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Building high secured software components is very important for component-based software projects. The confidentiality of software is one of the important factors determining the security of components. Estimating confidentiality near the beginning in the software development life cycle, particularly at design phase, may help the designers to integrate required highly secured for improving overall security of the developed software. In this paper researcher introduced a metric based model “Confidentiality Assessment Model (CAMOOD)”. This model measure the confidentiality induced by the use of various object-oriented design concepts like data hiding, aggregation, inheritance, coupling and cohesion. Herein, we compared our measurement results with various contributions.

Software E-Security, Confidentiality, Security Factors

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Surabhi Saxena, Devendra Agarwal, "Confidentiality Assessment Model to Estimate Security during Effective E-Procurement Process," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.361-365, 2018.

Monitoring of dynamic environments that change rapidly with time is the prime application of wireless sensor networks. This change of behaviour is reasoned to either certain external factors or limitation of system designs itself in unpredicted causality. To adapt such conditions, machine learning techniques are deemed to be beneficial in eliminating the need for unnecessary redesign. Moreover, the techniques based on machine learning encourages many practical solutions to maximize usages of resource and thus enhances the lifespan of the sensor network. In this paper, an extensive literature is furnished over machine learning techniques that are used to address the issue of node localization in wireless sensor networks (WSNs). Strengths and weaknesses of each of the proposed algorithm in literature have been analysed and evaluated against the problem it has been developed. A comparative table is also presented to guide future designers in developing machine learning solutions suitable for specific application challenges in localization.

Wireless sensor networks, machine learning, localization, clustering, data aggregation

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S. Pandey, "Localization Adopting Machine Learning Techniques in Wireless Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.366-374, 2018.

The key qualities of distributed computing are the capacity of scaling assets basically endlessly, the ability to pay just when an asset is really required, and the disposal of extensive forthright expenses for clients [1,2]. What`s more, low costs and usability urge ventures to use distributed computing to have their IT framework. Distributed computing is offered by cloud suppliers, among which the most conspicuous illustrations are Amazon Web Services (AWS) , Google Cloud , and Microsoft Azure . Each cloud supplier has distinctive evaluating systems; be that as it may, for processing assets they offer two classes of items: ondemand cases and saved examples. On-request cases are virtual machines made and paid for just when used. A cloud client includes and expels a request example with greatest adaptability. Then again, held cases are computational assets saved and paid for a specific period, with a forthright expense. The last class requires a larger amount of duty for the client; in this manner, if broadly used, they result to be less expensive amid a long haul usage. All together stay away from pointless costs, clients of distributed computing need watchful arranging. On one hand saved occurrences are helpful for fetched reserve funds. Then again, if held occurrences are underutilized, they create superfluous expenses. As of now, specialists have broadly examined the field of cost enhancement in distributed computing. A standout amongst the most encouraging strategies is to use Integer Programming to demonstrate the enhancement issue [3, 4]. Different creators misuse a two-advance approach: to start with, they propose a request forecaster and after that, they plan to locate an ideal arrangement with transformative algorithms[5,6]. The paper assesses the proposed demonstrate utilizing information from an industry case, contrasting the execution and an brute-force approach.

Cloud Computing, Cost Optimization, Reserved Instances, Software as a service; Platform as a service; Infrastructure as a service

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B. Mahesh, "Cost Optimization Techniques in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.375-380, 2018.

The analysis of the Student academic performance in educational institutions is a crucial task to make managerial decisions and to impart quality education. The data pertaining to the educational institutions is increasing rapidly. Mining these large volumes of the data will help the management to make academia decisions. Predicting the academic performance of the student at an early stage of their course will help the academia to identify the merit students and also to put more efforts in developing remedial programs for the weaker students to improve their performance. In this paper, we applied k-means clustering algorithm for analysing the students result data and predicting the students’ performance.

Academic Performance, Data Mining, Student’s result data, clustering

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A Seetharam Nagesh, Ch V S Satyamurty, "Application of clustering algorithm for analysis of Student Academic Performance," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.381-384, 2018.

