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In this work, a novel quaternary algebra has been proposed that can be used to implement an arbitrary quaternary logic function in more than one systematic ways. The proposed logic has evolved from and is closely related to the Boolean algebra for binary domain; yet it does not lack the benefits of a higher-radix system. It offers seamless integration of the binary logic functions and expressions through a set of transforms and allows any binary logic simplification technique to be applied in quaternary domain. Since physical realization of the operators defined in this logic has recently been reported, it has become very important to have a well-defined algebra that will facilitate the algebraic manipulation of the novel quaternary logic and aid in designing various complex logic circuits. Therefore, based on our earlier works, here we describe the complete algebraic representation of this logic for the first time. The efficacy of the logic has been shown by designing and comparing several common logic circuits with existing designs in both binary and quaternary domain.

Propositional Logic, Quaternary algebra, Quaternary Transformation, Sum-of-products

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Ifat Jahangir, Anindya Das, Masud Hasan, "Facile Algebraic Representation of a Novel Quaternary Logic," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.1-15, 2016.

n the world of information and communication technologies (ICT) ,the up-and-coming trends like (mobile, cloud and big data )are imposing new challenges for coming internet technologies where the high bandwidth ,ever-present accessibility and dynamic management exist .however the dependency of traditional networks on the manual configuration for network devices made it very error prone and hard task to accomplish. Recently one of the most hopeful solutions for future is software defined networks (SDN) which considered important technology for the management of complex and large scale networks which requires re-policing and reconfiguration between whiles. SDN achieves the reconfiguration easily by decoupling the data plane from control plane which enables the network devices (switches/ routers) to easily forward the packets depending on the flow table rules set by control plane .but the implementation of SDN in the wired domain doesn’t mean it will carry the same facility in the wireless domain as a wireless software defined (SDWN) which raises the radio –specific problems in relate to channel estimation and link isolation .

Software defined networks(SDN), software defined wireless network (SDWN), OpenFlow, Computer networks, Network provisioning

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Ruya j. Hussein, Murat Iskefiyeli , "A Survey: Network Regeneration by Software Defined Network (SDN and SDWN)," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.16-20, 2016.

Wireless sensor systems rearrange the gathering and investigation of information from numerous areas. Target tracking and edge interruption recognition applications are advantage from the specially appointed adhoc and self-association abilities of wireless sensor systems. Be that as it may, sensor systems conveyed in antagonistic situations must be strengthened against assaults by foes. This proposal inspects the limitations that make wireless sensor system observation testing and assesses calculations that give starting point respectability and information trustworthiness for wireless sensor systems. We propose another confirmation system. This performs superior to anything exiting strategies in terms of vitality utilization and deferral.

Authentication, Secret Key, Cryptography, Private Key, Public Key

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Madhavi Karanam, "Shared Secret Key with Random Value Authentication Scheme in Wireless Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.21-24, 2016.

The web is vast, diverse and dynamic and increases scalability, temporal data and multimedia issues respectively. The expansion of the Internet has given rise to a wealth of data as big data that is now available for user access. Different types of data must be managed and organized so that can be accessed by different users effectively and efficiently. The log analysis is an important issue for the web application. Log file is not to be over emphasized as a source of information in systems and network management. Whereas conduct efficient investigation and gathering of use full information need to correlate different log file. Task of analyzing event log files with the ever-increasing size and complexity of today’s event logs has become cumbrous to carry out manually. Nowadays latest spotlighted is automatic analysis of these logs files. This paper is a review of the basics of log analysis as big data in the web environment.

Web Application, Log File, Data Mining, Big Data

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Rahul Pateriya, Nishchol Mishra, Sanjeev Sharma, "A Survey: Analytics of Web Log File Using Map Reduce and Hadoop," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.25-30, 2016.

The aim of the present work is to demonstrate the concept of a packet- interleaved WDM system i.e; hybrid optical access network, which serve as the important candidate of next generation access networks. The entire network topology design was simulated in the OPTIWAVE development environment, consisting of transmitter, channel and receiver section. Each section is elaborated, while the analysis of measured values from topology is presented in the last part of the article.

