Integrated MPPT and bidirectional DC DC converter with reduced switch multilevel inverters for electric vehicles applications.

The necessity for a clean and sustainable Renewable Energy Source (RES) is fueled by the intensifying environmental issue and steady decline of fossil resources. Additionally, expanding use of Electric Vehicles (EVs) across the globe is a result of rising carbon emissions and oil consumption. PV powered EV charging system has the ability to substantially reduce greenhouse emissions when compared with conventional sources-based EV charging system.

An event triggered control scheme for enhanced production of Escherichia coli and biomass concentration during fed-batch cultivation.

Control of a bioprocess is a challenging task mainly due to the nonlinearity of the process, the complex nature of microorganisms, and variations in critical parameters such as temperature, pH, and agitator speed. Generally, the optimum values chosen for critical parameters during Escherichia coli (E.coli) K-12fed-batch fermentation are37 C for temperature, 7 for pH, and 35 % for Dissolved Oxygen (DO).

A comprehensive review of analyzing the chest X-ray images to detect COVID-19 infections using deep learning techniques.

COVID-19, a highly infectious respiratory disease a used by SARS virus, has killed millions of people across many countries. To enhance quick and accurate diagnosis of COVID-19, chest X-ray (CXR) imaging methods were commonly utilized. Identifying the infection manually by radio imaging, on the other hand, was considered, extremely difficult due to the time commitment and significant risk of human error.

A realistic perspective for CO triggered tuning of electrical conductivity.

To seek sustainable CO sequestration and conversion, an electrochemical cell has been investigated for carbon capture and utilization strategy (CCU). In this cell, atmospheric CO is captured under ambient conditions and incorporated into power generation using zinc nanopowder as the catalyst. As a result, a method was developed to tune the electronic property of zinc by passing CO.

A deep transfer learning-based convolution neural network model for COVID-19 detection using computed tomography scan images for medical applications.

The Coronavirus (COVID-19) has become a critical and extreme epidemic because of its international dissemination. COVID-19 is the world's most serious health, economic, and survival danger. This disease affects not only a single country but the entire planet due to this infectious disease.

A case study on development of thermodynamic entropy measuring device and its implication on the human body.

In the field of thermodynamics, entropy is a measure of the degree of disorder of the system considered focus. The direct measurement of entropy for microscopic systems involving molecule-level variations exists. However, for a macroscopic system, it still remains a challenge.

Feature Selection by Hybrid Brain Storm Optimization Algorithm for COVID-19 Classification.

A large number of features lead to very high-dimensional data. The feature selection method reduces the dimension of data, increases the performance of prediction, and reduces the computation time. Feature selection is the process of selecting the optimal set of input features from a given data set in order to reduce the noise in data and keep the relevant features.

A comparative energy and exergy efficiency study of hemispherical and single-slope solar stills.

In this experimental work, a comparative energy and exergy efficiency study of hemispherical solar still and a single-slope solar still has been carried out. The experiments were conducted in southeast Algeria on 25-5-2020 and 3-6-2020 in the natural climatic environment, and daily accumulation of distilled water produced for both distilleries was measured. The maximum obtained cumulative yield of distilled products is equal to 5.