iosr-JCE   International Conference On Recent Advances In Computer Science, Engineering And Technology

Abstract: Advancements in social networking site and usage by people for various purposes like posting reviews of products which they purchase online has gained attention of researchers. These reviews are real time messages about people's opinions on different topics, current issues, complaints about products. One of the most interesting and challenging issue is to analyze these reviews on social sites such as Twitter in order to get valuable hidden patterns. In this paper, we have focused on classifying polarity of tweets into either positive, negative or neutral tweets............

Keywords - Twitter datasets, polarity classification, feature extraction, DSS.

[1]. A PappuRajan , S.P.Victor, Web Sentiment Analysis for Scoring Positive or Negative Words using Tweeter Data International Journal of Computer Applications (0975 – 8887) Volume 96– No.6, June 2014
[2]. Preety, Sunny , Dahiya, "SENTIMENT ANALYSIS USING SVM AND NAÏVE BAYES" International Journal of Computer Science and Mobile Computing, Vol.4 Issue.9, September- 2015, pg. 212-219
[3]. Rahul Rajput, Arun Kumar Solanki , "Review of Sentimental Analysis Methods using Lexicon Based Approach" , International Journal of Computer Science and Mobile Computing, Vol.5 Issue.2, February- 2016, pg. 159-166
[4]. Amit G. Shirbhate, Sachin N. Deshmukh , "Feature Extraction for Sentiment Classification on Twitter Data"International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064
[5]. Jonathon Read, "Using Emoticons to Reduce Dependency in Machine Learning Techniques for Sentiment Classification", In ACL,The Association for Computer Linguistics 2005,pg.43-48.

Abstract: This paper presents biometrics based iris, fingerprint and palmprint recognition and authentication system. Human iris is one of the most reliable biometric because of its uniqueness, stability and non-invasive nature. In this paper, several steps are used for iris recognition system. First, the image pre-processing is performed. Then with the use of Ridge Energy Detection Algorithm (RED), the features are extracted by filtering the normalized iris region. Finally two Iris Codes are compared and human identification is done. Fingerprint and palmprint images are enhanced using preprocessing techniques such as morphological operations..............
Keywords: RED, localization, normalization, Harris features, neighborhood operation, Euclidean, SFF

[1] Amel Saeed Tuama, "Iris Image Segmentation and Recognition", Int. J Comp Sci. Emerging Tech, Vol-3 No 2 April, 2012, pp. 529-551, April 1955.
[2] Li Ma, Yunhong Wang, Tieniu Tan, " Iris Recognition Using Circular Symmetric Filters", National Laboratory of Pattern Recognition, Institute of Automation, , IEEE 2002.
[3] Manu Garg, Er. Harish Bansal, "Fingerprint Recognition System using Minutiae Estimation ", International Journal of Application or Innovation in Engineering & Management (IJAIEM), Volume 2, Issue 5, May 2013.
[4] Ms. Apurva D. Dhawale, Prof. Dr. K. V. Kale, "Fusion of Iris and Palmprint Traits for Human Identification", International Journal of Computer Techniques, volume , January 2015.
[5] S. Palanikumar, M. Sasikumar and J. Rajesh 2011 Palmprint Enhancement Using Discrete Curvelet Transform. International Journal of Computer Science Issues, 8(4), No 2.

Abstract: To improve the performance of predictive model and data quality it is always necessary to use optimal feature to learn the predictive model i.e. always use relevant feature in dataset and discard the irrelevant feature by using the proper feature subset selection method. The feature subset selection method improves the quality of the data, reduce the dimensionality and improve the accuracy of classifier .In the present study different feature selection method is used to select the optimal relevant feature to predict the Epileptic seizure before its onset.