Hybrid PON, WDM, TDM, APD

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Aasif Bashir Dar, Furqan Zahoor, Rakesh Kumar Jha, Neeraj Tripathi and Manish Sabraj, "An Analysis of 16 Channel 64 User Hybrid WDM/TDM Topology in the Optiwave Simulation Environment," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.31-35, 2016.

Clustering incomplete mixed numerical and categorical datasets is one of the challenging task. Traditional algorithms like k-prototype algorithm is used for mixed dataset, but is limited to only complete datasets. To handle such incomplete datasets we use modified squeezer algorithm, which includes the new dissimilarity measure for incomplete dataset with mixed numerical and categorical attribute values. In this modified squeezer algorithm it not only cluster the incomplete dataset, it also need not to input the missing values and need not to initialize any clusters at the beginning. This algorithm is compared with traditional k-prototype algorithm on benchmark datasets. The experimental results shows that the modified squeezer algorithm gives better accuracy than the traditional algorithm and also it overcomes the limitation of initial clusters.

mixed dataset, k-prototype, modified squeezer algorithm, dissimilarity measure

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M.V.Jagannatha Reddy, B.Kavitha, "Clustering Incomplete Mixed Numerical and Categorical Datasets using Modified Squeezer Algorithm," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.36-41, 2016.

Fraud refers to abuse of organization’s system illegally. Fraud is the crime or offense of deliberately deceiving in order to damage them to obtain property or services unjustly. Fraud can be accomplished through the aid of forged objects. The scope of this paper is to investigate whether data mining techniques can be used for detecting fraud.

Fraud, Data Mining,Neural Computing,Self Organizing Map

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[11] Yufeng Kou,Chang-Tien lu,Sirirat Sinvongwattana Yo-ping Huang,”Survey Of Fraud Detection Techniques "Proceedings Of 2004 IEEE Intern. Conf. On networking,Taipei,March 21-23,2004.
[12] K. Chikin and I. Shlyik, “Countering Illegal Transactions in Internet Purchasing Systems,” World of Cards 7 (2002): 15-21.
[13] Bhatla, Prabhu, and Dua, “Understanding Credit Card Frauds.”
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Swati Sucharita Barik, "A Novel Approach for Detection of Fraud Using SOM," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.42-46, 2016.

MANETs have very unique characteristics like dynamic topology, wireless radio medium, limited resources and lack of centralized administration; as a result, they are sensitive to different types of attacks in different layers of protocol stack. Each node in a MANETs is capable of acting as a router. Routing is one of the aspects having various security concerns. MANETs has no rigid line of defense, so, it is accessible to both legitimate network users and malicious attackers. In the presence of mischievous nodes, one of the main challenges in MANETs is to design the robust security solution that can protect MANETs from various routing attacks. This paper present survey of common attacks on network layer namely Black-hole, Wormhole and Gray-hole attack which are serious threats for MANETs. This paper also discusses some proposed solutions which help to detect and prevent these attacks. MANETs can operate in isolation or in coordination with a wired infrastructure, often via a gateway node participating in both networks for traffic relay. This flexibility, along with their self-organizing powers, is one of MANET's biggest strengths, as well as their biggest security weaknesses.

