IOSR Journal of Computer Engineering (IOSR-JCE)

Sep. - Oct. 2016 Volume 18 - Issue 5

Version 1 Version 2 Version 3 Version 4 Version 5 Version 6

Paper Type : Research Paper
Title : Applying Back Propagation Algorithm for classification of fragile genome sequence
Country : India
Authors : Medha Patel || Dr. Devarshi Mehta || Dr. Patrick Patterson || Dr. Rakesh Rawal

Abstract: Most frequently occurring recurrent chromosomal translocation allied with all subtype of leukemia are available in Mitel Mann Data base. We have retrieved about 55 such genome sequence from TIC dB data base with 100% similarity score and got noncoding sequence of chromosome 9 and 22 as positive example of fragile site. Another 55 housekeeping genome sequence is taken for classification purpose. For content based analysis we have extracted 20 features of frequency density of mono nucleotide and dinucleotide. The network is designed by determining hyper parameters like number of hidden layer...........

Keyword: Back propagation, cancer classification, leukemia, non-coding sequence

[1]. Albano, F., Anelli, L., Zagaria, A., Coccaro, N., D'Addabbo, P., Liso, V., Rocchi, M. & Specchia, G. (2010). Genomic segmental duplications on the basis of the t (9; 22) rearrangement in chronic myeloid leukemia. Oncogene, 29(17), 2509-2516.
[2]. Aminzadeh, F., Shadgar, B., &Osareh, A. (20SS, 3(1), 11-20.
[3]. Basu, S., &Plewczynski, D. (2010). AMS 3.0: prediction of post-translational modifications. BMC bioinformatics, 11(1), 1.
[4]. Berretta, R., &Moscato, P. (2010). Cancer biomarker discovery: the entropic hallmark. PLoS One, 5(8), e12262.
[5]. Cho, S. B., & Won, H. H. (2003, January). Machine learning in DNA microarray analysis for cancer classification. In Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003-Volume 19 (pp. 189-198). Australian Computer Society, Inc..


Paper Type : Research Paper
Title : Design and analysis of the redundancy allocation problem using a greedy technique
Country : India
Authors : Souradeep Nanda || Siddharth Sharma || Piyush Kundnani || Anand Sanker Deb || Dr. C. Vijayalakshmi

Abstract: We present a very computationally light and fast approximation algorithm and then verify it with genetic algorithm and simulated annealing. We show that our algorithm is on par with GA and SA in terms of output produced while having a tightly bounded time complexity. Our algorithm works best when there is a strong positive correlation between the reliability of a component and its cost. We present two algorithms with the same essence. One of them is system cost bounded and the other is target reliability bounded. Our proposed algorithm works on a subsystem level redundancy instead of component level redundancy

Keyword: Redundancy Allocation Problem, Genetic Algorithm, Simulated Annealing, Greedy Algorithm

[1] Barlow, R. & Proschan, R. (1981). Statistical theory of reliability and life testing, Silver Spring, MD: Madison.

[2] Boland, P. J. & El-Neweihi, E. (1995). Component redundancy versus system redundancy in the hazard rate ordering. IEEE Transactions on Reliability 44, 614–619.

[3] Marco Caserta and Stefan Voß (2015). A Discrete-Binary Transformation of the Reliability Redundancy Allocation Problem

[4] Seyed Mohsen Mousavi, Najmeh Alikar and Seyed Taghi Akhavan Niaki (2015) An improved fruit fly optimization algorithm to solve the homogeneous fuzzy series-parallel redundancy allocation problem under discount strategies.

[5] Misra KB & Sharma U. An efficient algorithm to solve integer programming problems arising in system-reliability design. IEEE Trans Reliab 1991 ; 40(1):81–91


Paper Type : Research Paper
Title : Segmentation of Tumor Region from Brain Mri Images Using Fuzzy C-Means Clustering And Seeded Region Growing
Country : India
Authors : Harsimranjot Kaur || Dr. Reecha Sharma

Abstract: The detection of brain tumor is one of the most challenging tasks in the field of medical image processing, since brain images are very complicated and tumors can be analyzed efficiently only by the expert radiologists. Therefore, there is a significant need to automate this process. In this paper, a method for the automatic detection of the tumor from the brain magnetic resonance imaging (MRI) images has been proposed. For this, the region-based segmentation of the input MRI image is done............

