Volume-4 , Issue-7 , Jul - 2016 Go Back

Eye is the most valuable part of our body without the eye sight one cannot feel the beauty of this world. There are a lot of people who aware about the eye donation. In medical area almost everyone know this term and they are already aware and they are also aware the society. But if we are looking at the engineering area then we feel that the number of students and engineers are not very much aware about eye donation. The main cause of blindness is corneal diseases. Blindness can be removed if we have a number of eye donors, for this we have to aware about the eye denotation in each area. We must aware and motivate the people for eye donation by which we can decrease the number of blind persons.

Eye Donation, Weka

[1]. Mohan R K. Eye donation. Accessed from http://www.mohanfoundation. org. Accessed on 7 Dec 2012.
[2]. Ashok Gawali, Rajesh Dase, Kondiram Pawar & Umar Quadri, “Awareness and Knowledge Regarding Eye Donation in Students of Medical Colleges in Aurangabad [MS]”, International Journal of Current Medical And Applied Sciences ,vol.2. Issue: 1, 2014, PP 09-13 E-ISSN:2321-9335,P-ISSN:2321-9327.
[3]. G.Keerthana, Dr. V.Srividhya,” Performance Enhancement of Classifiers using Integration of Clustering and Classification Techniques”, International Journal of Computer Science Engineering, Vol. 3, No.3, 2319-7323, Page 200-203.
[4]. Tawseef Ayoub Shaikh , Amit Chhabra,” Effect of WEKA Filters on the Performance of the NavieBayes Data Mining algorithm on Arrhythmia and Parkinson’s Datasets “,International Journal of Computer Science and Engineering, Vol-2,issue-5, E-ISSN: 2347-2693
[5]. R. Kirkby, “WEKA Explorer User Guide for version 3-3-4”, University of Weikato, 2002.

Krishna Mohan Pandey, Vivek Kumar, "Analysis of Eye Donation Awareness in Engineering Students," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.122-124, 2016.

Face recognition in image processing is a challenging area in the field of computer vision. We recognize images in an efficient way using various techniques. Some of them are principal component analysis, Blurring techniques and Kernel methods. We present framework of these face recognition techniques and literature review is also provided. We apply wavelet transform on blurring techniques which is further trained with principal component analysis to check recognition rate.

Wavelet transform; Blurring techniques; Kernel Methods; PCA; Eigen values

[1] Kwang In Kim, Keechul Jung, and Hang Joon Kim, “Face recognition using kernel principal component analysis”, IEEE signal processing letters, Volume-9, Issue-2,Page No(40-43), February 2002
[2] Ming-Hsuan Yang, “Face Recognition Using Kernel Methods”, IEEE, 2002
[3] S. Thakur, J. K. Sing, D. K. Basu, M. Nasipuri,M. Kundu, “Face recognition using principal component analysis and RBF neural networks”, IJSSST, Volume-10, Issue-5,Page No(7-16).
[4] Masashi Nishiyama, Abdenour Hadid, Hidenori Takeshima, Jamie Shotton, Member, IEEE, Tatsuo Kozakaya, and Osamu Yamaguchi, “Facial deblur inference using subspace analysis for recognition of blurred faces”, IEEE transactions on pattern analysis and machine intelligence, Volume-33, Issue-4, April 2011.
[5] Saurabh P.Bahurupi, D.S.Chaudhari, “Principal component analysis for face recognition”, International Journal of Engineering and Advanced Technology (IJEAT), Volume-1, Issue-5, Page No (91-95), June 2012
[6] Sujata G. Bhele and V. H. Mankar, “A review paper on face recognition techniques”, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), Volume-1, Issue-8, Page No (339-347), October 2012.
[7] Rohina Ansari,Himanshu Yadav,Anurag Jain, “A survey on blurred images with restoration and transformation techniqu0-[]
,m ,.. es”,International Journal of Computer Applications, Volume-68, Issue-22,Page No(29-34), April 2013.
[8] Ritu Upadhayay, Rakesh Kumar Yadav, “Kernel principle component analysis in face recognition system: A Survey”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume-3, Issue-6, Page No(348-354), June 2013.
[9] Ashvini E. Shivdas, “Face recognition using artificial neural network”, International Journal of Research in Management, Science & Technology ,Volume-2, Issue-1,Page No(61-66), April 2014.
[10] Anamika Maurya, Rajinder Tiwari, “A novel method of image restoration by using different types of filtering techniques”, International Journal of Engineering Science and Innovative Technology (IJESIT) Volume-3, Issue-4,
Page No (124-130), July 2014.
[11] Ketki Kalamkar, Prakash Mohod, “A review on face recognition using different techniques”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume-5, Issue-1, Page No(99-103), January 2015.
[12] Farina Parveen Khan,R K Krishna, “Review on image recognition”, International Journal of Engineering Research and General Science Volume-3, Issue-2, Page No(1364-1369), March-April 2015 .
[13] Anchal Garg, Dr. Rohit Bajaj, “Facial expression recognition & classification using hybridization of ICA, GA, and Neural Network for Human-Computer Interaction”, Journal of Network Communications and Emerging Technologies (JNCET),Volume-2, Issue-1, Page No(49-58), May 2015.
[14] Dr. Asmahan M Altaher, “Face recognition techniques-an evaluation study”, Int. J. Advanced Networking and Applications, Volume-6, Issue-4, Page No (2393-2397), 2015.
[15] Suhas S Satonkar, Vaibhav M Pathak, Prakash B Khanale, “Blurred 2D face restoration and recognition using Artificial neural network”, International Journal of Applied Research; Volume-1, Issue-10, Page No(689-693), August 2015.
[16] Prabhjot Singh and Anjana Sharma, “Face recognition using principal component analysis in MATLAB”, International Journal of Scientific Research in Computer Science and Engineering, Volume-3, Issue-1, Page No (1-5), February 2015.
[17] Jian Huang, Pong C. Yuen, Member, IEEE, Wen-Sheng Chen, and Jian Huang Lai,“Choosing parameters of kernel subspace LDA for recognition of face images under pose and illumination variations”, IEEE Transactions on Systems, Man, And Cybernetics—part B: Cybernetics, Volume-37, Issue-4, August 2015.
[18] Dr. Vijayan Asari, “Vision Lab”, www. Face Recognition : University of Dayton,Ohio.com.

Dapinty Saini, Jagriti Sharma, "Image Processing: Review on Face Recognition Approaches," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.125-128, 2016.

The paper present NHPP Software Reliability Growth model involving test effort function(TEF) and fault removal efficiency(TEF). TEF deals with the problem of limited time and resources available during software testing phase. FRE addresses the problem of multiple occurrences of fault before its final removal. In this paper we propose p-TEF models which incorporate both TEF and FRE. p is FRE which represent fraction of faults detected and corrected. If p is less than one, then debugging is imperfect whereas for p equals to one debugging is perfect. Existing TEF models compared with p-TEF models using statistical tools SSE , R2 and AIC. Results suggest that the p-TEF models fits and predict faults detection data better.

