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309 articles for “support networks”
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Psychological Determinants of Farmers’ Adoption of Sustainable Practices: A Behavioural Approach to Agricultural Extension
Abstract: Sustainable agriculture has emerged as a global priority to balance productivity with environmental conservation. Yet, adoption of sustainable practices by farmers remains uneven, shaped not only by economic incentives but by underlying psychological and behavioural factors. This review explores the psychological determinants influencing farmers’ willingness to adopt sustainable agricultural practices across traditional and modern contexts. Drawing upon behavioural theories such as the Theory of Planned Behaviour and the Diffusion of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 101–109 Read article
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Bird-Tree Associations and Co-occurrence Patterns in Delhi: Implications for Urban Ecological Restoration and Invasive Species Management
Abstract: Urban trees and birds are intertwined indicators of ecological resilience in cities. This study maps citywide bird-tree interactions in Delhi, India, hosting more than 300 avian species. The city was divided into hexagonal grids, and bird–tree data (506 interactions) were collected through field surveys across 131 sites using standardized 1-kilometre transects. Native keystone species, like ficus, supported the greatest bird diversity, while invasive Prosopis juliflora was widely used for perching …
Published in Research & Reviews : Journal of Ecology · Vol. 15, Issue 2, 2026 · pp. 1–23 Read article
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Managing Pavement Settlement Risk: Impact of Waterlogging and Soil Conditions
Abstract: In the context of road infrastructure, the occurrence of waterlogging due to rainfall can have significant repercussions. Rainwater often infiltrates the road surface and, depending on factors such as the depth of the foundation and the extent of penetration into the ground, can lead to the soil beneath the road becoming either moist or saturated. This, in turn, can result in a reduction of the soil's bearing capacity. When vehicles …
Published in Trends in Transport Engineering and Applications · Vol. 10, Issue 2, 2023 · pp. 45–50 Read article
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Bird-Tree Associations and Co-occurrence Patterns in Delhi: Implications for Urban Ecological Restoration and Invasive Species Management
Abstract: Urban trees and birds are intertwined indicators of ecological resilience in cities. This study maps citywide bird-tree interactions in Delhi, India, hosting more than 300 avian species. The city was divided into hexagonal grids, and bird-tree data (506 interactions) were collected through field surveys across 131 sites using standardised 1-kilometre transects. Native keystone species like ficus supported the greatest bird diversity, while invasive Prosopis juliflora was widely used for perching …
Published in Research & Reviews : Journal of Ecology · Vol. 16, Issue 2, 2026 Read article
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Optimizing Tourist Mobility with Dijkstra’s Algorithm: A Review on Pollution Reduction through Smart Path Planning
Abstract: Although Tourism helps the economy, but it can also harm the environment, especially in popular tourist destinations. Optimizing routing is one way to reduce these environmental effects. This review paper examines how the well-known and traditional Dijkstra's method for shortest path computation is used to pollution management and support sustainable tourism. The study explores how intelligent traffic routing can minimize traffic congestion in environmentally sensitive areas and lower fuel consumption …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 20–29 Read article
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Internet of Things Connectivity Using Millimetre Wave: A Study
Abstract: Internet of Things(IoT) is undergoing rapid development, which is connecting millions of devices and causing sectors to undergo transformation. On the other hand, given this increase, the constraints of conventional wireless communication technologies are being stretched to their limits. Millimetre wave, often known as mmWave, is a high-frequency band that has the potential to revolutionise Internet of Things connectivity by providing much higher capacity levels and lower latency levels. Microwave …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 18–30 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1258–1284 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
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Renewable-Powered HVAC Systems: Advances in Solar, Bioenergy, and Heat Pump Technologies
Abstract: The global demand for refrigeration, air conditioning, heating, and ventilation (HVAC) systems has increased rapidly due to population growth, urbanization, industrialization, and rising expectations for indoor thermal comfort. These systems account for a substantial share of global energy consumption and greenhouse gas emissions, primarily because they rely heavily on fossil-fuel-based electricity and thermal energy. Consequently, the decarbonization of HVAC and refrigeration sectors has become a critical component of global climate …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 26–33 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 15–24 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article
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A review on Pole mounted GSM based circuit breaker
Abstract: At this modern age of technology-heavy machines working on live electric lines are more in numbers then compared to past few years. The fast development of electrical industries developed standards and established safety procedures to minimize various types of major hazards that may lead to severe injuries and death of the operators. However, if the scenario of the lines needs to be repaired that’s where the job will be endangered …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 1–8 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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A Five-Layer Architectural Framework for Sustainable and Scalable AI Systems
Abstract: Artificial Intelligence (AI) is not only about algorithms. AI works like a full “stack” of layers, from electricity to real-world user applications. In this paper, we explain a simple and student-friendly Five- Layer Architecture of AI: (1) Energy, (2) Chips, (3) Infrastructure, (4) Models, and (5) Applications. Each layer supports the next layer, like a cake with multiple layers. If any layer is weak, AI systems become slow, costly, or …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Optimal PMU Placement in Power Systems Using Graph Theory and PSAT
Abstract: Phasor measurement units (PMUs) play a vital role in modern power systems by delivering synchronized, real-time measurements. These devices enhance system reliability by supporting functions such as monitoring, protection, and control. By accurately capturing voltage and current phasors across different locations, PMUs enable better situational awareness and more effective decision-making in grid operations and management. Determining the optimal location of PMUs is essential to ensure system observability, reduce installation costs, …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 26–32 Read article
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Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
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Transforming Human Resources Leveraging AI Across the Associate Lifecycle for Strategic Success
Abstract: AI is taking the lead in changing the game in human resources by mitigating challenges and optimizing processes throughout the entire associate lifecycle. From pre-hire, AI helps with interview bias, enhances hire projections, and supports talent acquisition with predictive analytics. Once onboarded, AI helps with compensation benchmarking, automates performance feedback with the mitigation of bias, and analyzes associate sentiment through NLP and LLMs. In the middle of the life cycle, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 30–36 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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Self Healing Material: An Introduction
Abstract: Self-healing materials have emerged as a transformative innovation for sustainable infrastructure and advanced applications such as wearable electronics and smart transportation systems. These materials possess the intrinsic ability to repair damage autonomously or with minimal external intervention, thereby extending service life and reducing maintenance costs. Inspired by biological systems, self-healing mechanisms are broadly classified into extrinsic approaches, such as microcapsule and vascular networks based healing, and intrinsic mechanisms involving reversible …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 604–611 Read article