iosr-JCE   National Conference On Advances In Computational Biology, Communication, And Data Analytics (ACBCDA 2017)

Abstract: Genome assembling has been an active research area since the DNA structure was discovered and has gained much attention after the Human Genome project was launched. A large number of genomes have been assembled and many more are in the pipeline. A number of full-scale assemblers and other special-purpose modules have been reported. Since the volume of data involved in the genome assembly process is very large and requires significantly large computational power and processing time, many assemblers have utilized parallel computing to achieve faster and more efficient reconstruction of the DNA. A genome assembler has a multistep process which includes different components..........

Keywords - Parallel algorithms, genome assembly framework, high performance bioinformatics

[1]. Yiming He, Zhen Zhang, Xiaoqing Peng, Fangxiang Wu, and Jianxin Wang , De Novo Methods for Next Generation Sequencing Data, ISSNll1007-0214ll08/11llpp500-514 Volume 18, Number 5, October 2013
[2]. A. Kalyanaramana, S.J. Emrichb,c, P.S. Schnablec,d, S. Alurub,c, Assembling genomes on large-scale parallel computers, Journal of parallel and distributed computing,Elsevier 9 June 2007
[3]. Serafim Batzoglou,David B. Jaffe,ARACHNE: A Whole-Genome Shotgun Assembler, Cold Spring Harbor Laboratory Press ISSN 1088- 9051/01
[4]. Melissa de la Bastide andW. Richard McCombie,Assembling Genomic DNA Sequences with PHRAP, Current Protocols in Bioinformatics (2007) 11.4.1-11.4.15
[5]. James C. Mullikin and Zemin Ning,The Phusion Assembler, Cold Spring Harbor Laboratory Press ISSN 1088-9051/03

Abstract: The aim of this paper is to present a study on smart waste management that uses Internet of Things (IoTs) and big data analytics. This paper considered issues and challenges in smart city applications. The objective of this study is to analyze the problems in computer-based waste management systems and find out possible areas where solutions are required to overcome the drawbacks in web based waste management system.
Keywords: Smart waste, big data, task scheduling, data analytics, environment monitoring.

[1]. Shahrokni, K, van der Heijde, B, Lazarevic, D, Brandt, N, "Big Data GIS Analytics towards Efficient Waste Management in Stockholm," 2nd International Conference on ICT for Sustainability, Atlantis Press, pp.140-147, 2014.
[2]. Guerrero L. A., Maas G., Hogland W., "Solid waste management challenges for cities in developing countries," Journal of Waste Management, vol. 33, no.1, pp. 220-232, 2013.
[3]. M. Faccio, A. Persona, and G. Zanin, "Waste collection multi objective model with real time traceability data," Waste management, vol.31, no.12, pp. 2391-405, 2011.
[4]. Alexey Medvedev, Peter Fedcherikov, Theodoros Anagnostopoulos, Sergey Khoruzhnikov, "Waste Management as an IoT-Enabled Service in Smart Cities", Springer-Verilog, 2015.
[5]. Z. Perera C., Zaslavsky A., Christen P., Georgakopoulos D. "Sensing as a service model for smart cities supported by Internet of Things," Transactions on Emerging Telecommunications Technologies, vol.25, no.1, pp. 81-931.

Abstract: Now a day's safety and time are major issue. And home fires have taken a growing toll in lives and property in recent year. LPG is highly inflammable and can burn even at some distance from the source of leakage. Most fire accidents are caused because leakage of gas. In this project we are dealing with detection, monitoring and control system of LPG gas leakage. Using relay DC motor the stove knob is automatically controlled. Along with this safety measures the system has additional advantage of automatic rebooking of cylinder when the level of gas goes below the normal weight of cylinder.

Keywords- Gas sensor, GSM, DC motor, microcontroller, load cell.

[1]. http://edugreen.teri.res.in/explore/n_renew/lpg.htm, http://barabanki.nic.in/bbkgas/aboutlpg.asp.
[2]. http://www.pipelineandgasjournal.com/
[3]. http://playground.arduino.cc/
[4]. V. Ramya and B. Palaniappan, "Embedded system for Hazardous gas detection and Alerting," in Proc. of International Journal of Distribted and parallel system(IJDPS), vol. 3, no. 3, May 2012.
[5]. www.indane.co.in, www.hpgas.co.in.