The rapid increasing of real-time applications in today’s IoT (internet of things) world progressively lead to several problem issues such as, data volume, velocity, variety, and value. The study reveals that around 80% data in today’s IoT world are unstructured and needs an extensive knowledge exploration framework to turn the massively produced data into cognitive values (knowledge) of goldmines. In contemporary IoT vicinities, the time to get knowledge is very slow and the applicability of the knowledge is very poor, so the knowledge researchers start looking new framework that deals with the problems of semantic knowledge analytics and inference. In a typical semantic knowledge analytic scenario, context specification, rule specification, and frame specification may be used to define the structural relationships of knowledge, where the contexts, rules, and frames are stored as specification of framework and sub-framework. In this work, we investigate the viability of a context and rule Analytic framework (CORA-framework) for trustful knowledge analytic and inference in the cloud centric IoT vicinities. We also investigate a knowledge inference case in order to estimate the probabilistic error analysis based on outlier prospect and the knowledge analytic precision based on the root mean square error prospect. The analysis and discussion suggest implementing an outlier analytic mechanism to increase CORA-framework accuracy with estimating the error prediction outcome.

IoT (internet of things), context and rule specification, outlier analytic, IoT knowledge analytic, cloud

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[7] Dagnino, Aldo, and David Cox. "Industrial Analytics to Discover Knowledge from Instrumented Networked Machines." Proceedings of the 26th International Conference on Software Engineering and Knowledge Engineering (SEKE’14), Vancouver, Canada. 2014.
[8] Chang, H. T., Mishra, N., & Lin, C. C., IoT big-data centred knowledge granule analytic and cluster framework for BI applications: a case base analysis. PloS one, 10(11), 2015.
[9] Mishra, N., Chang, H. T., & Lin, C. C. Sensor data distribution and knowledge inference framework for a cognitive-based distributed storage sink environment. International Journal of Sensor Networks, 26(1), 26-42,2018.
[10] Mishra N,. "In-network Distributed Analytics on Data-centric IoT Network for BI-service Applications", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN: 2456-3307, Volume 2, Issue 5, pp.547-552, September-October.2017.
[11] Patnaik, B. C., & Mishra, N. “A Review on Enhancing the Journaling File System”, Imperial Journal of Interdisciplinary Research, 2, no. 11 (2016)
[12] Chang, H. T., Yu-Wen Li., & Mishra, N. “mCAF: A Multi-dimensional Clustering Algorithm for Friends of Social Network Services”, Springer Plus, 2016.
[13] Chang, H. T., Liu, S. W., & Mishra, N. “A tracking and summarization system for online Chinese news topics”, Aslib Journal of Information Management, 67(6), 687-699,2015.
[14] Mishra, N., Lin, C. C., & Chang, H. T. “A Cognitive Adopted Framework for IoT Big-Data Management and Knowledge Discovery Prospective”, International Journal of Distributed Sensor Networks, 2015.
[15] Mishra, N., Lin, C. C., & Chang, H. T. “Cognitive inference device for activity supervision in the elderly”, The Scientific World Journal, 2014.
[16] Mishra, N., Chang, H. T., & Lin, C. C. “Data-centric Knowledge Discovery Strategy for a Safety-critical Sensor Application”, International Journal of Antennas and Propagation, Article ID 172186, 11 pages, 2014. doi:10.1155/2014/172186.

Nilamadhab Mishra, Kindie Alebachew, Bikash Chandra Patnaik , "Knowledge Analytics in Cloud Centric IoT Vicinities," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.385-390, 2018.

With the explosive growth of user generated messages, twitter has become a social site where millions of users can exchange their opinions. Sentiment analysis on twitter data plays an important role in finding public opinions which have provided an economical and effective way timely, which is very useful for decision making in various domains. A company can take the public opinion in tweets to obtain user review towards its products where a politician can adjust his position with respect to the opinion change of the public. There have been a large number of research studies and industrial applications in the area of public sentiment tracking and modeling. Millions of users give their opinions on Twitter, making it a valuable platform for tracking and analyzing public sentiment. Such tracking and analysis can provide critical information for decision making in various domains. So, it has attracted attention in both academic and industry. Previous researches showed that the tweet was classified appropriately only if the tweet would contain the exact same label as the training set. But this approach fails when the tweet contains a synonym or a variant of the label instead of the exact same label.

