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.

Comparative analysis of human matrix metalloproteinases: Emerging therapeutic targets in diseases.

Abstract: The identification of specific target proteins for any diseased condition involves extensive characterization of the potentially involved proteins. Members of a protein family demonstrating comparable features may show certain unusual features when implicated in a pathological condition. Advancements in the field of computational biology and the use of various bioinformatics tools for analysis can aid researchers to comprehend their system of work in primary stages of research. This initial screening can help to reduce time and cost of testing and experimentation in laboratory. Human matrix metalloproteinase (MMP) family of endopeptidases is one such family of 23 members responsible for the remodeling of extracellular matrix (ECM) by degradation of the ECM proteins. Though their role has been implicated in various pathological conditions such as arthritis, atherosclerosis, cancer, liver fibrosis, cardio-vascular and neurodegenerative disorders, little is known about the specific involvement of members of the large MMP family in diseases. A comparative in silico characterization of the MMP protein family has been carried out to analyze their physico-chemical, secondary structural and functional properties. Based on the observed patterns of occurrence of atypical features, we hypothesize that cysteine rich and highly thermostable MMPs might be key players in diseased conditions. Thus, a plausible grouping of disease responsive MMPs that might be considered as promising clinical targets may be done. This study can be used as a fundamental approach to characterize, analyze and screen large protein families for the identification of signature patterns.

Fuzzy-based Leader Selection for Topology Controlled PEGASIS Protocol for Lifetime Enhancement in Wireless Sensor Network

Abstract: Wireless sensor Networks present a new generation of real time embedded systems with limited computation, energy and memory resources that are being used in wide variety of applications where traditional networking infrastructure is practically infeasible. Legitimate leader selection can drastically improve the lifetime of the sensor network. This paper proposes fuzzy logic methodology for leader election in PEGASIS based protocol PEGASIS-TC [1, 17] based on two descriptorsresidual energy of node and its proximity to Base Station. Simulation results show that depending on network configuration, a substantial increase in stability of network lifetime can be accomplished as compared to PEGASIS-TC.

Expanding the Kirkpatrick Evaluation Model-Towards more Efficient Training in the IT Sector

Abstract: The purpose of this paper is to investigate how the Kirkpatrick Learning Evaluation Model (1950) can be augmented to make it more credible and successful evaluation parameter in the changing times. Since the advent of Information Technology industry the rigid structures of organizations are replaced by the Flat/Matrix structures, removing the bars of time and place. This paper is an attempt to include three gaps identified in the Kirkpatrick Model, Training motivation, Organization citizenship behaviour and the Assessment of both the individual and the Organization simultaneously. Through co-relation and regression analysis these gaps were tested on the data obtained from 461 employees. The data support the various relationships to be included in Kirkpatrick Model and it identifies that for an effective training program it's essential to perform both pre-training and post-training analysis using the four parameters of Kirkpatrick Model viz. Reaction (changed to Motivation), Learning, Behaviour (or Performance) and Results.