iosr-JCE   Volume-19 ~ Issue-1 ~ Jan-Feb 2017

Abstract: We present a simple linear regression model fit in the direction of self-similarity behavior of internet user's arrival data pattern. It has been reported that Internet traffic exhibits self-similarity. Motivated by this fact, real time internet users arrival patterns considered as traffic and the results carried out and proven that it has the self-similar nature by various Hurst index methods. The present study provides a mathematical model equation in terms linear regression as a tool to predict the arrival pattern of Internet users data at web centers. Numerical results, analysis discussed and presented here plays a significant role in improvement of the services and forecasting analysis of arrival protocols at web centers in the view of quality of service (QOS).

Keyword: long-range dependence, self-similarity, Poisson Process, Linear Regression, Hurst Index.

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[2]. J.Beran, M. S. Taqqu and W. Willinger, Long- range dependence in variable bit rate traffic," IEEE Trans. on Communications, Vol. 43, pp.1566-1579
[3]. M. Crovella and A.Bestavros, Self-Similarity in World Wide Web traffic: evidence and possible causes, IEEE/ ACM Trans. Networking, pp.835-846, 1997.
[4]. Vern Paxson, Sally Floyd, Wide Area Traffic: The Failure of Poisson Modeling, IEEE/ACM Trans. Networking, 3, pp.226-244, 1995.
[5]. Allan T. Anderson, Bo Friis Nielsen , A Markovian Approach for Modeling Packet Traffic with Long Range Dependence, IEEE Journal on Selected Areas in Communications, Vol.16, No.5, pp.719-732, June 1998.

Abstract: Malicious URLs have been universally used to ascend various cyber attacks including spamming, phishing and malware. Malware, short term for malicious software, is software which is developed to penetrate computers in a network without the user's permission or notification. Existing methods typically detect malicious URLs of a single attack type. Hence such detection systems are failed to protect the users from various attacks. Malware spreading widely throughout the area of network as consequence of this it becomes predicament in distributed computer and network systems

Keywords: Malicious URLs, Analyzer, Malware

[1]. ClamAV. Clam AntiVirus. http://www.clamav.net
[2]. J. Nazario. PhoneyC: A Virtual Client Honeypot.In Proceedings of the USENIX Workshop on Large Scale Exploits and Emergent Threats, 2009.
[3]. A. Ikinci, T. Holz, and F. Freiling. Monkey Spider: Detecting Malicious Websites with Low-Interaction Honeyclients. In Proceedings of Sicherheit, Schutz und Zuverlässigkeit, April 2008.
[4]. C. Whittaker, B. Ryner, and M. Nazif, "Large-Scale Automatic Classification of Phishing Pages", In Proceedings of the 17th Annual Network and Distributed System Security Symposium (NDSS‟10),San Diego, CA, Mar 2010.
[5]. Luca Invernizzi, Santa Barbara,Stefano Benvenuti,Paolo Milani,Comparetti Lastline,Vienna, "EVILSEED: A Guided Approach to Finding Malicious Web Pages," in IEEE Symposium on Security and Privacy 20-23 May 2012, pp 428 – 442.

Abstract: In the approach of pattern recognition, feature descriptions are of greater importance. Features are represented in spatial domain and transformed domain. Wherein, spatial domain features are of lower representation, transformed domains are finer and more informative. In the transformed domain representation, features are represented using spectral coding using advanced transformation technique such as wavelet transformation. However, the feature extraction approach considers the band coefficients..............

Keywords: Pattern recognition, orientation spectral resolution, wavelet transformation, spectral features

[1]. Te-Wei Chiang, Tien-Wei Tsai, "Content-Based Image Retrieval via the Multiresolution Wavelet Features of Interest", Journal of Information Technology and Applications Vol. 1 No. 3, December, 2006.
[2]. Y. M. Latha, B.C.Jinaga, V.S.K.Reddy, "Content Based Color Image Retrieval via Wavelet Transforms", International Journal of Computer Science and Network Security, VOL.7 No.12, December 2007.
[3]. Mohan kumar, Madhavan J, "Content Based Image Retrieval Using 2-D Discrete Wavelet with Texture Feature with Different Classifiers", IOSR Journal of Electronics and Communication Engineering, Vol. 9, Issue 2, 2014.
[4]. Q. Tian, N. Sebe, M.S. Lew, E. Loupias, T. S. Huang, "Content-Based Image Retrieval Using Wavelet-based Salient Points", SPIE Photonics West, Electronic Imaging 2001, Storage and Retrieval for Media Databases, January, 2001.
[5]. AlinaBanerjeea, AmbarDuttab, "Performance Comparison of Cosine, Haar, Walsh-Hadamard, Fourier and Wavelet Transform for shape based image retrieval using Fuzzy Similarity Measure", International Conference on Computational Intelligence: Modeling Techniques and Applications (CIMTA) Procedia Technology, Elsevier, 2013.

