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130 articles for “supporting frame structure”
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Integrating Social Perception and Economic Valuation for Riparian Zone Preservation: Evidence from Kiliti Watershed, Ethiopia
Abstract: Riparian zones play a crucial role in maintaining watershed health by providing ecosystem services such as water filtration, erosion control, biodiversity conservation, and aesthetic and cultural benefits to surrounding communities. Despite their importance, riparian areas in many developing countries are increasingly degraded due to agricultural expansion, grazing pressure, and settlement encroachment. This study integrates social perception analysis with economic valuation to assess riparian zone preservation in the Kiliti Watershed, Northwestern …
Published in International Journal of Environmental Planning and Development Architecture · Vol. 4, Issue 1, 2026 · pp. 49–55 Read article
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
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Role of Quantum Chemistry in Catalysis: A Comprehensive Review
Abstract: Catalysis plays a crucial role in modern chemical manufacturing, energy conversion, and environmental protection by enabling chemical reactions to occur more rapidly, selectively, and with reduced energy consumption. A fundamental understanding of catalytic processes at the atomic and electronic levels is essential for the rational design and optimization of catalysts. Quantum chemistry has emerged as a powerful theoretical and computational framework that enables detailed investigation of electronic structure, reaction energetics, …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 · pp. 01–16 Read article
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(𝛅,Ü ) Convex Structure on Partial B-Metric Space Concerning Quasi Contraction and Fixed-Point Results
Abstract: This work introduces the concept of (δ,Ü )– Convex Partial b-Metric Spaces using convex structure. Motivated by this approach, we demonstrated fixed point results and their uniqueness, as well as quasi contraction, and provided some supporting instances for the established results. Our findings expand prior fixed-point results to a novel concept (δ,Ü )– Convex Partial b-Metric Spaces. To support our theoretical findings, we provide several instances that exemplify the established …
Published in Recent Trends in Mathematics · Vol. 1, Issue 1, 2024 Read article
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Human–Nature Relationships and Sustainable Development: Insights from Environmental Studies
Abstract: The accelerating environmental crisis highlights the need to re-examine the fundamental relationship between humans and nature. Conventional development models often promote a utilitarian view of nature, leading to ecological degradation, biodiversity loss, climate change, and unsustainable resource use. The research problem addressed in this study is the inadequate integration of human–nature relationship perspectives within sustainable development frameworks, despite growing recognition that environmental sustainability depends not only on technological innovations and …
Published in Research & Reviews : Journal of Ecology · Vol. 15, Issue 2, 2026 · pp. 38–43 Read article
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An Evaluationof Different Types Soil Stabilization Techniques
Abstract: Soil stabilization is the procedure of improving the shear strength parameters of soil and so increasing the bearing capability of land.It is needed when the territory available for construction is not suited to carry structural load. Soils exhibit generally undesirable engineering properties. Soil Stabilization is the modification of soils to raise their physical attributes.Stabilization can increase the shear intensity of a territory and/or control the shrink-swell properties of a stain, …
Published in Recent Trends in Civil Engineering & Technology · Vol. 9, Issue 3, 2019 · pp. 40–48 Read article
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Computational Study of Sombor Index on Generalized Abid–Waheed Graphs for Polymer Modeling
Abstract: This study investigates the topological properties of generalized Abid Waheed graphs. Development of theoretical models in chemistry, reducing computational complexity while analysing large molecules or networks Abid Waheed graphs play a significant role. Motivated by these findings, the research was extended to encompass generalized Abid Waheed graphs, characterized by r cycles of order s. A notable similarity between Abid Waheed graphs and Jahangir graphs was observed. The potential applications of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 267–274 Read article
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Using MCDM Methods in automotive industry- A Review
Abstract: In the automobile sector, choosing the best car necessitates weighing a number of factors, including cost, fuel economy, performance, safety, and environmental impact. In order to solve complicated situations that need the simultaneous evaluation of multiple conflicting aspects, Multi-Criteria Decision Making (MCDM) procedures are essential. Among the various MCDM approaches, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and MOORA are widely recognized for their straightforward structure …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 22–28 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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Integrated Computational and Bio-catalytic Transformations: DFT-Guided Mechanistic Insights, Machine Learning, and Nano-biocatalyst Engineering for Sustainable Catalysis