Keyword: Brain tumor segmentation, FCM, Region growing, Wavelet decomposition

[1]. Aswathy, S. U., G. Glan Deva Dhas, and S. S. Kumar, "A survey on detection of brain tumor from MRI brain images", In Control, Instrumentation, Communication and Computational Technologies (ICCICCT), International Conference on, pp. 871-877, IEEE, 2014.
[2]. Gordillo, Nelly, Eduard Montseny, and Pilar Sobrevilla, "State of the art survey on MRI brain tumor segmentation", Magnetic resonance imaging, Elsevier, vol. 31, no. 8, pp. 1426-1438, 2013.
[3]. Viji, K.A. and JayaKumari, J., "Modified texture based region growing segmentation of MR brain images" In Information & Communication Technologies (ICT), IEEE Conference on, pp. 691-695, IEEE, April 2013. [4]. Ahmed, M.N., Yamany, S.M., Mohamed, N., Farag, A.A. and Moriarty, T. "A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data", IEEE transactions on medical imaging, vol. 21, no. 3, pp.193-199, IEEE, 2002.
[5]. Aswathy, S. U., G. Glan Deva Dhas, and S. S. Kumar, "A survey on detection of brain tumor from MRI brain images", In Control, Instrumentation, Communication and Computational Technologies (ICCICCT), International Conference on, pp. 871-877, IEEE, 2014.


Paper Type : Research Paper
Title : Enhanced Denoising Algorithm for Improving Quality of Objects in Frames for Video Surveillance
Country : India
Authors : P.Vijayakumar || A.V.Senthilkumar

Abstract: In the 21st century's security awareness scenario, video surveillance plays an important role in improving security to people and property. Fully automatic surveillance systems are much sought after by both public and government organizations. These systems perform surveillance in four steps, namely, object detection, tracking, classification and interpretation. After object detection, more often, the detected objects have noise and insignificant extra objects; the presence of which effects the performance of the subsequent steps like tracking and classification.............

Keyword: Denoising, Morphological Operations, Noise Detection, Object Enhancement, Video Surveillance System

[1]. https://www.privacyinternational.org/reports/india/iii-surveillance-policies, Last access on February, 2014.
[2]. Jhingan, H. (2011) Under surveillance, Express Computer, http://www.expresscomputer online.com/20110630/securitystrategies01.shtml, Last Access on February, 2014.
[3]. Security Concerns to Drive CCTV Demand in India (2010), http://www.rncos.com/Press_Releases/Security-Concerns-to-Drive-CCTV-Demand-in-India.htm, Last Access on February, 2014.


Paper Type : Research Paper
Title : Multi-Platform Inter-APP Communication Solution for IOT Services Implementation
Country : Saudi Arabia
Authors : Dr. Gasim Alandjani

Abstract: Technology has totally changed the culture and working of people. With every passing day it is gaining popularity and becoming one of the most important gadgets of our lives. Researchers are enthusiastically pursuing areas of research which can contribute to Internet of Things (IoT). Now a day's sensing communication, control and actuation is becoming more refined and available everywhere, there is momentous overlap in these communities, still there are some missing gaps that need to be filled and addressed for better understanding of communication among these real life objects. The paper give an overview for inter app communication for multi-platforms users who will be using different IOT Services .

Keyword: IOT, Smart City, Smart Homes, Virtual Architecture, IOT Stack, Smart Devices, Sensors, Smart Vehicle.

[1]. Atzori, L., Iera, A., &Morabito, G. The Internet of Things: a survey. Computer Networks, 54 (2010), 2787–2805.
[2]. Treffyn et al." Approaching a human-centered internet of things". 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration ACM, New York, NY, USA, 363-366.

