The impact of work environment, individual characteristics, training design and motivation on training transfer to the work: the case of Saudi Arabian Public Security Organisation

The aim of this empirical study was to find out the impact of work environment, individual characteristics, training design and motivation on training transfer to the work in the context of public security. Methodology included a cross sectional questionnaire survey administered to a stratified convenience sample of 500 officers of Public Security Organisation in Saudi Arabia. The effective response rate was 70.2% (351 useable surveys returned out of 500 surveys administered). Data were analysed by running frequencies, descriptive statistics and exploratory factor analysis and structural equation modelling. Results showed that participants’ learning motivation was statistically significantly determined by peer support (β = .311, p = .000), training retention (β = .197, p = .027), goal orientation (β = .163, p = .036) and self-efficacy (β = .158, p = .047). Statistically significant predictors of transfer motivation were learning motivation (β = .401, p = .000), peer support (β = .224, p = .003), training retention (β = .176, p = .021) and self-efficacy (β = .152, p = .028), feedback (β = -.159, p = .014) and openness to change (β = -.147, p = .020). Statistically significant determinants of training transfer were training design (β = .318, p = .000), training retention (β = .313, p = .000), transfer motivation (β = .177, p = .008) and supervisor support (β = .146, p = .018). Training transfer to the work in the context of public security is positively affected by work environment, individual characteristics, training design and motivation factors but a negative association between transfer motivation and performance feedback and openness to change suggest a review of these factors in the context of public security organisations

Designing An Art Virtual Exhibition Through Applying Design Thinking Strategy

The idea of this research came in association with the establishment of an art exhibition in the depths of the global pandemic (COVIED-19) to review the learning outcomes of the courses that rely on computers by teaching some of the graphic design topics in the Department of Art Education at King Saud University. This research aims to identify a virtual exhibition (VE) through the application of design thinking (DT) in designing a virtual graphic art exhibition. This research deals with the nature and characteristics of (VE). In addition, it reviews the concept of the emergence of (DT) and its stages of development. It examines the practical experience of creating an exhibition by implementing the stages of (DT) based on the Stanford D.School model. Accordingly, (DT) explains obstacles that can be studied to find creative and obvious alternative solutions. This research derives its importance from the lack of research in the art field that applies (DT). It will support the method of implementing it in educational or artistic situations in the future. The results showed that the (DT) and its methods accommodated in choosing the appropriate model and reviewing creative solutions to the problems that users may face in creating or viewing (VE) through interactive display platforms. Technology and social media have supported prompt access and sharing of opinions and reactions to (VE). Hence, (VE) supports easy access, interaction about art and its techniques of (VE). Finally, designing a virtual art exhibition is more inexpensive than making an actual art exhibition

(4,4) superfield supergravity

We present the N=4 superspace constraints for the two-dimensional (2d) off-shell (4,4) supergravity with the superfield strengths expressed in terms of a (4,4) twisted (scalar) multiplet TM-I, as well as the corresponding component results, in a form suitable for applications. The constraints are shown to be invariant under the N=4 super-Weyl transformations, whose N=4 superfield parameters form another twisted (scalar) multiplet TM-II. To solve the constraints, we propose the Ansatz which makes the N=4 superconformal flatness of the N=4 supergravity curved superspace manifest. The locally (4,4) supersymmetric TM-I matter couplings, with the potential terms resulting from spontaneous supersymmetry breaking, are constructed. We also find the full (4,4) superconformally invariant (improved) TM-II matter action. The latter can be extended to the (4,4) locally supersymmetric Liouville action which is suitable for describing (4,4) supersymmetric non-critical strings.Comment: 32 pages, LaTeX, revised version (one reference added, and one Appendix is reduced

d=2, N=2 Superconformal Symmetries and Models

We discuss the following aspects of two-dimensional N=2 supersymmetric theories defined on compact super Riemann surfaces: parametrization of (2,0) and (2,2) superconformal structures in terms of Beltrami coefficients and formulation of superconformal models on such surfaces (invariant actions, anomalies and compensating actions, Ward identities).Comment: 43 pages, late

Real time emotions recognition through facial expressions

Human behavior is deeply influenced by emotions. Detection of emotions plays a pivotal role in understanding how individuals respond to various stimuli, such as reading text, encompassing feelings of anger, anxiety, confusion, or nervousness. Real-time facial emotion detection during online text reading represents an innovative approach for receiving immediate feedback based on readers’ emotional responses. Real-time emotion detection finds applications in interactive displays and holds immense potential for online learning platforms, where it can be utilized to analyze students’ emotional states and gauge their level of comprehension. Despite vast existing literature on emotion detection, real-time emotion detection is not very well studied. This study demonstrates the design and implementation of face emotion detection for students while they are using online learning platforms. The primary objective is capturing human emotions and storing them in the database after five seconds while they are reading online text. The system is implemented using SSD based on VB.NetV1. The proposed system has strong relevance for integration with online web applications to detect learners’ real-time emotions. Experiments are performed using CK+ and JAFFE face datasets and results show 96.46% and 98.43% accuracy, respectively. The system not only provides accurate results but also enables high-quality, robust, and real-time feedback based on the facial expressions of readers, facilitating a deeper understanding of students’ emotional engagement during their online learning experiences

