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Business rules could be look at different perspective in Information systems. A 4-dimensional rule framework is developed to describe rules in Business, Representation, System and Application dimension. Each dimension is laydown by a set of attributes to capture the essential characteristics of business rule. Business dimension talk about how business rule is in actual business. Representation dimensional talks about how to represent rule so that business people can easily write and understand rules. System dimension deal with the characteristics of tool developed to manage and store business rules for Business as well as Technical audience. The attributes of Application dimension describe the characteristics of executing rules in actual software system. OMG accepted a standard, namely, Semantics of Business Vocabulary and Business Rules, SBVR and claim that it is meant for business people. The authors developed a business rule model, called, Business Rules Oriented Business Model, BROBM to provide a comprehensive solution, start from the capturing business rule as see in business till the actual software application. In this paper, authors did a detailed analysis of SBVR and BROBM based on the attributes of 4-dimensional business rule framework.

Business rule, Business rule Manifesto, Business Motivation Model, 4- dimensional Business rule Framework, SBVR, Business Rules Oriented Business Model

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Design and Implementation of a Software System for High Level Business Rules” Accepted in International Journal of advanced science, Engineering and Information Technology, In press
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[19] Siji P D, M.L.Valarmathi, "Data Mining Approach for Feature Reduction Using Fuzzy Association Rule", International Journal of Computer Sciences and Engineering, Vol.5, Issue.11, pp.44-49, 2017.
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Deepak Kumar Sharma, Manish Mahajan, Dheerendra Singh, Naveen Praksh, "Analysis of Business Rules modeling Approaches using 4-Dimensional Business Rule Framework," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.135-142, 2017.

The shortcut tree routing has been advised to provide near prime routing path as well as maintaining the benefits of the ZigBee tree routing like low memory utility multi-hop routing capacity .But, in spite of the efforts to provide an efficient and reliable protocol, the unicast routing itself has the fundamental limitation in wireless environment due to loose, time period varying, and broadcast way of wireless medium. Such as, even one loose link on a path may result in the miscarriage of end-to-end packet delivery in wireless network setting. In this paper, we propose the rotatory shortcut tree routing that combines shortcut tree routing and rotatory routing. Instead of identifying a next hop node, this rotatory shortcut tree routing allows receiving nodes to compete to forward a packet with the primacy of remaining hops. Because it has acquired advantages of each protocol, it may offer reliable parcel conveyance benefit without any approach for multi-hop routing and forwarder candidate selection for rotatory routing.

ZigBee, Tree Routing, Hierarchical addressing, STR

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[4] Zhipeng Song, “ZigBee Network Tree Routing Algorithm based on Energy Balance”, International Journal of Smart Home Vol. 9, No. 4 (2015).
[5] ZigBee Document, “ZigBee Specification,” IEEE Trans.wireless system vol.Pp. 1–378, 2004
[6] T. Kim et al.,“neighbour table based shortcut tree routing in ZigBee wireless networks,” IEEE Trans. Parallel Diatribe. Syst., vol. 25, no. 3, pp. 706–716, 2014.
[7] Nessie Chakchouk, “A Survey on Opportunistic Routing in Wireless Communication Networks,” IEEE Commun. Surv. Tutorials, 2015.
[8] S. Chachulski et al., “Trading structure for randomness in wireless opportunistic routing,” ACM SIGCOMM Comput. Commun. Rev., vol. 37, no. 4, p. 169, 2007.
[9] J. Lou et al., “Opportunistic routing algorithm for relay node selection in wireless sensor networks,” IEEE Trans. Ind. Informatics, vol. 11, no. 1, pp. 112–121, 2015
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[11] Thomas L., “A Scheme to Eliminate Redundant Rebroadcast and Reduce Transmission Delay Using Binary Exponential Algorithm in Ad-Hoc Wireless Networks”, International Journal of Computer Sciences and Engineering, Vol.3, Issue.8, pp.1-6, 2017.