Fault removal efficiency, Test Effort Function, NHPP Models, Akaike’s Information Criterion

[1] S. Yamada, H. Ohtera, and H. Narihisa, “Software Reliability Growth Models with Testing-effort”, IEEE Trans. Reliability,1986, R-35,1, pp 19–23.
[2] S. Yamada, J. Hishitani, and S. Osaki, “Software Reliability Growth Model with Weibull Testing Effort: A Model And Application”, IEEE Trans. Reliability,1993, 42, pp 100–105.
[3] P.K. Kapur, and S. Younes, “Modeling an Imperfect Debugging Phenomenon with Testing Effort”, In: Proceedings of 5th International Symposium on Software Reliability Engineering, 1994, pp 178-183.
[4] M. Shepperd, and C. Schofield, “Estimating Software Project Effort using Analogies”, IEEE Trans. Software Engineering,1997, 23, pp 736–743.
[5] C.Y. Huang, S.Y. Kuo, and I.Y. Chen, “Analysis of a Software Reliability Growth Model with Logistic Testing-Effort Function”, In Proceedings of 8th International Symposium on Software Reliability Engineering (ISSRE’1997),1997, pp 378–388.
[6] C.Y. Huang, J.H. Lo, S.Y. Kuo, and M.R. Lyu, “Software Reliability Modeling and Cost Estimation Incorporating Testing-Effort And Efficiency”, In Proceedings of 8th International Symposium on Software Reliability Engineering (ISSRE’1999), 1999, pp 62–72.
[7] C.Y. Huang, and S.Y. Kuo, “Analysis of Incorporating Logistic Testing-Effort Function into Software Reliability Modeling”, IEEE Transactions On Reliability,2002, 51, 3, pp 261-270.
[8] C.Y. Huang, “Performance Analysis Of Software Reliability Growth Models With Testing-Effort And Change Point”, Journal of Systems and Software, 2005 76, pp 181- 194.
[9] M. Kumar, N. Ahmad, and S.M.K. Quadri, S.M.K. “Software Reliability Growth Models and Data Analysis with a Pareto Test-Effort”, RAU Journal of Research, 2005, 15 (1-2), pp 124-128.
[10] N. Ahmad, M.U. Bokhari, S.M.K. Quadri, and M.G.M. Khan, “The Exponentiated Weibull Software Reliability Growth Model with Various Testing-Efforts and Optimal Release Policy: A Performance Analysis”, International Journal of Quality and Reliability Management, 2008, 25 (2), pp 211-235.
[11] N. Ahmad, M.G.M Khan, S.M.K Quadri, and M. Kumar, M. “Modeling And Analysis of Software Reliability With Burr Type X Testing-Effort and Release-Time Determination”, Journal of Modeling in Management, 2009, 4(1), pp 28-54.
[12] N. Ahmad, M.G.M Khan, and L.S. Rafi, “Analysis of an Inflection S-Shaped Software Reliability Model Considering Log-Logistic Testing-Effort and Imperfect Debugging”, International Journal of Computer Science and Network Security,2011, 11, 1, pp 161-171.
[13] A.G. Agarwal, P.K. Kapur, G. Kaur, and R. Kumar, “Genetic Algorithm Based Optimal Testing Effort Allocation Problem for Modular Software”, BIJIT-BVICAM’s International Journal of Information Technology, 2012, 4,1, pp 445-451.
[14] K.V.S Reddy and B. Raveendrababu, “Software Reliability Growth Model with Testing-Effort by Failure Free Software”, International Journal of Engineering and Innovative Technology, 2012, Vol 2, 6, pp 103-107.
[15] D.R. Jeske, X.M. Zhang and L. Pham “Accounting for Realities when Estimating the Field Failure Rate of Software”, In Proceedings of 8th International Symposium on Software Reliability Engineering (ISSRE’01), 2001 pp 332-339.
[16] X.M. Zhang, X.L. Teng and H. Pham, “Considering Fault Removal Efficiency in Software Reliability Assessment”, IEEE Trans. Systems, Man and Cybernetics-Part A: System and Humans, 2003, 33, 1, pp 114-120.
[17] B. Purnaiah, K.V. Rama and V.K.G. Bala, “Fault Removal
Efficiency in Software Reliability Growth Model”, Advances in Computational Research, 2012 4, 1, pp 74-77.
[18] Musa. “DACS software reliability dataset”, Data & Analysis Center for Software, J.D. 980. www.dacs.dtic.mil/databases/sled/swrel.shtml.

Suneet Saxena, Ajay Gupta, "Estimation of Software Reliability Using p – TEF Models," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.129-132, 2016.

The advent of Wireless Sensor Networks (WSN) has given a new directions to agriculture research and farm trading. Currently every day WSN has wide use in agriculture sector. In this paper, we have tendency to review the potential WSN application that specifies the problems and necessary requirements for drip irrigation for the optimum utilization of the available water. We have tendency to gift works that is associated to use WSN in agriculture correctness and production management. In this regard, various methods of WSN deployment and implantations are surveyed. So we tried to highlight the challenges and problems of these solutions, while identifying the factor for improving the intelligent drip irrigation system.

