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
HYBRID WHALE-GREY WOLF OPTIMIZER FOR ADAPTIVE CLUSTER HEAD SELECTION AND ENERGY CONSERVATION IN WIRELESS SENSOR NETWORKS
WSNs are critical to the contemporary IoT and monitoring, yet the energy constraint, inefficient performance of cluster head (CH) selection, and fluctuating routing diminish the network lifetime and reliability. This paper will introduce a solution to these issues by proposing a Hybrid Whale -Grey Wolf Optimizer (HWGWO) to select the adaptive and e...
By K. Chandrasekhar, G. Prabakaran, P. Dileep Kumar Reddy
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
HYBRID FEATURE DESCRIPTORS WITH RESNET-BASED CLASSIFIERS FOR FAST TEXTILE FABRIC DEFECT DETECTION USING NOVEL HYBRID FEATURE EXTRACTION ALGORITHM
The detection of fabric defects through automation is important for ensuring the quality of the textile material because traditional detection methods are not only very time-consuming but also subjective and cannot be applied during the process of production. The traditional models that use techniques of image processing and deep learning have vari...
By Deepti Patil, Ambika
A BIOMEDICAL ASSESSMENT FRAMEWORK FOR EVALUATING ADAPTIVE PERSONALITY POTENTIAL AS AN INDICATOR OF ADDICTION REHABILITATION OUTCOMES
It is still very hard to predict addiction rehabilitation outcomes at the time of admission since current methods of evaluation do not recognize the interconnection between an individual's biomedical state and personality functioning. In this paper, Introduce Biomedical Assessment Framework for Evaluating Adaptive Personality Potential (BAF-APP), w...
By Nodira Makhkamova, Laylo Juraeva, Umurzak Jumanazarov, Mamuraxon Umaralieva, Mahfuza Sangirova, Nilufar Karimova, Fotima Gazieva
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