Work place: Indian Institute of Information Technology Allahabad, Uttar Pradesh -211012, India
E-mail: vrijendra.singh@gmail.com
Website:
Research Interests: Data Mining, Neural Networks, Computational Learning Theory
Biography
Vrijendra Singh is an Assistant Professor at Indian Institute of Information Technology, Allahabad. Prior to joining IIITA, he was a senior project associate at Indian Institute of Technology, Kanpur. He holds PhD in Computer Science (Independent Component Analysis and Blind Source Separation applications to Signal Processing and Artificial Neural Networks). He is highly engaged in teaching and research. His research interest includes information security and forensics, artificial neural networks, machine learning, computational neuroscience, enterprise resource planning, data mining and digital signal processing. He has published many papers in reputed journals, conferences and book chapters.
By Pooja Gupta Ankita Lavania Madhuri Agarwal Vrijendra Singh
DOI: https://doi.org/10.5815/ijeme.2015.03.02, Pub. Date: 8 Jul. 2015
With the onset of Digital age, digital videos have been highly prevalent in every sphere of our lives and have replaced other sources of entertainment, information sharing & social interaction. With the increasing use of Mobile devices, Internet & its application it has been quite evident that digital videos are generated and distributed with ease. Quite often such videos are used as evidence depending on the kind of information they provide. Since the video has been distributed at a large level it becomes very difficult to identify the generator device of the digital video especially if the case is of objectionable video contents etc. This paper aims at proposing a framework which will embed the generator device information in the video & will make sure the user identification information can't be changed during the distribution process using internet or other networking services (i.e. Bluetooth).
[...] Read more.By Prince Agarwal Manjari Sahai Vaibhav Mishra Monark Bag Vrijendra Singh
DOI: https://doi.org/10.5815/ijieeb.2014.04.03, Pub. Date: 8 Aug. 2014
In today’s highly competitive business environment, the rapidly changing customer demands and with the advent of enterprise wide information systems, the managers are bound to think beyond the conventional business processes and devise new ways to squeeze out costs and improve the performance without compromising on the quality at the same time. Supplier evaluation and selection is one such area which determines the success of any manufacturing firm. Supplier selection is the problem wherein the company decides which vendor to select to have that strategic and operational advantage of meeting the customers’ varying demands and fight the fierce competition. This paper presents a simple model based on Analytic Hierarchy Process (AHP) to help decision makers in supplier evaluation and selection, taking into account the firm’s requirements. The article is intended to help new scholars and researchers understand the AHP model and see different facets in first sight.
[...] Read more.By Manjari Sahai Prince Agarwal Vaibhav Mishra Monark Bag Vrijendra Singh
DOI: https://doi.org/10.5815/ijem.2014.01.01, Pub. Date: 8 May 2014
In the increasing competition it has become important in business world to understand the different aspects of production and purchasing to understand the need for desired material in the organization. The managers have an important responsibility of selecting a good supplier by evaluating them on different parameters which is directly or indirectly associated with their overall performance. For decision making based on multiple criteria evaluation many methods of Multi-Criteria Decision Making (MCDM) is used by firms. Data Envelopment Analysis (DEA) is prominently used by firms nowadays. In this paper, analysis of DEA is done by measuring supplier performance of two firms: multi-national telecommunication corporation and a manufacturing firm. The firm uses the methodology according to their requirement and criteria for evaluating their suppliers and find best among them.
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