Implementation of high step up converter using RBFN MPPT controller for fuel cell based electric vehicle application.

Fuel cell-based electric vehicles (EVs) are gaining popularity in the automotive industry due to strict carbon emissions and fuel efficiency regulations. Fuel cells have inherently low voltage characteristics, making it challenging to interface with EV drive systems. This work proposes a unique topology implementing a non-isolated high step-up DC-DC converter to integrate the Proton Exchange Membrane Fuel (PEMF) cell with the EV motor drive.

Moth-Flame Optimization for Early Prediction of Heart Diseases.

Heart disease is among the leading causes of mortality globally. Predicting cardiovascular disease is a major difficulty in clinical data analysis. AI has been demonstrated to be powerful in deciding and anticipating an enormous measure of information created by the health domain.

COVID-19 Detection Based on Lung Ct Scan Using Deep Learning Techniques.

SARS-CoV-2 is a novel virus, responsible for causing the COVID-19 pandemic that has emerged as a pandemic in recent years. Humans are becoming infected with the virus. In 2019, the city of Wuhan reported the first-ever incidence of COVID-19.

Diagnosis of Cervical Cancer based on Ensemble Deep Learning Network using Colposcopy Images.

Traditional screening of cervical cancer type classification majorly depends on the pathologist's experience, which also has less accuracy. Colposcopy is a critical component of cervical cancer prevention. In conjunction with precancer screening and treatment, colposcopy has played an essential role in lowering the incidence and mortality from cervical cancer over the last 50 years.

Forecasting of the SARS-CoV-2 epidemic in India using SIR model, flatten curve and herd immunity.

In this paper, we are presenting an epidemiological model for exploring the transmission of outbreaks caused by viral infections. Mathematics and statistics are still at the cutting edge of technology where scientific experts, health facilities, and government deal with infection and disease transmission issues. The model has implicitly applied to COVID-19, a transmittable disease by the SARS-CoV-2 virus.

COVID-19: Impact analysis and recommendations for power sector operation.

The demand of electricity has been reduced significantly due to the recent COVID-19 pandemic. Governments around the world were compelled to reduce the business activity in response to minimize the threat of coronavirus. This on-going situation due to COVID-19 has changed the lifestyle globally as people are mostly staying home and working from home if possible.

Investigation on the impacts of COVID-19 quarantine on society and environment: Preventive measures and supportive technologies.

The present outbreak of the novel coronavirus SARS-CoV-2, epicentered in China in December 2019, has spread to many other countries. The entire humanity has a vital responsibility to tackle this pandemic and the technologies are being helpful to them to a greater extent. The purpose of the work is to precisely bring scientific and general awareness to the people all around the world who are currently fighting the war against COVID-19.

Improved fault ride through capability of DFIG based wind turbines using synchronous reference frame control based dynamic voltage restorer.

Fault ride through (FRT) capability in wind turbines to maintain the grid stability during faults has become mandatory with the increasing grid penetration of wind energy. Doubly fed induction generator based wind turbine (DFIG-WT) is the most popularly utilized type of generator but highly susceptible to the voltage disturbances in grid. Dynamic voltage restorer (DVR) based external FRT capability improvement is considered.