Abstract: In today's world one of the most integral part is the data. There is lots of scattered (unstructured) data around that is available. Enterprises deal with lots of data and there are requirements that need to be imposed on such data in terms of access, control and maintenance. In order to achieve these functionalities it is very important to structure the data. Structuring of data is part of data governance and this can be achieved by various technologies. Since any enterprise has large amount of data we need cloud for storing this data. This paper presents the way of using Google cloud services and google apps in ordered to obtain uniform good quality data that can be further used for analysis purpose.

Keywords: Data governance, Data structuring, Google apps, Google Cloud storage, MVC Architecture

[1]. http://www.webopedia.com/TERM/C/cloud_storage.html
[2]. MOHAMMAD FIKRY ABDULLAH and DR. KAMSURIAH AHMAD, "The Mapping Process of Unstructured Data to Structured Data" 3rd International Conference on Research and Innovation in Information Systems – 2013. [3]. TATYANA SVIRIDOVA, LARISA SVIRIDOVA AND BOGDAN TYMOSHENKO "GOOGLE APPS AS SOLUTION OF COMMUNICATION ISSUES IN EDUCATIONAL PROCESS" MEMSTECH'2011, 11-14 May 2011, Polyana-Svalyava (Zakarpattya), UKRAINE
[4]. https://developers.google.com/apps-script/add-ons/
[5]. https://en.wikipedia.org/wiki/Model%E2%80%93view%E2%80%93controller

Abstract: Why does large number of data warehousing projects fail? How to avoid such failures? How to meet out user's expectations and fulfil data analysis needs of business managers from data warehousing solutions? How to make data warehousing projects successful? These are some of the key questions before data warehouse research community in the present time. Literature shows that large numbers of data warehousing projects undertaken eventually result in a failure. In this paper, we have designed a framework named "Data Warehouse Development Standardization Framework" (DWDSF), to help data warehouse developer's community in implementing effective data warehousing solutions............

Keywords: Data warehouse failure, Data warehouse framework, Data warehousing practices, Operational System limitations

[1]. Rami Rifaieh, Nabila Aïcha Benharkat, "Query-based Data Warehousing Tool", DOLAP'02, November 8, 2002, McLean, Virginia, USA. Copyright 2002 ACM 1-58113-590-4/02/0011
[2]. STAMFORD, CONN February 24, 2005
[3]. Jukic, N., (2006), "Modeling Strategies And Alternatives For Data Warehousing Projects.", Communications of The ACM April
[4]. 2006/Vol. 49, No. 4, p-83-90
[5]. http://www.embarcadero.com,Tech Notes, "Why Data Warehouse Projects Fail", January 2008.

Abstract: Journey is an inseparable part of human life which is responsible for human civilization development.Worldwide a large portion of population daily travel for work, shopping, social reasons and many other purposes. Nowadays road accidents, hijacking, robbery, snatching, trap of fraud parties have increased in such a level that people are always concerned about the security and safety of life as well as property during journey. In maximum cases vehicle drivers are found involved with these incidents and victims can't complain to the related authority due to the lack of evidence.Also law enforcement agencies is unable to take proper action against these crimes due to the scarcity of adequate information..........

Keywords: GPS tracking, Journey Safety, Security, Share, Smartphone.

[1]. Peden M, Scurfield R, Sleet D, Mohan D, Jyder A, Jarawan E, Mathers C (Eds) (2004). World Report on Road Traffic Injury Prevention. Geneva: World Health Organization.
[2]. Peden M, Hyder AA, Road traffic injuries are a global public health problem, BMJ, 2002, 1153-54.
[3]. Arif A. Lowest motor vehicle but highest road accidents in Bangladesh, Amar Desh, Jan 14, 2012, page 1, column 6.
[4]. The Daily Star, Road crashes killed at least 8,642 last year, Report, January 10, 2016. (http://www.thedailystar.net/frontpage/road-crashes-killed-least-8642-last-year-199699, accessed 24 December, 2016)
[5]. Numbeo, Crime in Bangladesh, (December, 2016), (https://www.numbeo.com/crime/country_result.jsp?country=Bangladesh, accessed December 25, 2016).

Abstract: Swarm robotics is a new approach to the coordination of multirobot systems which consist of large numbers of mostly simple physical robots In this paper, we will discuss this emerging filed, Swarm Robots. This filed has many applications. We will also discuss these applications in detail.