RESULTS OF CARDIAC-SURGERY IN THE ELDERLY USING NORMOTHERMIC TECHNIQUES

Background: Cardiac surgery is increasingly offered to older patients. A new method of myocardial protection, continuous normothermic blood cardioplegia, offers theoretical advantages over hypothermic methods because it avoids ischemia. We set out to study the results of continuous normothermic blood cardioplegia in older patients. Methods: We reviewed the medical records of 79 patients aged 70 years or older who underwent cardiac surgery using normothermic cardiopulmonary bypass and myocardial protective techniques between January 1992 and August 1993. Results: The mean +/-SD age of the patients was 74+/-3 years; 46 patients were men and 33 were women. Coronary artery surgery was performed in 33 patients, mitral valve replacement alone in 10 and with coronary artery surgery in six, aortic valve replacement in 20, aortic valve replacement with coronary artery surgery in six, the Bentall procedure in one, repair of a false aneurysm of the left ventricle with coronary surgery in one, and double valve replacement with coronary artery surgery in two. The complications were stroke in 2.5% of the patients (all of whom recovered completely), myocardial infarction in 6%, and postoperative bleeding requiring reoperation in 9%. The overall mortality was 10%. Conclusion: The morbidity and mortality for heart surgery in the elderly using continuous normothermic blood cardioplegia and normothermic systemic cardiopulmonary bypass were comparable to those achieved using hypothermic techniques

Ensemble Learning Based on Hybrid Deep Learning Model for Heart Disease Early Prediction

Many epidemics have afflicted humanity throughout history, claiming many lives. It has been noted in our time that heart disease is one of the deadliest diseases that humanity has confronted in the contemporary period. The proliferation of poor habits such as smoking, overeating, and lack of physical activity has contributed to the rise in heart disease. The killing feature of heart disease, which has earned it the moniker the “silent killer,” is that it frequently has no apparent signs in advance. As a result, research is required to develop a promising model for the early identification of heart disease using simple data and symptoms. The paper’s aim is to propose a deep stacking ensemble model to enhance the performance of the prediction of heart disease. The proposed ensemble model integrates two optimized and pre-trained hybrid deep learning models with the Support Vector Machine (SVM) as the meta-learner model. The first hybrid model is Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) (CNN-LSTM), which integrates CNN and LSTM. The second hybrid model is CNN-GRU, which integrates CNN with a Gated Recurrent Unit (GRU). Recursive Feature Elimination (RFE) is also used for the feature selection optimization process. The proposed model has been optimized and tested using two different heart disease datasets. The proposed ensemble is compared with five machine learning models including Logistic Regression (LR), Random Forest (RF), K-Nearest Neighbors (K-NN), Decision Tree (DT), Naïve Bayes (NB), and hybrid models. In addition, optimization techniques are used to optimize ML, DL, and the proposed models. The results obtained by the proposed model achieved the highest performance using the full feature set

Assessing Use of Caloric Information on Restaurant Menus and Resulting Meal Selection in Saudi Arabia: Application of the Theory of Planned Behavior

Background: Beginning in 2019, the Saudi Government required restaurants to post caloric information on menus to facilitate informed meal choices by Saudi consumers. Purpose: To assess the impact on consumer food choices, leveraging TPB, related to caloric information on menus among restaurants in Saudi Arabia. Methods: A cross-sectional study among adult Saudi consumers was conducted. Theoretically based on TPB, data were gathered on the use of caloric information on menus in restaurants across Riyadh. Results: Only 24.4% of participants utilized caloric information on menus to make a meal decision. Attitude (r = 0.65), and perceived behavioral control (r = 0.62) significantly correlated with intention. Multiple regression analysis showed that attitude (R 2 = 0.47, P = .05), and perceived behavioral control (R 2 = 0.11, P = .03) were significant predictors of using caloric information on menus for meal selection. Discussion: Among Saudi participants, the use of caloric information on menus was low in their meal decision. Interestingly, attitude was found to be a significant predictor of utilizing caloric information in making a meal decision. Translation to Health Education Practice: Consumer education should consider constructs of the TPB in intervention development and evaluation strategies to influence attitudes toward healthy eating behaviors and enhance the use of caloric information on restaurant menus in making informed meal decisions

Superspace Supervortices

We present the theory describing supersymmetrical vortices in the curved superspace of the (1,0) supergravity. The action is defined as a (1,0) locally supersymmetric $SU(2)/U(1)$ coset perturbed by the cosmological constant-like term. The perturbation is such that it preserves the integrability of the coset model. Because of supersymmetry the perturbed theory is an exact quantum system provided a proper dilaton is taken into account. The exact value of the dilaton is determined in the supersymmetric case by the quasi-classical background of the bosonic coset.Comment: UMDPP 94-074, QMW 93-35, 14 page