MANETs; Security; Attacks; Wormhole Attack; Black-hole Attack; Gray-hole Attack

[1] Umesh Kumar Singh, Shivlal Mewada, Lokesh Laddhani and Kamal Bunkar, “An Overview & Study of Security Issues in Mobile Ado Networks”, International Journal of Computer Science and Information Security (IJCSIS) USA, Vol-9, No.4, pp (106-111), April 2011
[2] Bo-Cang Peng and Chiu-Kuo Liang “Prevention techniques for flooding attack in Ad Hoc Networks”, IEEE, 2006
[3] Douglas S. J. De Couto, Daniel Aguayo, John Bicket, and Robert Morris, “A High-Throughput Path Metric for Multi-Hop Wireless routing”, in ACM Mobicom, 2003.
[4] D.M. Shila, and T. Anjali, “Defending selective forwarding attacks in WMNs”, IEEE International Conference on Electro/Information Technology, 2008, 96-101.
[5] X.P. Gao; and W. Chen, “A Novel Gray Hole Attack Detection Scheme for Mobile Ad-Hoc Networks[C]”, IFIP International Conference on Network and Parallel Computing Workshops, 2007, 209-214.
[6] Hongmei Deng, Wei Li, and Dharma P.Agrawal,“Routing Security in Wireless Ad Hoc Network”, IEEE Communications Magazine, vol. 40,Issue: 10, 2002
[7] Tamilselvan L, and Sankaranarayanan V, “Prevention of Black hole Attack in MANET”, Paper presented at the 2nd International Conference on Wireless Broadband and Ultra Wideband Communications, Sydney, Australia, 27-30 August 2007.
[8] Payal N. Raj and Prashant B. Swadas,”DPRAODV: A dynamic learning system against black hole attack in AODV based Manet”, International Journal of Computer Science Issues (IJCSI), Vol. 2, Issue 3, pp.: 54-59,
[9] Nital Mistry, Devesh C Jinwala, Member, IAENG, and Mukesh Zaveri, “Improving AODV Protocol against Black hole Attacks”, IMECS2010
[10] Hakem Beitollahi ⇑, Geert Deconinck (2012), Analysing well-known countermeasures against distributed denial of service attacks, Elsevier journal, vol 35, pages 1312-1332.
[11] Ningrinla Marchang a, Raja Datta (2008), Collaborative techniques for intrusion detection in Mobile ad-hoc networks, Elsevier journal, vol 6, pages 508-523.
[12] Sudip Misra, P. Venkata Krishna,_, Kiran Isaac Abraham, Navin Sasikumar, S. Fredun(2010), An adaptive learning routing protocol for the prevention of distributed denial of service attacks in wireless mesh networks, Elsevier journal,vol. 60,pages 294-306.
[13] Hung-Jen Liao, Chun-HungRichardLin, Ying-ChihLin, Kuang-YuanTung (2013), Intrusion detection system: A comprehensive review, Elsevier journal, vol.36, pages 16-24.
[14] Shelly Xiaonan Wu, Wolfgang Banzhaf (2010), the use of computational intelligence in intrusion detection systems: A review, Elsevier journal, vol.10, pages 1-35
[15] Adrian P. Lauf, Richard A. Peters, William H. Robinson(2010), A distributed intrusion detection system for resource-constrained devices in ad-hoc networks, Elsevier journal,vol.8,pages 253-266

Vaidya Omkar, Gautam Amiya, N Jaisankar, "A Study on Security Threats in Manets," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.47-53, 2016.

This paper conceptualizes a very important Software Process metric Cost of Quality (COQ) in different aspects and provides ways to optimize its value through prior activity planning and implementing the tasks according to the pre-planned effort distribution. The solution is built based on the analogy between effort and real life cost expenditure. While the solution is direct, it deals with multiple pre-requisites like understanding the components of COQ, setting its limits which ensures both quality and budget. There are multiple important sub concepts coming out of it like Systematic Planning, Wastage Elimination, Prioritization of Tasks, and Modulated Effort leading to generation of regulated COQ value as Output. This article showcases the Pilot Results as experienced from few real life projects from one organization and simulated the real life scenario through step by step utilization of the proposed solution. The result shows that proposed solution is able to reduce variance by approx. 99% while achieving the sigma level improvement of approx. 3σ. The solution also ensures many potential benefits in many aspects like identifying gaps / quality vulnerabilities based on previous performances, prioritization of task, maintenance of balance between Cost & Quality, controlled utilization of available resources, waste identification, quantification & elimination.