N.Durga Prasad, D.Sai Ganesh, "Rotatory Shortcut Tree Routing In ZigBee Networks," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.143-146, 2017.

Although the Internet has transformed the way our world operates, it has also served as a venue for cyberbullying, a serious form of misbehavior among youth. With many of today`s youth experiencing acts of cyberbullying [2], a growing body of literature has begun to document the prevalence, predictors, and outcomes of this behavior, but the literature is highly fragmented and lacks theoretical focus. Therefore, our purpose in the present article [1] is to provide a critical review of the existing cyberbullying research. This systematic review and meta-analysis [6][7] offers a synthesis of the relationship between cyber-victimization and educational outcomes of adolescents aged 12 to 17, including 25 effect sizes from 12 studies drawn from a variety of disciplines. The general aggression model is proposed as a useful theoretical framework from which to understand this phenomenon. Additionally, results from a meta-analytic review are presented to highlight the size of the relationships between cyberbullying and traditional bullying, as well as relationships between cyberbullying and other meaningful behavioral and psychological variables. A series of random-effects meta-analyses [12] using robust variance estimation revealed associations between cyber-victimization [4] and higher class presence problems (r = .20) and academic achievement problems (r = .14). Results did not differ by provided definition, publication status, reporting time frame, gender, race/ethnicity, or average age. Implications for future research are discussed within context of theoretical, critical, and applied discussions.

cyber-victimization, victimization, meta-analysis, adolescents, academic achievement, school attendance, Cyberbullying Detection, Text Mining, Representation Learning

[1]. P. Baldi, “Autoencoders, unsupervised learning, and deep architectures,” Unsupervised and Transfer Learning Challenges in Machine Learning, Volume 7, p. 43, 2012.
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[14]. P. Baldi, “Autoencoders, unsupervised learning, and deep architectures,” Unsupervised and Transfer Learning Challenges in Machine Learning, Volume 7, p. 43, 2012.
[15]. M. Chen, Z. Xu, K. Weinberger, and F. Sha, “Marginalized denoising autoencoders for domain adaptation,” arXiv preprint arXiv: 1206.4683, 2012.
[16]. T. K. Landauer, P. W. Foltz, and D. Laham, “An introduction to latent semantic analysis,” Discourse processes, vol. 25, no. 2-3, pp. 259–284, 1998.
[17]. T. L. Griffiths and M. Steyvers, “Finding scientific topics,” Proceedings of the National academy of Sciences of the United States of America, vol. 101, no. Suppl 1, pp. 5228–5235, 2004.
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Manorama Singh, Abhay Kumar, "Identification of Psychological Harassment Via Digital Communication Media," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.147-150, 2017.

Web mining is a tremendous growth in social networks for intent knowledge of various information’s, comments, reviews, tags about choosing concern life objects, there is an increasing demand for data prediction because of a different point of user interest i.e.,” think to best”. The users will be trusted to using these online reviews and to get information about the opinions of products from others. Due to the reviews product was successive based on threating of user point opinion regarding the given object. The social comment should the hidden sentiments of the user opinions. A most problematic challenge in web mining is to identify the sentiments and aspects opinion of the people to perform the data classification based on these features Opinion summarization. To propose a multilevel semantic pattern incremental algorithm (MSPI) with intent to divisive rank clusters which they analyze the hidden user opinion sentiments and classifies the user hidden points. Initially to preprocess the product reviews and to apply the multilevel semantic analyzer form extraction data points. The data points are ranked based on algometric rank clusters to optimized result case. The data sources to be taken for the social web from a customer review of the product list. In this paper, experiments were conducted to compare the performance of existing clustering and classification algorithm produce higher prediction rate based on hidden sentiment case reviews.