Drip Irrigation System, Precision Farming,Wireless Sensor Network

[1] Shiv Sutar, Swapnita-Jayesh, and Komal-Priyanka, “Irrigation and Fertilizer control for Precision Agriculture using WSN: Energy Efficient Approach”, International Journal of Advances in Computing and Information Researches1(1): 2012
[2] Awati J. S., Patil V. S., “Automatic Irrigation Control by using wireless sensor networks”, Journal of Exclusive Management Science - 1 (6), 2012
[3] Snyder, R. L., Melo-Abreu, J. P., “Forest protection: fundamentals, practice, and economics” (PDF). Food and Agriculture Organization of the United Nations. ISSN 1684-8241, 2005.
[4] Williams, J. F.; S. R. Roberts; J. E. Hill; S. C. Scardaci; G. Tibbits. "Managing Water for 'Weed' Control in Rice". UC Davis, Department of Plant Sciences. Retrieved 2007-03-14.
[5] "Aridpoop -05-15". Retrieved 2012-06-19.
[6] Mader, Shelli "Center pivot irrigation revolutionizes agriculture". The Fence Post Magazine. Retrieved June 6, 2012.
[7] Provenzano, Giuseppe, “Using HYDRUS-2D Simulation Model to Evaluate Wetted Soil Volume in Subsurface Drip Irrigation Systems”. J. Irrig. Drain Eng. 133 (4): 342–350, 2007.
[8] Tamoghna Ojha, Sudip Mishra and Narendra Singh Raghuwanshi, “Wireless Sensor Network for Agriculture: State–of-art in Practice and Future Challenges”, Computers and Electronics in Agriculture (Elsevier) 118:66-84, 2015
[9] Javier Sanchez-Llerena, Antonio Lopez-Pineiro, Angel Albarran and David Pena, “ Short and Long term effects of different Irrigation and tillage Systems on Soil Properties and Rice productivity under Mediterranean” , European Journal of Agronomy (Elsevier), 77: 101-110, 2016
[10] H. Navarro-Hellin, J. Martinez-del-Rincon, R. Domingo-Miguel, F. Soto-Valles and R. Torres-Sanchez, “ A Decision Support System for Managing irrigation in Agricluture”, Computer and electronics in Agriculture(Elsevier), 124: 121-131, 2016
[11] Jose Polo, Gemma Hornero, Coen Duijneveld, Alberto Garcia and Oscar Casas, “Design of Low cost ireless Sensor Network with UAV mobile node for Agriculture Applications” , Computer and electronics in Agriculture (Elsevier), 119: 19-32, 2015
[12] Guodong Sun, Tao Hu, Gaoxiang Yang and JianboJia, “ Real Time and Clock-shared Rainfall Monitoring with a Wireless Sensor Network”, Computer and electronics in Agriculture (Elsevier), 119: 1-11, 2015
[13] YD Kim, YM Yang, WS Kang, DK Kim, “On the design of beacon based wireless sensor network for agricultural emergency monitoring systems”, Computer standards & interfaces 36 (2):288-299, 2014
[14] Zhen Li, “Practical deployment of an infield soil property wireless sensor network”, Information Sciences 57(11): 1-24 , 2014
[15] Aqeel-ur-Rehman, “A review of wireless sensors and networks' applications in agriculture”, International Journal of Distributed Sensor Networks 2, 2014
[16] B.Majonea, “Wireless Sensor Network deployment for monitoring soil moisture dynamics at the field scale”, Procedia Environmental Sciences (Elsevier)19:426 – 435, 2013
[17] Xin Dong, “Autonomous precision agriculture through integration of wireless underground sensor networks with center pivot irrigation systems”, Ad Hoc Networks 11(7):1975-1987, 2013
[18] Xiaoqing Yu, “A survey on wireless sensor network infrastructure for agriculture”, Computer Standards & Interfaces35(1):59–64, 2013 
[19] Robert W. Coates, “Wireless sensor network with irrigation valve control”, Computers and Electronics in Agriculture (Elsevier) 96:13–22, 2013
[20] Yingli Zhua, “Applications of wireless sensor network in the agriculture environment monitoring”, Procedia Engineering (Elsevier) 12(16):608–614, 2011
[21] Zhao Liqiang, “A Crop Monitoring System Based on Wireless Sensor Network”, Procedia Environmental Sciences (Elsevier) 12(11):558–565, 2011
[22] Soledad Escolar Daz, “A novel methodology for the monitoring of the agricultural production process based on wireless sensor networks”, Computers and Electronics in Agriculture (Elsevier) 76(2): 252-265, 2011

Manish B. Giri, Ravi Singh Pippal, "Agricultural Environmental Sensing Application Using Wireless Sensor Network for Automated Drip Irrigation," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.133-137, 2016.

Develop a proper method in multimedia data management is important to support multimedia application’s domain. Multimedia is defined as the combination of more than one media; they may be of two types - static and dynamic media. Text, graphics, and images are categorized as static media; on the other hand, objects like- animation, music, audio, speech, video are categorized as dynamic media. To manage this multimedia database management system is essential. Multimedia database management system can be defined as software system that manages a collection of multimedia data. Generally, multimedia database contains text, image, animation, video, audio, movie sound etc. But, all data are stored in the database in binary form. The paper presents the effective framework for the multimedia database management in terms of B-tree indexing. The framework is to ensure that the process of data manipulation, store, in a distributed environment can be conducted in an efficient manner.

Multimedia database, Multimedia Metadata, Multimedia database management and Indexing

[1] Bhavani Thuraisingham, “Managing and Mining multimedia Database”,International Journals on Artificial Intelligence Tools,Vol.13,No.3,739-759,20 March 2004.
[2] Samir Kumar Jalal, “Multimedia Database: Content and Structure”, Workshop on Multimedia and Internet Technologies 26th to 28th February, 2001.
[3] Siddu P. Algur1, Basavaraj A. Goudannavar2*, Prashant Bhat3, “Metadata Based Approach for Web Multimedia Model”, International Journal of Computer Science Trends and Technology (IJCST) – 4(10): October, 2015, ISSN: 2277-9655
[4] YANG Changchun, YI Li, “A Data Mining Model and Methods Based on Multimedia Database”, 978-1-4244-5143-2/10/$26.00 ©2010 IEEE.
[5] S´ebastien Laborie, Ana-Maria Manzat and Florence Sedes, “Managing and querying efficiently distributed semantic multimedia metadata collections”, Digital Object Identifier 10.1109/MMUL.2009.68 1070-986X/$26.00 © 2009 IEEE
[6] Farham Mohamed, M Nordin A Rahman, Yuzarimi M Lazim and Saiful Bahri Mohamed, “Managing Multimedia Data: A Temporal-Based Approach”, International Journal of Multimedia and Ubiquitous Engineering Vol. 7, No. 4, October, 2012.
[7] Cristina Ribeiro, Gabriel David, “A Metadata Model for Multimedia Databases”, International Journal of Multimedia and Ubiquitous Engineering Vol. 7, No. 4, October, 2012.
[8] Siddu P. Algur1, Basavaraj A. Goudannavar2*,“Web Multimedia Mining: Metadata Based Classification and Analysis of Web Multimedia”, International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE) November-2015, pp. 324-330 ISSN: 2277-128X
[9] E. Chavez, J.Marroquin, and G. Navarro, “Overcoming the curse of dimensionality”, in Proc. European Workshop on Content-Based Multimedia Indexing (CBMI), 1999, pp. 57-64.
[10] Database Management System And Security Chapter – 2, http://shodhganga.inflibnet.ac.in/bitstream/10603/24846/3/ch.%202%20dbms%20and%20security.pdf
[11] Bhavani Thuraisingham, “Security and privacy for multimedia database management systems”, Multimed Tools Appl (2007) 33:13–29, Springer Science + Business Media, LLC 2007.
[12] Dr.S.Vijayarani and Ms. A. Sakila, “Multimedia Mining Research – An Overview Metadata Model for Multimedia Databases”, International Journal of Computer Graphics and Animation (IJCGA) Vol. 5, No. 1, January, 2015.
[13] D Jyothsna R. Nayak and Diane J. Cook, “Approximate Association Rule Mining”, From: FLAIRS-01 Proceedings 2001, AAAI (www.aaai.org).
[14] S Xinchen, MihaelaVorvoreanu, and Krishna Madhvan, “Mining Social Media Data for Understanding Students’ Learning Experiences”, IEEE computer society.1939-1382(c)2013 IEEE.

Siddu P. Algur, Basavaraj A. Goudannavar, "Managing and Mining Web Multimedia – B-Tree Indexing Approach," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.138-147, 2016.

A heat exchanger is one of the key components in air-conditioning and refrigeration systems. Condensers and evaporators are typically heat exchangers which are used to condense vapors into liquid and evaporate liquid into vapor respectively also known as phase transition. To obtain the dynamic performance of the heat exchanger system, simulation in transient state is required. For prediction of such performance a homogeneous vapor liquid two phase flow model is used. To obtain the solution of the model science of the computations need to be used efficiently. In the present paper an efficient computational model and method are proposed. The method is capable of predicting the refrigerant temperature distribution, velocity of refrigerant, tube wall temperature as a function of position and time. A single tube heat exchanger with refrigerant R22 as working fluid was chosen as a sample and some tests were carried out to determine its transient response. The examination of results indicates that the computational model provides a reasonable prediction of dynamic response.

