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.

Organic Molecular Crystals with Dual Stress-Induced Mechanical Response: Elastic and Plastic Flexibility

Abstract: The envisaged shift in the interest of crystal engineering researchers from crystal structure to mechanical property has sown the seeds of analogous understanding and interpretation of the molecula...

Extendable Switched-Capacitor Multilevel Inverter With Reduced Number of Components and Self-Balancing Capacitors

Abstract: Multilevel inverters (MLIs) with self-balanced switched-capacitors (SC) have received wide recognition for increasing the reliability and efficiency of renewable energy and high-frequency power distribution systems. This article presents a new SC MLI structure using a reduced number of components. The proposed dual-source SC MLI can be extended in various ways to increase the voltage levels at the output. The SCs are self-balanced by using a suitable charging–discharging pattern, and thereby, voltage boosting is achieved. The operational analysis and features of the proposed 25-level MLI are delineated in detail. Comparative analysis with state-of-the-art MLIs in terms of the number of components, voltage stress, and cost factor demonstrate the merit of the proposed extendable SC MLIs. Extensive simulation of the proposed MLI structure is performed on the MATLAB/Simulink environment using both the low and high switching frequency control schemes. Furthermore, simulation results are validated experimentally by developing a prototype of the proposed MLI under load variations, frequency change condition, and variation in the modulation index.

Synthesis of Au-V2O5 composite nanowires through the shape transformation of a vanadium(III) metal complex for high-performance solid-state supercapacitors

Abstract: A simple redox transformation between a vanadium(III) metal complex and gold(III) chloride aided by a cost-effective modified hydrothermal procedure has been adopted for the synthesis of Au-V2O5 composite nanowires. The stability of pseudocapacitive electrode materials in acidic electrolytes is a major challenge. However, the synthesized Au-V2O5 composite nanowires are stable in acidic electrolyte when compared to the precursor component, V2O5. Electrochemical measurement shows a specific capacitance of 419 F g−1 at 1 A g−1 current density in 0.5 M H2SO4 solution for the synthesized composite nanowires. However, the precursor component V2O5 shows a lower specific capacitance under identical conditions. The synthesized composite nanowires, as a pseudocapacitive electrode material, respond to a wide range of working potential windows (+1.6 V), resulting in maximum energy and power densities of 53.33 W h kg−1 and 3.85 kW kg−1 respectively. Moreover, the Au-V2O5 nanowires show high cyclic stability (89% specific capacitance retention) for up to 5000 consecutive charge–discharge (CD) cycles at 10 A g−1 constant current density, due to the composite formation by redox transformation, which reflects the stability of the composite in acidic electrolyte.

FallSense : An Automatic Fall Detection and Alarm Generation System in IoT-Enabled Environment

Abstract: In this paper, we elaborate the design, implementation, and testing of a system— FallSense , which is able to detect accidental falls of human beings in a precise way. The distinguishing feature of FallSense is its endeavors beyond the scope of accelerometer, which is a component of traditional body sensor network. Along with this acceleration measuring unit, FallSense uses the benefits of an Internet-of-Things-enabled environment, which consists of a number of infrared transmitter–receiver pairs and ultrasonic sensors. Employing a fuzzy inference system, FallSense fuses the data from multiple sensors and becomes over sure before inferring that a fall has occurred. Depending on the inputs from multiple sensors, FallSense generates a value between 0 and 1, which signifies the chance of fall. Results show that multi-sensor-based FallSense achieves overall 16% improvement in comparison with the existing approaches, on an average. Beyond the theoretical modeling, this paper also practically implemented the same with the help of the real-sensing units.

A Node Overhaul Scheme for Energy Efficient Clustering in Wireless Sensor Networks

Abstract: Clustering of wireless sensor network nodes, a fundamental operation, is aimed at achieving load balancing and prolonged network lifetime. Low-energy adaptive clustering hierarchy protocol, the prominent standard, achieves these. An improved protocol, balance cluster formation, provides the additional advantage of equal size clusters, but at the cost of overlapping of clusters. This letter presents a node overhaul scheme that achieves load balancing and energy efficiency while also maintaining uniform size clusters without any overlapping. The proposed solution first forms initial clusters and later refurbishes the initial clusters based on a second best choice cluster head, wherever applicable. The results so obtained show a substantial improvement in network lifetime and node death rate as compared to other simulated methods.