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High speed and high quality communication is the requirement of users in the public environment for transmission of different forms of data. WiMax technology is able to provide the data at high communication rate and with higher bandwidth. The incorporation of MIMO technique in WiMax system not only provide robust platform to fading but boost up the system performance. In this paper, 2×2 WiMax MIMO architecture is simulated with specification of different modulation techniques (64-QAM,BPSK) and for different fading channels (Rayleigh, AWGN) by using MATLAB. The analysis results are generated in terms of BER rate. The simulation results identified that the communication in WiMax MIMO is achieved at lower BER rate.

WiMax, MIMO, Rayleigh, AWGN, Modulation Scheme, BER

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[20] B. Sahoo, R. R. Prasad and P. Samundiswary, "BER analysis of mobile WiMAX system using LDPC coding and MIMO system under Rayleigh channel," In the Proceedings of 2013 International Conference on Communication and Signal Processing, Melmaruvathur, 2013, pp. 514-518.
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Parul Sangwan, Vikas Nandal, "BER Performance Analysis of WiMax MIMO System Under Different Channel Conditions," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.394-400, 2018.

Social networks are simple graphs where nodes represent either the people or the groups and links represent their relationships. Social networks explicitly exhibit relationships among individuals and groups. It is used for trust calculation, information sharing and recommendation, ontology construction and relation and relevance detection. Semantic Web is not a separate web but it is an extension of the current web in which information has well-defined meaning enabling computers and people to work better with cooperation. Semantic web (SW) has proven to be a useful data integration tool, facilitating the meaningful exchange of heterogeneous data. Ontology is a tool for data integration. Social Tagging Systems (STSs) allow collaborative users to share and annotate many types of resources (webpages, songs, etc.) with descriptive and semantically meaningful information called tags. Our proposed system constructs social network among individuals based on users’ interest predicted from their tag usage in the Social Tagging System using semantic web.

Social Tagging System (STS), Social Network (SN), Semantic Web (SW), Randomized Singular Value Decomposition (RSVD), Recommendation, User interest

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R. Indra, M. Thangaraj, "Social Networking using Semantic Web with Social Tagging System," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.401-406, 2018.

IoT is the internet of things where various small utility based networks interconnect to each other. Thus, they can share the data amongst enormous connected devices and small IoT based network for utility share the data to the remote network. This way the network can have the vulnerability to various types of attacks. While there is an attack situation the network performance will be downgraded. The trust-based scheme has been used for detection of the Sybil and the Jellyfish attacker node. This technique will be based on self-cooperation between the nodes. Where each node mark the trust value of the other node. Only trusted nodes will be marked as the intermediate node. In consequently, no malicious node can be the part of the network. The performance can be enhanced using the trust based value technique. This performance has been measured under two different parameters like the end to end delay and the throughput.

Ad-hoc ,Sybil, Internet of Things. Jellyfish, ESCT, Trust Value , Security Challenges, Delay variance, end to end encryption,Throughput

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[6] M. Todd Gardner, Cory Beard, Deep Medhi ”Using SEIRS Epidemic Models for IoT Botnets Attacks” 2017 ISBN 978-3-8007-4383-4 pp 1-8 IEEE DRCN CONFERENCE 2017.

[8] Sapna Hans and Jitendra Kumar,” A Review on Jellyfish Attack in MANET”, 2015 Int. Journel of Engineering, Applied and Management Sciences Paradigms, Vol 24, Issue 01.
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Manveen Kaur, Jashanpreet Kaur, "Identification and Removal of Jelly-Fish Attack in IoT," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.407-414, 2018.