Vapor liquid two phase flow Homogeneous Model, set of nonlinear equations, finite difference method, and MATLAB program

[1] G. F. Hewitt, Hemisphere Handbook of Heat Exchanger Design. Hemisphere Publishing Corporation, New York (1990).
[2] Wang H. & Touber S., 1991, “Distributed and non-steady-state modelling of an air cooler”, International Journal of Refrigeration, Vol. 12.
[3] Notes on Fundamentals of Multiphase flow, Prof. Michael L. Corradini, Department of Engineering Physics, University of Wisconsin, Madison WI 53706.
[4] Bird, R.B., Stewart, W.E., and Lightfoot, E.N., Transport Phenomena, John Wiley and Sons, 2nd edition, New York, NY, 2002.
[5] M. Turaga, S. Lin and P. P. Fazio, Performance of direct expansion plate finned tube coils for air cooling and dehumidifying coils. Int. J. Refrig. 11, 78-86 (1988).
[6] J. C. Chen, A correlation for boiling heat transfer to boiling fluids in convective flow. ASME Paper 63-34 11, 78-86 (1963).
[7] W. Roetzel, Y. Xuan, Dynamic Behaviour of Heat Exchangers, Computational Mechanics Publications, WIT Press, 1999.
[8] H. P. Williams, P. F. Brian, A. T. Saul and T. V. Williams, Numerical Recipes--The Art of Scientific Computing. Cambridge University Press, Cambridge (1986).
[9] Palen, J.W., Breber, G., Taborek, J., 1979. Prediction of flow regimes in horizontal tube side condensation. Heat Transfer Eng. 1, 47–57.
[10] Dobson M.K. and Chato J.C., 1998, “Condensation in Smooth Horizontal Tubes”, ASME Journal of Heat Transfer, Vol.120, No.1, pp.193-213.
[11] Xia J., Zhou X., Jin X. & Zhou Z, 1999, “Dynamic simulation of superheat at the evaporator outlet of the air conditioner with inverter”, Proc. 20th International Congress of Refrigeration, Sydney, Paper No. 561.
[12] J.L. Xu, P. Cheng, T.S. Zhao, Gas liquid two-phase flow regimes in rectangular channels with mini/micro gaps, International Journal of Multiphase Flow 25 (1999) 411-432.

Sandeep Malhotra, "Computational Science of Vapor Liquid Two Phase Flow Inside Heat Exchanger Tube," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.148-153, 2016.

Image Processing and Analysis can be defined as the act of examining images for the purpose of identifying objects and judging their significance. In current days, image processing techniques are widely used in many medical areas for improving earlier detection and treatment stages. The microscopic images of the blood cells are observed to find out many diseases. Changes in the blood condition show the development of diseases in an individual. Leukemia can lead to death if it is left untreated. Leukemia is detected only by analyzing the white blood cells. So our study is focused only on the white blood cells (WBCs). In a manual method of Leukemia detection, experts check the microscopic images. This is lengthy and time taking process which depends on the person’s skill and not having a standard accuracy. In this paper we are focusing, automated approach of leukemia detection. The automated Leukemia detection system analyses the microscopic image it extracts the required parts of the images and applies some filtering techniques. K-means clustering approach is used for white blood cells detection.

Segmentation, filtering techniques, K-Means clustering algorithm

[1] Kisung Lee, Anna V. Danilina, Matti Kinnunen, Alexander V. Priezzhev, And Igor Meglinski, Senior Member, IEEE- Probing The Red Blood Cells Aggregating Force With Optical Tweezers, IEEE Journal Of Selected Topics In Quantum Electronics, Vol. 22, No. 3, May/June 2016
[2] Shuang Qiu, Nai J. Ge, Dong K. Sun, Sheng Zhao, Jian F. Sun∗, Zhao B. Guo, Ke Hu, And Ning Gu- Synthesis And Characterization Of Magnetic Polyvinyl Alcohol (Pva) Hydrogel Microspheres For The Embolization Of Blood Vessel, IEEE Transactions On Biomedical Engineering, Vol. 63, No. 4, April 2016
[3] Acharya, Student Member, IEEE, Sriparna Saha, Member, IEEE, And Yamini Thadisina- Multiobjective Simulated Annealing-Based Clustering Of Tissue Samples For Cancer Diagnosis,IEEE Journal Of Biomedical And Health Informatics,Vol.20.No.2.March2016
[4] Kisung Lee, Anna V. Danilina, Matti Kinnunen, Alexander V. Priezzhev, And Igor Meglinski, Senior Member, IEEE- Probing The Red Blood Cells Aggregating Force With the Optical Tweezers, IEEE Journal Of Selected Topics In Quantumelectronics,Vol.22.No.3, May/June2016
[5] Patiwet Wuttisarnwattana, Madhusudhana Gargesha, Wouter Van't Hof, Kenneth R. Cooke, And David L. Wilson*― Automatic Stem Cell Detection In Microscopic Whole Mouse Cryo-Imaging, IEEE Transactions On Medical Imaging, Vol.35.No.3,March2016
[6] Eluru, Rajesh Srinivasan, And Sai Siva Gorthi- Deformability Measurement Of Single-Cells At High-Throughput With Imaging Flow Cytometry, Journal Of Lightwave Technology, Vol. 33, No. 16, August 15, 2015
[7] Manuel Gonzalez´-Hidalgo, F. A. Guerrero-Pena,˜ S. Herold-Garc´Ia, Antoni Jaume-I-Capo,´ And P. D. Marrero-Fernandez´- Red Blood Cell Cluster Separation From Digital Images For Use In Sickle Cell Disease, IEEE Journal Of Biomedical And Health Informatics, Vol. 19, No. 4, July 2015
[8] Chih-Chung Chen, Yu-An Chen, And Da-Jeng Yao* Centrifugal Filter Device For Detection Of Rare Cells With Immuno-Binding, IEEE Transactions On Nanobioscience, Vol. 14, No. 8, December 2015
[9] Agaian S., Madhukar M., And Chronopoulos A.T. ―Automated Screening System For Acute Myelogenous Leukemia Detection In Blood Microscopic Images‖, IEEE Systems Journal, 2014, Vol. 8, No. 3.
[10] Chun-Li Chang, Shadia I. Jalal, Wanfeng Huang, Aamer Mahmood, Member, IEEE, Daniela E. Matei, And Cagri A. Savran, High-Throughput Immunomagnetic Cell Detection Using A Microaperture Chip System, IEEE Sensors Journal, Vol. 14, No. 9, September 2014
[11] S.Agaian, M. Madhukar And A. Chronopoulos“Automated Screening System For Acute Myelogenous Leukemia Detection In Blood Microscopic Images,” In Proc. IEEE Journal, 2014.
[12] C. Lopez And S. Agaian, ―Iterative Local Color Normalization Using Fuzzy Image Clustering,‖ In Proc. Spie, Mobile Multim./Image Process., Security, Appl., 2013, Vol. 8755, Pp. 87
[13] Dong Ping Tian, “A Review On Image Feature Extraction And Representation Techniques,”In International Journal Of Multimedia And Ubiquitous Engineering,Vol. 8, No. 4, July, 2013,Pp.385-396
[14] Ms. Minal D. Joshi And Prof. A.H.Karode , “Detection Of Acute Leukemia Using White Blood Cells Segmentation Based On Blood Samples”, Ijecet Volume 4, May June, 2013
[15] D. Mandal, K. Panetta, And S. Agaian, ―Face Recognition Based On Logarithmic Local Binary Patterns,‖ In Proc. Spie, Image Process., Algorithmssyst. Xi, 2013, Vol. 8655, Pp.14-12.
[16] Leyza Baldo Dorini, Rodrigo Minetto, And Neucimar Jeronimoˆ Leite- Semiautomatic White Blood Cell Segmentation Based On Multiscale Analysis, IEEE Journal Of Biomedical And Health Informatics, Vol. 17, No. 1, January 2013
[17] Halim Nha, Mashor My, Hassan R. Automatic Blasts Counting For Acute Leukemia Based On Blood Samples. Int J Res Rev Comput Sci 2011;2(August(4)).
[18] Madhloom Ht, Kareem Sa, Ariffin H, Zaidan Aa, Alanazi Ho, Zaidan Bb. Anautomated White Blood Cell Nucleus Localization And Segmentation Using Imagearithmetic And Automated Threshold. J Appl Sci 2010;10(11):959–66.
[19] Guieb, E. C., And Samaneigo. J. M.-Image Noise Reduction Using Cellular Automata. Cmsc 190 Special Problem, Institute Of Computer Science.2007
[20] N. T. Umpon. Patch based white blood cell nucleus segmentation using fuzzy clustering. ECTI Transaction Electrical Electronics Communications, 3(1):5–10, 2005.

