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548 articles for “Predictive AI”
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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Heart Attack Prediction Using Machine Learning
Abstract: Heart attacks have become a prevalent and serious condition in recent years due to a variety of causes. Numerous variables, including age, sex, fat, and others, can be used to predict it. In the current study, it was found that a data set with 13 parameters and 302 distinct data values, collected from a Kaggle dataset to assess patient condition, was covered. This article delves into the application of machine …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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A SHAP - Enhanced Voice-Based Conversational Agent for Agriculture Using BERT
Abstract: The integration of advanced artificial intelligence technologies into modern agriculture has become increasingly important for narrowing the persistent knowledge gap faced by farmers, especially in regions with limited access to expert advisory services. While state-of-the-art language models such as BERT (Bidirectional Encoder Representations from Transformers) demonstrate exceptional performance in understanding and generating natural language, their opaque “black-box” nature often limits user confidence, trust, and widespread adoption. Farmers may hesitate to …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Computational Fluid Dynamics and Composite Material Study on Scoop-Type Savonius Turbine for Train-Based Energy Generation
Abstract: This study investigates the feasibility of integrating a scoop-type savonius vertical-axis wind turbine (VAWT) on the rooftop of a moving train to generate renewable onboard power. The motivation stems from increasing demands for sustainable energy solutions and reducing reliance on fossil fuels, particularly in transportation. A two-blade savonius turbine, with dimensions of 0.4 m in diameter and 0.5 m in height, was modeled in PTC Creo Parametric 3.0 and analyzed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 566–580 Read article
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Smart Monitoring and Controlling of the Battery and Motor
Abstract: The demand for effective battery and motor monitoring and management to guarantee dependability, safety, and peak performance has increased due to the quick development of electric vehicles and smart industrial systems. The smart monitoring and control methods used in battery management systems and motor control systems are thoroughly reviewed in this paper. In addition to speed, torque, efficiency, and fault situations in motors, it emphasizes important characteristics like temperature, voltage, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 11–15 Read article
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Geo AI-Powered Urban Footprints
Abstract: In the contemporary era, building footprints are of paramount importance for accurate and current inventories in the development of infrastructure and geospatial analysis. Traditional methods, relying on manual digitization, were largely unsustainable as the urban regions were growing rapidly. Manual digitization was expensive and lacked geometric precision. This paper introduces an automated, end-to-end GEO AI-powered framework for high-end fidelity building footprint extraction from Google Satellite Data. Our approach for this …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Fabrication, Numerical Simulation and Compact Modeling of Ph-BTBT-C10 Organic Thin Film Transistor
Abstract: Flexible and cost-effective electronics have been necessitated by the advent of organic thin-film transistors (OTFTs). This study aims to study the performance of OTFT using a 2-decyl-7-phenyl-[1]benzothieno[3,2-b][1]benzothiophene (Ph-BTBT-C10) organic semiconductor. The paper also explore accurate device modeling for technology optimization and circuit design that supports device improvement. This research includes device fabrication, numerical simulation using TCAD, compact modeling, and parameter extraction. By combining temperature-dependent bandgap narrowing with existing theories, this …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 1–18 Read article
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Exploring Potential Phytochemicals for Myasthenia Gravis Treatment: A Molecular Docking and ADME Analysis Approach
Abstract: Objective: Muscle feebleness and exhaustion derived from a disruption in neuromuscular transference are hallmarks of the crippling autoimmune disease myasthenia gravis (MG). The drawbacks of the current MG therapy options are frequently partial efficacy and adverse effects. To investigate the potential of phytochemicals in MG control, in this work we integrated molecular docking with ADME (absorption, distribution, metabolism, and excretion) analysis using a computer method. We identified molecules exhibiting favorable …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 2, 2024 · pp. 1–13 Read article
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Computational Intelligent Techniques for Enhancing the Capabilities and Efficiency of Smart Water Meters
Abstract: In recent years, the realm of smart water meters has undergone a transformative evolution driven by the integration of computational intelligent techniques. This research work embarks on an exploration of the multifaceted applications of these techniques, delving into their profound impact on enhancing the functionality and efficiency of smart water meters. The convergence of artificial intelligence (AI) and machine learning (ML) algorithms with smart water meters presents a paradigm-shifting opportunity …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 66–74 Read article
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Demand Forecasting for Perishable Food Commodities Using Data Analytics
