THE STRUCTURAL MODEL OF CAUSAL RELATIONSHIPS BETWEEN KNOWLEDGE MANAGEMENT ELEMENTS, ORGANIZATIONAL MEMORY, AND KNOWLEDGE ACCUMULATION AT KING ABDULAZIZ UNIVERSITY
The study was to examine the direct influence of the presence of the elements of knowledge management on the preservation of knowledge accumulation, the direct influence of the elements on the utilization of the organizational memory dimensions, and the direct influence of organizational memory on the preservation of knowledge accumulation at King ...
By Anwar Ali Alhadawi, Mohammad Jafar Arif
INVESTIGATION INTO THE OPTIMAL THERMAL EFFICIENCY OF A POROUS MEDIUM INSIDE A DUCT CONTAINING GLASS BEADS
In the current experimental study, a rectangular channel packed with a porous medium is used to study the thermo-hydraulic performance of a forced convection air heater. In addition to heat transfer enhancement, various experimental setups (Works 1 to 4) have been used to investigate the combined effects of the disruption of the thermal boundary la...
By Mohammed Z. Hameed, Musa Weis Mustafa
A STUDY ON THE COMPLETENESS OF PATIENT MEDICAL DOCUMENTATION BY PHYSICIANS IN MULTISPECIALTY HOSPITALS
In multi-specialty hospitals, maintaining comprehensive and accurate medical records is a mechanical necessity for high-quality care, regulatory compliance, and medicolegal protection. While physicians are the primary authors of these clinical records, a focus on care execution over documentation often leads to critical gaps in recording patient pr...
By A. Jasmin, K. Ravichandran, K. Anandhi
METAHEURISTIC-BASED OPTIMIZATION OF COMPOSER DEEP LEARNING MODELS FOR SEPSIS PREDICTION AND CLASSIFICATION
Heterogeneous, high-dimensional, and complex clinical data have remained a key challenge for early sepsis detection in intensive care units. This paper introduces a Hybrid GAP-HMSOA-GNN-COMPOSER architecture that incorporates a graph-based relational model and metaheuristic optimization to learn and generate accurate, reliable sepsis predictions. T...
By K. Sameera, P. Amudhavalli
INFLUENCING FACTORS ON MIGRATION: EVIDENCE AND POLICY IMPLICATIONS FOR AN EMERGING COUNTRY
International migration from developing economies is increasingly driven by the interplay between economic incentives, social networks, and the institutional environment. The understanding of these drivers is central to policy design aimed at maximizing the benefits of labor mobility, minimizing human capital loss, and capturing positive impacts of...
By Dao Tuan Minh
ARTIFICIAL INTELLIGENCE IN AUDITING: EVALUATING THE IMPACT OF GENERATIVE AND PREDICTIVE MODELS ON AUDIT QUALITY AND EFFICIENCY
Artificial intelligence (AI) is significantly contributing to beneficial transformations in auditing by enhancing analytical capabilities, automating monotonous tasks, and refining decision-making processes. This piece of research looks into the effects of predictive and generative AI on the quality of auditing as well as its efficiency. Moreover, ...
By S. Edmund Christopher, Jaishu Antony, Zaheda Daruwala, Mahmoud Abouagwa
EFFECT OF GRAPHENE AND GRAPHENE-FERROMOLYBDENUM ON MECHANICAL, ELECTRICAL, AND THERMAL PROPERTIES OF FSPED COPPER HYBRID COMPOSITES
Copper has good electrical and thermal conductivities and is used in numerous electrical and electronic applications as well as thermal management applications, but not for mechanical applications because of its low mechanical strength. In this research work, fabrication of graphene and graphene ferromolybdenum (Gr–FeMo) reinforced copp...
By P Vineeth Krishna, Sabitha Jannet, R Raja
AN ANALYSIS OF PSYCHOPHYSIOLOGICAL DEVELOPMENT IN CHILDREN BORN THROUGH IN VITRO FERTILIZATION HIGHLIGHTING COGNITIVE AND BEHAVIORAL CHARACTERISTICS
More than ten million infants have been conceived through in vitro fertilization (IVF), but uncertainties remain about whether methods used in assisted conception leave any trace of their influence on psychophysiological development in later life. This review presents findings from empirical and meta-analytic studies published between 2010 and 2025...
By Nodir Yadgarov, Sarvinoz Otamuratova, Nilufar Rakhmonova, Munisa Sanayeva, Iqbolkhon Abdurakhmanova, Mehriniso Abuzalova, Begali Rayimov
MULTILINGUAL XLM-R FOR MENTAL HEALTH SIGNAL DETECTION IN LOW-RESOURCE TAMIL LANGUAGE THROUGH CROSS-LINGUAL AND BILINGUAL LEARNING
Mental-health NLP (Natural Language Processing) remains strongly English-centric, limiting language-inclusive digital health technologies for low-resource languages such as Tamil. This study investigates whether multilingual representation learning can transfer a specialised mental-health classification task to Tamil and whether bilingual English&n...
By Deivanai Gurusamy, Midhunchakkaravarthy Janarthanan
EMOTIONAL INTELLIGENCE AND HUMAN–AI COLLABORATION: A MULTILEVEL ANALYSIS OF EMPLOYEE CREATIVITY AND ADAPTIVE PERFORMANCE
Workplaces that are equipped with artificial intelligence (AI) technology have changed the relationship between technology and people at work and require knowledge about how the interaction between human competencies and the conditions of an organization impacts work. This paper examines the role of emotional intelligence and the ability to collabo...
By Tisha Tomy, R. Sheeja, V. Santhosh Kumar, Veera Shireesha Sangu, Ruben Anto Michael, Pavithra Srinivas