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.

Real time object detection and tracking: Histogram matching and Kalman filter approach

Abstract: In this paper we present an approach to develop a real-time object tracking system using a static camera to grab the video frames and track an object. The work presents the concepts of histogram matching and absolute frame subtraction to implement a robust automated object tracking system. Once the object is detected it is tracked using discrete Kalman filter technique. The histogram matching algorithm proposed here helps to identify when the object enters the viewing range of the camera and the absolute frame subtraction gives better results even with low quality videos. Such a tracking system can be used in surveillance applications and proves to be cost effective.

Cascadable current-mode first-order all-pass filter based on minimal components.

Abstract: A novel current-mode first-order all-pass filter with low input and high output impedance feature is presented. The circuit realization employs a single dual-X-second-generation current conveyor, one grounded capacitor, and one grounded resistor, which is a minimum component realization. The theoretical results are verified using PSPICE simulation program with TSMC 0.35 μm CMOS process parameters.

Visualization, analysis and structural pattern infusion of DBLP co-authorship network using Gephi

Abstract: DBLP (Digital Bibliography & Library Project) has the huge collection (around 3.4 million) of journal articles with its meta data, papers published in various national and international conferences, and other number of online publications in the field of computer science. Research data on DBLP increases enormously which arises many research problems in the domain of bibliography data network analysis such as citation index and co-authorship etc. For this purpose, many researchers' work is available on Data visualization, Data Mining, Data Analysis and prediction of the same. Here in this research paper, we are showing results of visualizing and analyzing DBLP Co-authorship network with the help of Gephi tool. We use DBLP dataset which is an undirected graph and contains 17280 nodes and 58539 edges. In this Graph nodes are taken as author and edges connect two nodes/authors according to their association in considered research papers' dataset. There will be more than one edge in between two nodes if both the researcher co-authored more than one paper. Attention has been devoted towards statistic based analysis with some varying measuring factors such as connected nodes, clustering coefficient, page rank, Average path length and Graph density. We apply Force Atlas2 for community generation and thereafter graph represent co-authorship network communities. We discuss and detail about collect, analyze and visualize co-authorship data which is further used for understanding the academic collaboration and finding the research communities for specific knowledge domain. Even we discuss about analysis of individual researcher and their community in the past through repetitive co-published work.