Abstract: This paper introduces a comprehensive study aimed at enhancing the forecasting of perishable food item demand. Focusing on solving the critical issue of waste management within the supply chain of food products, the research undertakes a comparative analysis of various machine learning models. The development of an optimized model that is capable of accurately forecasting the demand for perishable food items is the focus of this research. The research includes …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 3, 2024 · pp. 27–37 Read article
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Energy-efficient HVAC System with Decision Tree Classifier and Real-time SMS Notification
Abstract: This research paper explores the design and implementation of an energy-efficient heating, ventilation, and air conditioning (HVAC) system aimed at optimizing energy consumption and enhancing operational efficiency. The system incorporates high-efficiency components, including axial flow fans, motors, and intelligent variable frequency drives, achieving an overall system efficiency of up to 85%. By utilizing both static and dynamic pressures, the HVAC system operates more effectively under varying conditions compared to traditional …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 29–34 Read article
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The Next Era of Solid-State Innovation: Beyond Silicon
Abstract: The semiconductor industry is getting close to the physical and economic boundaries of silicon-based technology. A new era of solid-state innovation is beginning. Beyond Silicon: The Next Era of Solid-State Innovation looks at the materials, device layouts, and manufacturing methods that are about to change the way electronics and energy work. The article talks about improvements in wide- and ultra-wide-bandgap semiconductors, two- dimensional materials, and quantum and neuromorphic systems that …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 19–23 Read article
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A Study to Assess the Risk Factors Associated with Sudden Death in Population on Hemodialysis
Abstract: Background: Patients with chronic kidney disease (CKD) receiving maintenance hemodialysis (HD) experience disproportionately high mortality, with sudden death remaining a leading cause. Multiple clinical, biochemical, and care-related factors influence outcomes, yet comprehensive risk stratification models and the role of dialysis timing and early nephrology care remain inadequately explored in resource-limited settings. Objectives: This study aimed to (i) identify clinical and biochemical risk factors associated with mortality in HD patients, (ii) …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 14–19 Read article
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Navigating the Principles and Practice of Oral Anticoagulant Therapy: A Comprehensive Healthcare Guide
Abstract: Oral anticoagulant therapy plays a critical role in the prevention and treatment of thromboembolic disorders, including atrial fibrillation (AF), venous thromboembolism (VTE), and mechanical heart valve replacement. This research article aims to provide a comprehensive overview of the principles and practice of oral anticoagulant therapy, focusing on the mechanisms of action, pharmacokinetics, clinical indications, monitoring, and management of associated complications. The cornerstone of oral anticoagulant therapy includes vitamin K antagonists …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 76–82 Read article
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Evaluation of Selected Common Wheat (Triticum aestivum L.) Genotypes for Diverse Traits at Kokate and Hossana, Southern Ethiopia
Abstract: During the 2018/19 cropping season, a field trial involving 49 bread wheat (Triticum aestivum L.) genotypes was conducted at the Kokate and Hossana research sub-stations in Southern Ethiopia. The aim was to assess various characteristics within these genotypes. A simple lattice design was employed, and data on 11 quantitative traits were gathered and analyzed using SAS statistical software. The analysis of variance (ANOVA) revealed that there were notable differences in …
Published in Research & Reviews : Journal of Botany · Vol. 14, Issue 1, 2025 · pp. 1–11 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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In-silico Approach of Few Selected Phytoconstituents on Newer Cancer Targets
Abstract: Background: Cancer’s high death rates are mainly due to, drug resistance and unmet medical demands. It necessitates novel anticancer medications. AI tools aid in efficient and faster drug discovery by analyzing data, modeling processes and optimizing pipeline stages. Aim: The aim of this present study is to evaluate phytoconstituents against novel and newer cancer targets. Methodology: The ligands Daidzein, Resveratrol and Genistein were targeted against the Glutamate dehydrogenase (PDB ID …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 12–17 Read article
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Advancements in Metal-Plastic Hybrid Structures: Experimental Analysis and Design Optimization of 3D-Printed Honeycomb Frameworks
Abstract: The exploration of metal-plastic hybrid structures has gained significant attention due to their potential for lightweight, high-strength applications across industries such as aerospace, automotive, and construction. This study investigates the experimental and design enhancements of a metal-plastic hybrid structure utilizing a honeycomb architecture produced through 3D printing. By integrating metals with plastic polymers in a honeycomb configuration, this hybrid approach aims to combine the high strength and stiffness of metals …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 36–43 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article