Understanding energy metabolism and intracellular energy transmission requires knowledge of the function and structure of the mitochondria. Issues with mitochondrial morphology, structure, and function are the most prevalent symptoms. They can damage organs such as the heart, brain, and muscle due to a variety of factors, such as oxidative damage, incorrect metabolism of energy, or genetic conditions. The control of cell metabolism and physiology depends on functional connections between mitochondrial and biological surroundings. Therefore, it is essential to research mitochondria in situ or in vivo without isolating them from their surrounding biological environment. Finding and spotting abnormal alterations in mitochondria is the

            The unpredictable and huge data generation nowadays by smart computing devices like (Sensors, Actuators, Wi-Fi routers), to handle and maintain their computational processing power in real time environment by centralized cloud platform is difficult because of its limitations, issues and challenges, to overcome these, Cisco introduced the Fog computing paradigm as an alternative for cloud-based computing. This recent IT trend is taking the computing experience to the next level. It is an extended and advantageous extension of the centralized cloud computing technology. In this article, we tried to highlight the various issues that currently cloud computing is facing. Here

Coronavirus: (COVID-19) is a recently discovered viral disease caused by a new strain of coronavirus.

The majority of patients with corona-virus infections will have a mild-moderate respiratory disease that recovers without special care. Most often, the elderly, and others with chronic medical conditions such as asthma, coronary disease, respiratory illness, and malignancy are seriously ill.

    COVID-19 is spread mostly by salivary droplets or nasal secretions when an infected person coughs or sneezes.

    COVID-19 causes severe acute respiratory illness (SARS-COV-2). The first incidence was recorded in Wuhan, China, in 2019.  Since then it spreads leading to a pandemic.

Continuous escalation of the cost of generating energy is preceded by the fact of scary depletion of the energy reserve of the fossil fuels and pollution of the environment as developed and developing countries burn these fuels. To meet the challenge of the impending energy crisis, renewable energy has been growing rapidly in the last decade. Among the renewable energy sources, solar energy is the most extensively available energy, has the least effect on the environment, and is very efficient in terms of energy conversion. Thus, solar energy has become one of the preferred sources of renewable energy. Flat-plate solar collectors are one of the extensively-used and well-known types of solar collectors. However, the effectiveness of the coll

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and