Keywords- Feature Selection, Relieff, Statistical Dependency (SD), Mutual Information (MI)

[1] Pinar Yildirim" Filter Based Feature Selection Methods for Prediction of Risks in Hepatitis Disease" International Journal of Machine Learning and Computing, Vol. 5, No. 4, August 2015 DOI: 10.7763/IJMLC.2015.V5.517
[2] R. Kohavi, A study of cross-validation and bootstrap for accuracy estimation and model selection, in: C.S. Mellish, ed., Proceedings IJCAI-95, Montreal, Que. (Morgan Kaufmann, Los Altos, CA, 1995) 1137-l 143.
[3] T. M. Phuong, Z. Lin et R. B. Altman. Choosing SNPs using feature selectio. Proceedings / IEEE Computational Systems Bioinformatics Conference, CSB. IEEE Computational Systems Bioinformatics Conference, pages 301-309, 2005. PMID 16447987
[4] kenji kira "a practical approach to feature selection" ml92 proceedings of the ninth international workshop on machine learning pages 249-256
[5] S. Francisca Rosario, Dr. K. Thangadurai "RELIEF: Feature Selection Approach" international journal of innovative research & development Vol 4 Issue 11, 218-224

Abstract: This paper presents the experimental evaluation of Gabor filter and Zernike moments for extracting the face features. The dimensionality of the input image is reduced for the overloading process of Gabor filters. 40 sub-images were obtained from the original images by using the Gabor filters in 5 scales and 8 orientations. From each sub-image, four Zernike features were extracted. Thus, the total numbers of features are 160. The k-Nearest Neighbor (k-NN) classifier is used for the matching purpose............

Keywords: Facial Expression, Gabor filter, KNN, ORL, Zernike moments

[1]. Matthew A. Turk and Alex P. Pentland, Face Recognition Using Eigenfaces, Vision and Modeling Group, The Media Laboratory Massachusetts Institute of Technology 1991.
[2]. Peng Yang, Shiguang Shan, Face Recognition Using Ada-Boosted Gabor Features, IEEE International Conference on Automatic Face and Gesture Recognition, Korea, 356-361, May 2004
[3]. Anissa Bouzalmat and Arsalane Zarghili, Facial Face Recognition Method using Fourier Transform Filters Gabor and R_LDA, International Conference on Intelligent Systems and Data Processing (ICISD) 2011.
[4]. Chengjun Liu and Harry Wechsler, Independent Component Analysis of Gabor Features for Face Recognition, IEEE Transactions on Neural Networks, Vol. 14, No. 4, JULY 2003.
[5]. Linlin SHEN, Gabor Features and Support Vector Machine for Face Identification, Biomedical Soft Computing and Human Sciences, Vol.14, No.1, pp.61-66 (2009).

Abstract: In this research we are focused on measuring the impact of main author on dependent author/followers. When dependent author use the work of main author, the dependent author may carry some impression of main author in his writing. Text similarity is comparison between query text and text from main document. This comparison gives most similar documents to user. Text similarity is important in the classifying the text as well as document. Using cosine similarity algorithm we can measure similarity between two different documents and also we can find impression of main author on dependent author. Up till now this work is not available for Marathi and English language it's the first attempt in this direction where significance of author. This will also be applied in detection of plagiarism.

Keywords:- Cosine similarity, lexical similarity, semantic similarity, text frequency, inverse document frequency.

[1] Retrieved August 31, 2016, from shodhganga.inflibnet,http://shodhganga.inflibnet.ac.in/bitstream/10603/28514/11/11_chapter%203.pdf.
[2] Chong, M. Y. M. (2013). A study on plagiarism detection and plagiarism direction identification using natural language processing techniques.
[3] Pradhan, N., Gyanchandani, M., & Wadhvani, R. (2015). A Review on Text Similarity Technique used in IR and its Application. International Journal of Computer Applications, 120(9).
[4] Chapman, S. (2006). Simmetrics: java & c #. net library of similarity metrics.
[5] Irving, R. W., & Fraser, C. B. (1992, April). Two algorithms for the longest common subsequence of three (or more) strings. In Annual Symposium on Combinatorial Pattern Matching (pp. 214-229). Springer Berlin Heidelberg.

Abstract: In this paper; we have highlighting on Biometric Fingerprints SWT Multi-Level Feature Fusion, SVM Classification approach to automate the Gender Recognition System. As a need in forensic investigation facet day by day new solutions are designed to solve the crime investigating and other issues. So, we have used 3000 samples of classified fingerprint database. Multi-level 2-D Stationary Wavelet Transform (SWT), Singular Valued Decomposition (SVD) technique have used as a feature extraction methods. The fusions of these multilevel extracted features are used in further process. At last, Support Vector Machine (SVM) is used to classify the datasets.