Abstract: Agricultural scientists play an important role in detecting and finding cure for plant diseases. Sometimes manual identification of disease is time consuming and laborious process. One of the most important factors contributing to low yield is disease attack. Many studies show that quality of agricultural products may be reduced due to various factors of plant diseases. In banana plant, diseases which are commonly observed are panama wilt, yellow sigatoka, black sigatoka, banana streak virus and banana bunchy top virus [10]. The banana plant leaf diseases not only restrict the growth of the plant but also destroy the crop. Banana plant leaf diseases must be identified early and accurately.............

Keywords: Pattern recognition, image processing techniques, ANN, SVM, PNN, MSOFM & GA.

[1]. Stephen Gang Wu, Forrest Sheng Bao, Eric You Xu, Yu – Xuan Wang and Yi – Fan Chang, "A leaf recognition algorithm for plant classification using probabilistic neural network", IEEE 7th International Symposium on Signal Processing and Information Technology, 2007.
[2]. A.Meunkaewjinda, P. Kumsawat, K. Attakitmongcol and Sri Kaew,"grape leaf disease detection from color imagery using hybrid intelligent system", proceedings of ecti-con 2008.
[3]. Shen Weizheng, Wu,Yachun, Chen Zhanliang and Wei Hongda, "Grading method of leaf spot disease based on image processing", Proceedings Of 2008 International Conference On Computer Science And Software Engineering, Volume 06,2008.
[4]. Dheeb Al Bashish, Malik Braik, and Sulieman Bani-Ahmad , "A Framework for Detection and Classification of Plant Leaf and Stem Diseases", 2010 International Conference on Signal and Image Processing.
[5]. Yuan Tian, Chunjiang Zhao, Shenglian Lu, and Xinyu Guo, "SVM-based Multiple Classifier System for Recognition of Wheat Leaf Diseases" Proceeding of 2010 Conference on Dependable Computing (CDC'2010) Nov. 20-22 2010, Yichang, China

Abstract: Machine learning is a subfield of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data. Both systems search through data to look for patterns. Spam filtering, face recognition, recommendation engines, when you have a large data set on which you'd like to perform predictive analysis or pattern recognition, machine learning is the way to go. This science, in which computers are trained to learn from, analyze, and act on data without being explicitly programmed, has surged in interest of late outside of its original cloister............

Keywords:- Big Data, Big Data Application, Text Analytics, Audio Analytics, Video Analytics.

[1]. Aha,D. Kibler,D. (1991): Instance-Based Learning Algorithms. In Machine Learning, vol. 6 - 1. Kluwer Academic Publishers.
[2]. Breiman, L. , Friedman,J.H., Olshen,R.A. & Stone,C.J. (1984): Classification and Regression Trees, Wadsworth Int. Group, Belmont, California, USA.
[3]. Clark, P., Niblett, T. : Induction in noisy domains, in Proc. of the 2th European Working Session on Learning , Bratko,I. and Lavrac,N. (eds.), Sigma Press, Wilmslow, 1987.
[4]. Dillon,W., Goldstein,M. (1984) : Multivariate Analysis methods and applications. John Wiley & Sons.
[5]. Friedman,J. (1991): Mutivariate Adaptative Regression Splines. In Annals of Statistics , 19:1.

Abstract: Fraud is increasing dramatically with the expansion of all modern technology and global communication systems, resulting in extreme loss to the businesses. Hence, fraud detection has become an important issue to be explored. Fraud detection involves identifying fraud as quickly as possible once it has been perpetrated. Insurance fraud is a criminal offence where one engages in the illicit act of intentionally falsifying a claim in an attempt to defraud an insurance company with the expectation of receiving income when not entitled to payment from the benefits being sought...........

Keywords: Fraud Detection, Hybrid Model, Kmeans clustering, SPSS, Support Vector Machines.

[1] Song Chen , Aryya Gangopadhyay ,"Health Care Fraud Detection with Community Detection Algorithms", Information Systems University of Maryland Baltimore Country Email: song8@umbc.edu, Information Systems University of Maryland Baltimore Country Email: gangopad@umbc.edu.
[2] Chun Yan, "The Identification Algorithm and Model Construction of Automobile Insurance Fraud Based on Data Mining", College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao of Shandong Province.
[3] Yufeng Kou, Chang-Tien Lu, Sirirat Sinvongwattana Yo-Ping Huang," Survey of Fraud Detection Techniques ",Dept. of Computer Science Virginia Polytechnic Institute and Engineering and State University Tatung University Falls Church, VA 22043, USA Taipei, Taiwan 10451 Email: yphuang@cse.ttu.edu.tw
[4] Hyun-Chul Kim, Shaoning Pang, Hong-Mo Je, Daijin Kim, Sung Yang Bang ,"Pattern Classification Using Support Vector Machine Ensemble",Department of Computer Science and Engineering, Pohang University of Science and Technology San 3 I , Hyoja-Dong, Nam-Gu, Pohang, 790-784, KOREA { grass,snpang,invu7 I ,dkim,sybang} @postech.ac.kr.

