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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 paper, the formation and stability of the reduced AgNPs in the colloidal solution were monitored by UV-Vis spectrophotometer analysis, which revealed a characteristic surface plasmon resonance (SPR) peak at 435nm, which corresponds to the absorption band of silver nanoparticles.
Abstract: The biosynthesis of nanoparticles by microorganism is considered a green, non-toxic, and environment-friendly technology. The present study reported for the first time, a rapid and green method for synthesis of silver nanoparticles (AgNPs) using cyanobacteria Nostoc linckia. UV-Vis spectrophotometer, X-ray diffraction (XRD), FT-IR, transmission electron microscopy (TEM), and energy dispersive X-ray (EDX) spectroscopy were used to confirm the formation of silver nanoparticles. The formation and stability of the reduced AgNPs in the colloidal solution were monitored by UV-Vis spectrophotometer analysis. The UV-Vis spectrum revealed a characteristic surface plasmon resonance (SPR) peak at 435 nm, which corresponds to the absorption band of silver nanoparticles. A shift in the absorption bands in FT-IR after the formation of nanoparticles confirmed that the microorganism extract acted not only as reducing agents but also as capping agents to stabilize the formed nanoparticles. X-ray diffraction pattern revealed the crystalline nature of the synthesized nanoparticles. Transmission electron microscope showed spherical shaped nanoparticles. The silver nanoparticles obtained were in the range of 5–60 nm as obtained from TEM. Selected area electron diffraction (SAED) confirmed the formation of metallic Ag. The presence of elemental silver was confirmed by EDX-ray spectroscopy analysis, which showed the peak in silver region at approximately 3 KeV. The AgNPs obtained showed highly potent antibacterial activities toward four different pathogenic bacteria, such as Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus susp. aureus, and two tested fungal strains (Candida albicans and Aspergillus niger).

40 citations

Journal ArticleDOI
TL;DR: A machine learning—radiomics based classification pipeline is proposed, to perform this predictive modelling task of breast tumour malignancy using ultrasound imaging, in a much more efficient manner, and achieves the state‐of‐the‐art accuracy, area under the curve, F1‐score and Mathews correlation coefficient values.

40 citations

Journal ArticleDOI
TL;DR: An in-depth analysis of the effects of class imbalance and class overlapping in conventional learning models has been presented and the proposed model evolves to eliminate borderline, redundant and overlapping cases with the account of Tomek-link pair and sparse neighbourhood.
Abstract: The class imbalance problem engraves the traditional learning models by degrading performance and yielding erroneous outcomes. It is the scenario where one of the class representation is over-shado...

40 citations

Book ChapterDOI
01 Jan 2019
TL;DR: It is the ability of the deep neural network’s techniques to perform complex correlation among speech signal features, which enhances its performance over traditional approaches.
Abstract: Automatic language identification has always been a challenging issue and an important research area in speech signal processing. It is the process of identifying a language from a random spoken utterance. This era is dominated by artificial intelligence and specifically, deep learning techniques. Prominent among the deep learning techniques are feed-forward deep neural network, convolutional neural network, long short term memory-recurrent neural network, etc. The various types of deep neural network techniques that were recently introduced have overshadowed conventional methods such as Gaussian mixture model, hidden Markov model, etc. These techniques showed significant improvement in recognition performance over various parameters. It is the ability of the deep neural network’s techniques to perform complex correlation among speech signal features, which enhances its performance over traditional approaches. This chapter provides in-depth concepts of various deep learning techniques for spoken language identification. It also explores and analyzes several works for speech recognition. Advantages and limitations of each of the techniques are reviewed. A summary of future scope for spoken language identification is also reviewed.

40 citations

Journal ArticleDOI
TL;DR: In this paper, a new formulation to maximize the operational profit of a micro grid connected hybrid system having wind farm and pumped storage unit for a day ahead electricity market in a frequency based pricing environment is presented.

40 citations


Authors

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