Keywords: Biometric, Fingerprint, Gender, Forensic, Multi-Level

[1]. Davide Maltoni ,Salil Prabhakar, Dario Maio, Anil K. Jain Salil Prabhakar, "Handbook of Fingerprint Recognition", Second Edition, Springer,2009.
[2]. John D. Woodward, Jr. Nicholas M. Orlans, Peter T.Higgins, "Biometrics‟, McGrew-Hill @2003
[3]. [Online] Available: http://www.prnewswire.com/news-releases/biometric-systems-market-2015---2020-research-reports-518453221.html dt.11/10/2015.
[4]. D.A. Ashbaugh, Quantitative–Qualitative Friction Ridge Analysis: An Introduction to Basic and Advanced Ridgeology, CRC Press, 1999.
[5]. CDEFFS: The ANIS/NIST Committee to Define an Extended Fingerprint Feature Set, 2007. , [Online] Available : http://fingerprint.nist.gov/standard/cdeffs/index.html

Abstract: Diabetes Mellitus (DM), commonly referred as diabetes is a disorder that most of the people suffer from and which also leads to death many of the times. Type 1, Type 2 and Gestational diabetes are the types of diabetes. The database taken for present study is of patients suffering from Type 1 DM. In Type 1 diabetes a patient has to take external insulin to maintain the blood glucose level (BGL). Insulin is a hormone produced in the pancreas which maintains the BGL of a person. BGL is responsible for a person's daily activity. Within a specified target range the blood glucose level has to be maintained..............

Keywords— BGL, Diabetes, Regular insulin dose, NPH insulin dose , SVM

[1]. "Better Health Channel". Copyight © 1999/2016 State of Victoria [Internet]. Cited 2016 August 27. Available from https://www.betterhealth.vic.gov.au/health/conditionsandtreatments/diabetes-and-insulin?viewAsPdf=true.
[2]. Anupriya K Kamble, Ramesh R Manza and Yogesh M Rajput, Review on Diagnosis of Diabetes in Pima Indians, IJCA Proceedings on National Conference on Digital Image and Signal Processing NCDISP 2016(2):12-15, August 2016.
[3]. Shoback, Greenspan‟s basic & clinical endocrinology. Edited by David G. Gardner, Dolores(9th ed.) (New York:McGraw-Hill Medical, 2011).
[4]. "National Institute of Diabetes and Digestive and Kidney Diseases" [Internet]. Cited 2015 Dec. 1. Available from https://www.niddk.nih.gov/health-information/health-statistics/Pages/default.aspx#category=diabetes

Abstract: As technology increases day by day, it's not limited to computer era it extends further in mobile technology. As mobile users has tremendously increased in last five years due to the vast use of internet and fast internet services. Users are using internet facility in mobiles for the various purposes like business, shopping, communication, etc. purposes. As every technology has pros and cons, in mobile technology especially in business sectors it has several disadvantages which forwardly referred as online or cyber crimes such as tampering with computer source documents, hacking, and forgery, financial crimes for e-business...........

Keywords - Mobile Technology, Cyber space and online frauds

[1]. Peter Tarasewich, Robert C. Nickerson, Merrill Warkentin, Issues In Mobile E-Commerce", Communications of the Association for Information Systems (Volume 8, 2002) 41-64
[2]. Mitesh Pravinchandra Mandaliya, "Mobile Commerce: The New Era of Shopping", International Journal of Innovations in Engineering and Technology (IJIET), Volume 4 Issue 4 December 2014 , ISSN: 2319 – 1058.
[3]. http://www.myspeed.trai.gov.in/
[4]. http://indiainbusiness.nic.in/newdesign/index.php?param=newsdetail/10367
[5]. Krishna Prakash and Balachandra, Security Issues And Challenges In Mobile Computing And M-Commerce, International Journal of Computer Science & Engineering Survey (IJCSES) Vol.6, No.2, April 2015

Abstract: The term of Li-Fi technology you can use wireless internet where you cannot use Wi-Fi or other network. Everyone gotten traced for slow speeds you face when multiple devices is tapped into the network. As more and more people and their many devices access wireless internet, clogged airwaves are going to make it increasingly difficult to latch onto a reliable signal. But radio waves are just one part of the spectrum that can carry our data. What if we could use other waves to surf the internet? One German physicist ,DR.Harald Haas..........

