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784 articles for “model-based approach”
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Thermo-Structural Machine Learning Framework for Malicious Sample Detection and Validation in Polymer Composite Materials
Abstract: The increased use of polymer composites in aerospace, automotive, biomedical and industrial applications has increased the urgency of developing dependable methods to detect malicious samples with counterfeited resins, unauthorized additives, recycled components, hidden flaws, or purposefully degraded physical properties. Most current machine learning techniques have focused either on isolated spectral analysis or detecting flaws in materials; as such, they are unable to perform joint verification of both chemical authenticity and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Predict the Severity of Diabetes Cases, Using K-Means and Decision Tree Approach
Abstract: In recent years, diabetes has emerged as one of the most prevalent infections, and its prevalence is rapidly increasing globally. Type 2 diabetes is common throughout the world. For the management and prophylaxis of diabetes, early detection is crucial. Machine Learning (ML) approaches are rapidly gaining importance in the field of diagnostic purposes due to their ability to classify data. In this article, a mixed recommended technique is presented to …
Published in Journal of Advances in Shell Programming · Vol. 9, Issue 2, 2022 · pp. 24–31 Read article
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A Novel Approach to Reduce Image Retrieval Problem Using Gabor Transform, Wavelet Transform and Euclidean Distance Measure
Abstract: In the processing of image, pattern recognition and computer vision, the image retrieval is a most famous research area. Our paper presents a new method in CBIR through merging the low level feature i.e. texture, color and shape features. At first, we transform the color space from RGB model to HSV model, and then extract color histogram to form color feature vector. CBIR is the process where search of image …
Published in E-Commerce for Future & Trends · Vol. 3, Issue 1, 2016 · pp. 10–15 Read article
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Artificial Intelligence and Machine Learning Approaches for Corrosion Prediction and Management of Steel Reinforcement in Concrete: A Systematic Review
Abstract: Load bearing concrete structures need steel reinforcement bar (rebar), which are prone to attack by the corrosive environment inside the concrete due to constant ingress of moisture, pollutant gases and anions (mainly Cl−, SO42−). In recent models for the potential life span, the causes of failure of concrete structures have been established principally due to the chloride (Cl−) ion, because of the ease in transportation of Cl− in concrete and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Optimizing Power Generation from Building Ventilation Systems: A Study on Exhaust Fan Efficiency
Abstract: Due to population growth, the world's energy consumption has increased dramatically in both wealthy and developing nations in recent years, and by 2042, it is predicted to have doubled or more. Since a few years ago, the use of innovative sustainable power sources to meet energy demands has been gradually increasing. We've chipped away at a different idea because of this. As an alternative energy source, renewable energy (RE) resources …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 2, 2023 · pp. 22–27 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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Rheumatoid Arthritis and Stem Cell Therapies Perspectives for It
Abstract: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by systemic inflammation, primarily affecting synovial joints, leading to joint destruction and systemic complications. The pathogenesis involves immune system dysregulation, autoantibody production, and enzymatic imbalances. Enzymes, including matrix metalloproteinases (MMPs), serine proteases, and kinases, play crucial roles in these processes. Their dysregulation contributes significantly to disease progression through the imbalance of pro-inflammatory cytokines, oxidative stress, and extracellular matrix (ECM) degradation. MMPs, …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
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Routing Protocols in FANETs with Future Enhancements
Abstract: Flying Ad Hoc Networks (FANETs), which are swarms of Unmanned Aerial Vehicles (UAVs), are an emerging solution which revolutionized the area of mission-critical and infrastructure-less communication systems. These networks provide real-time data transfer for use cases such as disaster relief, battlefield observation, environmental monitoring, and 6G-based smart cities. However, the dynamic profile of FANETs, which is defined by high 3D mobility, limited energy resources, unstable wireless links, and constant topology …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 8–13 Read article
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Hierarchical Methodology Approach to SOC Design: A Comprehensive Look
Abstract: The design scale of a chip has increased many folds in the last few years and shows a continuous exponential trend. This is made possible by the reduction in transistor size and an evolving process technology. As a result, it is possible to move to SoC technology (System on Chip-A single die consisting of multiple subsystems) rather than a traditional ASIC. This has obviously resulted in an increase in the …
Published in Journal of VLSI Design Tools and Technology · Vol. 10, Issue 3, 2020 · pp. 35–42 Read article
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Machine Learning-Based Task Scheduling and Resource Optimization in Edge-IoT Systems
Abstract: The rapid expansion of Internet of Things (IoT) applications has introduced significant challenges in managing computational workloads across distributed edge environments. Edge- IoT systems are characterized by limited computational capacity, dynamic task arrivals, and strict latency constraints. Traditional heuristic-based scheduling techniques often fail to adapt to fluctuating workloads and heterogeneous resource availability. This study proposes a machine learning-based task scheduling and resource optimization framework for Edge-IoT systems. The proposed model …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Design and Analysis of a Lower Control Arm in Car by Finite Element Analysis Approach