Abstract: This paper presents a correspondence measure method based on novel method which combines a permutation of Voila Jones Face Detection method and Eigen Face Recognition (Identification) technique. The proposed strategy used to defeat the issue of low precision by adjusting the face using Voila Jones Face detection method followed by Eigen Face Recognition technique. Compared to other Face Detection methods, the proposed method is very efficient for the Face Detection purpose. The system is built to meet real time face recognition criteria.

Keywords— Eigen faces recognition (Identification) technique, Low Precision, Voila Jones Face detection method

[1] Marijeta Slavkovic, Dubravka Jevtic, "Face Recognition using Eigenface Approach", Serbian Journal of Electrical Engineering,vol. 9, no. 1, February 2012, 121-130
[2] Yongzhong Lu, Jingli Zhou, Shengsheng Yu," A Survey of Face Detection, Extraction and Recognition",Computing and Informatics, Vol. 22, 2003,
[3] Yi-Qing Wang, "An Analysis of the Viola-Jones Face Detection Algorithm", Image processing On Line,4(2014),pp.128-148
[4] Paul Viola Michael Jones, "Rapid Object Detection using a Boosted Cascade of Simple Features" ,Conference on Computer Vision and Pattern Recognition 2001,1-9
[5] Rajesh Kumar Gupta,Umesh Kumar Sahu ,"Real Time Face Recognition under Different Conditions ",International Journal of Advanced Research in Computer Science and Software Engineering Volume 3, Issue 1, January 2013 ,86-89

Abstract: The field of artificial intelligence, or AI, attempts to understand intelligent entities as well as construct them to make the operation reasonably simple and easy, correct and precise. Artificial neural networks are typical example of a modern interdisciplinary subject. Sophisticated modeling technique that can be used for solving many complex problems serves as an analytical tool for qualified prognoses of the results. Using the concept of the artificial neural networks and the results of the performed numerical analyses make the field of Civil Engineering more accurate, precise and efficient especially in the fields of smart materials and many more.

Keywords - Artificial Intelligence, Artificial Neural Network, Smart Materials, EHS and GIS

[1]. Russell, S. and Norvig, P. (1995)―Artificial Intelligence: A Modern Approach‖, Prentice Hall.
[2]. Schalkoff, R. J. (1990), ―Artificial Intelligence: An Engineering Approach‖, McGraw-Hill, New York.
[3]. Adeli, H. & Hung, S. L. ,‖Machine Learning—Neural Networks, Genetic Algorithms, and Fuzzy Systems ―,John Wiley &Sons, Inc., New York, 1995
[4]. Flood, I.; Nabil, K. Neural networks in civil engineering II: Systems and application. // Computing in Civil Engineering. 8, 2(1994), pp. 149-162.
[5]. Flood, I.; Paul, C. Modeling construction processes using artificial neural networks. // Automation in Construction. 4, 4(1996), pp. 307-320.

Abstract: As we know Database models, specially relational databases, enables information to be efficiently stored and queried, but it futile in the applications that require a more 'enriched' meaning i.e. Semantic information. So a successful new approach to represent semantic information has been defined in the last decade known as Ontologies. In the Semantic Web the information can be represented in the form of XML, RDF or OWL languages. Ontologies are the web documents generated to provide more accurate web content, thus by improving the performance of information retrieval............

Keywords: Jena framework, OWL files, Relational Databases, Semantic Web, SPARQL Query.

[1]. Rajeshkumar T, Ramathilagam C, Dr. M.L.Valarmathi, Efficient Semantic Information Retrieval System from Relational Database , International Journal of Computer Science and Mobile Computing, Vol.3 Issue.4, April- 2014, pg. 1122-1129 .
[2]. Carmen Martinez-Cruz, Ignacio J. Blanco and M. Amparo Vila, Ontologies versus relational databases: are they so different? A comparison, Artif Intell Rev (2012)38:271–290 DOI 10.1007/s10462-011-9251-9 Published online: 15 June 2011 ©Springer Science+Business Media B.V.2011.
[3]. Mohammed Reda Chbihi Louhdi, Hicham Behja and Said Ouatik El Alaoui, Transformation Rules For Building Owl Ontologies From Relational Databases, Sundarapandian et al. (Eds) :ICAITA, SAI,SEAS, CDKP, CMCA-2013 pp. 271–283,2013. © CS & IT-CSCP 2013.
[4]. Zhou S., Ling H., Han M. and Zhang,H,Ontology Generator from Relational Database Based on Jena,Computer and Information Science, 3, pp.263-267, 2010.
[5]. C.Ramathilagam and M.L.Valarmathi, A Framework for OWL DL based Ontology Construction from Relational Database using Mapping and Semantic Rules , International Journal of Computer Applications (0975 – 8887) Volume 76– No.17, August 2013 ..