Keywords: Wi-Fi, Li- Fi, VLC, Visible light communication, ICT. MBPS, VLC transmitter, photo detector, amplification and processing, data utilization, server, lamp driver, LED based headlights, LED based backlights, penetrate through wall.

[1] M. Afgani, H. Haas, H. Elgala, and D. Knipp, "Visible Light Communication using OFDM" in Proc. of the 2nd International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (TRIDENTCOM), Barcelona, Spain, March 1-3 2006, pp. 129-134.
[2] D. Tsonev, S. Sinanović, and H. Haas, "Enhanced Subcarrier Index Modulation (SIM) OFDM" in Proc. Of IEEE Global Communications Conference (IEEE GLOBECOM 2011), Houston, Texas, USA, 5-9 Dec. 2011.
[3] M. Di Renzo, H. Haas, and P.M. Grant, "Spatial Modulation for Multiple- Antenna Wireless Systems: A Survey", IEEE Communications Magazine, vol. 49, no. 11, Nov. 2011.
[4] H. Haas, "Wireless Data from Every Light Bulb", TED Website, Aug. 2011. [Online]. Available: http://bit.ly/ted_vlc.
[5] H. Elgala, R. Mesleh, and H. Haas, "Indoor Optical Wireless Communication: Potential and State-of-the- Art", IEEE Communications Magazine, vol. 49, no. 9, pp. 56-62, Sep. 2011, ISSN: 0163-6804.

Abstract: One of the important applications of natural language processing is text summarization. But not much work has been done in Marathi language. The current paper, represent the question based text summarization system for Marathi language with rule based stemmer. The proposed rule based stemmer is used to stem Marathi word. This technique is used for generation of the appropriate question on given input/text.

Keywords – Text Summarization, Natural Language processing (NLP), Stemming.

[1] Atif, K. and Naomie, S., A review on abstractive summarization methods, Journal of Theoretical and Applied Information Technology, 59(1), 2014.
[2] Gaikwad D.K and C.Namrata Mahender, A Review Paper on Text Summarization, International Journal of Advanced Research in Computer and Communication Engineering. 3(5), 2016.
[3] Gupta, V. and Lehal, G.S., A survey of text summarization extractive techniques, Journal of emerging technologies in web intelligence, 2(3), 2010, pp.258-268.
[4] Gupta, V., Hindi Rule Based Stemmer for Nouns, International Journal of Advanced Research in Computer Science and Software Engineering, 4(1), 2014,pp.62-65.
[5] Mishra, U., Prakash C., MAULIK: An Effective Stemmer for Hindi Language, International Journal on Computer Science and Engineering (IJCSE), 5(4), 2012

Abstract: In the past decade, interest in using biometric technologies for person authentication in security system. Voice is one of the most Promising and mature biometric modalities for access control.In this paper present text-dependent speaker recognition in noisy environment.Used low-pass filter to remove the background noise from noised speech signal.For extraction used speech parameterization method such as MFCC and completion of parameterization of speech, Vector quantization has been used in the learning and recognition purpose. We have achieved 90 % recognition rate for noisy environment as compare to existing system used in different technique.