Abstract: AbstractSuspension system is the most important part in any vehicle. It directly affects the human safety as well as performance. The lower control arm is a wishbone-shaped metal strut that attaches to the wheel assembly. Structural optimization techniques under static load conditions have been widely used in automobile industry for lightweight vehicle to increase its performance level. This study deals with finite element analysis of the lower control arm of …
Published in Journal of Instrumentation Technology & Innovations · Vol. 8, Issue 2, 2018 · pp. 17–24 Read article
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Real-time Facial Recognition with Convolutional Neural Networks for Personalized Music Therapy
Abstract: In this project, a web-based application has been developed that integrates computer vision-based facial recognition, multiple algorithms, and machine learning approaches. The given system obtains a user’s emotions in the real-time frame by analyzing facial expressions such as eyes, mouth, the forehead, and so on. It detects emotions like happiness, sadness, that is neutrality, or rock. For a given detected emotion, language, and a user’s chosen artist, the system recommends …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 67–76 Read article
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Forest Fire Hazards Vulnerability and Risk Assessment in Bhajji Forest Range of Himachal Pradesh (India): A Geospatial Approach
Abstract: The vulnerability of the Indian forests to fire varies from place to place depending upon the type of vegetation and climate. The coniferous forest in the region is very prone to fire. Objective of the current work is to prepare a model which articulate the forest fire risk and assess the fire vulnerability so that the concerned authorities can minimize the fire danger. Fire hazard mapping was performed using knowledge …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 1, 2017 · pp. 25–40 Read article
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Codal Validation and Optimization of Gantry Girders Under Variable Wheelbase and Impact Loads: A Review of Analytical, Numerical, and Codal Approaches
Abstract: Gantry girders serve as critical structural elements in industrial facilities such as steel plants, workshops, and heavy manufacturing units, where electric overhead traveling (EOT) cranes operate. The design of these girders is governed by stringent codal provisions to ensure safety under bending, shear, and deflection. However, discrepancies between codal predictions, analytical formulations, and finite element analysis (FEA) results, particularly under variable wheelbase and dynamic impact loads, have been widely reported. …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 23–29 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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A Machine learning approach to asses carbon emission, utility to produce biomaterial
Abstract: The transportation sector, and the automotive industry in particular, has grown significantly over the last ten years. However, these quick advancements have also brought about important problems that require workable answers. The problem of carbon emission is responsible for global warming due to greenhouse gas emission. The present work is focused on CO2 emission from public and personal transport within Agra city on a real-time basis. In the context of …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 22–30 Read article
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DC Motor Control using Deep Reinforcement Learning for Enhanced Robustness and Precision
Abstract: DC motors remain the workhorse of industrial automation and mobile robotics, but achieving simultaneous high-speed transient response and negligible steady-state error under variable load conditions continues to challenge classical Proportional-Integral-Derivative (PID) controllers. These model-dependent systems often require extensive tuning and struggle to maintain optimal performance when confronted with parametric uncertainties, non-linear friction, or sudden voltage fluctuations. This study presents a novel, model-free control paradigm utilizing Deep Reinforcement Learning (DRL)—specifically, a …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 22–29 Read article
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Examining the Influence of DEM Resolution in Flood Hazard Assessment using the Flood Modeller Pro 2D Solver
Abstract: Floods are the most frequent natural hazards that threat the human life, environment and infrastructure. The flood prediction models that have wide use in the recent years represent important tools for flood management decisions aiming to mitigate the impacts of the flood events. The accuracy of the constructed prediction models is based on the quality of the primary data, such as the terrain’s resolution. This study examines the effect of …
Published in Journal of Water Resource Engineering and Management · Vol. 4, Issue 1, 2017 · pp. 14–24 Read article
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Spintronic Logic Device Modeling and Energy Optimization for Beyond-CMOS Computing Systems
Abstract: The continuous scaling limitations of conventional CMOS technology have accelerated the exploration of alternative computing paradigms for next-generation low-power and high-performance systems. Spintronic logic devices have emerged as a promising solution due to their non-volatility, ultra-low switching energy, high integration density, and compatibility with beyond-CMOS architectures. This research presents a comprehensive modeling and energy optimization framework for spintronic logic devices applied in beyond- CMOS computing systems. The proposed work investigates …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education
Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article