National Institute of Technology, Meghalaya

About: National Institute of Technology, Meghalaya is a education organization based out in Shillong, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 503 authors who have published 1062 publications receiving 6818 citations. The organization is also known as: NIT Meghalaya & NITM.

Redox-Mediated Shape Transformation of Fe3O4 Nanoflakes to Chemically Stable Au−Fe2O3 Composite Nanorods for a High-Performance Asymmetric Solid-State Supercapacitor Device

Abstract: Development of a stable and highly active metal oxide based electrochemical supercapacitor is a major challenge. Herein, we report a Au–Fe2O3 nanocomposite having tiny amount of gold (3 atomic % Au...

Fuzzy clustering for semi-supervised learning --- case study: construction of an emotion lexicon

Abstract: We consider the task of semi-supervised classification: extending category labels from a small dataset of labeled examples to a much larger set. We show that, at least on our case study task, unsupervised fuzzy clustering of the unlabeled examples helps in obtaining the hard clusters. Namely, we used the membership values obtained with fuzzy clustering as additional features for hard clustering. We also used these membership values to reduce the confusion set for the hard clustering. As a case study, we use applied the proposed method to the task of constructing a large emotion lexicon by extending the emotion labels from the WordNet Affect lexicon using various features of words. Some of the features were extracted from the emotional statements of the freely available ISEAR dataset; other features were WordNet distance and the similarity measured via the polarity scores in the SenticNet resource. The proposed method classified words by emotion labels with high accuracy.

Self-Controlled High-Performance Precharge-Free Content-Addressable Memory

Abstract: Content-addressable memory (CAM) is a hardware search-engine used for parallel lookup that assures high-speed match but at the cost of higher power consumption. Both low power NAND-type and high-speed NOR-type match-line (ML) schemes suffer from requirement of the precharge prior to the search. Recently, a precharge-free ML structure has been proposed but with inadequate search performance. In this brief, a self-controlled precharge-free CAM (SCPF-CAM) structure is proposed for high-speed applications. The proposed architecture is useful in applications where search time is very crucial to design larger word lengths. The proposed $128 \times 32$ -bit SCPF-CAM structure has been implemented using predictive 45-nm CMOS process and simulated in SPECTRE at the supply voltage of 1 V. The ML delay using the proposed SCPF-CAM architecture has been reduced by 88% and 73% compared to the precharge-free and traditional NAND-type ML structure.