Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Cluster analysis & Wireless sensor network. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Reflection/refraction pattern of quasi-(P/SV) waves in dissimilar monoclinic media separated with finite isotropic layer

Abstract: This paper concentrates on the study of reflection and refraction of incident quasi (P/SV) waves in dissimilar monoclinic media separated by an isotropic layer of finite thickness. It is shown that...

Sustainable Supply Chain Management: A Three Dimensional Framework and Performance Metric for Indian IT Product Companies

Abstract: In the current business environment firms have started conceding pressure from the government, international agencies and not-for-profit organizations to make their business activities more responsible towards environment as well as society. Their supply chain management has also imbibed environmental and social concern to its reincarnation as Sustainable Supply Chain Management (SSCM). This paper with help of integrative literature review, experience survey and case study method, develops a three dimensional SSCM framework and its performance metric for Indian IT product industry. This framework suggests Supply Chain (SC) actors on X-axis, Management/Economic (M) on Y-axis and Sustainability (S) on Z-axis. The three levels of Y progresses from operational to tactical and then strategic, whereas Z axis levels are innovation, environment and social. The framework identifies sub-dimensions of sustainability and their connectivity with supply chain process. This research also identifies and proposes the Management and Sustainability performance metric for suggested framework. This framework will help IT product companies to (re)design their SC and develop performance measures on identified metrics.

A comparative study of classification techniques by utilizing WEKA

Abstract: In software engineering, information retrieval which is also referred as data mining has attracted many researcher's attention. By the virtue of its definition, data mining is responsible for extracting relevant data from large volume of database or dataset. In this context, several techniques have been proposed in literature. Through this paper, an attempt to comparative analysis of various classification algorithms has been made. Such analysis has been done with the help of data mining tool named WEKA on dataset of alcohol consumption by school students. WEKA is a open framework programming tool consisting of various inbuilt classification algorithms like J48, Random Forest, Decision Tree, Random Tree, NaiveBayes, SimpleNaiveBayes, NaiveBayes, DecisionStump, etc. However, the comparison of these algorithms has been made with the help of approaches that include correctly classified, incorrectly classified, Accuracy and many others parameters.

Significance of Clustering Coefficient over Jaccard Index

Abstract: Link prediction is a key task to identify the future links among existing non-connected members of a network, by measuring the proximity between nodes in a network. Node neighbourhood based link prediction techniques are immensely used for prediction of future links. These techniques can be applied on various applications like biological protein- protein interaction network, social network, information network and citation network to predict the future links. Every network has got certain structural properties. For predicting the accuracy of future links, structural properties might play an important role. Current work is an effort to find out the correlation between structural properties of network and prediction accuracy. Positive Correlation will signify that knowing the structural properties of a Network will assist us to know the prediction accuracy in advance.