Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Existing recommendation systems lack to address the need of several problems in education domain due to the availability of limited information. Study of recommendation systems to facilitate students’ education in their relevant services is being carried out in different perspective. Hence, the objective of this work is to apply existing knowledge for decision making to recommend students during their course registration process in an institution. The situation where more number of experts involves in decision making was influenced by Fuzzy Soft Expert Set (FSES). This work emphasizes the application of FSES for facilitating students’ course registration process assuming that the same course is offered by more number of faculty members during a semester. As more number of experts involved in this process and the uncertainty of the available data, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) along with FSES was considered. A new methodology FSES-TOPSIS was also applied in this work. The proposed method was accurate enough to enable students to rank the faculty members based on their previous performance and to enroll themselves with the faculty members of their interest. The method proposed here can be extended for various problems of similar nature. © The Author(s) 2019.

Department of Information Technology

School of Information Technology and Engineering

Vellore Campus

Department of Information Security

School of Computer Science and Engineering

The International Journal of Electrical Engineering & Education

Recommendation system for under graduate students using FSES-TOPSIS

A cold-start problem faced by a recommender system leads to serious causes and ruins the functionality of the entire system, sometimes responsible for losing new users also due to poor accuracy in recommendations. Recommendation becomes very rigid in case of a new recommender system where the product details exist but no user started viewing or rating the products yet. Similarly, when a new product is added the corresponding ratings are missing or when a new user enters the system, there is lack of knowledge about the preferences of the new user. This work concentrates on the aforementioned cold-start problems by designing a hybrid recommender engine for academic choices. Users’ preferences diverge time to time and domain to domain. Academia is one such field in which students’ feel more challenging to pick up their course after completing their school, which determines the future of a student. This may be due to either less perception about the available choices or more information overload in the internet. There is no single point of contact which helps the students to explore and suggest the enormous choices in education. Recommender system is a tool which suggests the users to find out the best products based on their tastes and needs. Another bigger challenge in this system is missing ratings. Existing user profiles represents the preferences alone and not the rating about the courses or institutes. This work proposes such a personalized recommender system which recommends opt courses for a student based on his expected score as well as preference. The proposed methodology was evaluated on real data set available from previous year engineering counselling conducted by Anna University. © BEIESP.

International Journal of Innovative Technology and Exploring Engineering

Mitigating cold start problem in a personalized recommender system

Trends in Mathematics Advances in Algebra and Analysis

A Novice’s Application of Soft Expert Set: A Case Study on Students’ Course Registration

Fulltext

Indian Journal of Science and Technology

A Novice’s Perception of Partial Homomorphic Encryption Schemes

Department of Software Systems

Advances in Intelligent Systems and Computing Proceedings of the Second International Conference on Computer and Communication Technologies

An Intelligent Packet Filtering Based on Bi-layer Particle Swarm Optimization with Reduced Search Space

Intelligent applications using evolutionary algorithms are becoming famous because of their ability to handle any real time complex and uncertain situations. Swarm intelligence, now-a-days has become a research focus which studies the collective behavior existing among the natural species which lives in group. Bacteria Foraging Optimization (BFO) is an optimization algorithm based on the social intelligence behavior of E.coli bacteria. Literature has witnessed the applications of BFO algorithm and the results reported are promising with regard to its convergence and accuracy. Several studies based on distributed control and optimization also suggested that algorithm based on BFO can be treated as global optimization technique. In this chapter, we have focused on the behavior of biological bacterial colony followed by the optimization algorithm based on bacterial colony foraging. We have also explored variations in the components of BFO algorithm (Revised BFO), hybridization of BFO with other Evolutionary Algorithms (Hybrid BFO) and multi-objective BFO. Finally, we have analyzed some applications of BFO algorithm in various domains. © Springer-Verlag Berlin Heidelberg 2015.

Multi-objective Swarm Intelligence Studies in Computational Intelligence

A Comprehensive Review on Bacteria Foraging Optimization Technique

Mobile money transfer is a way of sharing the available talk value from one mobile to other mobile. This service is useful when our family members or friends are in a situation in which they cannot recharge their talk value in mobiles. Currently this has been implemented between two mobiles which belong to the same network. In this paper, we have proposed a method to transfer the talk value from one mobile to another mobile which belongs to a different network. Both the networks of the sender and the receiver could be benefited through a predefined commission. © Research India Publications.

World University root node

International Journal of Applied Engineering Research

A framework for talk value transfer among diverse mobile service providers

VIT Unitversity

Composites: Mechanics, Computations, Applications, An International Journal

DETECTION OF WELD DEFECTS IN RADIOGRAPHIC IMAGES BASED ON REGION COUNTING AND CLASSIFICATION USING FEED FORWARD NEURAL NETWORK WITH BACK PROPAGATION