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Institution

National Institute of Technology, Silchar

EducationSilchar, Assam, India
About: National Institute of Technology, Silchar is a education organization based out in Silchar, Assam, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 1934 authors who have published 4219 publications receiving 41149 citations. The organization is also known as: NIT Silchar.


Papers
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Journal ArticleDOI
TL;DR: In this article, the circuit performance of an ultra-thin 3D double gate junctionless nanowire transistor, with an emphasis on digital applications, is investigated, and extensive analysis of inverter circuit and universal gates are performed using mixed mode simulation.

21 citations

Journal ArticleDOI
01 Jul 2014
TL;DR: This work proposes a method to extract symbolic weights from a trained neural network by observing the wholetrained neural network as an AND/OR graph and then finds solution for each node that becomes the weight of a corresponding node.
Abstract: Case Based Reasoning (CBR) is an analogical reasoning method, which solves problems by relating some previously solved problems to a current unsolved problem to draw analogical inferences for problem solving. But CBR faces the challenge of assigning weights to the features to measure similarity between a current unsolved case and cases stored in the case base effectively and correctly. The concept of neural network’s pruning is already used to sort out feature weighting problem in CBR. But it loses generality and actual elicited knowledge in the ANN’s links. This work proposes a method to extract symbolic weights from a trained neural network by observing the whole trained neural network as an AND/OR graph and then finds solution for each node that becomes the weight of a corresponding node. The proposed feature weighting mechanism is used in CBR to build a hybrid expert system for classification task and the performance of the proposed hybrid system is compared with that with other feature weighting mechanisms. The performance is validated on swine flu dataset and ionosphere, sonar and heart datasets collected from UCI repository. From the empirical results it is observed that in all the experiments the proposed feature weighting mechanism outperforms most of the earlier weighting mechanisms extracted from trained neural network.

21 citations

Journal ArticleDOI
TL;DR: A hierarchical flood resilience model for housing infrastructure is developed using the decision-making trial and evaluation laboratory (DEMATEL) and the interpretive structure modeling (ISM) methods and implemented for a community in northeast India for flood resilience assessment and risk-informed decision making.

21 citations

Journal ArticleDOI
01 Feb 2014
TL;DR: A multi-objective binary-coded genetic algorithm is proposed for this purpose, whose effectiveness is demonstrated through the application to a real case study and a number of large-size hypothetical instances.
Abstract: Embedded systems have become integral parts of today's technology-based life, starting from various home appliances to satellites. Such a wide range of applications encourages for their economic design using optimization-based tools. The JPEG encoder is an embedded system, which is applied for obtaining high quality output from continuous-tone images. It has emerged in recent years as a problem of optimum partitioning of its various processes into hardware and software components. Realizing pairing and conflicting nature among its various cost terms, for the first time the JPEG encoder is formulated and partitioned here as a multi-objective optimization problem. A multi-objective binary-coded genetic algorithm is proposed for this purpose, whose effectiveness is demonstrated through the application to a real case study and a number of large-size hypothetical instances.

21 citations

Journal ArticleDOI
TL;DR: In this article, the optimal cutting parameters in face milling operation of AISI 1005 steel using TiN coated tool were optimized with consideration of surface roughness (Ra) and material removal rate (MRR).

21 citations


Authors

Showing all 2010 results

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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202335
2022149
2021947
2020742
2019596
2018451