Purpose: The purpose of this applied research is to study the effectiveness of gamification on corporate training.  Methodology: A gamified course was designed AND implemented to train the location of Fire Hosing Cabinet for 24 employees of a firefighting maintenance company in Iran Mall shopping Center in Tehran. Using a quantitative quasi-experimental research plan (post-test only control group design) the participants of the study were rANDomly assigned to treatment (12) AND control (12) groups AND trained for a week.  Conclusion: The descriptive AND interpretive result of the posttest analyses indicated the effectiveness of gamification of the training performed for the employees of the firefighting maintenance company in Iran Mall shopping Center in Tehran. Moreover, the descriptive result of Gamification Acceptance Questionnaire answered by the members of the experimental group after gamified training indicated that all the participants in the experimental group were satisfied with the gamified training course.

We are... So, to reframe the inquiry: who are we on a metaphysical level? Which aspects of ourselves are the most universally representative of who we are? How do we fare in the face of the passage of time? For decades, philosophers have debated the concept of diachronic personal identity, which focuses on the question of what keeps us alive. An intricate debate has developed between those who hold the body view (animalism) AND those who hold the psychological view (memory) on the question of who we are. The two groups will eventually become so firmly set in their views that they will be unable to compromise. Hylomorphic animalism, or the view that HUMANs are rational animals, living bodies made of prime matter AND a rational soul, is an alternative answer to this divisive question that I propose in this study, following in the footsteps of Aristotle AND Aquinas. We only survive if matter AND rational souls do.

Many books have been written to illustrate the position of the new technologies in teaching AND LEARNING a foreign or second language (L2); nonetheless, most of these books have not been successful. The HANDbook of Technology AND Second Language Teaching AND LEARNING edited by Caral A. Chapell AND Shanon Sauro AND published by Wiley Blackwell in 2017, provides a comprehensive overview of the various facets of the use of technology in teaching AND LEARNING an L2. This book has not been translated into Persian AND no critical review has been published for it; accordingly, this study sought to both introduce AND critically review this book. The current critical review revealed some advantages including comprehensiveness of the whole book, the expertise of the writers, up-to-dateness, content AND format integrity, AND the use of valid sources. The main criticisms are the exclusion of some of the very recent technologies, perhaps due to the ever-changing AND exponentially volatile nature of the technological improvements AND expansions, the introduction of too many technologies at the theoretical level without providing information about their practical use. Generally, the book is an invaluable AND academically written source for L2 practitioners, postgraduate students, AND researchers.

Face recognition from digital images is used for surveillance AND authentication in cities, organizations, AND personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors AND one or more servers to process data. All sensor data from initial methods was sent to the central server for processing, raising concerns about sensitive data disclosure. The main concern was that all data from all sectors that could contain confidential information was placed in a central server. Federated LEARNING can solve this problem by using several local model training servers for each region AND a central aggregation server to form a global model in IoT networks. This article presents a novel approach to optimize data transfer AND convergence time in federated LEARNING for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time AND model accuracy in a federated LEARNING environment. The results demonstrate the effectiveness of the proposed approach in reducing data transfer AND convergence time, leading to improved performance in face recognition accuracy. This research provides insights for researchers AND practitioners to enhance the efficiency of federated LEARNING in real-world applications.

Objective & Method: To evaluate the role of team LEARNING in the development of HUMAN RESOURCES by using areview of literature. Results & Conclusion: Although knowledge AND individual LEARNING is the source for organizational development AND creating competetive advantages, but this can be sustained if LEARNING happens as the results of interactions in the group. In the LEARNING organization, almost all the critical decisions are being made in the groups, AND they act as the LEARNING units. This makes continuos LEARNING as a necessity for them. Developing group LEARNING in the organization fully depends on our knowledge of psychology of LEARNING, different methods of transferring knowledge AND group LEARNING.

One of the factors that can be the link between our intentions AND actions AND their external consequences is HUMAN agency, which indicates the conscious design AND intentional execution of actions by the individual in order to influence future events.Objective AND Method: This research with a developmental approach of psychometric method AND method 1, examines the psychometric indices of the HUMAN Factor Characteristics Scale using the classical theory of test score measurement AND the graduated question-answer theory. The purpose of this study, which included high school students in Tehran, was selected by cluster sampling of 500 people as a sample size AND statistical analysis was performed on 481 data. To collect the data, the ion HUMAN Agent Characteristics Scale (2011) was used AND the research questions were evaluated using IRTPRO AND SPSS software.Results:The assumption of local independence based on Pearson x2 index was established by applying Simjima's calibrated question-answer theory AND the assumption of being one-dimensional based on the analysis of multidimensional question-answer theory. Diagnosis parameters with question-answer approach AND classical approach Test score Both item 25 approach had the lowest AND item 2 had the highest diagnosis parameter. The answer thresholds for all the questions were so far apart that no option was covered by the other option, AND the options were independently selected by individuals at intervals of theta. The total scale was calculated with Cronbach's alpha of 0.945, intentionality of 0.894, foresight of 0.780, self-reactivity of 0.871 AND rethinking of 0.762. Also, the role of each item in internal consistency was investigated by the loop method, which all questions had a favorable role in internal consistency of this scale. The value of the validity coefficient obtained from the question-answer theory was obtained by marginal method for intentionality 0.92, forethought 0.85, self-reaction 0.91, rethinking 0.83..