Kayathri K, Kumar Parasuraman and Arumuga Maria Devi, "Acute Mylogenous Leukemia Detection in Blood Microscopic Images," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.154-160, 2016.

The requirement for development of CBIR is enhanced as a result of giant progress in volume of snap shots as good as the preferred software in a more than one fields.spatial layout, shape, colour, and texture are the special qualities to represent by the table of contents images. These peculiar points by snap shots are extracted and applied for a similarity assess among graphics.. The paper offers a overview on various approaches of content based photo retrieval (CBIR). CBIR is a process throught which different images are retrieved by a giant database collection. These databases are prepared using various visual features Like. spatial layout, shape, colour, and texture that are extracted making use of different techniques. As image database volume is increasing rapidly, researchers are looking to a better mechanism to retrieve images and to obtain more accurate results.

Color,feature,txture,shape,CBIR

[1]. Kamlesh Kumar, Zain-ul-abidin, Jian-Ping Li and Riaz Ahmed Shaikh, “ Content Based Image Retrieval Using Gray Scale Weighted Average Method” Vol. 7, No. 1,IJACSA 1 January 2016
[2]. Manoharan Subramanian, and Sathappan Sathappan, “An Efficient Content Based Image Retrieval using Advanced Filter Approaches” Vol. 12, No. 3, May 2015
[3]. Gurmeet Kaur and Er. Arshdeep Singh “A Review Paper on Content Based Image Retrieval” Kaur et al., International Journal of Advanced Research in Computer Science and Software Engineering 5(4), pp. 1404-1406, April- 2015,
[4]. Ekta Gupta and Rajendra Singh Kushwah, “ Combination of Local, Global and k-mean using Wavelet Transform for Content Base Image Retrieval” International Volume 116 – No. 14, April 2015
[5]. Nishu and Navdeep Kaur, “A Literature Survey of Facial Recognition of Identical Twins” Vol. 4, Issue 3, March 2015
[6]. Mohammed Alkhawlani and Mohammed Elmogy, “ Text-based, Content-based, and Semantic-based Image Retrievals: A Survey” Volume 04 – Issue 01, January 2015
[7]. Kavita Chauhan and Shanu Sharma, “A Review on Feature Extraction Techniques for CBIR System” Accepted 31- July - 2015 Article ID ICIEMS018 eAID ICIEMS.2015.018 Received 10 - July - 2015
[8]. L. Haldurai, V. Vinodhini, “A Study on Content Based Image Retrieval Systems” International Journal of Innovative Research in Computer and Communication Engineering -2015.
[9]. Ekta Gupta and Rajendra Singh Kushwah’’Combination of Local, Global and k-mean using Wavelet Transform for Content Base Image Retrieval’’ International Journal of Computer Applications (0975 – 8887) Volume 116 – No. 14, April 2015
[10]. Aditi Giri and Yogesh Kumar Meena, “content based image retrieval using integration of color and texture features” (IJARCET) l 2014.
[11]. Aditi Giri and Yogesh Kumar Meena “Content based image retrieval using integration of color and texture features” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 3 Issue 4, April 2014.
[12]. Vijaylakshmi Sajwan” Content Based Image Retrieval Using Combined Features (Color and Texture)” Volume No.3, Issue No.4, pp : 271-273 Volume No.3, Issue No.4, pp : 271-273 01 , April 2014.
[13]. Yogita Mistry and Dr.D.T. Ingole, “Survey on Content Based Image Retrieval Systems”. International Journal of Innovative Research in Computer and Communication Engineering 2013
[14]. Ms. K. Arthi and Mr. J. Vijayaraghavan, “Content Based Image Retrieval Algorithm Using Colour Models” International Journal of Advanced Research in Computer and Communication Engineering 2013
[15]. S.Meenachi Sundaresan, Dr. K.G.Srinivasagan, “Design of Image Retrieval Efficacy System Based on CBIR”., , IJARCSSE 2013
[16].
[17]. R.Malini1andC.Vasanthanayaki “An Enhanced Content Based Image Retrieval System using Color Features” Volume 2 Issue 12 Dec,2013.
[18]. Reshma Chaudhari and A. M. Patil, “Content Based Image Retrieval Using Color and Shape Features”
[19]. . IJAREEIE-2012
[20]. Suchismita Das, Shruti Garg and G. Sahoo “Comparison of Content Based Image Retrieval Systems Using Wavelet and Curvelet Transform” The International Journal of Multimedia & Its Applications (IJMA) Vol.4, No.4, August 2012.
[21]. S. Mangijao Singh and K. Hemachandran “Content-Based Image Retrieval using Color Moment and Gabor Texture Feature” IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 5, No 1, September 2012.
[22]. Reshma Chaudhari and A. M. Patil” Content Based Image Retrieval Using Color and Shape Features” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 1, Issue 5, November 2012.
[23]. Bansal M., Gurpreet K., and Maninder K., “Content-Based Image Retrieval Based on Color,” International Journal of Computer Science and Technology, vol. 3, no. 1, pp. 295-297, 2012.
[24]. Wasim Khan, Shiv Kumar. Neetesh Gupta and Nilofar Khan, “A Proposed Method for Image Retrieval using Histogram values and Texture Descriptor Analysis”. , ,IJSCE 2011
[25]. Gulfishan Firdose Ahmed and Raju Barskar” A Study on Different Image Retrieval Techniques in Image Processing” International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-1, Issue-4, September 2011.
[26]. Mrs Monika Jain and Dr. S.K.Singh “A Survey On: Content Based Image Retrieval Systems Using Clustering Techniques For Large Data sets” International Journal of Managing Information Technology (IJMIT) Vol.3, No.4, November 2011.

