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

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

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

Meta-heuristics and nature inspired algorithms have been prominent solvers for highly complex, nonlinear and hard optimization problems. The Gaining-Sharing Knowledge algorithm (GSK) is a recently proposed nature-inspired algorithm, inspired by human and their tendency towards growth and gaining and sharing knowledge with others. The GSK algorithm have been applied to different optimization

A multi-unit resource allocation system usually contains several processes and a number of resources with multiple units. Due to the competition for shared resources in these systems, deadlocks may occur. Recently, researchers have shown an increased awareness in deadlock control strategies for such a kind of systems without considering the dynamic changes such as processing failures and rework by

Pandemics raise huge challenges yet brought several opportunities. The sudden attack of COVID-19 revealed the importance of the information technology (IT) applications. The Reliance on the IT sector has become imperative to ensure sustainability and to raise most sectors' performance efficiency, especially the services' ones. This study applied PESTEL analysis to evaluate the current status of IT

Artificial Intelligence has been strongly evolving disrupting almost every research and application domain. One of the key attributes - and at the same time an enabler - of today's innovations is the massive connectivity resulted in the opportunity to exploit Artificial Intelligence across distributed network of self-contained smart agents those could range from software bots to complex devices

The huge amount of data being generated and transferred each day on the Internet leads to an increase of the need to automate knowledge-extraction tasks. Sentiment analysis is an ongoing research field in knowledge extraction that faces many challenges. In this paper, different machine learning, neural networks, deep learning models were evaluated over the IMDB benchmark dataset for movies reviews

VANETs are considered as sub-category from MANETs. They provide the vehicles with the ability of communication among each other to guarantee safety and provide services for drivers. VANETs have many network vulnerabilities like: Working on wireless media makes it vulnerable to many kinds of attacks and nodes can join or leave the network dynamically making change in its topology which affects

Classification of edge-on galaxies is important to astronomical studies due to our Milky Way galaxy being an edge-on galaxy. Edge-on galaxies pose a problem to classification due to their less overall brightness levels and smaller numbers of pixels. In the current work, a novel technique for the classification of edge-on galaxies has been developed. This technique is based on the mathematical