediterranean journal of social sciences MCSER publishing, Roma-Haly, Vol. 4 No. 11 Oct. 2013.
4. Parr, R., and Smith. G. (2005), “Intellectual property: valuation, Exploitation,and infringement Damages, income approach-qualifying the economic benefits, John Wiley and Sons, Inc. Pp. 206.
5. Wurzer, J.A., D; Giammarino P. (2009) IP management: SMEs, smaller IP owners seek better management and relirms:
6. Davis, J., and Harrison, S.(2001) Evison in the boardroom: “How leading Companies realize value from their intellectual assets, John Wiley and sons, New York, pp 1-36.
7. Marschork. J. and Radner, R. Economic theory of Teams. New Haven, Conn: Yoke university press, 1972. 8. The Brigespan Group “Designing an effective organization structure “Jan 2009
9. Peter this “strategic organization design: An integrated approach” Mercer Delta consulting (2000): Interview with peter this, equinox organizational consisting, Bridgespan analysis.
10. Sechneidermom, A. (2006). “The first Balanced Score Card”. Uttp://www.schneidermom.com/concepts/the-first-balance-csorecard/BSC-INTRO-AND-CONTANTS.htm.
11. Edvinsson, L. (1997): Developing intellectual capital at Scandia: Long Range Planning, 30(3): 366-373.
12. Mikael Collan fuzzy or linguistic input scorecard for IPR evaluation “journal of Applied Operational Research (2013) 5(1), 22-29.
13. Ashwork, M. and Kath Lean M. (2003) “Critical Human capital, working paper” Asos Carnefisn Mellon, Pittsburgh PA.
14. Borgath, S.P. (2003) “The key Ployer problem. Dyromic society network modeling and Analysis workshop summary and papers.
15. Brass, D. (1984) “A structural analysis of individual influence in an organization. Admini.sci.Ourat. 26 331-348.
16. Carley, Kathleen M. (2002) “Smart Agents and organization of the future” the Hand book of new media. Edited by Lech Lievroon and Sonia liveigstrme. Ch 12 pp. 206-220.
17. Carley, Change and Learning within organization in Dynamics of organization: computational modeling and organizational themes Edith by Aless and Lomi and Erk R. Lerken, M.T press./AAA 11 press/live Oke, Ch. 1. Pp 63-92.
|
75-80
|
Download Abstract Book