web mining, opinion mining, sentiment analysis, clustering, rank prediction

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[5] Blessy Selvam,"A Survey on Opinion Mining FrameWork", International Journal of Advanced Research in computer and communication Engineering, vol 2, Issue 9, 2013.
[6] B Vijay. Raut, .D. Londhe,” Survey on Opinion Mining and Summarization of User Reviews on Web” International Journal of Computer Science and Information Technologie, vol 17,issue 5,pp.564-579,2014.
[7] R Soni1, K. J. Mathai” Effective Sentiment Analysis of a Launched Product using Clustering and Decision Trees” International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 1,2016
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[9] H Suresh, G Raj . “A Novel Cluster-Based Unsupervised Technique for Twitter Sentiment Analysis”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 6, Issue 7,pp.345,362, 2017
[10] L.Zhu, A. Galstyan, “Tripartite Graph clustering for Dynamic Sentiment Analysis on Social Media”, International Social and Information Networks,’ vol 14, pp.1531-1542, June. 2014.
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[12] L .F .S. Coletta, N. F. F da Silva, E. R. Hruschka, E. R. Hruschka, “ Combining Classification and Clustering for Tweet Sentiment Analysis”,Brazilian journal on Intelligent Systems,vol 2,Issue 12,pp784,797 2016.
[13] M. Unnisa, A. Ameen, S. Raziuddin, “ Opinion Mining on Twitter Data using Unsupervised Learning Technique “, International Journal of Computer Applications, Vol. 148, No.12, pp.12-19, 2016.
[14] N. Pooranam, G. Shyamala, “A Statistical Method of Knowledge Extraction on Online Stock Forum Using Subspace Clustering with Outlier Detection”, International Journal of Innovative Research in Science, Engineering and Technology, Vol.5, Issue 5, May.2016.
[15] A.Shukla, R. Misra, “Sentiment Classification and Analysis using Modified K-Means and Naïve Bayes Algorithm”, International Journal of Computer Applications, Vol. 86, No.22, pp.43-58, 2015.
[16] Xiaolong Wang, Furu Wei, Xiaohua Liu, Ming Zhou, Ming Zhang,” Topic-Sentiment Analysis in Twitter: A Graph-based Hashtag Sentiment Classification Approach”, ACM, CIKM’11, October 24–28, 2011.
[17] Glasgow, Scotland, UK, 2011.Andrius Mudinas, Dell Zhang, Mark Levene,” Combining Lexicon and Learning based Approaches for Concept-Level Sentiment Analysis”, IEEE Transactions on Affective Computing, vol 4,issue 99,pp.15-32 ,2012.
[18] L.williams ,” Idiom based features in sentiment analysis: Cutting the Gordian knot”, IEEE Trans. On knowledge and data engineering, vol. 24, no. 4, 2012.
[19] D park, S.kim“ConceptVector: Text Visual Analytics via Interactive Lexicon Building Using Word Embedding” IEEE Transactions on Visualization and Computer Graphics , Vol 24, Issue 1, 361 – 370, 2018.
[20] R.Xia , J.Jiang, and H.He, “Distantly Supervised Lifelong Learning for Large-Scale Social Media Sentiment Analysis” IEEE transactions on affective computing, vol. 8, no. 4 ,pp. 751 – 770,2017

A. Muruganantham, S. P. Victor, "Analysis of Multilevel-Semantic Prediction based on User Point of Sentiment Opinion (MSP-UPSO) in Social Web Mining," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.151-158, 2017.

Now a days, most dangerous form of disease is melanoma. Melanoma is type of skin cancer that develops from melanocytic cells. Due to malignancy feature melanoma skin cancer is also known as malignant melanoma. Melanoma cancers have various stages which will increase the death rate of patients. So early detection and treatment of melanoma implicate higher chances of cure. Traditional methods for detecting skin cancer are painful, invasive and time consuming. Therefore, in order to overcome the above stated issues different techniques used for skin cancer detection. These techniques works on image so there is no physical contact with skin, so this is non-invasive. These techniques use Image Processing tools for the detection of Melanoma Skin Cancer. These techniques first pre-process the skin image which is followed by image segmentation. Feature extraction is performed on segmented lesion. The extracted features are used to classify the image as normal skin and melanoma cancer lesion.