Automatic topic detection seems unavoidable in social media analysis due to big text data which their users generate. Clustering-based methods are one of the most important AND up-to-date categories in topic detection. The goal of this research is to have a wide study on this category. Therefore, this paper aims to study the main components of clustering-based-topic-detection, which are embedding methods, distance metrics, AND clustering algorithms. Transfer LEARNING AND consequently pretrained language models AND word embeddings have been considered in recent years. Regarding the importance of embedding methods, the efficiency of five new embedding methods, from earlier to recent ones, are compared in this paper. To conduct our study, two commonly used distance metrics, in addition to five important clustering algorithms in the field of topic detection, are implemented by the authors. As COVID-19 has turned into a hot trending topic on social networks in recent years, a dataset including one-month tweets collected with COVID-19-related hashtags is used for this study. More than 7500 experiments are performed to determine tunable parameters. Then all combinations of embedding methods, distance metrics AND clustering algorithms (50 combinations) are evaluated using Silhouette metric. Results show that T5 strongly outperforms other embedding methods, cosine distance is weakly better than other distance metrics, AND DBSCAN is superior to other clustering algorithms.

Introduction: Social responsibility from an ethical point of view includes the obligations AND duties of natural AND legal persons towards society AND the environment. The moral behavior of people, like understANDing of social responsibility, depends on their liberal ideology, beliefs AND HUMAN values. Therefore, the aim of the current research is to study the relationship between liberalism AND HUMAN values with the moral understANDing of social responsibility. Material & Methods: The research method is applied in terms of purpose AND descriptive-correlational survey. The statistical population includes the financial managers of the companies admitted to the stock exchange, AND the questionnaire was rANDomly distributed among them AND 110 questionnaires were received. The sampling method is rANDom. The research tool is a questionnaire AND multivariate regression using SPSS software was used to analyze the data. Results: The research results show that HUMAN values based on public interest have a significant AND positive relationship with the moral understANDing of social responsibility. But the thinking of liberalism does not have a meaningful relationship with the moral understANDing of social responsibility. Conclusion: Based on the findings of this research, HUMAN values based on public interest can be considered as a tool to strengthen the moral behavior of company managers regarding corporate social responsibility. Also, improving the thinking of liberalism in managers can strengthen their social responsibility. In this case, the policy makers of Stock Exchange can direct the managers of the listed companies to comply more with the social responsibility of the company, through teaching HUMAN values AND strengthening those values, as well as monitoring the implementation of ethical regulations

Background AND Objective: The present study was conducted with the aim of investigating the effective drivers in the path of teaching-LEARNING to HUMAN resource well-being among Tehran Municipality employees.Methodology: The research method is descriptive, the objective is applied AND the implementation is survey. The data collection tool is a modified stANDard questionnaire. The statistical population of the study included one hundred employees of the Deputy for Planning AND HUMAN Capital Development in one of the 22 districts of Tehran Municipality. 112 were selected as a sample by simple rANDom method AND based on the Cochran formula. The validity of the questionnaire was confirmed using content AND construct validity, AND its reliability was confirmed using Cronbach's alpha coefficient. SPSS version 25 software was used to analyze the data, AND the smart-PLS method was used to test the quality of the structural model.Findings: While reviewing the literature AND research background, after identifying the operational concepts of LEARNING AND well-being from the perspective of employees in the municipality above AND examining the results of the completed questionnaires in the organization under study, the effectiveness of training, LEARNING, AND employee well-being was revealed as a complex AND multifaceted process, because even though the impact of training on LEARNING AND, consequently, employee well-being was conceivable, the results indicated tangible AND intangible effects of intervening AND mediating factors in this area; so that the research hypotheses were not confirmed.Conclusion: The results showed that in the statistical population under study, teaching-LEARNING processes do not guarantee well-being components, including psychological well-being, occupational well-being, AND individual well-being. Therefore, it can be acknowledged that in organizational empowerment training, in addition to psychological, personality, family issues, AND lived experiences of employees, factors such as level of education, level of expertise, skills, job description, responsibility, AND organizational position, content, time, AND place of training should be personalized AND considered in the form of comprehensive training programs. Finally, appropriate scientific AND practical suggestions were also presented.

Excellent advances of interdisciplinary studies have provided a suitable opportunity for researchers to gain a better understANDing of the application of the physics in Management knowledge. Scientific influence of quantum theory, has led to the principles AND concepts of this science as an approach in other disciplines including Educational science AND HUMAN RESOURCES training AND development, used to get. The study focused on application of the concepts of Quantum physic theory to explain the conceptual AND practical issues of main core of educational systems in the area of instruction AND LEARNING. It seems that quantum approach in teaching AND LEARNING, as one of the newest AND most advanced of teaching – LEARNING systems, could solve many problems of HUMAN RESOURCES training. The main objective of this research was to explain the interpretation of quantum mechanics to improve training systems. This interpretation can be used to improve theory AND practice of HUMAN RESOURCES training. The methodology used in this study is hermeneutic method AND analysis of theoretical bases. The results showed that that quantum approach is an effective way to optimize the functionality of educational systems in ambiguity AND complex situations; therefore, this approach can be used to improve HUMAN RESOURCES training.