Abstract: With the increasing demand for need of retrieval of images based on different properties, characteristics there has been tremendous research going on in the field of Content-based image retrieval (CBIR), also known as query by image content. Content here is referred to visual features such as colour, texture,shape, spatial layout of an image. This paper proposes a novel approach wherein content based image retrieval is based on color and texture primarily implementing color histogram for color based and gabor filter for texture based retrieval. Colour histogram comprises of two colour models (RGB and HSV).............

Keywords –Colorhistogram, Gabor Filter,Hsv,Rgb, Quadhistogram

[1] Reshma Chaudhari, A. M. Patil, P. G. Student, Department of E.C.E, J. T. M. College of Engineering, Faizpur, Jalgaon, India, Professor, Department of E.C.E, J.T. M. College of Engineering, Faizpur, Jalgaon, India, 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.
[2] K. Haridas, Dr. Antony Selvadoss Thanamani, Ph.D Scholar, Department of Computer Science , NGM College Pollachi HOD, Department of Computer Science (Aided), NGM College. Well-Organized Content based Image Retrieval System in RGB Color Histogram, Tamura Texture and Gabor Feature. Pollachi International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 10, October 2014 .
[3] A.Kannan,Dr.V.Mohan,Dr.N.Anbazhagan, "Image Clustering and Retrieval using Image Mining Techniques", IEEE International Conference on Computational Intelligence and Computing Research, 2010.
[4] Cheruvu Mahammad Ibraheem, Dr. G. Umamaheswara Reddy M.Tech (Communication Systems), Department of E.C.E., S.V. University, Tirupati, Content Based Image Retrieval using HSV Color, Shape and GLCM Texture International Journal of Advanced Research in Computer and Communication Engineering Vol. 4, Issue 10, October 2015.
[5] Ms. Pragati ashok deole, prof. Rushi longadge m. Tech. (cse) in G. H. Raisoni Academy of Engineering and Technology, Nagpur (MS) India Content Based Image Retrieval using Color Feature Extraction with KNN Classification International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology

Abstract: In wireless ad hoc networks providing privacy and maintaining the individual nodes is challenging because of node mobility and changing of topology in the networks. In this paper we are intended to provide the privacy and security to the data. Channel error and malicious packet dropping are two cause of packet drop in the wireless ad hoc network. Existing techniques uses cryptographic methods to record the forwarded packets to detect the packet loss but these are applicable only when the packets are highly selective. In this the link errors may not be significantly smaller than the packet dropping rate of the insider attack. . The main aim is to find out whether the packet loss is due to connection...........

Keywords:- Homomorphic linear authenticator (HLA), Entropy method, Malicious node detection, Packet dropping, Signature generation.

[1]. Tao shu and marwan krunz ,privacy- preserving and truthful detection of packet dropping attacks in wireless ad hoc networks ieee transactions on mobile computing, vol. 14, no. 4, april 2015
[2]. J. N. Arauz, 802.11 Markov channel modeling, Ph.D. dissertation,School Inform. Sci., Univ. Pittsburgh,Pittsburgh, PA, USA,2004.
[3]. [3] G. Ateniese, S. Kamara, and J. Katz, Proofs of storage from homomorphic identification protocols, in Proc.Int. Conf. Theory Appl. Cryptol. Inf. Security, 2009, pp. 319333
[4]. L. Buttyan and J. P. Hubaux, Stimulating cooperation in selforganizing mobile ad hoc networks, ACM/Kluwer Mobile Netw. Appl., vol. 8, no. 5, pp. 579–592, Oct. 2003.
[5]. K. Balakrishnan, J. Deng, and P. K. Varshney, TWOACK: Preventing selfishness in mobile ad hoc networks, in Proc. IEEE Wireless Commun. Netw. Conf., 2005, pp. 2137–2142

Abstract: Visual impairments, as well as other physical and cognitive disabilities, imply a certain degree of dependency in ordinary task performance, such as shopping in a retail store. Ambient assisted living (AAL) technologies have tried to encourage the independence of impaired or elderly people. IN addition to home assistance, daily activities such as shopping are of interest in any AAL scenario that attempts to solve open problems such as navigation or unassisted indications. Visually impaired people might have problems identifying the object with which they want to interact............