Keywords: Robot, Intelligence, Swarm, Applications

[1]. Camazine, S., Deneubourg, J.L., Franks, N., Sneyd, J., Theraulaz, G., Bonabeau, E.: Self-Organisation in Biological Systems. Princeton University Press, NJ, USA (2001).
[2]. Beni, G., Wang, J.: Swarm intelligence. In: Proc. of the Seventh Annual Meeting of the, Tokyo, Japan (1989) 425–428.
[3]. Beni, G.: From swarm intelligence to swarm robotics. In S¸ahin, E., Spears, W., eds.: Swarm Robotics: State-of-the-art Survey. Lecture Notes in Computer Science 3342, Springer-Verlag (2005) 1–9.
[4]. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York, NY, USA (1999).
[5]. Dudek, G., Jenkin, M., Milios, E., Wilkes, D.: A taxonomy for multi-agent robotics. Autonomous Robots 3 (1996) 375–397.

Abstract: Synthetic Aperture RADAR(SAR) images get inherently affected by speckle noise which is multiplicative in nature. This noise affects the image spatial statistics and properties. Over the past several years, many SAR denoising algorithms have been developed to reduce speckle noise. Some of the standard speckle filters are Gamma MAP, Lee, Frost and Kuan filters. Further, these have also been modified to obtain better results after filtering, than their original counterparts. Apart from the standard speckle filters, advanced SAR filters like Block Matching 3 Dimensional (BM3D) are also present..............

Keywords: BM3D, Frost, Gamma MAP, Kuan, Lee, Quality Assessment, SAR, Speckle

[1]. D. A. Bhattacharya, "Speckle filtering/speckle statistics," ppt.
[2]. L. Gagnon and A. Jouan, "Speckle filtering of sar images - a comparative study between complex-wavelet-based and standard filters," SPIE Proc. conference Wavelet Applications in Signal and Image Processing V, 1997.
[3]. E. Nezry, "Adaptive speckle filtering in radar imagery," Thesis Paper, pp. 3–56, 2014.
[4]. J. S. Lee, "Digital image enhancement and noise filtering by use of local statistics," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-2, No-2, 1980.
[5]. R. Touzi, "A review of speckle filtering in the context of estimation theory," IEEE Transactions on Geoscience and Remote Sensing, vol. 40, pp. 2392–2404, 2002.

Abstract: Digital Image Processing is a very vast field It has many applications in every field and one such application is in drug industry. Drug Industry is leading industry. Manufacturing process in drug Industry is increasing day by day as we are dependent on these medicines. But these medicines might be defected, tablets may be broken, there may be missing tablet in a strip and consumption of such drugs might be dangerous. This paper shows different methods in digital image processing technique to find the defects in tablets. Four methods are used in order to detect the defect in tablet strip.

Keywords: Digital Image Processing, Morphology opening, Template Matching, Mathematical Manipulation, Euler's number

[1]. Huvaida Manzoor, Yogeshwar SinghRandhawa-Comparative studies of algorithms using Digital Image Processing in Drug Industry –published at: "International Journal of Scientific and Research Publications (IJSRP), Volume 4,Issue 4,April 2014 Edition".

[2]. Manzoor,Huvaida, and Yogeshwer Singh Randhawa. "Edge Detection in Digital Image Using Statistical Method."
[3]. Ştefan Oprea, Ioan Liţă, Mariana Jurianu, Daniel Alexandru Vişan, Ion Bogdan Cioc, "Digital Image Processing Applied in Drugs Industry for Detection of Broken Aspirin Tablets" Electronics,Communications and Computers Department, University of Pitesti Str.Targul din Vale Nr. 1 Pitesti, Romania,2008
[4]. El-Khamy,S.E., Lotfy,M., El-Yamany,N.A.,"A Modified Fuzzy Sobel Edge Detector",17. National Radio Science Conference, Feb.22-24 2000, Minufiya University, Egypt
[5]. Hardeep Kaur and Er.Nidhi Garg, "Inspection of Defective Pharmaceutical Capsules using Harris Algorithm", International Journal of Advances in Electronics Engineering,2009

Abstract: Since the Boko-haram insurgency, in 2009 armed conflicts have become the order of the day in North-eastern Nigeria leading to a high number of civilian and sometimes military casualties. For a while the whereabouts and tactics of fighting back the insurgency eluded the Nigerian military mainly because the insurgent are locals with a good knowledge of the terrain. Thus, making it easier to make forays on motorized vehicles and still elude capture. For the military to be able to undertake offensive and rescue mission campaigns with fewer military casualty, knowledge of the terrain to which personnel are being deployed is very crucial. Thus, the ability of a field commander to carry out a successful spatial terrain analysis using up-to-date satellite/aerial images could mean the difference between life and death...........

