Graphs are used in various disciplines such as telecommunication, biological networks, as well as social networks. In large-scale networks, it is challenging to detect the communities by learning the distinct properties of the graph. As deep learning has made contributions in a variety of domains, we try to use deep learning techniques to mine the knowledge from large-scale graph networks. In this

COVID-19 is a growing problem worldwide with a high mortality rate. As a result, the World Health Organization (WHO) declared it a pandemic. In order to limit the spread of the disease, a fast and accurate diagnosis is required. A reverse transcript polymerase chain reaction (RT-PCR) test is often used to detect the disease. However, since this test is time-consuming, a chest computed tomography

In machine learning, searching for the optimal feature subset from the original datasets is a very challenging and prominent task. The metaheuristic algorithms are used in finding out the relevant, important features, that enhance the classification accuracy and save the resource time. Most of the algorithms have shown excellent performance in solving feature selection problems. A recently

Background: Taurine-upregulated gene 1 (TUG1) is one of the long noncoding RNAs (lncRNAs) that plays a role in melanogenesis. MicroRNA-377 (miRNA-377) is a conserved noncoding RNA that regulates angiogenesis and promotes oxidative stress. Peroxisome proliferator-activated receptors (PPARs) are components of the nuclear hormone receptor superfamily. PPAR-γ activators stimulate melanogenesis

Introduction: The hyper-catabolic state is a devastating pathophysiological response to severe injury, infection or burns. Nandrolone decanoate (ND) is a potent anabolic steroid have many clinical indications, but not investigated in burn injuries yet. Patients and methods: A prospective randomized control study included 40 burned patients who were treated in Burn unit from burn injuries ranged

Measuring phase noise in oscillators is crucial in communication systems, vibration analysis, and frequency synthesizers. Traditionally, this measurement is done in frequency domain by estimating the ratio of the power density at an offset frequency from the carrier to the power of the carrier signal. This approach is hardware intensive and dependent on the the offset frequency, for which there

Although the majority of existing License Plate (LP) recognition techniques have significant improvements in accuracy, they are still limited to ideal situations in which training data is correctly annotated with restricted scenarios. Moreover, images or videos are frequently used in monitoring systems that have Low Resolution (LR) quality. In this work, the problem of LP detection in digital

Recently, public healthcare systems become one of the most pivotal parts in our daily life. Resulting in an insane increase in Medical data like medical images and patient information. Having huge amount of data requires more computational power for efficient data management. In addition, data security, privacy and trustworthy have to be maintained and guaranteed. Most medical information in the

Recently, the numerical optimization field has attracted the research community to propose and develop various metaheuristic optimization algorithms. This paper presents a new metaheuristic optimization algorithm called Honey Badger Algorithm (HBA). The proposed algorithm is inspired from the intelligent foraging behavior of honey badger, to mathematically develop an efficient search strategy for

Information Centric Networks (ICNs) overcome the current IP-based networks weakness and aim to ensure efficient data distribution. The Main ICN features are location-independent naming, in-network caching, name-based routing, built-in security, and high mobility. ICN vehicular networks stratify the ICN architecture on the Vehicular Ad hoc Networks (VANETs) to reinforce a massive amount of data