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309 articles for “FEA”
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A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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Silicon Symphony: The Science of Semiconductors Circuits
Abstract: Modern electronics are built on the foundation of semiconductor circuits, which precisely and efficiently control the flow of electrical impulses. This article takes a look at the underlying physics of semiconductor materials and how their unique electrical properties allow the design and functioning of diodes, transistors and integrated circuits. This study links microscopic scientific principles to the behaviour of real circuits. It considers essential concepts such as charge carriers, doping …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Fracture Analysis of Laminated composite plates using Extended Finite Element Method: A Review
Abstract: Laminated composite plates are used in aerospace, automotive, and marine industries. They feature great durability against fatigue, a high strength-to-weight ratio, and mechanical attributes that may be altered. However, they are prone to fracture and delamination under complex loading, requiring accurate fracture analysis for structural integrity. Traditional finite element methods (FEM) need extensive mesh refinement for modelling crack propagation which increases the computational costs. The Extended Finite Element Method (XFEM) …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 16–25 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Functional Biomolecules in Animal Nutrition: Biochemical Mechanisms and Their Impacts on Growth Performance and Health Outcomes
Abstract: Functional biomolecules have emerged as critical modulators of animal nutrition, extending beyond conventional nutrient supply to regulate biochemical and physiological processes that determine growth performance and health outcomes. This review synthesizes current knowledge on diverse classes of bioactive compounds, including amino acids, peptides, fatty acids, vitamins, minerals, phytochemicals, and microbial-derived metabolites, and their roles in livestock systems. Emphasis is placed on underlying biochemical mechanisms such as enzyme activation, nutrient signaling …
Published in International Journal of Nutritions · Vol. 3, Issue 2, 2026 Read article
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Performance Improvement of Standalone Solar PV Pumping System Using Supercapacitor
Abstract: Two of the most pressing issues when it comes to rural communities of arid and semi-arid regions are water shortage and unstable grid electricity. Standalone solar photovoltaic (PV) pumping systems have been introduced as a clean, low maintenance alternative to diesel powered pumps, but their performance is limited by intermittent nature of sunlight and limited energy buffering capacity of conventional batteries. The paper is an investigation into the incorporation of …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 54–62 Read article
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Contextualising health-disaster risk reduction pillars for under-resourced rural secondary schools in Limpopo Province, South Africa
Abstract: School communities in under-resourced rural settings face a disproportionate burden of health-related disasters, including outbreaks, water and sanitation failures, food insecurity and compound events that disrupt learning and wellbeing. Yet school based disaster risk reduction (DRR) evidence in Southern Africa is uneven with limited empirically guidance tailored to the organisational and infrastructural realities of disadvantaged schools. Drawing on the Comprehensive School Safety Framework and the World Health Organization's Health Emergency …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 124–135 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Design and Development of a Smart Automated Packaging System for Poultry Drumsticks
Abstract: The present work aims to design and implement an automated packaging system for poultry drumsticks that enhances operational efficiency, product quality, and adaptability. The integrated system offers a solution that complies with industrial quality and safety standards by sorting products, getting accurate weighing, and efficiently portioning food into 1-kilogram standardized units. By effectively reducing human involvement, operational inefficiencies, workforce requirements, and contamination hazards, the automation system becomes sufficiently adaptable to …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Assessment of Knowledge, Attitudes and Practice of Family Planning among Women of Reproductive Age in Northern Nigeria: A Sociological Study
Abstract: Family planning is a very vital element of reproductive health that enables individuals and couples to decide on how many and how far they would have their children. It is important in enhancing maternal health, child health, alleviating poverty and enhancing sustainable development. Although family planning services are available in Nigeria, their use has been low in most regions in the country especially Northern Nigeria. The paper evaluated the KAP …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 45–64 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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NeoVax: Smart Child Vaccination and Monitoring Platform
Abstract: Child vaccination plays a crucial role in preventing life-threatening diseases and ensuring long-term public health. Despite the availability of structured immunization programs, many children miss scheduled vaccinations due to lack of awareness, busy lifestyles of parents and absence of effective reminder systems. This research paper presents NeoVax, a smart and user-friendly child vaccination reminder and management system designed to address these challenges using digital technology.NeoVax is an Application that enables …
Published in International Journal of Children · Vol. 3, Issue 2, 2026 · pp. 14–20 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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Blockchain for Secure Health Records in India: Aligning with Ayushman Bharat
Abstract: India’s healthcare ecosystem continues to face significant hurdles, particularly in the efficient management, protection, and accessibility of patient health records. For decades, medical data in the country has remained scattered across institutions, recorded in incompatible formats, and stored in systems that rarely communicate with each other. These gaps not only slow down clinical decision-making but also increase exposure to data breaches and other cybersecurity risks. In this context, blockchain technology …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 01–05 Read article
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An Overview on Energy Harvesting Using Piezoelectric Material for Wi-Fi Systems
Abstract: The rapid proliferation of wireless-networked devices has intensified the demand for sustainable, maintenance-free power sources that can keep small-scale Wi-Fi modules operational in hard-to-reach or infrastructure-limited environments. This study investigates the feasibility of harvesting ambient mechanical energy using piezoelectric transduction technology and directly feeding the harvested power to a low-power Wi-Fi communication subsystem. A compact energy-harvesting module was engineered from lead-zirconate-titanate (PZT) cantilevers with resonant frequencies tuned to the dominant …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 56–63 Read article