National Institute of Technology, Silchar

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: Computer science & Control theory. The organization has 1934 authors who have published 4219 publications receiving 41149 citations. The organization is also known as: NIT Silchar.

A sustainable protocol for production of biodiesel by transesterification of soybean oil using banana trunk ash as a heterogeneous catalyst

Abstract: Due to the world wide attention regarding depletion of non-renewable resources, detrimental effect of toxic chemicals to the environment and uncontrollable up surge of waste materials, scientific community is showing substantial focus on valorization of waste into various significant products. In this study, Musa acuminata banana trunk ash (MBTA) was utilized as a waste biomass–derived heterogeneous catalyst for transesterification of soybean oil to biodiesel at ambient temperature. To characterize the solid catalyst, different analytical and spectroscopic techniques were adopted that enabled to investigate its chemical composition and morphology. EDX, XRF, and XRD analysis revealed the presence of several oxides of alkali metals and alkaline earth metals besides carbon in the ash sample. A high conversion of biodiesel (98.39%) was achieved under our optimized reaction conditions using the waste biomass catalytic system. The catalyst was recoverable up to 5 times without much depreciation in its catalytic activity. The catalyst being a waste-material is therefore cheap, easily-to-prepare, biodegradable, recyclable, and environmentally benign which makes it a prospective candidate for “green catalyst” in biodiesel synthesis.

A Hybrid Case Based Reasoning Model for Classification in Internet of Things (IoT) Environment

Abstract: This article describes how the enormous size of data in IoT needs efficient data mining model for information extraction, classification and mining hidden patterns from data. CBR is a learning, mining and problem-solving approach which solves a problem by relating past similar solved problems. One issue with CBR is feature weight to measure the similarity among cases to mine similar past cases. NN's pruning is a popular method, which extracts feature weights from a trained neural network without losing much generality of the training set by using four mechanisms: sensitivity, activity, saliency and relevance. However, training NN with imbalanced data leads the classifier to get biased towards the majority class. Therefore, this article proposes a hybrid CBR model with RUS and cost sensitive back propagation neural network in IoT environment to deal with the feature weighting problem in imbalance data. The proposed model is validated with six real-life datasets. The experimental results show that the proposed model is better than other feature weighting methods.

Active power management of isolated renewable microgrid generating power from Rooftop solar arrays, sewage waters and solid urban wastes of a smart city using Salp swarm algorithm

Abstract: This work is a maiden attempt to manage the active power of an isolated renewable microgrid with Rooftop solar arrays, Micro-hydro generator, Biomass fired combined heat and power, Aqua-electrolyzer, and Fuel cells, by optimized load frequency control using a recent Salp Swarm Algorithm. The effort has put on to propose the mathematical model of a renewable microgrid generating power from solar irradiances, urban solid wastes, and sewage waters of a smart city like Bhubaneswar, for a dual objective of power and waste management. The importance of choosing the above combination of resources for microgrid is the effective co-compensation with climatic changes between solar PV and micro-hydro units naturally. Since sufficient solar energy is available during summer, but the water potential reduced subsequently for micro-hydro power generation. In other hands, during monsoon, water potential is highly available as rainwater adds to the sewage, but there are insufficient sunrays for PV units. The Biomass-based CHP is considered to give support to microgrid during non-availability of solar energy. It becomes a great challenge to coordinate between generation and load demand efficiently with the considered sources of renewable energy due to their inherent dependency towards climatic variations. To overcome this issue, the responses of the system are studied for different scenarios of renewable sources availability and load changes for optimal frequency control. The proposed microgrid is simulated with MATLAB-Simulink for four different scenarios and the optimized responses are reported to be competent in maintaining power frequency within the acceptable limit.

Paederia foetida Linn. promoted biogenic gold and silver nanoparticles: Synthesis, characterization, photocatalytic and in vitro efficacy against clinically isolated pathogens.

Abstract: Development of newer improved therapeutic agents with efficient antimicrobial activities continues to draw attention of researchers till date. Moreover, abatement of polluting dyes released from industry with enhanced efficiency is currently being considered as challenging task for people working on material sciences. In the present study, we report a facile biogenic synthesis of gold and silver nanoparticles (NPs) in which aqueous extracts of Paederia foetida Linn. was used as reducing as well as stabilizing agent. The biosynthesized Au and Ag NPs were characterized by UV-visible spectroscopy (UV-vis), Fourier transform infrared spectroscopy (FTIR), powder X-ray diffraction analysis (XRD) and transmission electron microscopy (TEM). The photocatalytic activity of these nanoparticles were tested against Rhodamine B (RhB). The antimicrobial activity of these biosynthesized NPs were investigated against four human pathogens viz. B. cereus, E. coli, S. aureus and A. niger. Biogenic silver nanoparticles presented a strong antimicrobial activity against B. cereus (26.13) followed by E. coli (26.02), S. aureus (25.43) and A. niger (22.69). Ag NPs owing to their small size (5-25nm) could have easily penetrate into the cell membrane, disturb the metabolism, cause irretrievable damage finally leading to the microbial cell death. Interestingly biogenic gold nanoparticles didn't show any antimicrobial activity.