Keywords:- Feature, Recogination, MFCC, Noise

[1]. Campbell, J.P., Jr.; "Speaker recognition: a tutorial" Proceedings of the IEEE Volume 85, Issue 9, Sept. 1997 Page(s):1437 – 1462.
[2]. PRADEEP. CH," Text Depedent Speaker Recognition Using MFCC And LPC VQ", National Institute of Technology, Rourkela, 2007.
[3]. Fu Zhonghua; Zhao Rongchun; "An overview of modeling technology of speaker recognition", IEEE Proceedings of the International Conference on Neural Networks and Signal Processing Volume 2, Page(s):887 – 891, Dec. 2003.
[4]. Nakai, M.; Shimodaira, H.; Kimura, M.; "A fast VQ codebook design algorithm for a large number of data", IEEE International Conference on Acoustics, Speech, and Signal Processing, Volume 1, Page(s):109 – 112, March 1992.
[5]. D. Reynolds and B. Carlson, "Text-Dependent Speaker Verification Using Decoupled and Integrated Speaker and Speech Recognizers," In EUROSPEECH in Madrid, ESCA, pp.647-650, 1995.

Abstract: In the recent era medical image processing, for Ultrasound images, sonography machines are frequently used by healthcare professionals. The use of ultrasound imaging in medical diagnosis is well established because of its noninvasive nature, low cost, capability of forming real time image.The prenatal diagnoses of chromosomal disorders have been focused by researchers for detecting Down Syndrome (DS) in human fetuses. Trisomy 21 is recognized as severe chromosomal abnormality occurring approximately once in every 800 to1000 live births and the risk increase with the extra maternal age. In sonography test Nuchal translucency (NT) thickness is the most effective marker of trisomy 21. The main problem during diagnosis is the distortion of visual signals and continuing improvement in image quality is expected from computer professionals.

Keywords: Prenatal, gastation week, ultrasound, sonography, speckle noise, Down Syndrome (DS),trisomy 21, Nuchal translucency (NT)

[1]. K. Kirk Shung,‖ Diagnostic Ultrasound: Past, Present, and Future‖, Journal of Medical and Biological Engineering, 31(6): 371-374 ,J. Med. Biol. Eng., Vol. 31 No. 6 JAN 2011.
[2]. S. Grace Chang, Bin Yu, and Martin Vetterli,―Spatially Adaptive Wavelet Thresholding with Context Modeling for Image Denoising‖,IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 9, NO. 9, SEPTEMBER 2000
[3]. S.Sudha, G.R.Suresh and R.Sukanesh, ‖Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding based on Weighted Variance‖,International Journal of Computer Theory and Engineering, Vol. 1, No. 1, April 2009.
[4]. K. Karthikeyan. C. Chandrasekar.‖Speckle Noise Reduction of Medical Ultrasound Images using Bayesshrink Wavelet Threshold‖,International Journal of Computer Applications (0975 – 8887) Volume 22– No.9, May 2011.

Abstract: Web Applications are very common now a days. Almost all the services are provided through web applications too. So web applications are important and its security relies on server-side. For securing web applications its server-side must be secured. Web applications can be attacked through SQL injection, cross-site scripting, cookie theft, browser hijacking etc. This paper is going to deal with attacks like SQL injection, cross-site scripting, file inclusion vulnerabilities and cross site request forgery.

Keywords: Cross Site Request Forgery, Cross-Site Scripting, File Inclusion Vulnerability, SQL Injection, Web Application, Web Application Security

[1]. Ashwani Garg and Shekhar Singh, "A Review on Web Application Security Vulnerabilities", IJARCSSE, 2013
[2]. Denzyl P. Dayal, "Handbook Of Cyber Crimes"(Dominant Publishers & Distributors Pvt Ltd)
[3]. http://www.ciso.in/why-we-need-web-application-security/
[4]. Xiaowei Li and Yuan Xue, "A Survey on Web Application Security", Department of Electrical Engineering and Computer Science Vanderbilt University
[5]. Punam Thopate, Purva Bamm, Apeksha Kamble, Snehal Kunjir and Prof S.M.Chawre, "Cross Site Scripting Attack Detection & Prevention System", IJARCET, Volume 3 Issue 11, November 2014

Abstract: Internet revolution resulted in an explosive growth in multimedia applications. The rapid advancement of internet has made it easier to send the data/image accurate and faster to the destination. Watermarking biometric data is a still a relatively new issue, but it is of growing importance as more robust methods of verification and identification are being used. Using least significant bit technique isolating particular bits of pixel value in an image highlighting interesting aspects of that image. Higher order bits usually contain most of the significant visual images & lower order bits contain subtle details

