Background Numerous studies indicated that workers in the health sector suffer from work stress, hassles, and mental health problems associated with COVID-19, which negatively affect the completion of their job tasks. These studies pointed out the need to search for mechanisms that enable workers to cope with job stress effectively. Objectives This study investigated psychological flow, mental immunity, and job performance levels among the mental health workforce in Saudi Arabia. It also tried to reveal the psychological flow (PF) and mental immunity (MI) predictability of job performance (JP). Method A correlational survey design was employed. The study sample consisted of 120 mental health care practitioners (therapists, psychologists, co

  The research addressed the formal functions resulting from the use of various guiding signs in the design of the interior spaces of airports in various pragmatic, expressive and psychological aspects. The aim is to identify the functions the guiding signs perform in facilitating and organizing the travelers' movement and satisfying the needs of the visitors and users of the unfamiliar places which they intend to visit, the nature of the services offered by these signs as one of the important parts within their general design. The research also identified the concept and types of signs as a means of visual communication and how to employ them in the design of the airports public spaces, and what are the criteria of their use and fu

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

An aircraft's landing stage involves inherent hazards and problems associated with many factors, such as weather, runway conditions, pilot experiences, etc. The pilot is responsible for selecting the proper landing procedure based on information provided by the landing console operator (LCO). Given the likelihood of human decisions due to errors and biases, creating an intelligent system becomes important to predict accurate decisions. This paper proposes the fuzzy logic method, which intends to handle the uncertainty and ambiguity inherent in the landing phase, providing intelligent decision support to the pilot while reducing the workload of the LCO. The fuzzy system, built using the Mamdani approach in MATLAB software, considers critical

لقد ألقت أزمة جائحة كورونا بظلالها على قطاع التعليم بصورة عامة، والتعليم العالي بصورة خاصة؛ إذ دفعت اغلب الجامعات والقطاعات التعليمية التابعة لها لإغلاق أبوابها او العمل فيها بصورة متقطعة، وذلك حفاظا على سلامة الموظفين والتدريسيين والطلبة من الإصابة بمخاطرها التي بات انتشارها يشكل وعلى الرغم من أهمية تكنولوجيا المعلومات والتعليم الالكتروني في التعليم الجامعي، الا ان ذلك التعليم المتمثل باستخدام مختلف تك

   This research includes the application of non-parametric methods in estimating the conditional survival function represented in a method (Turnbull) and (Generalization Turnbull's) using data for Interval censored of breast cancer and two types of treatment, Chemotherapy and radiation therapy and age is continuous variable, The algorithm of estimators was applied through using (MATLAB) and then the use average Mean Square Error (MSE) as amusement  to the estimates and the results showed (generalization of Turnbull's) In estimating the conditional survival function and for both treatments ,The estimated survival of the patients does not show very large differences

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims