Arabic language; philology; 20th century; history and criticism.

Fake news detection involves predicting the likelihood that a particular news article is intentionally deceptive. Arabic FND started to receive more attention in the last decade, and many detection approaches demonstrated some ability to detect fake news on multiple datasets. However, most existing approaches do not consider recent advances in natural language processing, i.e., the use of neural networks and transformers. This paper presents a comprehensive comparative study of neural network and transformer-based language models used for Arabic FND. We examine (...) the use of neural networks and transformer-based language models for Arabic FND and show their performance compared to each other. We also conduct an extensive analysis of the possible reasons for the difference in performance results obtained by different approaches. The results demonstrate that transformer-based models outperform the neural network-based solutions, which led to an increase in the F1 score from 0.83 to 0.95, and it boosted the accuracy by 16% compared to the best in neural network-based solutions. Finally, we highlight the main gaps in Arabic FND research and suggest future research directions. (shrink)

BackgroundA different ethos with respect to the perception of medical ethics prevails in societies in transition such as those in the Arabian Peninsula, which makes it difficult to apply international principles of bioethics in medical practice. This study aimed to develop and psychometrically test an instrument that measures physicians’ awareness of bioethics and medical law and their attitudes towards the practice of medical ethics. Additionally, it examined physician correlates influencing the awareness of bioethics.MethodsFollowing a rigorous review of relevant literature by (...) a panel of experts, a 13-item instrument, the Omani physicians’ bioethics and medical law awareness (OBMLA) questionnaire was developed with the aim of assessing physicians’ awareness of bioethics and medical law. The study tool’s construct validity and internal consistency reliability were examined by exploratory factor analysis (EFA) and Cronbach’s alpha. In a cross-sectional study, the questionnaire was distributed among a random sample of 200 physicians at a tertiary hospital in Muscat, Oman. Participant characteristics that may influence awareness of bioethics and medical law were explored.ResultsThe EFA of the OBMLA questionnaire resulted in three well-loading factors: (1) Physicians’ bioethics practice subscale (2) incentive related bioethics subscale and (3) medical law awareness subscale. Internal consistency reliability ranged between Cronbach’s α: 0.73–0.8. Of the total 200 participants, 52% reported that teaching medical ethics during medical school was inadequate. The overall mean (standard deviation, SD) of the bioethics awareness score and Omani medical law awareness were 27.6 (3.5) and 10.1 (2.1) respectively. The majority of physicians (73%) reported that they frequently encountered ethical dilemmas in their practice and 24.5% endorsed the view that unethical decisions tended to occur in their practice.ConclusionThe study provides an insight into the practice of bioethics, and the awareness of bioethics and medical law among physicians in a teaching hospital in Oman. The OBMLA questionnaire appears to be a valid and reliable tool to assess a physician’s awareness of bioethics and medical law. In this preliminary study, it appears that participants have suboptimal scores on the indices which measure practice and awareness of bioethics and medical law. (shrink)

BackgroundImplementation of quarantine and lockdown to COVID-19 pandemic has created dramatic negative psychological impact mainly the general population’s health worldwide. We aimed to assess the prevalence and predictors of anxiety and stress severity among the Palestinian population.MethodsA cross-sectional web-based survey was conducted. An anonymous online questionnaire and snowball recruiting technique were used to target the general public in Palestine between 6 and 16 April, 2020 during COVID-19 pandemic lockdowns. Multivariate logistic regression models were developed for the outcome variables.ResultsOf the 2819 (...) individuals who completed the questionnaire, more than two thirds of them were females. Nearly, were residing at the West Bank. The mean age of participants was 29.47 years. The anxiety prevalence was with had mild/moderate severity. The stress prevalence was with had mild/moderate severity. The prevalence of both anxiety and stress was. In multivariate analysis, exposure to confirmed case of COVID-19, inadequacy of food supply and jobs that acquire leaving home during lockdown were significantly related to higher anxiety degree. As for stress, low monthly income, cohabitation with a person of a high-risk group and inadequacy of food supply were significantly related to higher stress degree.ConclusionYoung adults with low socioeconomic status and inadequate food supply were more likely to have a higher degree of stress and/or anxiety. Providing alternative economical sources for those in need, and spreading more awareness regarding the pandemic, supporting the population’s psychological wellbeing, community connection and the availability of specialist mental health services are crucial to overcome the mental impacts of COVID-19 in Palestine. (shrink)

A critical edition of "Tahdhīb Al-Akhlāq", a treatise ascribed to the Jacobite theologian, logician, and translator in Abbasid period, Yahya ibn Adi.

BackgroundPsychological distress/morbidity is amongst the primary reason for the cause of pain at multiple sites, its progression, and recovery. Though still not very clear if physical pain in the neck or the back may predict psychological morbidities or not. Thus, we investigated the association between combined neck or back pain and psychological distress/morbidity.MethodsA cross-sectional study was conducted in Al-Kharj, Saudi Arabia, including 1,003 individuals. The questionnaire comprised of General Health Questionnaire-12 and some questions about neck and back pain. Data analysis (...) was done using statistical software SPSS version 26.0.ResultsThe results of the multivariate analysis revealed a significant positive association between neck/back pain status and total GHQ score. Having neck/back pain had almost a 2.5 times greater risk of psychological distress/morbidity. Further, females were more likely to have a higher risk of psychological distress/morbidity than males while adjusting for sociodemographic and clinical characteristics.ConclusionThe combination of neck and back pain was significantly associated with the Saudi population’s psychological problems. Therefore, the Saudi government needs to devise high-risk strategies and allocate adequate resources to the cause so that at-risk people can be shielded from the adverse complications arising from this condition in the long run. (shrink)