Abstract: Computational catalysis has emerged as a transformative scientific discipline that integrates quantum chemistry, molecular modeling, machine learning, and density functional theory (DFT) to understand catalytic mechanisms and design highly efficient catalytic systems for sustainable industrial applications. The increasing global demand for environmentally responsible chemical manufacturing has accelerated research on advanced catalytic materials including transition metal catalysts, metal–organic frameworks (MOFs), homogeneous catalysts, heterogeneous systems, and bimetallic catalysts involving nickel and iron. …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 36–44 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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AI-Optimized Biodegradable Polymer Composites for Medical Applications
Abstract: The value of biodegradable polymer composites in the medical practice has been massive as the composites may be deployed to provide temporary structural support, and they are also safe to degrade within the human body. However, the conventional material design process is trial and error, which is ineffective and inefficient. The article proposes a hybrid model involving experimental characterization, as well as an artificial intelligence (AI)-based model, to optimize biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 41–49 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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AI-Driven Prediction of Mechanical and Thermal Properties in Polymer-Based Functionally Graded Composites
Abstract: The proposed architecture of the current paper is an artificial intelligence (AI)-driven model of forecasting mechanical and thermal aspects of polymer-based functionally-graded composites (FGCs). Traditional micromechanical and finite element models, which are practical in homogeneous composites, might not be able to account in nonlinear interaction that is caused by compositional gradient. To overcome the challenge, machine learning (ML) models like artificial neural network (ANN), support vectors regression (SVR), and gradient-boosted …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 70–89 Read article
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AI-Optimized Nano-Silica Reinforced PCM Composites for Predictive Solar-Thermal Energy Storage Networks
Abstract: This study presents an AI-optimized nano-silica reinforced polymer composite phase change material (PCM) for predictive solar-thermal energy storage networks. The proposed composite combines paraffin wax, high-density polyethylene (HDPE), and uniformly dispersed nano-silica particles to improve thermal conductivity, structural stability, leakage resistance, and long-term cycling performance. The composite was fabricated through melt blending and ultrasonication-assisted nanoparticle dispersion, followed by comprehensive morphological, chemical, thermal, and thermophysical characterization using scanning electron microscopy (SEM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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How Accurate is AI in Education? A Critical Examination of AI in School Education
Abstract: Artificial Intelligence (AI) is reshaping education by supporting personalized learning, streamlining administrative work, and offering intelligent tutoring systems, especially in K-12 and higher education. This research explores AI’s application in classroom instruction, student assessment, and adaptive learning, with a focus on its accuracy in school-based environments. AI tools like automated grading and intelligent tutors demonstrate strong performance in structured tasks such as multiple-choice assessments and content recommendations. However, they struggle …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 11–17 Read article
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Electromagnetic Propulsion Train for Future Transportation
Abstract: The Electromagnetic Propulsion Train project focuses on the development and analysis of a prototype system that achieves linear motion through the application of controlled electromagnetic forces. Unlike conventional railway systems that rely primarily on mechanical drive mechanisms such as wheels, axles, and traction motors, this project explores an alternative propulsion approach based on electromagnetic interaction. In this system, a sequence of electromagnets is strategically positioned along the track to generate …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 2, 2025 · pp. 25–31 Read article
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The Power of Narrative: A Mixed Methods Investigation of Storytelling in Social Media Based Social Cause Campaigns and Its Impact on Audience Engagement Among Young Adults
Abstract: Background: The proliferation of digital platforms has fundamentally transformed how social cause organisations communicate with their target audiences. Storytelling has emerged as a strategic tool for driving emotional resonance and behavioural change among young adults a demographic that is both digitally native and increasingly socially conscious. This study investigates (1) how storytelling in social media–based social cause campaigns influences the digital interaction behaviour of young adults, and (2) whether such …
Published in Recent Trends in Social Studies · Vol. 3, Issue 2, 2026 · pp. 37–48 Read article