[3]. C.P. Mayer. Security and Privacy Challenges in the Internet of Things. KiVS Workshop on Global Sensor Network, 2009.

[4]. P. Tavel. Modeling and simulation design. 2007.

[5]. Next Generation Mobile Networks http://www.ngmn.org/fileadmin/ngmn/content/images/news/ngmn_news/NGMN_5G_White_Paper_V1_0.pdf


Paper Type : Research Paper
Title : Transforming XML into Object-Relational Schema
Country : Morocco
Authors : Mustapha Machkour || Karim Afdel

Abstract: Recently, there is a vast increase in the use of XML for describing and exchanging data. To manipulate efficiently these data, it would be wise to use database systems which represent an appropriate tool to store and manage data. To have this purpose, we need to transform XML schema into database models such as relational and Object-Relational (OR). The aim of this work is to present a methodology that transforms an XML schema into the OR model.............

Keyword: Database model, Mapping, Object-Relational model, Transformation, XML.

[1] Informix, Http://Www-3.Ibm.Com/Software/Data/Informix/, 2003. .
[2] Alfred V. Aho, Monica S. Lam, Ravi Sethi, and J. D. Ullman, Compilers Principles, Techniques, & Tools, (in, 2nd ed, England: Pearson Education, 2007) pp. 42-50, 197-199, 204-205.
[3] Alfred V. Aho, Monica S. Lam, Ravi Sethi, and J. D. Ullman, Compilers Principles, Techniques, & Tools, (in, 2nd ed, England: Pearson Education, 2007) pp. 116-122,159-163.
[4] T. Bray, Paoli, J., Sperberg-Mcqueen, and a. M. C. M., E., Extensible Markup Language (Xml) 1.0 (Second Edition), W3C Recommendation. http://www.w3.orglTR2OOOlREC- XML-20001006l, 2000/10.
[5] E. Castro, D. Cuadra, and M. Velasco, From Xml to Relational Models, Informatica, vol. 21(4), pp. 505-519, 2010/12.


Paper Type : Research Paper
Title : Robust control for nonlinear uncertain descriptor systems
Country : Saudi Arabia
Authors : Mourad Kchaou

Abstract: The present paper considers the sliding mode control (SMC)design problem for nonlinear uncertain descriptor systems. The goal is todesign an adaptivesliding mode controllerto drive the trajectories of the resulting closed-loop system onto a prescribed sliding surface and maintained there for all subsequent times. The appealing attributes of this approach include: (i) the closed-loop system exhibits a strong robustness against nonlinear dynamics and (ii) the control scheme enjoys the chattering-free characteristic. An example is provided to illustrate our control strategy.

Keyword: Input nonlinearity, Descriptor systems, LMI, sliding mode control

[1]. Cui, W.; Fang, J.; Shen, Y. & Zhang, W."Dissipativity analysis of singular systems with Markovian jump parameters and mode-dependent mixed time-delays",Neurocomputing, 2013, 110, 121-127
[2]. Feng, Z.; Lam, J. &Gao, H."𝛼-Dissipativity analysis of singular time-delay systems"Automatica, 2011, 47, 2548-2552
[3]. Chang, J. "Dynamic output feedback integral sliding mode control design for uncertain systems", International Journal of Robust and Nonlinear Control, 2012, 22, 841-857
[4]. Li, F., Wu, L., Shi, P. and Lim, C. "State estimation and sliding mode control for semi-Markovian jump systems with mismatched uncertainties," Auomatica (51), 2015, pp. 385-393.
[5]. Liu, L., Pu, J., Song, X., Fu, Z. and Wang, X. "Adaptive sliding mode control of uncertain chaotic systemswith input nonlinearity," Nonlinear Dyn (76:1857-1865), 2014.