Dharmendra Pandey and Shivpratap kushwah, "A Review on CBIR with its Advantages and Disadvantages For Low-level Features," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.161-167, 2016.

Digital media, like video, audio, images and multimedia documents can be protected against copyright infringements with imperceptible, incorporated patterns. Such methods are based on steganography and digital watermarking techniques. Digital watermarking technology can provide persistent identification of copyrighted subject matter to facilitate rights management in the emerging complex hybrid digital/analog devices and home networks. For both analog and digital content, digital watermarks enable copyright holders to protect their content from unauthorized use, as well as enable content owners to effectively communicate their copyrights, monitor use of their content, and track unauthorized distribution of licensed content. Most watermarks are inserted as a plain-bit or adjusted digital signal using a key-based embedding algorithm. The embedded information is hidden and linked inseparably with the source data structure. For the most favourable watermarking application, a trade-off between opposing criteria like robustness, non-perceptibility, non-detectability and protection include to be ended. Most watermarking algorithms are not resistant in opposition to all attacks, and even gracious attacks like file and data modifications can demolish the watermark very easily.

Singular value decomposition, Fals positive problem, Digital Watermarking.

[1]. A. Adhipathi Reddy *, B.N. Chatterji, “A new wavelet based logo-watermarking scheme,” Pattern Recognition Letters 26., ,pp. 1019-1027, 2005.
[2]. Ahmad A. Mohammad_, Ali Alhaj, Sameer Shaltaf, “An improved SVD-based watermarking scheme for protecting rightful ownership,” Signal Processing 88., pp. 2158-2180, 2008.
[3]. Barni M, Bartolini F, Piva A ,”Improved wavelet based image watermarking through pixel wiseMasking,”IEEE Trans Image Process 10(5):pp.783–79, 2001.
[4]. B.Chandra Mohan, S.Srinivaskumar$, B.N.Chatterji* ,”A Robust Digital Image Watermarking Scheme using Singular Value Decomposition (SVD), Dither Quantization and Edge Detection,” ICGST-GVIP Journal, ISSN: pp.1687-398X , Volume 8, Issue 1, 2008.
[5]. Chandra D ,”Digital image watermarking using singular value decomposition,” In: Proceedings of the IEEE 45th Midwest Symposium on Circuits and Systems., Oklahoma State University, USA, Vol. 3, pp. 264–267, 2002.
[6]. Chih-Chin Lai ,”A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm,” Digital Signal Processing 21.,pp. 522-527, 2011
[7]. Chih-Chin Lai, and Cheng-Chih Tsai ,”Digital Image Watermarking Using Discrete Wavelet Transform and Singular Value Decomposition,” IEEE transactions on instrument and measurement, vol. 59, no. 11, pp. 0018-9456, 2010
[8]. Chirag Jain1, Siddharth Arora1, and Prasanta K. Panigrahi1,2 ,”A Reliable SVD based Watermarking Scheme,” Preprint submitted to Elsevier, 3, 2008.
[9]. Cox I, Miller ML, Bloom JA,” Digital watermarking. Morgan Kaufmann,” 2001.
[10]. Djurovic I, Stankovic S, Pitas I ,”Digital watermarking in the fractional Fourier transformation Domain,” J Netw Comput Appl 24(4):pp. 167–173, 2001
[11]. Ehsan Vahedi , Reza Aghaeizadeh Zoroofi, Mohsen Shiva,” Toward a new wavelet-based watermarking approach for color images using bio-inspired optimization principles,”Digital Signal Processing 22 , 2012
[12]. Emir & Ahmet ,”Robust DWT-SVD Domain Image Watermarking: Embedding Data in All Frequencies,”Department of Computer and Information Science, 2004
[13]. Franco Del Colle and Juan Carlos G´omez ,”A new DWT-SVD based perceptual fidelity metric for quality assessment of watermarking schemes,” European signal processing conference, 2010
[14]. Ganic E, Eskicioglu AM ,”Robust embedding of visual watermarks using DWT-SVD,” J Electron Imaging 14(4):043004, 2005
[15]. Gaurav Bhatnagar • Balasubramanian Raman ,”A new robust reference logo watermarking scheme,” Multimed Tools Appl, 2011
[16]. Gaurav Bhatnagar a, Q.M. Jonathan Wua, Balasubramanian Raman b ,”Robust gray-scale logo watermarking in wavelet domain,” Computers and Electrical Engineering, 2012
[17]. Gaurav Bhatnagar, Balasubramanian Raman 1 ,”A new robust reference watermarking scheme based on DWT-SVD,”Computer Standards & Interfaces xxx, 2009
[18]. Hsu, C.-T., Wu, J.-L., "Multiresolution Watermarking for Digital Images", in IEEE Transactions on Circuits and Systems - II: Analo and Digital Signal Processing, vol. 45, no. 8, pp. 1097-1101, August 1998
[19]. Jiang-Lung Liu, Der-Chyuan Lou *, Ming-Chang Chang, Hao-Kuan Tso ,”A robust watermarking scheme using self-reference image,” Computer Standards & Interfaces 28 , 2006.
[20]. Jianhua Songa*, Jianwei Songb ,Yuhua Baob ,”A Blind Digital Watermark Method Based on SVD and Chaos,” International Workshop on Information and Electronics Engineering, 2012.
[21]. Jinhua Liu •Kun She ,”A Hybrid Approach of DWT and DCT for Rational Dither Modulation Watermarking,” Springer Science Business Media, LLC, 2011.
[22]. Jih Pin Yeh, Che-Wei Lu, Hwei-Jen Lin, and Hung-Hsuan Wu ,”Watermarking technique based on DWT associated with embedding rule,” International journal of circuits systems and signal processing Issue 2, Volume4, 2010.
[23]. J.L. Liu, D.C. Lou, M.C. Chang, H.K. Tso, “A robust watermarking scheme using self reference image,” Computer Standards and Interfaces 28, pp.356–367, 2006.
[24]. Kaewkamnerd, N., Rao, K.R., "Wavelet based image adaptive watermarking scheme" in IEEE Electronics Letters, vol.36, pp.3 12-313, 17 Feb.2000
[25]. Kundur. D., Hatzinakos, D., "Digital Watermarking using Multiresolution Wavelet Decomposition", Proc. IEEE Int. Conf. On Acoustics, Speech and Signal Processing, Seattle, Washington, vol. 5, pp. 2969-2972, May 1998.
[26]. Lin W-H, Horng S-J, Kao T-W, Chen R-J, Chen Y-H, Lee C-L, Terano T,” Image copyright protection with forward error correction,” Expert Syst Appl (SCI 1/64, 2596) 36(9):pp. 11888–11894, 2009.