Image Pre-processing, Segmentation, Feature Extraction, Classification, Melanoma Skin Cancer

[1] Z. Waheed, M. Zafar, A. Waheed, F. Riaz, “An Efficient Machine Learning Approach for the Detection of Melanoma using Dermoscopic
Images”, International Conference on Communication, Computing and Digital Systems (C-CODE), pp.316-319, 2017.
[2] O. Abuzaghleh, B. D. Barkana, M. Faezipour, “Noninvasive Real-Time Automated Skin Lesion Analysis System for Melanoma Early Detection and Prevention”, IEEE Journal of Translational Engineering in Health and Medicine, Vol.3, 2015.
[3] O. Abuzaghleh, B. D. Barkana, M. Faezipour, “SKINcure: A real time image analysis system to aid in the malignant melanoma prevention and early detection”, in Proc. IEEE Southwest Symp. Image Anal. Interpretation (SSIAI), pp. 85-88, 2014.
[4] Soumya R S, Neethu S, Niju T S, Renjini A, Aneesh R. P, “Advanced Earlier Melanoma Detection Algorithm Using Colour Correlogram”, International Conference on Communication Systems and Networks (ComNet), Trivandrum, pp.190-194, 2016.
[5] P. A. Somnathe , P. P. Gumaste, “A System for Classification of Skin Lesions in Dermoscopic Images”, International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.175-179, 2016.
[6] Suganya R, “An Automated Computer Aided Diagnosis of Skin Lesions Detection and Classification for Dermoscopy Images”, International Conference On Recent Trends In Information Technology, 2016.
[7] M. W. Rashad, M. Takruri, “Automatic Non-Invasive Recognition of Melanoma Using Support Vector Machines”, 978-1-5090-4568-6/16/$31.00 IEEE, 2016.
[8] S. Jain, V. jagtap, N. Pise, “Computer aided Melanoma skin cancer detection using Image Processing”, International Conference on Intelligent Computing, Communication & Convergence, pp.735-740, 2015.
[9] T. Y. Tan, L. Zhang, M. Jiang, “An Intelligent Decision Support System for Skin Cancer Detection from Dermoscopic Images”, International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), pp.2194-2199, 2016.

S.S. Mane, S.V. Shinde, "Different Techniques for Skin Cancer Detection Using Dermoscopy Images," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.159-163, 2017.

India is perched on the cusp of computerized development. The administration has defeated its depreciators with a hawk looked at center to accomplish this objective for the nation. It is currently up to organizations to guarantee they are prepared and arranged to load and attempt the open doors this advancement will bring. The Indian government has lodged on a program to transform the nation into an advanced economy. It has make open a progression of activities—from presenting Digital Locker, which takes out the requirement for individuals to convey printed versions of reports issued by the administration, to demonetization, which has impelled the utilization of computerized installments the nation over. The move towards an advanced economy is probably going to help enact a new rush of financial development, draw in greater venture, and make new employments, over numerous divisions. Notwithstanding, it additionally represents a major test, that of cybersecurity. With the move towards a computerized economy, expanding measure of buyer and national information will be put away carefully and an extensive number of exchanges will be done on the web, by organizations, people and also government divisions. In any case, it additionally represents a major test, that of cybersecurity. With the move towards a computerized economy, expanding measure of shopper and national information will be put away carefully and a substantial number of exchanges will be completed on the web, by organizations, people and also government divisions. That makes India a greater focus for digital lawbreakers and programmers. Different partners, particularly Indian organizations, should be better arranged to deal with this risk. National cybersecurity technique is a fundamental component as cybersecurity is expected to ensure also, empower computerized economy.

cybersecurity, Digital India, Online transaction, personal data security, national cybersecurity strategy, cyber threats, cybercrime.

[1] (October 2017) www.securingourecity.org
[2] (October 2017) www.ccdcoe.org
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Singh Anurag, Singh Brijmohan, "Cyber Security Policies for Digital India: Challenges & Opportunities," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.164-168, 2017.