The aim was to investigate and assess the acceptance of virtual classes among Arabic language student teachers during and beyond covid-19. Quantitative research is carried out with the aim to assess the acceptance of virtual classes among Arabic language student teachers during and beyond covid-19. It uses a survey-based methodology to obtain data from the respondents. An online questionnaire was used to collect data via Facebook and WhatsApp groups. 450 questionnaire responses were received. They were 300 males, and 150 females. (...) Results indicated that the student behavioral intention to use educational technology is positively affected by perceived usefulness, perceived ease of use. PU, PEOU yielded a coefficient of multiple regression of 0. 450 and a multiple correlation square of 0. 435. This shows that 43.5% of the total variance in student behavioral intention to use educational technology is accounted for by the combination of PU, PEOU. Efforts to integrate educational technology into teacher education and Arabic language student teachers education programs are necessary. (shrink)

This paper describes an intelligent algorithm for traffic sign recognition which converges quickly, is accurate in its segmentation and adaptive in its behaviour. The proposed approach can segment images of traffic signs in different lighting and environmental conditions and in different countries. It is based on using Kohonen's Self-Organizing Maps as a clustering tool and it is developed for Intelligent Vehicle applications. The current approach does not need any prior training. Instead, a slight portion, which is about 1% of the (...) image under investigation, is used for training. This is a key issue to ensure fast convergence and high adaptability. The current approach was tested by using 442 images which were collected under different environmental conditions and from different countries. The proposed approach shows promising results; good improvement of 73% is observed in faded traffic sign images compared with 53.3% using the traditional algorithm. The adaptability of the system is evident from the segmentation of the traffic sign images from various countries where the result is 96% for the nine countries included in the test. (shrink)

Arabic lanaguage; history and criticism.

Modernism (Art); aesthetics; philosophical aspects; philosophy, modern; 20th century.

Mobile app stores provide an extremely rich source of information on app descriptions, characteristics, and usage, and analyzing these data provides insights and a deeper understanding of the nature of apps. However, manual analysis of this vast amount of information on mobile apps is not a simple and straightforward task; it is costly in terms of human effort and time. Computational methods such as topic modeling can provide an efficient and satisfactory approach to mobile app information analysis. Topic modeling is (...) a type of statistical modeling technique for discovering abstract topics that occur in a set of documents. This study explores the relationship between features of Arabic apps and investigates how well the current predefined Google Play app categories represent the type and genre of Arabic mobile apps. Based on the textual app description analysis, we aim to design and develop a sustainable classification system using the Latent Dirichlet Allocation method of topic modeling in order to cover the Arabic apps classification in Google Play app store. Our study supports the hypothesis that the textual app descriptions are effective in suggesting new categories for Arabic mobile apps in Google Play app store. Also, the results indicated that the current classification on Google Play app store is not suitable for our case study “Arabic apps,” as well as it is not sustainable, as it can not cover the new app types including Arabic apps. This study offers an important contribution to Arabic app analysis and design, to improve app search and exploration in several domains such as business, marketing, and technical development. Furthermore, it provides insights for the future of Arabic app research and provides guidance for the development of an Arabic app dashboard that will support users on how to select an app based on their specific needs. (shrink)

Quality assurance in higher education is a hot topic with theincreased number of students graduating from postgraduate programmesoffered by the higher education institutions. This qualitative study aimed tolook at the history and the current status of the quality assurance mechanismsin the Maldives; identify its strengths and weaknesses; and make informedrecommendations. Critical event narrative inquiry was used and data werecollected through interviews and analysis of documents. Content analysis ofdata collected revealed that Maldives was one of the very first countries inthe region (...) to establish such a mechanism and it was very similar to that ofAustralia. The most significant finding was that the body mandated to assurehigher education quality and did not have any power or regulatory authority.Therefore, it is important that the authority be an independent body establishedby an act of parliament with the regulatory power. (shrink)

Data mining’s primary clustering method has several uses, including gene analysis. A set of unlabeled data is divided into clusters using data features in a clustering study, which is an unsupervised learning problem. Data in a cluster are more comparable to one another than to those in other groups. However, the number of clusters has a direct impact on how well the K-means algorithm performs. In order to find the best solutions for these real-world optimization issues, it is necessary to (...) use techniques that properly explore the search spaces. In this research, an enhancement of K-means clustering is proposed by applying an equilibrium optimization approach. The suggested approach adjusts the number of clusters while simultaneously choosing the best attributes to find the optimal answer. The findings establish the usefulness of the suggested method in comparison to existing algorithms in terms of intra-cluster distances and Rand index based on five datasets. Through the results shown and a comparison of the proposed method with the rest of the traditional methods, it was found that the proposal is better in terms of the internal dimension of the elements within the same cluster, as well as the Rand index. In conclusion, the suggested technique can be successfully employed for data clustering and can offer significant support. (shrink)

Web search engines usually keep users’ profiles for multiple purposes, such as result ranking and relevancy, market research, and targeted advertisements. However, user web search history may contain sensitive and private information about the user, such as health condition, personal interests, and affiliations that may infringe users’ privacy since a user’s identity may be exposed and misused by third parties. Numerous techniques are available to address privacy infringement, including Private Information Retrieval protocols that use peer nodes to preserve privacy. Previously, (...) we have proved that PIR protocols are vulnerable to the QuPiD Attack. In this research, we proposed NN-QuPiD Attack, an improved version of QuPiD Attack that uses an Artificial Neural Network based model to associate queries with their original users. The results show that the NN-QuPiD Attack gave 0.512 Recall with the Precision of 0.923, whereas simple QuPiD Attack gave 0.49 Recall with the Precision of 0.934 with the same data. (shrink)