Paper Type : Research Paper
Title : A More Secure Position Based Graphical Password Authentication
Country : India
Authors : Mohd. Aqil Khan || YDS Arya || Gaurav Agarwal

Abstract: We are proposing a new pass-point graphical password authentication by using a simple virtual environment. Our virtual environment is influenced by a social networking site's game. In this system, user interacts with the virtual environment and user can generate sequence of interactions according to his /her choice which will gather by a background process. This process decides whether the user is authenticated user or a not, depending on which the system allows or denies accessing the resources............

Keyword: Graphical password; Pass-Point; Authentication; Position based Graphical password

[1] BBC News, Cash Machine Fraud up, Say Banks, Nov. 4, 2006.
[2] ATM fraud- Banking on your money - Dateline NBC - Consumer Alert http://www.msnbc.com
[3] S. Akula and V. Devisetty, "Image Based Registration and Authentication System," in Proceedings of Midwest Instruction and Computing Symposium, 2004.
[4] Handbook of Fingerprint Recognition by Davide Maltoni, Dario Maio, Anil K. Jain, Salil Prabhakar
[5] Regunathan Radhakrishnan, Nasir Memon - On The Security Of The Sari Image Authentication System 2002 Polytechnic University, Brooklyn


Paper Type : Research Paper
Title : Key Policy Attribute Based Encryption in Cloud Storage
Country : India
Authors : Prof. Dipa Dharmadhikari || Sonali Deshpande

Abstract: Cloud Computing is the rapid growing technology and enables highly scalable services to be easily consumed over the Internet on an as-needed basis. It is a kind of Internet-based computing that provides shared processing resources and data to computers and other devices. Cloud computing has become a highly demanded service or utility due to the advantages of high computing power, cheap cost of services, high performance, scalability, accessibility as well as availability. Some cloud vendors are experiencing growth rates of 50% per year but being still in a stage of infancy, it has pitfalls that need to be addressed to make cloud computing services more reliable and user friendly. Data sharing is an important functionality in cloud storage............

Keyword: Identity Based Encryption, Identity-Based Proxy Re-Encryption, key Policy Attribute Based Encryption. key Aggregate Cryptosystem.

[1]. Peter Mell, Tim Grance, "The NIST Definition of Cloud Computing", Version 15, 10-7-09. [2]. Robert Bohn ,http://www.nist.gov/itl/cloud/News/September 15, 2016.
[3]. Cheng-Kang Chu, Sherman S. M. Chow, Wen-Guey Tzeng, Jianying Zhou, and Robert H.Deng, "Key-Aggregate Cryptosystem for Scalable Data Sharing in Cloud Storage", IEEE, 2014.
[4]. Jinguang Han, Willy Susilo, Yi Mu, Jun Yan," Privacy-Preserving Decentralized Key-Policy Attribute-Based Encryption" IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 23, NO. 11, NOVEMBER 2012 .
[5]. F. Guo, Y. Mu, Z. Chen, and L. Xu, "Multi-Identity Single-Key Decryption without Random Oracles," Proc. Information Security and Cryptology (Inscrypt '07), vol. 4990, pp. 384-398, 2007.


Paper Type : Research Paper
Title : A Survey on Routing Protocols influencing Mobile Sink in enhancing life time of WSN for Data gathering
Country : India
Authors : S.Suseela || S. Jeevanantham

Abstract: Wireless Sensor Network is a group of specialized sensors have the ability to sense, monitor, communicate to the neighbors and recording conditions at assorted locations such as temperature, sound, pressure, security purpose etc. The sensed data's incurred for estimation and then forwarded to the neighbors. There are many challenging issues in WSN such as localization, synchronization, data aggregation, dissemination, database querying, architecture, middleware, security, power consuming, routing, abstractions and higher level algorithms. Maximizing the lifetime of energy dearth Wireless Sensor Networks is a very big challenging issue in the present context. An optimized solution is needed to increase the lifetime of the Wireless Sensor Networks.............

Keyword: Wireless Sensor Networks, Routing protocols, Data gathering, Data Dissemination, node life, Mobile Sink, power efficiency, challenges.