Cost of Quality, Wastage Elimination, MUDA Wastes, Cost-Quality Balance, Cost Optimization, Quality Vulnerability, Quality Maintenance Effort

[1] The Cost of Quality | 2012-11-02 | Quality Magazine, September 12 – 17 2016, The Cost of Quality.
http://www.qualitymag.com/articles/90842-the-cost-of-quality
[2] What is planning and why you need to plan, in_cr_ove’s TQM School: Cost Of Quality (COQ) by Sanjeev Dhawan.
http://www.tqmschool.com/articles/TQM%20-%20Cost%20of%20Quality.pdf
[3] Cost of Quality article shows how much it can be and the cost elements.
http://www.halfcostproducts.com/cost_of_quality.htm
[4] QUALITY DIGEST / ARTICLE / GODFREY, Quality Management: Cost of Quality Revisited by A. Blanton Godfrey.
http://www.qualitydigest.com/apr/godfrey.html
[5] Cost of Quality: Not Only Failure Costs, Arne Buthmann.
http://www.isixsigma.com/implementation/financial-analysis/cost-quality-not-only-failure-costs/
[6] Cost of Quality (COQ) – ASQ, Excerpted from The ASQ Quality Improvement Pocket Guide: Basic History, Concepts, Tools, and Relationships, Grace L. Duffy, ASQ Quality Press, 2013, pages 62–65.
[7] Quality Costs – Wikipedia, the free encyclopedia, 9 April 2016, at 20:38
https://en.wikipedia.org/wiki/Quality_costs
[8] Managing Quality: Modeling the Cost of Quality Improvement, Arthur B. Jeffery, University of South Alabama.
http://www.cameron.edu/uploads/images/4496/Article_-47x10.25.pdf
[9] Quality Costs-Four Types of Quality Cost-Prevention-Appraisal Costs|Internal-External Failure Costs-Definition|Examples.
http://www.accountingdetails.com/quality_costs.htm
[10] iSix Sigma: Defect Prevention: Reducing Costs and Enhancing Quality, Mukesh Soni
http://www.isixsigma.com/industries/software-it/defect-prevention-reducing-costs-and-enhancing-quality/
[11] Sakthi Kumaresh et. al., Defect Analysis and Prevention for Software Process Quality Improvement, International Journal of Computer Applications (0975 – 8887) Volume 8– No.7, October 2010.
http://www.ijcaonline.org/volume8/number7/pxc3871759.pdf
[12] The Importance of Daily and Weekly Planning.
http://www.lifehack.org/articles/lifestyle/the-importance-of-daily-and-weekly-planning.html
[13] What is planning and why you need a plan.
http://www.time-management-guide.com/planning.html
[14] 7 Wastes Muda Article on the Seven Wastes of Lean Manufacturing, August 29, 2003, David McBride
http://www.emsstrategies.com/dm090203article2.html
[15] The Seven Wastes | 7 Mudas | Lean Manufacturing Tools.
http://leanmanufacturingtools.org/77/the-seven-wastes-7-mudas/
[16] Transient State and Steady State Response of Control System | Electrical4u.com.
http://www.electrical4u.com/transient-state-and-steady-state-response-of-control-system/
[17] Steady state – Wikipedia, the free encyclopedia, 20 May 2016, at 09:25
https://en.wikipedia.org/wiki/Steady_state

[18] Transient response – Wikipedia, the free encyclopedia, 16 April 2016, at 18:18
https://en.wikipedia.org/wiki/Transient_response
[19] Affect of Six Sigma Methdology on Reliability and Quality of Product, IJCSE Research Paper Volume-3, Issue-8, E-ISSN: 2347-2693, Aug/30/2015,
Kumar Shashvat1*, Arshpreet Kaur2, Raman Chadha, Department of Computer Science and Engineering, Punjab Technical University, India.
http://www.ijcseonline.org/pdf_paper_view.php?paper_id=615&17-IJCSE-01238.pdf

Suvra Nandi , "Quality Maintenance Effort Optimization in Software Industry," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.54-65, 2016.

