Work place: Department of Computer Science &Engineering, Dr. B. C. Roy Engineering College, Durgapur, West Bengal (India)-713206
E-mail: cse.gsmt@gmail.com
Website:
Research Interests: Computer systems and computational processes, Neural Networks, Data Structures and Algorithms, Logic Calculi, Mathematics of Computing, Mathematics
Biography
Gour Sundar Mitra Thakur, Asst. Professor (CSE/IT), Dr. B. C. Roy Engineering College, Durgapur, West Bengal, India. B.Tech (C.S.E.), M.tech (CS).Currently pursuing PhD from National Institute of Technology, Durgapur in Mathematics, Areas of Interests are Fuzzy Logic and Fuzzy Mathematics, Soft Computing, Intelligent Systems and Neural Networks.
By Ashima Aggarwal Gour Sundar Mitra Thakur
DOI: https://doi.org/10.5815/ijisa.2014.08.09, Pub. Date: 8 Jul. 2014
Performance Appraisal of employees plays a very critical role towards the growth of any organization. It has always been a tough task for any industry or organization as there is no unanimous scientific modus operandi for that. Performance Appraisal system is used to assess the capabilities and productiveness of the employees. In assessing employee performance, performance appraisal commonly includes assigning numerical values or linguistic labels to employees performance. However, the employee performance appraisal may include judgments which are based on imprecise data particularly when one employee tries to interpret another employee’s performance. Thus, the values assigned by the appraiser are only approximations and there is inherent vagueness in the evaluation. By fuzzy logic perspective, the performance of the appraisee includes the evaluation of his/her work ability, skills and adaptability which are absolutely fuzzy concepts that needs to be define in fuzzy terms. Hence, fuzzy approach can be used to examine these imprecise and uncertainty information. Consequently, the performance appraisal of employees can be accomplished by fuzzy logic approach and different defuzzification techniques are applied to rank the employees according to their performance, which shows inconsequential deviation in the rankings and hence proves the robustness of the system.
[...] Read more.By Koushal Kumar Gour Sundar Mitra Thakur
DOI: https://doi.org/10.5815/ijitcs.2012.06.08, Pub. Date: 8 Jun. 2012
Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is considers as major soft-computing technology and have been extensively studied and applied during the last two decades. The most general applications where neural networks are most widely used for problem solving are in pattern recognition, data analysis, control and clustering. Artificial Neural Networks have abundant features including high processing speeds and the ability to learn the solution to a problem from a set of examples. The main aim of this paper is to explore the recent applications of Neural Networks and Artificial Intelligence and provides an overview of the field, where the AI & ANN’s are used and discusses the critical role of AI & NN played in different areas.
[...] Read more.By Preet Inder Singh Gour Sundar Mitra Thakur
DOI: https://doi.org/10.5815/ijieeb.2012.02.05, Pub. Date: 8 Apr. 2012
There are multiple numbers of security systems are available to protect your computer/resources. Among them, password based systems are the most commonly used system due to its simplicity, applicability and cost effectiveness But these types of systems have higher sensitivity to cyber-attack. Most of the advanced methods for authentication based on password security encrypt the contents of password before storing or transmitting in the physical domain. But all conventional encryption methods are having its own limitations, generally either in terms of complexity or in terms of efficiency.
In this paper an enhanced password based security system has been proposed based on user typing behavior, which will attempt to identify authenticity of any user failing to login in first few attempts by analyzing the basic user behaviors/activities and finally training them through neural network and classifying them as genuine or intruder.
Subscribe to receive issue release notifications and newsletters from MECS Press journals