Al Ain University of Science and Technology

About: Al Ain University of Science and Technology is a education organization based out in Al Ain, United Arab Emirates. It is known for research contribution in the topics: Higher education & Computer science. The organization has 369 authors who have published 1077 publications receiving 7930 citations.

Mobility prediction as a time function for mobile networks in 3-D space: A Framework

Abstract: Mobility prediction has attracted increasing interest in recent years, as correct and accurate prediction can lead to efficient data delivery and provide the user with high quality of service. Moreover, it enables the network to plan for future tasks in the suitable time. In this paper, we present a framework for a prediction scheme that predict the future mobility of mobile networks in three-dimensional space using polynomial regression and provide a time-space mapping to produce a time function for the three components of the trajectory for the node

Activation of the GLP-1 receptor by chloropyrimidine derivatives

Abstract: The anti-diabetic activities of a series of chloropyrimidine derviatives 2a-k and 4a-k were investigated after they were designed, synthesized, and docked against the GLP-1 receptor target. In comparison to exenatide, which was utilized as a reference drug, the three chloropyrimidine synthesized compounds 2c, 2f and 4c exhibited potent in vitro and in vivo antidiabetic activities. Interestingly, compounds 2c, 2f and 4c showed to be the most effective in lowering blood glucose levels and led to even higher glucose uptake than the reference drug, exenatide. Consistent with the in vitro and in vivo data, compounds 4c and 2f had the lowest docking energy scores (Glide-XP score = 5.1 kcal/mol) and the greatest ligand efficiency score (> − 0.40 kcal/mol) among all docked compounds. These findings give up new possibilities for the development of high-efficacy compounds to treat hyperglycemia.

Toward constructive harmonisation of Islamic family law and CEDAW: a study on the UAE’s reservation to CEDAW Article 16 and equal rights to marriage and family relations

Abstract: The purpose of this study is to provide an evaluation of the United Arab Emirates’ (UAE) reservations to the Convention on the Elimination of All Forms of Discrimination against Women’s (CEDAW) Article 16 through the frame of constructive harmonisation between Islamic family law and CEDAW. It has been divided into two sections: firstly, women’s rights in Islamic family law, and secondly, the UAE’s reservation to CEDAW Article 16 and equal rights to marriage and family relations. The study concluded that gender equality under CEDAW and the complementarity principle of Shari’ah are two different concepts, since complementarity includes gender differences, but equality does not. According to the study, both concepts can be helpful in identifying areas of harmonisation since most Arab countries, including UAE, have enacted or amended laws that interpret Shari’ah in a way that is compatible with Human rights treaties, including CEDAW. As a result, the UAE may not be able to maintain most of its CEDAW reservations, including Article 16.

Analysis of the meanings of the measurement, assessment, and evaluation in ISO/IEEE software engineering standards

Abstract: Software engineering international standards have been developed to eliminate the gaps between the practitioners in understanding and implementing the software engineering terms and techniques. However, in presence of the coordination lack between the standardization bodies and even between the different work-groups within the same standardization body, some of these standards came up with a set of conflicted definitions and meanings of the same terms. Thus, this will make it difficult or impossible for the practitioners to implement such standards in a correct and rigorous way. In this paper, the meanings of the 'measurement', 'assessment', and 'evaluation' terms and the relationship between them in different ISO and IEEE standards will be discussed.

IEEE Access Special Section Editorial: Scalable Deep Learning for Big Data

Abstract: Deep learning (DL) has emerged as a key application exploiting the increasing computational power in systems such as GPUs, multicore processors, Systems-on-Chip (SoC), and distributed clusters. It has also attracted much attention in discovering correlation patterns in data in an unsupervised manner and has been applied in various domains including speech recognition, image classification, natural language processing, and computer vision. Unlike traditional machine learning (ML) approaches, DL also enables dynamic discovery of features from data. In addition, now, a number of commercial vendors also offer accelerators for deep learning systems (such as Nvidia, Intel, and Huawei).