[27]. Lin W-H, Wang Y-R, Horng S-J,” A wavelet-tree-based watermarking method using distance vector of binary cluster,” Expert Syst Appl (SCI 1/64, 2596) 36(6):pp. 9869–9878, 2009.
[28]. Lin W-H, Wang Y-R, Horng S-J, Pan Y ,” A blind watermarking method using maximum wavelet coefficient quantization,” Expert Syst Appl (SCI 1/64, 2596) 36(9):11509–11516, 2009.
[29]. LinWH, Horng SJ, Kao T, FanWP, Lee CL, PanY ,”An efficient watermarking method based on significant difference of wavelet coefficient quantization,” IEEE Trans Multimed (SCI 12/86, 2288) 10(5):pp. 746–757, 2008.
[30]. Lu, C-S., Liao, H-Y., M., Huang, S-K., Sze, C-J., "Cocktail Watermarking on Images", 3rd International Workshop on Information Hiding, Dresden, Germany, Sep 29-Oct. 1, 1999
[31]. Mohammad AA, Alhaj A, Sameer S ,”An improved SVD-based watermarking scheme for protecting rightful ownership,” Sig Process 88:2158–2180, 2008.
[32]. Mohammad-Reza Keyvanpour*a, Farnoosh Merrikh-Bayatb,” Robust Dynamic Block-Based Image Watermarking in DWT,”Domain Procedia Computer Science 3, 2011
[33]. Paul Bao and Xiaohu Ma,” Image Adaptive Watermarking Using Wavelet Domain Singular Value Decomposition,” IEEE transactions on circuits and systems for video technology , VOL. 15, NO. 1, January, 2005
[34]. Prayoth Kumsawat, Kitti Attakitmongcol, Member, IEEE, and Arthit Srikaew,” A New Approach for Optimization in Image Watermarking by Using Genetic Algorithms,”IEEE transactions on signal Processing,VOL. 53, NO. 12, 2005.
[35]. Punit Pandey,Shishir Kumar,Satish K Singh,”Rightful ownership through image adaptive DWT-SVD watermarking algorithm and perceptual tweaking,” http://link.springer.com/article/10.1007/s11042-013-1375-2# , 2013
[36]. Qiang Li, Chun Yuan,Yu-Zhuo Zhong,”Adaptive DWT-SVD Domain Image Watermarking Using Human Visual Model,” ICACT, 2007
[37]. Rashmi Agarwal, M.S. Santhanam1 ,” Digital watermarking in the singular vector domain,” Preprint submitted to Elsevier Science, 2008.
[38]. Raval, M.S., Rege, P.P., "Discrete wavelet transforrn based multiple watermarking scheme", Conference on Convergent Technologies for sia-Pacific Region, TENCON , vol. 3, pp. 935 - 938, 15- 17,Oct. 2003
[39]. Ray-Shine Run a,b, Shi-Jinn Horng a, Jui-Lin Lai b, Tzong-Wang Kao c, Rong-Jian Chen b,” An improved SVD-based watermarking technique for copyright protection,” Expert Systems with Applications 39, 2012.
[40]. R.Dhanalakshmi K.Thaiyalnayaki,” Dual Watermarking Scheme with Encryption,” (IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, No. 1, 2010.
[41]. R. Liu, T. Tan ,” An SVD-based watermarking scheme for protecting rightful ownership,” IEEE Transactions on Multimedia, vol. 4, no.1, pp.121–128, 2002.
[42]. Rosiyadi D, Horng S-J, Fan P, Wang X, Khan MK, Yi P ,” An efficient copyright protection scheme for e-government document image,” IEEE Multimed 19(3):pp. 62–73, 2012.
[43]. S. Joo, Y. Suh, J. Shin, H. Kitkuchi,” A new robust watermarking embedding in to wavelet DC Components,” ETRI Journal 24 (5) 401–404, 2002.
[44]. Sonika Bansal, Punit pandey,” On the security of robust reference logo watermarking scheme in fractional fourier tranform domain,” International Conference on Information system and computer networks (IEEE), 2013.
[45]. S.Ramakrishnan1, T.Gopalakrishnan2, K.Balasamy3,” A wavelet based hybrid SVD algorithm for digital image watermarking,”Signal & Image Processing: An International Journal (SIPIJ) Vol.2, No.3,2011
[46]. Tao, P & Eskicioglu, AM 2004, 'A Robust Multiple Watermarking Scheme in the Discrete Wavelet Transform Domain', in Symposium on Internet Multimedia Management Systems V, Philadelphia, PA.
[47]. Vidyasagar M. Potdar, Song Han, Elizabeth Chang ,”A Survey of Digital Image Watermarking Techniques,” 3rd IEEE International Conference on Industrial Informatics (INDIN), 2005.
[48]. Vivekananda Bhat K , Indranil Sengupta, Abhijit Das,” An adaptive audio watermarking based on the singular value decomposition in the wavelet domain,” Digital Signal Processing 20,2010
[49]. Xiaojun Qi, Stephen Bialkowski, and Gary Brimley,”An adaptive QIM and SVD based digital image watermarking scheme in the wavelet domain,” IEEE , 2008.
[50]. Xiao-Ping Zhang, Senior Member, IEEE, and Kan Li , Comments on “An SVD-Based Watermarking Scheme for Protecting Rightful Ownership,” IEEE transactions on multimedia,, VOL. 7, NO. 2, 2005.
[51]. Yavuz E, Telatar Z ,” Improved SVD-DWT based digital image watermarking against watermark Ambiguity,” In: Proc. ACM Symposium on Applied Computing, pp 1051–1055 ,2007.
[52]. Yongdong Wu ,” On the Security of an SVD-Based Ownership Watermarking,” IEEE transactions on multimedia, VOL. 7, NO. 4, 2005.
[53]. Yu FQ, Zhangi ZK, Xu MH,” A digital watermarking algorithm for image based on fractional Fourier transform”, In: Proceeding of ieee conf. on industrial electronics and applications, Singapore, pp 1–5 ,2006.
[54]. Zhu, W., Xiong, Z., and Zhang, Y.-Q., "Multiresolution Watermarking for Images and Video", in IEEE Trans. on circuit and System for Video Technology, vol. 9, no. 4, pp. 545-550, June, 1999.

Deepali Gudware, "A Novel Watermarking Approach Based On Singular Value Decomposition," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.168-177, 2016.

The main problem in the proposed work was the sinkhole attack which was detected and removed by implementing appropriate protocol such as AODV i.e. ad hoc on-demand distance vector (AODV) routing. In this paper, eliminate the sinkhole attack from network by using a novel algorithm for sinkhole detection. The algorithm first finds a list of suspected nodes through checking data consistency and then effectively identifies the intruder in the list through analyzing the network flow information. The algorithm is also robust to deal with multiple malicious nodes that cooperatively hide the real intruder.