Cancer classification from gene expression data is one of the most challenging research areas in the field of computation biology, bioinformatics and machine learning as the number of clinically labeled samples are very few compared to number of genes present. Also the cancer subtype classes are often highly overlapping, imprecise, and indiscernible in nature. Various machine techniques have been developed and applied on gene expression data for cancer sample classification. Here in this article, an empirical study of cancer classification from microarray gene expression data is performed using fuzzy-rough nearest neighbour techniques where performance of four different types of classifiers viz., Fuzzy nearest neighbour, Fuzzy-rough nearest neighbour, Vaguely quantified fuzzy-rough nearest neighbour and Ordered weighted average based fuzzy-rough nearest neighbor are investigated. The experiments are carried out on eight publicly available real life microarray gene expression cancer datasets. To assess the results of the classifiers percentage accuracy, precision, recall, macro averaged F1 measure, micro averaged F1 measure and kappa are used. The comparative study of the investigated methods is also done using paired t-test. Fuzzy-rough nearest neighbour method is found to be better for most of the data sets for cancer classification.

Cancer Classification, Fuzzy-Rough set, Vaguely Quantified, Ordered Weighted Average, Microarray Gene Expression data

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Ansuman Kumar, Anindya Halder, "Cancer Classification from Gene Expression data using Fuzzy-Rough techniques: An Empirical Study," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.415-420, 2018.

Crystal Oscillators are key parts employed in several electronic circuits, similar to in portable applications, digital and microprocessor-based devices. so as to save lots of power, low-power consuming circuit is commonly desired. A high demand of oscillator in portable instruments leads to high performance crystal oscillators to implement in silicon chip. A 20 MHz Pierce crystal oscillator is designed in a 0.13m CMOS process using Mentor Graphics with 1V supply. This exhibits approximately a section noise of -60dB/Hz at one megahertz offset. This employed in communication system similar to Electronic Warfare system.

CMOS, Low Power, Crystal Oscillator, Pierce Oscillator

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P.L. Suryawanshi, V.R. Pawar, "Design of Low Power Pierce Crystal Oscillator Using CMOS Technology," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.421-423, 2018.

Software reliability is one of the main factors to measure the quality of software. Since software errors cause spectacular failures in some cases, we need to measure the reliability factor to determine the quality of software product, predict reliability in the future, and use it for planning resources needed to fix failures. Software reliability models are applicable tools to analyze software in order to evaluate the reliability of software. During the past twenty five years, more than fifty different models have been proposed for estimating software reliability but many of software practitioners do not know how to utilize these models to evaluate their products. In this paper we will present a survey on different models of software reliability and their characteristics.

Reliability Prediction, Non-Homogeneous Poisson Process, Failure Intensity

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Nishi, Dinesh Kumar, "A Review: Reliability Evaluation of Interlocking Software based on NHPP model," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.424-427, 2018.

Fingerprint analysis is the most essential part of human identification or human recognition. The biometric technique has been used to eye, facial, speech for recognition etc. In this paper we have discussion about the working of biometric system, pattern recognition. Review about the various technique used in finger print matching, image segmentation and its application. To mark the fingerprint from the image processing of Euclidean distance is required which will learn from the previous values and drive new values on the basis of current situations. In this paper, various techniques of image segmentation and fingerprint matching has been reviewed and discussed in terms of their outcomes.

Correlation, Minutiae, Gabor Filters, Neural Network

[1] Umesh Singh Tomar, Abhinav Vidwans, “A Review of Fingerprint Recognition by Minutiae’s Analysis” in IJEAIS (International Journal of Engineering and Information Systems) Issues, Vol. 1 Issue 8, ISSN: 2000-000X, October – 2017.
[2] Heli Shah, Rajat Arora, “A Machine Learning Approach for Enhanced Fingerprint Recognition Technique” in IJCA (International Journal of Computer Applications) Issues, Volume 176 – No, October 2017.
[3] Farah Dhib Tatar and Mohsen Machhout, “Improvement of the fingerprint recognition process” in IJBB (International Journal on Bioinformatics & Biosciences) Issues, Vol.7, No.2, June 2017
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[7] Neeraj Bhargava, Anchal Kumawat, Ritu Bhargava, “Fingerprint Matching of Normalized Image based on Euclidean Distance” in (International Journal of Computer Applications) Issue,Volume 120 – No.24, June 2015.
[8] Farah Dhib Tatar1 And Mohsen Machhout2, “Improvement Of The Fingerprint Recognition Process”, IJBB (International Journal on Bioinformatics & Biosciences) Issue, Vol.7, No.2, June2017
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[11] Heli Shah, Rajat Arora, “A Machine Learning Approach for Enhanced Fingerprint Recognition Technique”,IJCA (International Journal of Computer Applications) Issue,ISSN0975 – 8887 Volume176, No.6, October 2017

V K Choudhary, Krishna Malik, "A Review On Finger Print Detection Technique," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.428-432, 2018.