Classifier, Opinion Mining, Lexicon, Sentiment Analysis, Twitter

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S.S. Ansari, T. Diwan, "Survey on Tweet Segmentation and Sentiment Analysis," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.391-394, 2018.

Opportunistic void avoidance routing (OVAR) convention has been proposed for UWSNs. It is an any cast, geographic and entrepreneurial steering convention. Expanding consideration has as of late been given to underwater sensor networks (UWSNs) due to their capacities in the sea checking and asset revelation. UWSNs are looked with changed difficulties, the most remarkable of which is maybe how to proficiently convey parcels considering the majority of the limitations of the accessible acoustic correspondence channel. The proposed an improved directing convention, called opportunistic void avoidance routing (OVAR). This address the void issue and the vitality unwavering quality exchange off in the determination of sending set. OVAR exploits disseminated beaconing, builds the contiguousness chart at each jump and chooses a sending set that holds the best exchange off amongst unwavering quality and vitality proficiency. The one of a kind highlights of OVAR in choosing the hopeful nodes in the region of each different prompts the determination of the concealed node issue.

Underwater sensors, Opportunistic Routing

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K. Mithun Kumar, P. Varaprasada Rao, "A Survey on Enhanced Routing Protocol for Underwater Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.395-401, 2018.

Machine Translation provides a solution in breaking the language barrier so that humans can transform information, it is important application of Natural Language Processing There are many different languages spoken in this world. Among those language English is the global language. Though it is global language many people can’t understand English especially in rural areas of India. From the many years machine translation has been a topic of research. There are many methods and techniques for achieving the machine translation. In India many regional languages are spoken. The mother of all these native languages in India is Sanskrit. A great storage of knowledge with subjects like medicine, mathematics, Geography, Geology, Astronomy, philosophy and many others is kept alive and fresh in Sanskrit for thousands of years. Hence here we have chosen Sanskrit as the target language. Most of the literature, political documents etc. are available in English. So we have chosen English as a source language. This paper illustrates about the language translation mechanism which converts English text to Sanskrit text using Rule Based approach. Presently work on machine translation in India is performed at various locations like JNU, IIT Kanpur, CDAC Pune and many more.

Rule based dictionary approach, Parser, Bilingual dictionary, Formant Synthesizer. Morphological analyzer, Corpus based translation, English-to-Sankrit Transliteration

XI. References
[1] V.M.Barkade, “English to Sanskrit machine translation semantic mapper”, International Journal of Engineering Science and Technology Vol. 2(10), 2010, 5313-5318, 2010
[2] V.M Barkade, “English to Sanskrit Machine Translator Lexical Parser and Semantic Mapper”, National Conference On "Information and Communication Technology", NCICT-IOJ, 2010.
[3] Vimal Mishra, “Approach of English to Sanskrit machine translation based on case-based reasoning, artificial neural networks and translation rules”, International Journal of Knowledge Engineering and Soft Data Paradigms, 2010-12-01
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Authors Profile
Mr.P.R.Devale pursued Bachelor of Engineering in Computer Engineering from Walchand College of Engineering, Sangli (India) in 1992 and he pursued his Master of Engineering in Computer Engineering from Bharati Vidyapeeth Demmed Univesity College of Engineering, Pune (India) in 2004. Currently he is pursuing his Ph.D in Computer Engineering from Bharati Vidyapeeth Deemed University, Pune (India).
Mr.S.H.Patil pursued Bachelor of Engineering in Computer Engineering from Walchand Institute of Technology, Solapur (India) in 1989 and he pursued his Master of Engineering in Computer Engineering from University of Pune (India), in 1992. He has completed his Ph.D in Computer Engineering from Bharati Vidyapeeth Deemed University, Pune (India) in 2009. Currently he is working as Professor in the Department of Computer Engineering in Bharati Vidyappeth Deemed University College of Engineering, Pune (India).