Keywords: Insurgency, Terrorism, Boko-haram, geospatial analysis, GIS, remote sensing, North-east, Nigeria.

[1]. Adebayo, H. (2015). 'Over 200 Boko Haram terrorists surrender — Nigerian Army'. Accessed: 3rd/dec/2015. Available: http://www.premiumtimesng.com/news/headlines/190597-over-200-boko-haram-terrorists-surrender-nigerian-army.html.
[2]. Adegbola, A.A. and Olayinka E.A. (1976). A review of range management problems in the Southern Guinea and Derived Savanna zones of Nigeria. Tropical Grassland Journal v10(1).
[3]. Adegbola,S.A. (1979). An Agricultural Atlas of Nigeria, Oxford, University Press, Oxford.
[4]. Adepoju M. O, Sadiya.T. B., Mohammed S. O., Halilu S. A., 1Ibrahim I., Shar J.T. (2015). Comparison and Analysis of the Pixel-based and Object-Oriented Methods for Land Cover Classification with TM+ Data. IOSR Journal of Environmental Science, Toxicology and Food Technology, 9(2.)
[5]. Akinfala, F. F., Akinbode, G. A., & Kemmar, I. (2014). 'Boko Haram and Terrorism in Northern Nigeria: (A Psychological Analysis)', British Journal of Arts and Social Sciences,Avail: http://www.bjournal.co.uk/BJASS.aspx, 17(1).

Abstract: Building secure stream cipher algorithm in fast and comfortable manner is consider point of interest for most of those interested in building encryption algorithms to conceal their information and prevent detection it by unauthorized persons. The main goal of this paper is to design a package to implement and evaluate most of stream cipher algorithms in fast, convenient manner. The package provides the ability to the designer to design stream cipher algorithms either visually or by C# programming language. The proposed package provides number of the components required to build stream cipher algorithm...........

Keywords: Design,Evaluating,NIST statistical tests, Package, Stream cipher algorithm

[1] Rainer A. Rueppel, Analysis and Design of Stream Ciphers (Berlin, Springer, 1986).
[2] Darrel Hankerson, Alfred Menezes, Scott Vanstone,Guide to Elliptic Curve Cryptography (New York, Springer, 2004).
[3] William Stallings, Cryptography and Network Security Principles and Practice (Boston, Pearson, 2011).
[4] Richard R. Brooks, Introduction to Computer and Network Security (Boca Raton, CRC Press, 2014).
[5] Christof Paar and Jan Pelzl, Understanding Cryptography a Textbook for Students and Practitioners (Berlin, Springer, 2010).

Abstract: The main purpose of data mining is to extract knowledge from large amount of data. Artificial Neural network (ANN) has already been applied in a variety of domains with remarkable success. This paper presents the application of hybrid model for stroke disease that integrates Genetic algorithm and back propagation algorithm. Selecting a good subset of features, without sacrificing accuracy, is of great importance for neural networks to be successfully applied to the area. In addition the hybrid model that leads to further improvised categorization...........

Keywords: ANN, Back Propagation algorithm, Data mining, Feed Forward Network, Genetic algorithm, Hybrid model, Neuron.

[1] Ms. Dharmistha D.Vishwakarma "Genetic Algorithm based Weights Optimization of Artificial Neural Network" International Journal of Advanced Research in Electrical ,Electronics and Instrumentation Engineering(2278-8875),Volume1,Issue 3,August 2012.
[2] P.Venkatesan ,V.Premlatha," Genetic Neuro Approach for classification", International Journal of Science and Technology (2224-3577)Volume 2 No.7,July 2012
[3] Kafka Khan ,Ashok Sahai ," A Comparison of BA,GA,PSO,BP and LM for Training Feed Forward Neural Networks in e - Learning Context"I.J.Intelligent System and applications,2012,7,23-29.
[4] Asha Gowanda Karegowada,A.S.Manjunath ," Application of Genetic algorithm optimized Neural Network Connection Weights for medical diagnosis of PIMA Indian Diabetes "International Journal on SoftComputing(IJSC),Volume2,No.2,May 2011
[5] D.Shanthi, Dr.G.Sahoo, Dr.N.Saravanan "Evolving Connection Weights of Artificial Neural Networks Using Genetic Algorithm with Application to the Prediction of Stroke Disease", International Journal of Soft Computing Year: 2009 | Volume: 4 | Issue: 2 | Page No.: 95-102