Internet of Things (IoT) can possibly enhance the way we associate with things. IoT imagines the possibility of all-inclusive availability of everything which is characterized as the worldwide system of remarkably identifiable and addressable savvy things representing the capacity to interface and speak with other brilliant things. Each savvy protest comprises of a chip, handset module, sensors and power source. The greater part of the circumstances these frameworks need to manage low power and lossy systems (LLNs), where nodes have restricted memory, preparing capacity, and power. In any case, stringent Quality of Service (QoS) is required which is trying to give as the sensors are interconnected utilizing lossy connections. A routing protocol is required as these devices can be scattered in a spontaneous way. In this paper a novel hierarchal routing protocol has been proposed and compared with existing TEEN routing protocol. The proposed mechanism is implemented using MATLAB 2017 and compared with existing TEEN routing protocol.

IoT (Internet of Things), Energy, Routing, Cluster, Cluster head and TEEN (Threshold Sensitive Energy Efficient Sensor Network Protocol).

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Naresh Kumar, Manpreet Singh, "An Energy Efficient Hierarchical Routing Protocol in IoT," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.433-436, 2018.

Watermarking is used for protection of Rights, authentication and lots of other applications. The work deals with implementation of combined watermarking technique based on Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). This combined technique utilizes the benefits of both transforms; IWT and SVD. Here, the cover image is decomposed into four sub bands (LL, LH, HL and HH) using IWT; then SVD was applied to LL sub band. After embedding, IWT-SVD technique is tested under various attacks such as: noise addition, resizing filtering etc. and simulation results demonstrated that this combined technique is robust against those attacks. All simulation results display in tabular forms.

Digital Image Watermarking, IWT, SVD, PSNR,NCC

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Amit Kumar , Girish Parmar, Rajesh Bhatt, "IWT-SVD based Image Watermarking under Various Attacks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.437-441, 2018.

Along line of research has shown the vital significance of recognizing and observing company’s contestants. In the framework of this activity various questions are emerge like: In what way we justify and measure the competitiveness between two items? Who are the most important competitors of a specified item? What are the various features of an item that act on competitiveness? Inspired by this issue, the advertising and administration group have concentrated on observational strategies for competitor distinguishing proof and in addition on techniques for examining known contenders. Surviving examination on the previous has concentrated on mining near articulations (e.g.one product is superior then other product) from the web or other documentary sources. Despite the fact that such articulations can without a doubt be indications of strength, they are truant in numerous spaces. By surveying the various papers, we found the conclusion of basic significance of the competitiveness between two items on the basis of market sectors. In this paper, we state novel description of the competitiveness between two items, based on the market sector. This system estimation of competitiveness uses customer reviews of different domains, a plentiful source of information. This system shows an efficient approach for evaluating competitiveness in large review datasets and finding the top-k competitors. Our experiments are based on a corpus of Yelp.in, TripAdvisor.com, and Amazon customer reviews which states that the proposed methodology can extract comparative relations more precisely. In this paper, we state an efficient framework for the classification of reviews of mainstream domain using k-means clustering and Naïve Bayes algorithm. This system evaluates the competitiveness of two items from frequent item set to find top-k competitor using Apriori algorithm.

Data mining, Web mining, Information Search and Retrieval, K_means clustering, Naïve Bayes Classifier, Rule mining.

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A.A. Kushwah, Y.C. Kulkarni, "Identifying Competitors from Large Unstructured Dataset Using Naïve Bayes Classifier and Apriori Algorithm," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.442-450, 2018.