Keywords: AAL, IOT, RFID Tag, RFID Reader

[1] www.businessinsider.com/what-is-the-internet-of-things-definition-2016-8 Dec 19, 2016
[2] www.technovelgy.com/ct/technology-article.aspRFID stands for Radio-Frequency Identification.
[3] https://www.barcodesinc.com/articles/barcode-technology.htm

[4] http://rfid.thingmagic.com/rfid-blog/bid/36709/RFID-for-Document-Management
[5] Noel James et al., "Smart Shopping Facilitator For Blind", International Journal of Engineering Research in Electrical and Electronics Engineering (IJEREEE) Vol 1, Issue 3, April 2015.
[6] Jethava, Hiren, Sameena Zafar, and MukeshSaini. "Electronic Shopping Cart Facility for Blind People Using USB Firmware." International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 6, June 2014)

Abstract: The main objective of this system is to develop a system, which is used for ATM security applications. Card-less ATM is a desktop application where fingerprint of the user is used as an authentication. The user has to login using his fingerprint and a unique pin number to do any banking transactions. The fingerprint features are unique for each human being so the user can be identified uniquely and is also the safe and secure method.

Keywords: ATM, biometric, fingerprint scanner, pin, security.

[1]. Fingerprint Recognition using Image Segmentation by Sangram Bana and Dr. Davinder Kaur.
[2]. An Identity Authentication System using Fingerprint by Anil Jain , Salil Prabhakar, Lin Hong and Sharath Pankanti.
[3]. ATM Transaction Using Biometric Fingerprint Technology by Mahesh Patil, Sachin Wanere, Rupesh Malghane and Aashay Tiwari.
[4]. An Introduction to Biometric Recognition by Anil Jain , Salil Prabhakar and Arun Ross.
[5]. Multimodal Biometrics by Arun Ross and Anil K Jain.

Abstract: The most important task of a soldier is to guard the nation and they do it efficiently. Every person know about this fact. They serve and only serve and sometimes die serving, simply obey the orders what you get from authorities. Never say no, never be demanding and this is much necessary for army to function properly. Actually they have to deal with their civil and military life both at the same time. They are posted in harsh terrains, Sometimes Himalayas, sometime desert and sometime in water. Soldiers die every day and no one gives any kind of help.................

Keywords: Soldier,Families, Donation, Help, Security

[1]. Souvik Roy and P. Venkateswaran ," Online Payment System using Steganography and Visual Cryptography",IEEE Trans, vol. 18, no. 6, 2014
[2]. Anti-Phishing Working Group (APWG), "Phishing Activity Trends Report, 2013," http://docs.apwg.org/reports/apwg_trends_report_q2_2013.pdf International Journal of Engineering Science and Computing, May 2016 4874 http://ijesc.org/
[3]. Jihui Chen, XiaoyaoXie, and Fengxuan Jing, "The security of shopping online," Proceedings of 2011 International Conference on Electronic and Mechanical Engineering and Information Technology (EMEIT), vol. 9,pp. 4693-4696, 2011.
[4]. L. Zhang, H. Wang, and R. Wu, "A high capacity Steganography scheme for JPEG 2000 baseline system", IEEE Trans. Image Process vol. 18, no. 8, 2009.

Abstract: Sentiment Analysis is an evolving field of research in text mining field. Nowadays, the opinions expressed through reviews are increasing day by day on the web. It is practically unfeasible to analyze and extract opinions from such huge number of reviews manually. To solve this problem an automated opinion mining approach is needed. Extraction of mood from texts is a demanding task as it involves understanding the underlying semantic. One aspect of research which is considered in this paper is to classify a given tweet/paragraph whether it is of Positive............

Keywords: AFINN, Machine learning, Product reviews, Sentiment analysis, Valence..

[1]. P. Tripathi, S. Kr. Vishwakarma, A. Lala ,"Sentiment Analysis of English Tweets Using RapidMiner," 2015IEEE International Conference on Computational Intelligence and Communication Networks.
[2]. T.C. Chinsha , S. Joseph " A Syntactic Approach for Aspect Based Opinion Mining," Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing.
[3]. M. Gupta, A. Dalmia, A. Jaiswal and C. T. Reddy ,"Sentiment Analysis in Twitter".
[4]. X. Fang and J. Zhan," Sentiment analysis using product review data" Springer. 2015.
[5]. F. A. Nielsen," A new ANEW: Evaluation of a word list for sentiment analysis in microblogs," DTU Informatics, Technical University of Denmark, Lyngby, Denmark..