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435 articles for “sub-modeling”
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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Artificial Intelligence in Drug Repurposing: A Short Impact Assessment
Abstract: Artificial intelligence (AI) in pharmaceutical repurposing has become a game-changing tool that opens new avenues for the application of new drugs that have already been approved. Traditional drug discovery is a lengthy and expensive process, whereas AI can rapidly analyze vast datasets of biological, chemical, and clinical information to predict drug-disease interactions. AI-driven techniques, such as machine learning, natural language processing, and deep learning, enable the identification of potential repurposing …
Published in Trends in Drug Delivery · Vol. 11, Issue 3, 2024 · pp. 42–45 Read article
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Tri-Band Edge-Cut Rectangular Microstrip Patch Antenna on Composite Substrate for RF Energy Harvesting in IoT Networks
Abstract: The increasing use of Internet of Things devices underscores the pressing need for sustainable energy solutions, since traditional batteries necessitate regular replacement and constrain scalability. Radio frequency energy harvesting is a viable option; nonetheless, antenna design continues to provide a significant problem owing to the requirements for compactness, efficiency, and multi-band functionality. A hybrid composite substrate configuration combining FR4 (εr = 4.3) and RT Duroid (εr = 2.2) is employed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 867–883 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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Polymer Composite-Enhanced Anaerobic Digestion of Kitchen Waste for Optimised Biogas Production: Process Design, Parametric Study, and Simulation Analysis
Abstract: There is an urgent need for decentralised sustainable biogas production from organic waste due to the rising amount of food waste in cities. The application of polymer composite material including HDPE tanks, PVC pipes, and FRP secondary containment systems presents a promising option compared to conventional MS digester fabrication in terms of durability, excellent thermal insulation capability, light weight, and easier installation. This study explores the possibility of adopting a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 803–818 Read article
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Group-Theoretic Symmetry Indices for Modular Building Layouts under Seismic Load Redistribution
Abstract: Symmetry in modular buildings operates simultaneously as an architectural language, a structural regularizer, and a computational design variable. This paper develops a group-theoretic framework for evaluating and optimizing plan symmetry in modular buildings subjected to seismic load redistribution. The building layout is modeled as a finite occupancy–stiffness field defined on a rectangular lattice, where each module encodes both mass and stiffness contributions. Planar reflections and quarter-turn rotations are represented as …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 01–07 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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Muscle vs. Heart: A Comprehensive Review of Anabolic Steroid-Induced Cardiovascular Risks
Abstract: Anabolic-androgenic steroids (AAS) are widely used by athletes and bodybuilders to enhance muscle mass and performance. However, their misuse is associated with serious and often underrecognized cardiovascular risks. Despite their popularity, particularly among young adults, the long-term consequences of AAS abuse on cardiovascular health remain insufficiently explored in the literature. This review aims to: 1. Analyze the cardiovascular implications of AAS use. 2. Elucidate the molecular and physiological mechanisms contributing …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 2, 2026 Read article
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Investigations Into the Potential for Anthracene Decomposition of Novel Soil Bacterium, Pseudomonas putida P7
Abstract: Bioremediation of hazardous contaminants holds immense importance for the preservation of a clean and healthy environment. Conversely, the accumulation of toxicants can be mitigated with the assistance of microorganisms capable of breaking down these harmful substances into benign molecules. Anthracene is frequently used as a model molecule for studies on PAH pollution because it is found in many carcinogenic PAHs. Therefore, the hunt for new microorganisms with the ability to …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 2, 2024 · pp. 29–44 Read article
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Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
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Integration of Vertical Axis Wind Turbines into Urban Environments: Feasibility and Design Considerations
Abstract: Abstract This study aims to comprehensively investigate the performance of Savonius rotor wind turbines through a combination of numerical simulations and experimental testing. Initially, 3-dimensional CAD software Solidworks and ANSYS will be utilized to design detailed models of the turbines. Numerical meshes will then be generated around these models using FLUENT software, incorporating the k-ε turbulence model to simulate fluid flow fields. Parameters such as drag coefficient, lift coefficient, pressure …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 20–25 Read article
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Estimation of Soil Erosion Using GIS in Pune District, Maharashtra
Abstract: The Varandha Ghats pans approximately 14.62 km 2 , where changes in temperature, vegetation, topography, and soil characteristics are causing continuous soil erosion. Catchment heterogeneity and climatic variations cause spatial variability in hydrological processes. Differences in land use, soil type, topography, and rainfall patterns influence how water moves and accumulates across regions, resulting in diverse hydrological responses. This complexity challenges accurate modeling and effective water resource management strategies across variable …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 26–33 Read article
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Synthesis and characterization of mixed SnO2-ZnO Nano composites material to study the kinetics of catalytic reduction of Aromatic Nitro compounds
Abstract: A straightforward and cost-effective method was employed to synthesize zinc oxide (ZnO) nanostructures supported on tin oxide (SnO₂) for catalytic applications. This hybrid nanocomposite, formed by integrating ZnO with SnO₂, exhibited impressive catalytic activity in the reduction of various nitro compounds. The synergistic interaction between ZnO and SnO₂ significantly enhanced the surface area and active sites of the catalyst, thereby improving its overall efficiency. The resulting SnO₂-ZnO nanocomposite not only …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 3, 2025 · pp. 8–14 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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Bonding Strength Characteristics of FRP Cylindrical Composites Under Hygrothermal Loading
Abstract: This study investigates the bonding strength characteristics and stress distribution patterns in fiber-reinforced polymer (FRP) cylindrical composites subjected to hygrothermal loading conditions. A four-phase cylindrical model incorporating AS-Graphite and S-Glass fibers with low modulus epoxy coating was analyzed under four distinct pressure loading conditions (25.984, 38.976, 77.953, and 155.906 MPa). Comprehensive stress analysis revealed significant variations in von-Mises stress, maximum principal stress, and minimum principal stress across fiber, coating, matrix, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 950–967 Read article
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R-M and M-R Model for Interpreting Logic State of Memristor Aided NOR with Enhanced Noise Margin
Abstract: Memristive crossbar arrays are one of the fascinating subjects in the field of nanoelectronics and memory devices. The arrangement of arrays consists of grid-like structure with rows and columns of memristors which are resistive devices that can preserve their resistance state even after power is turned OFF. They have now emerged as a promising alternative to traditional memory technologies due to their high density, non-volatility and low power consumption. This …
Published in Recent Trends in Mathematics · Vol. 1, Issue 1, 2024 · pp. 35–41 Read article
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Designing and Modeling of Giant Magnetoresistance (GMR) Materials based Devices in Electrical Power and Biomedical Systems
Abstract: This paper presents Designing and Modeling of Giant Magnetoresistance (GMR) Devices in Electrical Power and Biomedical Systems and the related materials. The GMR, inverse GMR, and Spin valve using exchange bias have been analytically derived and discussed from the designing point of view for optimizing the performance of the GMR based Devices in Electrical systems. More recently, GMR has been used in sensors, magnetic memory chips, and hard-disk read-heads. The …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 1, 2025 · pp. 22–32 Read article
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Effects of Reels and short videos on human mind and Academic Life
Abstract: The rapid rise of short-form video platforms such as Instagram Reels, TikTok, and YouTube Shorts has fundamentally reshaped the way people consume information and entertainment. While these applications offer quick engagement and social connection, their excessive use has raised serious concerns about their psychological and academic impacts. This research investigates the relationship between short-form video addiction, mindfulness, academic anxiety, and academic engagement among university students. Drawing upon the theoretical framework …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article