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
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
HUMAN WELL-BEING, SYMBOLISM, AND ERGONOMIC ASPECTS OF ROCK ART AND NATURAL SHELTERS
Among the most important aspects of the cultural heritage of mankind, rock art and natural shelters have both aesthetic and practical purposes, as well as help to improve the psychological state, symbolic communication, and ergonomics. The paper examines rock art and natural shelters in three major frames, namely: (1) their symbolic and psychologic...
By Mehmet Sarıkahya, Serap Paçal, Ersan Sarikahya
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
EXPLORING DRIVERS OF AI ADOPTION IN PERFORMANCE MANAGEMENT SYSTEM: A COMPREHENSIVE REVIEW
The rise of AI technology has greatly transformed the traditional PMS and improved its effectiveness and reliance on data in HRM. This study mainly aims to identify the essential variables determining the implementation of AI in PMS, including the benefits, ethics, challenges, and impacts. The descriptive research methodology was used by means of a...
By K. Nivethaa, Annie Sam
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
ASSESSING THE ROLE OF ETHNOPSYCHOLOGICAL DIMENSIONS IN WORK–FAMILY BALANCE AMONG TECHNICAL ORGANIZATION
The balance between occupational pressures and family obligations continues to be a consistent issue in technical organizations because of their highly scheduled structure, shifts in production systems, and command organization culture combined with deep-rooted cultural traditions. This research focuses on the effect of ethnopsychological character...
By Olmosbek Eshmuradov, Salim Doniyorov, Shohida Jumayeva, Nigora Turaeva, Muxayyo Karimova, Kamola Sadirova, Gavhar Mengliyeva
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
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
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