A secure solution based on load-balancing algorithms between regions in the cloud environment.

The problem treated in this article is the storage of sensitive data in the cloud environment and how to choose regions and zones to minimize the number of transfer file events. Handling sensitive data in the global internet network many times can increase risks and minimize security levels. Our work consists of scheduling several files on the different regions based on the security and load balancing parameters in the cloud. Each file is characterized by its size. If data is misplaced from the start it will require a transfer from one region to another and sometimes from one area to another. The objective is to find a schedule that assigns these files to the appropriate region ensuring the load balancing executed in each region to guarantee the minimum number of migrations. This problem is NP-hard. A novel model regarding the regional security and load balancing of files in the cloud environment is proposed in this article. This model is based on the component called "Scheduler" which utilizes the proposed algorithms to solve the problem. This model is a secure solution to guarantee an efficient dispersion of the stored files to avoid the most storage in one region. Consequently, damage to this region does not cause a loss of big data. In addition, a novel method called the "Grouping method" is proposed. Several variants of the application of this method are utilized to propose novel algorithms for solving the studied problem. Initially, seven algorithms are proposed in this article. The experimental results show that there is no dominance between these algorithms. Therefore, three combinations of these seven algorithms generate three other algorithms with better results. Based on the dominance rule, only six algorithms are selected to discuss the performance of the proposed algorithms. Four classes of instances are generated to measure and test the performance of algorithms. In total, 1,360 instances are tested. Three metrics are used to assess the algorithms and make a comparison between them. The experimental results show that the best algorithm is the "Best-value of four algorithms" in 86.5% of cases with an average gap of 0.021 and an average running time of 0.0018 s.

Cross-cultural adaptation and validation of the Arabic version of the Pain Self-Efficacy Questionnaire in Arab people with chronic low back pain.

BACKGROUND: The Pain Self-Efficacy Questionnaire (PSEQ) is widely used worldwide to measure pain self-efficacy. However, an Arabic translation is not available yet. OBJECTIVE: The study aimed to culturally adapt and validate the Arabic version of the Pain Self-Efficacy Questionnaire (PSEQ-A) in Arab people with Chronic Low Back Pain (LBP). METHODS: This study was conducted in two phases. The first phase involved translation and cross-cultural adaptation of the PSEQ into Arabic. The second phase aimed to examine the reliability and validity of the PSEQ-A. One hundred Arab people with chronic LBP completed the PSEQ-A and some self-report questionnaires, such as pain intensity, fear of movement, disability, and life quality. RESULTS: Cronbach's alpha for the PSEQ-A was 0.90. The interclass correlation coefficient of the PSEQ-A was 0.79. The standard error of the measurement and the minimal detectable change of the PSEQ-A scores were 5.27 and 14.60, respectively. The PSEQ-A has one factor structure. The PSEQ-A correlated significantly (P < .01) with disability, fear of movement, and quality of life in the expected hypothesized directions. CONCLUSION: The PSEQ-A was well accepted and exhibited validity and acceptable reliability in Arab people with chronic LBP.

Algorithms for the executable programs planning on supercomputers.

This research dealt with the problem of scheduling applied to the supercomputer's execution. The goal is to develop an appreciated algorithm that schedules a group of several programs characterized by their time consuming very high on different supercomputers searching for an efficient assignment of the total running time. This efficient assignment grantees the fair load distribution of the execution on the supercomputers. The essential goal of this research is to propose several algorithms that can ensure the load balancing of the execution of all programs. In this research, all supercomputers are assumed to have the same hardware characteristics. The main objective is to minimize the gap between the total running time of the supercomputers. This minimization of the gap encompasses the development of novel solutions giving planning of the executable programs. Different algorithms are presented to minimize the gap in running time. The experimental study proves that the developed algorithms are efficient in terms of performance evaluation and running time. A comparison between the presented algorithms is discussed through different classes of instances where in total the number of instances reached 630. The experiments show that the efficient algorithm is the best-programs choice algorithm. Indeed, this algorithm reached the percentage of 72.86%, an average running time of 0.0121, and a gap value of 0.0545.

COPE.er Method: Combating Digital Addiction via Online Peer Support Groups.

Digital addiction (hereafter DA) denotes a problematic relationship with technology described by being compulsive, obsessive, impulsive and hasty. New research has identified cases where users' digital behaviour shows symptoms meeting the clinical criteria of behavioural addiction. The online peer groups approach is one of the strategies to combat addictive behaviours. Unlike other behaviours, intervention and addictive usage can be on the same medium; the online space. This shared medium empowers influence techniques found in peer groups, such as self-monitoring, social surveillance, and personalised feedback, with a higher degree of interactivity, continuity and real-time communication. Social media platforms in general and online peer groups, in particular, have received little guidance as to how software design should take it into account. Careful theoretical understanding of the unique attributes and dynamics of such platforms and their intersection with gamification and persuasive techniques is needed as the ad-hoc design may cause unexpected harm. In this paper, we investigate how to facilitate the design process to ensure a systematic development of this technology. We conducted several qualitative studies including user studies and observational investigations. The primary contribution of this research is twofold: (i) a reference model for designing interactive online platforms to host peer groups and combat DA, (ii) a process model, COPE.er, inspired by the participatory design approach to building Customisable Online Persuasive Ecology by Engineering Rehabilitation strategies for different groups.