P.R. Devale, S.H. Patil, "Machine Translation : Need of the Time," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.402-404, 2018.

CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) is a test to distinguish a human from a robot. There are different kinds of CAPTCHA available and there security varies accordingly such as text based CAPTCHA, picture based CAPTCHA, 3D CAPTCHA, Audio CAPTCHA and Gaming CAPTCHA. This paper is based on gaming CAPTCHA and gaming CAPTCHA may have static object and targets, as well as dynamic, but only dragging the object to the target is not supposed to be the best security because nowadays attacking level has been raised. CAPTCHA should be more advanced and analytical for best security in the field of CAPTCHA. This paper proposed an advanced gaming CAPTCHA which is more advanced and analytical or intellectual. And this gaming CAPTCHA is often easy and interactive for human and impossible for robot. This system took the CAPTCHA into another level.

Gaming CAPTCHA, Puzzle, Robot, Action Script, WAMP Server, MySQL

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[2] Jing-Song Cui, Jing-Ting Mei, Xia Wang, Da Zhang, Wu-Zhou Zhang, “A CAPTCHA Implementation Based on 3D Animation”, IEEE Transaction, 2009.
[3] Chun-Ming Leung, “Depress Phishing by CAPTCHA with OTP”, IEEE Transaction, 2009.
[4] Aadhirai R, Sathish Kumar P J and Vishnupriya S, “Image CAPTCHA: Based on Human Understanding of Real World Distances”, IEEE Transaction, 2012.
[5] Song Gao, Manar Mohamed, NiteshSaxena and Chengcui Zhang, “Gaming the game: Defeating a game CAPTCHA with efficient and robust hybrid attacks”, IEEE Transaction, 2014.
[6] ArtemShumilov, AndreyPhilippovich, “Cloud-Based CAPTCHA Service”, IEEE Transaction, 2016.
[7] Vipin Kumar and Atul Barve, “Dynamic Object and Target based Gaming CAPTCHA for Better Security Analysis”, International Journal of Computer Applications (0975 – 8887) Volume 162 – No 5, 2017.

Madhav Chaturvedi, Ankur Taneja, "Advanced Gaming CAPTCHA for Better Security Concern," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.405-408, 2018.

Part-of-speech (POS) tagging plays significant role in almost every natural language processing task. This paper addresses a problem of POS tagging for Marathi language. Marathi is free word order, morphologically rich and highly inflectional Indian language. Supervised learning method that uses Hidden Markov Model is implemented to mark Marathi text using POS tags. The dataset required for training the algorithm consists of 12,000 Marathi sentences comprising news from popular Marathi newspaper. The algorithm for POS tagging predicts the tag for current word using the previous word tag pair. The POS tagging system has reported 86.61% accuracy in predicting correct POS to the words.

Marathi, HMM, POS, Part of Speech, Tagset, Supervised learning

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[6] H B Patil, A S Patil and B V Pawar. “Part-of-Speech Tagger for Marathi Language using Limited Training Corpora”. IJCA Proceedings on National Conference on Recent Advances in Information Technology NCRAIT(4), 2014, pages 33-37.
[7] Pallavi Bagul, Archana Mishra, Prachi Mahajan, Medinee Kulkarni, Gauri Dhopavkar, "Rule Based POS Tagger for Marathi Text". In proceeding of: International Journal of Computer Science and Information Technologies, Vol. 5 (2) , 2014, 1322-1326.
[8] Jyoti Singh, Nisheeth Joshi, Iti Mathur “Part Of Speech Tagging Of Marathi Text Using Trigram Method”. International Journal of Advanced Information Technology (IJAIT) Vol. 3, No.2, DOI: 10.5121/ijait2013.3203.
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[10] Javed Ahmed Mahar, Ghulam Qadir Memon, “Rule Based Part of Speech Tagging of Sindhi Language”. In proceeding of International Conference on Signal Acquisition and Processing 978-0-7695-3960-7/10,2010 IEEE DOI 10.1109/ICSAP.2010.27.

Nita V. Patil, "POS Tagging for Marathi Language using Hidden Markov Model," International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.409-412, 2018.