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
ACAPE-FID ADAPTIVE CONVOLUTION-ASSISTED POLAR ENCODER WITH FLEXIBLE ITERATIVE DECODING FOR HIGH-EFFICIENCY FPGA WIRELESS COMMUNICATION
Reliable wireless communication needs a highly efficient Forward Error Correction (FEC) technique in order to counter the effects of noise, interference, and losses. Most existing FEC techniques add too much redundancy and create extra latency, thereby reducing the efficiency of bandwidth utilization. Hence, the purpose of the current research is t...
By T. Ranjitha Devi, C. Kamalanathan
HOUSEHOLD E-WASTE MANAGEMENT AND CIRCULAR ECONOMY PATHWAYS IN KERALA WITH FOCUS ON POLICY AWARENESS AND DISPOSAL BEHAVIOUR
Electronic waste (e-waste) is posing an increasing challenge to environmental sustainability and human health in India, especially among the digitalizing states such as Kerala. This study examines the household electronic waste generation, disposal, concerns, policy awareness, and opportunities of circular economy through surveying 150 households i...
By K.V. Nidhi Varghese, D. Mahila Vasanthi Thangam
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
QUANTUM-ENHANCED DEEP LEARNING MODEL FOR CROP–WEED CLASSIFICATION IN SORGHUM IMAGERY USING THE SORGHUM CROP WEED DATASET CLASSIFICATION
Classification of crops and weeds is an important aspect in precision agriculture, as it aids in providing a means for efficient weed control and reduced herbicide applications to achieve high crop productivity. In this paper, a quantum-classical hybrid deep learning approach is presented for accurate identification of crops and weeds from sorghum ...
By J. Justina Michael, Logeshwari Radhakrishnan, R. Radhika, P.L. Joseph Raj, M. Mahalakshmi
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
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