[1] I.F.Akyildiz,W.Su,Y.Sankarasubramaniam,E.Cayirci, Wireless sensor networks:asurvey, Elsevier, Computer Networks 38 (2002) 393–422.
[2] J. N. Al-Karaki and A. E. Kamal, "Routing techniques in wireless sensor networks: a survey", IEEE Wireless Communications, vol. 11, December (2004), pp. 6-28.
[3] X. Min, S. Wei-ren, J. Chang-jiang and Z. Ying, "Energy efficient clustering algorithm for maximizing lifetime ofwireless sensor networks", J AEU-International Journalof Electronics and Communications, vol. 64,(2010), pp.2 89–298.
[4] Abbasi, A.A.; Younis, M. A Survey on ClusteringAlgorithms for Wireless Sensor Networks. Computer Network. 2007, 30, 2826–2841.
[5] Suchita R.Wankhade1 and NekitaA.Chavhan, A ReviewOn Data Collection Method With Sink Node In Wireless Sensor Network, International Journal of Distributed andParallel Systems (IJDPS) Vol.4, No.1, January 2013.


Paper Type : Research Paper
Title : Study on Hadoop Cluster
Country :  
Authors : J. Alocious Jesintha Mary

Abstract: In today's world, require Data Recovery system is most challenging aspects in the internet or World Wide Webapplications. Now a day's evens a Tera Bytes (TB) and Peta Bytes(PB) of data is not enough for storing large chunks of database(DB). Hence IT industries use concept is known as Hadoop in their applications. This approach has been adopted in Cloud computing environment for unstructured data. Hadoop is an open source distributed computing framework based on java and supports large set of distributed data processing............

Keyword: Big data, Hadoop, Hadoop cluster, HDFS, Name node, Datanode, Job tracker, task tracker.

[1]. Apache. Hadoop. http://hadoop.apache.org/.
[2]. Luiz André Barroso and UrsHölzle.The Case forEnergy-Proportional Computing.Computer, 40(12), 2007.
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[4]. Jeffrey Dean and Sanjay Ghemawat. MapReduce: SimplifiedData Processing on Large Clusters. Commun.ACM, 2008.
[5]. Chang Fay et al. Bigtable: A Distributed Storage System forStructured Data. OSDI, USENIX, 2006.


Paper Type : Research Paper
Title : A study on Clustering Algorithms for XML Data Clustering
Country : India
Authors : S.Saranya || B.S.E.Zoraida

Abstract: Nowadays mining meaningful information from large scale web documents is more important to satisfy the user demand. XML and RDF documents are supporting the semantic information retrieval to interpret and extract meaningful information for user query. XML documents have light weight code and logical structure, which facilitate easy exchange of data values and structure information in terms of knowledge. Many mining techniques and algorithms are used to enhance the performance of XML information Retrieval. Classification (Supervised Learning) and Clustering (Unsupervised Learning) are the preprocessing techniques used to grouping up the similar data objects based on similarity criteria............

Keyword: Clustering, XML, Data Clustering.

[1]. Yuekui Yang, Yajun Du, Yufeng Hai, Zhaoqiong Gao, "A Topic-Specific Web Crawler with Web Page Hierarchy Based on HTML Dom-Tree", 2009 IEEE , Asia-Pacific Conference on Information Processing.
[2]. Dragos Arotaritei,Sushmita,Web mining: a survey in the fuzzy framework, Fuzzy Sets and Systems 148,p.5-19,2004.
[3]. LI Guoliang , FENG Jianhua, ZHOU Lizhu ," Keyword Searches in Data Centric XML Documents Using Tree Partitioning, Tsinghua Science and Technology, February 2009, 14(1): 7-18
[4]. Ritu Khatri, Kanwalvir Singh Dhindsa, Vishal Khatri, " Ivestigation and Analysis of New Approach for Intellignet Semantic Web Search Engines, IJRTE April 2012.
[5]. Amit Mishra, Sanjay Kumar jain, " A Survey on question answering system with classification, Journal of King Saud University - Computer and Information Sciences


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