Mobile Ad hoc Network (MANET) is one of the most promising technologies in the recent years. In MANET, a wireless network is quickly formed using mobile nodes. Because of its characteristics such as open and undefined medium, limited resources, offering a secure data transmission in presence of malicious nodes in the network is main issues of the MANET. The black hole and gray hole attacks are major security threats in MANET, in which the packets are dropped in intermediate nodes. The main objective of this paper is to study the techniques used to eliminate the packet drop in intermediate nodes using malicious node detection techniques. In this paper, various malicious node detection methods such as Local anomaly detection and Cooperative anomaly detection , Fuzzy and wavelet transform based IDS system , Modified DSR protocol , Kullback-Leibler divergence approach, FireCol , hash function based method and cooperative bait detection scheme (CBDS) are studied and analyzed. The findings of this work proved that the cooperative bait detection achieves better results than the other approaches in terms of packet delivery ratio and end-to-end delay.

MANET, Black Hole Attack, Gray Hole Attack and Bait Detection Mechanism

[1] Jaydip Sen, M. Girish Chandra, Harihara S.G., Harish Reddy, P. Balamuralidhar, ”A Mechanism for Detection of Gray Hole Attack in Mobile Ad Hoc Networks”,IEEE, January 2007.
[2] Yu Chen, Kai Hwang, and Wei-Shinn Ku, "Collaborative detection of DDoS attacks over multiple network domains", IEEE Transactions on Parallel and Distributed Systems, Volume 18, Issue 12, pp. (1649-1662), December 2007.
[3] Bharat Bhargava, Ruy De Oliveira, Yu Zhang, and Nwokedi C. Idika, "Addressing collaborative attacks and defense in ad hoc wireless networks" IEEE International Conference on Distributed Computing Systems Workshops (ICDCS), pp. (447-450), June 2009. ISBN : 978-0-7695-3660-6
[4] Weichao Wang, Bharat Bhargava, and Mark Linderman, "Defending against collaborative packet drop attacks on MANETs", International Workshop on Dependable Network Computing and Mobile Systems (DNCMS 2009), New York, USA, Volume 27, 2009.
[5] Vishnu, K and Amos J. Paul, "Detection and removal of cooperative black/gray hole attack in mobile ad hoc networks", International Journal of Computer Applications, Volume 1, Issue 22 pp. (38-42), February 2010.
[6] Mohanapriya, M, Ilango Krishnamurthi , “ Modified DSR protocol for detection and removal of selective black hole attack in MANET” , Elsevier, pp. (530-538), February 2014.
[7] Yang Xiang, Ke Li, and Wanlei Zhou, "Low-rate DDoS attacks detection and traceback by using new information metrics", IEEE Transactions on Information Forensics and Security, Volume 6, Issue 2, pp. (426-437), January 2011.
[8] Jian-Ming Chang, Po-Chun Tsou, Han-Chieh Chao, and Jiann-Liang Chen, "CBDS: a cooperative bait detection scheme to prevent malicious node for MANET based on hybrid defense architecture", Wireless Communication, Vehicular Technology, Information Theory and Aerospace and Electronic Systems Technology (Wireless VITAE), 2nd International Conference, pp. (1-5). IEEE, February 2011.
[9] Jerome Francois, Issam Aib, and Raouf Boutaba, "FireCol: a collaborative protection network for the detection of flooding DDoS attacks", IEEE/ACM Transactions on Networking (TON) Volume 20, Issue 6 pp. (1828-1841), April 2012.
[10] Jian-Ming Chang, Po-Chun Tsou, Isaac Woungang, Han-Chieh Chao, and Chin-Feng Lai (2015), “Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A Cooperative Bait Detection Approach” IEEE systems journal, Volume 9, Issue 1, pp. (65-75), January 2015.

M. Nachammai and N. Radha, "Survey on Black Hole and Gray Hole Attacks in MANET," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.66-70, 2016.