Sorting algorithm has a great impact on computing and also attracts a grand deal of research. Even though many sorting algorithms are evolved, there is always a scope of for a new one. As an example, Bubble sort was first analyzed in 1956, but due to the complexity issues it was not wide spread. Although many consider Bubble sort a solved problem, new sorting algorithms are still being evolved as per the problem scenarios (for example, library sort was first published in 2006 and its detailed experimental analysis was done in 2015) [11]. In this paper new adaptive sorting method Paper sort is introduced. The method is simple for sorting real life objects, where the input list is almost but not completely sorted. But, one may find it complex to implement when time-and-space trade-off is considered.

Adaptive sort, Time complexity, Paper sort, Sorted list, Un-sorted list

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[11] N. Faujdar, S. Ghrera, “A Detailed Experimental Analysis of Library sort Algorithm”, INDICON, IEEE, pp. 1-6, 2015

Rina Damdoo, Kanak Kalyani, "An Adaptive Sorting Algorithm for Almost Sorted List," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.169-172, 2017.

“A breakthrough in machine learning would be worth ten Microsofts”- -Bill Gates, Chairman, Microsoft The fact that humans have been progressing to reach a point where machine does most, if not all the mechanical labor is not new. What is new is the use of machines that is intelligent enough to replace humans in analyzing situations, portraying situations and scenarios, and then taking the (presumably) right decisions. This paper focuses on the use of machine learning that has replaced certain functions related to Human Resources Management, specifically in the IT industry. The paper is sectioned into five parts. In the first section the topic on hand is introduced, evolution of Machine Learning, introducing congruence of Machine Learning with HR functions such as Recruitment, Performance Management, Training & Development, Managing Attrition, Compensation Management etc. Section two, does a literature review that outlines the work previous written in this area i.e review of literature is done on this aspect. Section three takes a case study approach to highlight select IT companies that are using AI/ML for their HR functions. The fourth section attempts to design a simple Model from the literature review done. The fifth section presents the authors’ conclusion of the findings, and draws a futuristic picture.

Machine Learning (ML), Replacing HR with ML, AI and HRM

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Malathi Sriram, L. Gandhi, "Exploring the dynamica virtus of Machine Learning (ML) in Human Resource Management - A Critical Analysis of IT industry," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.173-180, 2017.

Biometric is widely used as proper authentication of a person in an organization, Institute and at much more places. This is considered as original identification of one by offering different biometric techniques which includes Hand Biometric, Fingerprint Biometric, Face Biometric, Signature Biometric, Ear Recognition and many more. Considerably, every technique of biometric includes one or other negative outcome that enables one to use more technique to develop pure authentication of person. This paper reflects the use of personal fingerprint scanning biometric that gives proper giveaway of features of person’s identification. The proposed research presents the content in very detailed way from introduction to biometric with specifically concentrated to fingerprint biometric and then integrating that real-time data with JAVA based software testing and developing innovative college student attendance system. The benefits of using proposed software give a new way to allot ids to professors and students with automation of sending attendance with customized options for need.

Biometric, Real time Attendance, Fingerprint Matching, Person identification, Arduino UNO

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Ravinder Kumar, Ramneek Kalra, "Desktop Biometric: The Easy way for Biometric Authentication," International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.181-186, 2017.

The amount of data is increasing now a days due to usage of portable resources like smart phones, tablets and many more for accessing social sites. The requirement to analyze such big data to extract meaningful data came into existence. Traditional methods have been explored by number of researchers to analyze such data. These methods removed faulty data, uncertain data or misclassified data for better analyses. But this leads to loss of data. There is need to take into consideration the rectification of uncertainty in aspect of big datasets also. So, In this paper we survey big data, some traditional methods for data analyses, advance methods for data analyses, issues related to these methods, misclassification concept, the survey of rectification techniques for high accuracy followed by bearer future scope.

Big Data, Misclassification, Machine Learning, Knowledge, Discovery, Mining

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