Traditional mobile application development requires going through multiple development cycles in order for an application to work on different platforms. In cross-platform development, the application goes through only one development cycle to be deployed in multiple environments. Various cross-platform methodologies were explored to make it easy for developers to deploy their apps; one of which

To automate the process of segmenting an anatomy of interest, we can learn a model from previously annotated data. The learning-based approach uses annotations to train a model that tries to emulate the expert labeling on a new data set. While tremendous progress has been made using such approaches, labeling of medical images remains a time-consuming and expensive task. In this paper, we evaluate

Non-Synonymous Single-Nucleotide Variants (nsSNVs) and mutations can create a diversity effect on proteins as changing genotype and phenotype, which interrupts its stability. The alterations in the protein stability may cause diseases like cancer. Discovering of nsSNVs and mutations can be a useful tool for diagnosing the disease at a beginning stage. Many studies introduced the various predicting

Spinal motoneurons (MNs) play a crucial role in movement control. Decoding the firing activity of spinal MNs could help in real-life challenges, such as enhancing the control of myoelectric prostheses and diagnosing neurodegenerative diseases. In this paper, we propose a machine learning approach to automatically classify MNs based on their firing activity. Applying the proposed approach to data

The human genetic diseases associated with many factors, one of these factors is the non-synonymous Single Nucleotide Variants (nsSNVs) cause single amino acid change with another resulting in protein function change leading to disease. Many computational techniques have been released to expect the impacts of amino acid alteration on protein function and classify mutations as pathogenic or neutral

The autonomous driving needs some several features to achieve driving without human interference. One of these features is vehicle classification and detection since the target of this process is to help the CPU ''Central Processing Unit" of the vehicle to see what is around the vehicle, in order to evaluate the situation to take the best decision for each situation in real time. This paper is

Fifth generation (5G)networks aim at utilizing many promising communication technologies, such as Cloud Computing, Network Slicing, and Software Defined Networking. Supporting a massive number of connected devices with 5G advanced technologies and innovating new techniques will surely bring tremendous challenges for trust, security and privacy. Therefore, secure mechanisms and protocols are

Hearing is one of human's senses that helps in the interaction with the surrounding world. Earlier researches proved that excessive pitched exposure or even regular exposure to acoustic noise with a high sound pressure levels leads to side effects on the hearing sense; severe impacts leads to Noise Induced Hearing Loss (NIHL) which in turn affects humans quality of life. In the era of Internet of

During humans' lifetime, their bodies deal with different chemicals through various sources. Chemical toxicity is a challenging problem that needs rapid and efficient methods for evaluation of environmental chemicals, or medications development. Computer science helps in toxicity prediction through building models from pre-tested compounds by learning from data. These models raise a flag to avoid

Histogram of oriented gradient (HOG) feature has been widely used in vehicle detection. In this paper, a modified version of HOG is proposed by introducing compass gradient into the HOG calculation. Three different versions of the modified HOG features are used as an input for linear and nonlinear support vector machine (SVM). The modified HOG variants proved to have better classification