Wireless Sensor Networks, Routing Algorithm, Malicious Detection Approach

[1] S. Ahmad Salehi, M. A. Razzaque, Parisa Naraei, Ali Farrokhtala, “Detection of Sinkhole Attack in Wireless Sensor Networks”, IEEE International Conference on Space Science and Communication, 2013, pp. 361 – 365.
[2] A. Vijayalakshmi, T. Shrimathy, T. G. Palanivelu, “Mobile Agent Middleware Security for Wireless Sensor Networks”, IEEE International Conference on Communication and Signal Processing, 2014, pp. 1669 - 1673.
[3] Vandana B. Salve, Leena Ragha, Nilesh Marathe, “AODV Based Secure Routing Algorithm against Sinkhole Attack in Wirelesses Sensor Networks”, IEEE International Conference on Electrical, Computer and Communication Technologies, 2015, pp. 1 – 7.
[4] Mohamed Guerroumi, Abdelouahid Derhab, Kashif Saleem, “Intrusion detection system against SinkHole attack in wireless sensor networks with mobile sink”, IEEE International Conference on Information Technology, 2015, pp. 307- 313.
[5] D. Sheela, C. Naveen Kumar, G. Mahadevan, “A non cryptographic method of sink hole attack detection in wireless sensor networks”, IEEE International Conference on Information Technology, 2011, pp. 527 – 532.
[6] Mohamed Guerroumi, Abdelouahid Derhab, Kashif Saleem, “Intrusion Detection System against Sink Hole Attack in Wireless Sensor Networks with Mobile Sink”, IEEE International Conference on Information Technology - New Generations, 2015, pp. 307 – 313.
[7] Krishan Kant Varshney, P. Samundiswary, “Performance analysis of malicious nodes in IEEE 802.15.4 based wireless sensor network”, IEEE International Conference on Information Communication and Embedded Systems, 2014, pp. 1–5.
[8] Ritwik Banerjee, Chandan Kr. Bhattacharyya, “Energy efficient routing and bypassing energy-hole through mobile sink in WSN”, IEEE Conf. on Computer Communication and Informatics (ICCCI), 2014, pp. 1 – 6.
[9] Babar Nazir, Halabi Hasbullah, “Mobile Sink based Routing Protocol (MSRP) for Prolonging Network Lifetime in Clustered Wireless Sensor Network”, IEEE Conf. on Computer Applications and Industrial Electronics (ICCAIE), 2010, pp. 624 – 629.
[10] Pushpendu Kar, Sudip Misra, “Reliable and Efficient Data Acquisition in Wireless Sensor Networks in the Presence of Tran faulty Nodes”, IEEE Conf. on IEEE Transactions on Network and Service Management, 2016, pp. 99 – 112.
[11] Siba Mitra, Ajanta De Sarkar, “Energy aware fault tolerant framework in Wireless Sensor Network”, IEEE Conf. on Applications and Innovations in Mobile Computing (AIMoC), 2014, pp. 139 – 145.
[12] Priyanka Deshpande, Mangala S. Madankar, “Techniques improving throughput of wireless sensor network: A survey”, IEEE Conf. on Circuit, Power and Computing Technologies (ICCPCT), 2015, pp. 1 – 5.
[13] Imran Makhdoom, Mehreen Afzal, Imran Rashid, “A novel code attestation scheme against Sybil Attack in Wireless Sensor Networks”, IEEE Conf. on Software Engineering Conference (NSEC), 2014, pp. 1 – 6.
[14] J. Krithiga, R. C. Porselvi, “Efficient Code Guard mechanism against pollution attacks in interflow Network coding”, IEEE Conf. on Communications and Signal Processing (ICCSP), 2014, pp. 1384 – 1388.
[15] R. Geetha, S. Raj Anand, E. Kannan, “Fuzzy logic based compromised node detection and revocation in clustered wireless sensor networks”, IEEE Conf. on Information Communication and Embedded Systems (ICICES), 2014, pp - 1 – 6.
[16] Yong-Sik Choi, Young-Jun Jeon, Sang-Hyun Park, “A study on sensor nodes attestation protocol in a Wireless Sensor Network”, The 12th IEEE International Conf. on Advanced Communication Technology (ICACT), 2010, pp. 574 - 579.
[17] Yuling Lei, Yan Zhang, Yanjuan Zhao, “The Research of Coverage Problems in Wireless Sensor Network”, IEEE Conf. on Wireless Networks and Information Systems, 2009, pp. 31 – 34. DOI: 10.1109/WNIS.2009.38
[18] Ruchi Mittal, M. P. S Bhatia, “Wireless sensor networks for monitoring the environmental activities”, IEEE Conf on Computational Intelligence and Computing Research (ICCIC), 2010, pp. 1 – 5.
[19] Nikhil Marriwala, Priyanka Rathee, “An approach to increase the wireless sensor network lifetime”, IEEE Conf. on Information and Communication Technologies (WICT), 2012, pp. 495 – 499.
[20] Guanglai Chen, Shoujun Wang, Lifei Li, “Notice of Retraction the design of wireless wave height sensor network node based on Zigbee technology”, IEEE Conf. on Electric Information and Control Engineering (ICEICE), 2011, pp. 3683 – 3686. DOI: 10.1109/ICEICE.2011.5777656
[21] NS-2, The ns Manual (formally known as NS Documentation) available at following link: http: //www. isi.edu/nsnam/ ns/do
[22] Gisung Kim, Younggoo Han, Sehun Kim, “A cooperativesinkhole detection method for mobile ad hoc networks”, International Journal of Electronics and Communication 64 (2010) 390–397
[23] J.M.L.P. Caldeira, J.J.P.C. Rodrigues, P. Lorenz, L. Shu, “Intramobility handover enhancement in healthcare wireless sensor networks”, 14th International Conference one-Health Networking, Applications and Services (Healthcom), 2012, pp. 261 – 266.
[24] Charanpreet Kaur and Amit Chhabra, "An Energy Efficient Multihop Routing Protocol for Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Volume-03, Issue-07, pp. 86 - 91, Jul -2015.
[25] R. Silva, J. Sa Silva, M. Simek, F. Boavida, “A new approach for multi-sink environments in WSNs”, International Symposium on Integrated Network Management, 2009. IM '09. IFIP/IEEE, pp. 109 – 112.
[26] Qingtian Sun, Shunfu Jin, Chen Chen, “Energy analysis of sensor nodes in WSN based on discrete-time queueing model with a setup”, Chinese Control & Decision Conference (CCDC), 2010, pp. 4114 – 4118, DOI: 10.1109/CCDC.2010.5498425.
[27] L. Lazos, R. Poovendran, C. Meadows, P. Syverson, L.W. Chang, “Preventing wormhole attacks on wireless ad hoc networks: a graph theoretic approach”, in: Proceedings of WCNC ’05, March 2005, pp.1193–1199.
[28] J. Petajajarvi, H. Karvonen, “Soft handover method for mobile wireless sensor networks based on 6LoWPAN”, International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS), 2011, pp. 1 – 6, DOI: 10.1109/DCOSS.2011. 5982208.
[29] Rohit Aggarwal, Er. Khushboo Bansal, “An Efficient Intruder Detection System against Sinkhole Attack in Wireless Sensor Networks: A Review”, International Journal of Computer Sciences and Engineering (IJCSE), pp. 64 – 68, Volume-4, Issue-4, April 2016,

Rohit Aggarwal and Khushboo Bansal , "Result Based approach on Intrusion Detection System against Sinkhole Attack in Wireless Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.178-182, 2016.