Keywords: LSB plane, gray level slicing, MSB plane

[1]. I.J. Cox, M.L. Miller, Jeffrey A. Bloom, J. Fridrich and T. Kalker, Digital Watermarking and Steganography, Second Edition, Elsevier, 2008, ISBN: 978-0-12-372585-1
[2]. Feng-Hsing Wang, Jeng-Shyang Pan, Lakhmi C Jain, Innovations in Digital Watermarking Techniques, Springer, 2009, ISBN: 978-3-642-03186-1 (Print) 978-3-642-03187-8 (Online)
[3]. M. K. Arnold, M. Schmucker, S. D. Wolthusen, Techniques and Applications of Digital Watermarking and Content Protection, Artech House, 2003, ISBN: 1-58053-
[4]. I. J. Cox, M. L. Miller, J. A. Bloom, "Digital Watermarking", Morgan Kaufmann Publishers, 200
[5]. K.M. Mrao,"overview of image proessing ,"8th otober 1995NRSA ,hydrabad.-37

Abstract: Detection of vehicles is the most imperative domain in recent years. It performs vital role in civilian and military application, vehicle tracking is one of the major application in defense sector. Traffic planning, city planning, traffic surveillance and control are the fundamental application in civilian sector. This research paper introduces morphological techniques for video vehicle detection which are based on Morphological approach. Literature survey presents recent work on vehicle detection techniques on vision based vehicle detection using sensors. Tracking the vehicle motion and recognize their features has been rising research area in the field of computer vision and image processing. Analysis of traffic images perform following steps............

Keywords: Vehicle detection, Median Filter, Traffic surveillance, Thresholding, Edge Detection

[1] Z. Sun, R. Miller, G. Bebis and D. DiMeo, "A Real-Time Precrash Vehicle Detection System," Proc. IEEE Int‟l Workshop Application of Computer Vision, (2002) December.
[2] Vehicle Detection by Independent Parts for Urban Driver Assistance "IEEE transactions on intelligent transportation systems, vol. 14, no. 4, (2013) December.
[3] IEEE transactions on intelligent transportation systems, vol. 12, no. 2, (2011), June.
[4] FLEXYS: Motion-based Traffic Analysis and Incident Detection (IBBT/VUB-ETRO)
[5] IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org ISSN (e): 2250-3021, ISSN (p): 2278-8719 Vol. 04, Issue 07 (July. 2014), ||V4|| PP 39-43

Abstract: The purpose of this paper is to review various face detection and recognition methods, Face recognition has been a fast growing, and Face Recognition is the problem related to the field of machine learning, challenging and interesting area in real time application. Computer vision and image analysis. Paper an effort is made to review an extensive range of present methodology of face recognition techniques

Keywords: Face recognition Techniques, Face Detection, Feature Extraction, Application

[1]. Shou-Jen Lin, Chao-Yang Lee, Mei-hsuan Chao, Chi-Sen Chiou, Chu-Sing Yang, "The Study And Implementation Of Real-Time Face Recognition And Tracking System‟, Proceedings of the Ninth International Conference on Machine Learning and Cybernetics, Qingdao, 11-14 July 2010.
[2]. Sarala A. Dabhade & Prof. Mrunal S. Bewoor " Real Time Face Detection and Recognition using Haar - Based Cascade Classifier and Principal Component Analysis‟ International Journal of Computer Science and Management Research Vol 1 Issue 1 Aug 2012 ISSN: 2278-733X.
[3]. Yun-Hee Han,Keun-Chang Kwak,‖ Face Recognition and Representation by Tensor based MPCA Approach‖,2010 The 3rd International Conference on Machine Vision (ICMV 2010)
[4]. Seema Asht, Rajeshwar Dass, Dharmendar, "Pattern Recognition Techniques", International Journal of Science, Engineering and Computer Technology, vol. 2, pp. 87-88, March 2012.
[5]. Ambika Ramchandra and Ravindra Kumar,"Overview Of Face Recognition System Challenges," International Journal of Scientific & Technology Research (IJSTR), vol. 2, issue 8, Aug.2013.