The coronavirus (COVID-2019) quickly spread throughout the world and came to be a pandemic. To avoid further spreading this epidemic and treat affected patients rapidly, it is important to recognize the positive cases as early as possible. In this paper, deep learning techniques are employed to detect COVID-19 from chest X-ray images quickly. The images of the two classes, COVID and No-findings

Feature selection is critical in analyzing microarray data, which has many features (genes) or dimensions. However, with only a few samples the large search space and time consumed during their selection make selecting relevant and informative genes that improve classification performance a complex task. This paper proposed a hybrid model for gene selection known as (SVM-mRMRe), the proposed model

This Electronic Health (E-Health) is a broad expression that enables the communication between healthcare professionals in handling patient information through the cloud. Exchanging medical data over the public cloud requires securing transferring for the data that's direct many researchers in proposing different secure schemes to enable users to handle data safely without hacking or alternating

In this paper, we propose an effective saliency detection method based on dense and sparse representation in-terms of an optimized background template. Firstly, the input image is divided into compact and uniform super-pixels. Then, the optimized background template is produced by introducing boundary conductivity measurement to improve the dense and sparse representation of the image's super

The precise detection and segmentation of cells in microscopic image sequences is an essential task in biomedical research, such as drug discovery and studying the development of tissues, organs, or entire organisms. However, the detection and segmentation of cells in phase contrast images with a halo and shade-off effects is still challenging. Lately, Mask Regional Convolutional Neural Network

Pediatric septic shock is generally considered as a devastating clinical syndrome that can lead to tissue damage and organ failure due to the over exaggerated immune response to an infection. Therefore, in this paper, we attempted to early identify the clinical course of such disease with the aid of peripheral blood T-cells of 181 pediatric patients who admitted to Intensive Care Unit (ICU)

Improvement of structural efficiency in various materials is critically important for sustainable society development and the efficient use of natural resources. Recently, a lot of attention in science and engineering has been attracted to heterogeneous-structure materials because of high structural efficiency. However, strategies for the efficient design of heterogenous structures are still in

Vehicular Ad Hoc Networks is an evolving research field that has the potential to address safety on roads. This tends to attract car manufacturers and suppliers to develop in evolving the industry vision. VANET demonstrates a different kind of communications targeting the main objective, which is safety besides entertainment services. This is achieved using the Internet through the infrastructure

The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics. A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specic time period. A nonlinear binary

A consistency analysis is performed for one of the famous Tajweed rules in the Holy Quran - Madd rules. They are tested on records of one of the famous reference reciters - Sheikh El-Hosary-to find a consistent boundaries and to evaluate the performance of other new learners. A vowel detection algorithm is used to detect the duration of the detected Madd patterns. This algorithm was applied on a