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340 articles for “reliability modeling”
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Gear-Related Stress Analysis and Comparison Between the Fem and Agma Standards
Abstract: In many different devices, gears enable the efficient transfer of motion and torque. They are an essential component of modern mechanical power transmission systems. It has been demonstrated that bending and surface contact stresses at the gear tooth are the primary causes of gear failure, despite their widespread use. Too much stress can lead to tooth wear, pitting, or breakage, which can ultimately reduce the operating life and reliability of …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 13–18 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Design Strategies of Polymer Composite Components for Sustainable Renewable Energy Microgrids
Abstract: Increasing power demand and variable performance requirements in renewable-energy systems motivate integrating advanced polymeric and composite materials into microgrid components to improve reliability and performance. This paper presents a design and control framework for a standalone microgrid that couples power-electronic and energy-conversion subsystems with polymer-composite–based components to enhance durability, thermal management, and electromagnetic shielding. The microgrid uses a doubly fed induction generator (DFIG) for wind generation to enable independent active …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 63–71 Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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Enhancing Security of UPI Payments Through Artificial Intelligence
Abstract: The integration of Artificial Intelligence (AI) into modern digital payment systems has brought about a significant transformation in the banking and financial sector. Among these systems, the Unified Payments Interface (UPI), developed by the National Payments Corporation of India (NPCI), has emerged as one of the most successful real-time payment mechanisms due to its simplicity, accessibility, and efficiency. With the incorporation of AI technologies, UPI has witnessed notable improvements in …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 7–12 Read article
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Dielectric Elastomers in Actuation and Energy Applications: Material Behavior and Design Strategies
Abstract: Dielectric elastomers (DEs), a class of electroactive polymers, have attracted significant attention for their ability to undergo large, reversible deformations under electric stimulation. This unique capability makes them highly suitable for a range of actuation and energy harvesting applications, especially in the emerging fields of soft robotics, flexible electronics, artificial muscles, and sustainable power generation systems. DEs offer compelling advantages such as low weight, mechanical flexibility, high energy density, and …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 13–18 Read article
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Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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Role of Machine Learning Principles for Efficient Nuclear Fuel Management and Design
Abstract: The introduction of machine learning (ML) and evolutionary computation methods in addressing complex nuclear fuel management challenges has brought a significant positive change in the domain of nuclear fuel management. Key applications include fuel assembly design optimization, core loading pattern determination, burnup calculation acceleration, fuel performance prediction, and spent fuel characterization. The analysis reveals significant improvements in computational efficiency, prediction accuracy, and optimization capabilities when ML techniques are properly integrated …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–33 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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Electromagnetic Transients in Strongly Non-Uniform Overhead High Voltage Lines
Abstract: This paper addresses the electromagnetic transients in high strongly non-uniform overhead voltage lines. For their simulation, a novel Laplace-domain approach has been introduced. The voltage and current patterns in terms of location and complex frequency are determined by a set of simultaneous algebraic and partial differential equations. To solve them numerically, an effective Mathematica code is proposed. By contrasting the outcomes of their application to multiple case studies with those …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 1, 2025 · pp. 30–36 Read article
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Review On BIM-Based (Revit+Robot Software) Comparative Wind Load Analysis of High-Rise RCC Buildings in Zone-III, IV and V
Abstract: Wind load is one of the most critical factors influencing the design and serviceability of high-rise reinforced concrete (RCC) buildings. As building height increases, wind-induced effects such as storey drift, lateral displacement, and structural stiffness become dominant design considerations. Numerous studies have been conducted using conventional and advanced techniques such as Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and Building Information Modelling (BIM). However, limited research focuses on comparative …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Analyzing Thermal Expansion in Polymer Composites Through Heat Transfer Simulations
Abstract: Although lightweight and strong, polymer composites require careful handling in environments where temperatures shift. Their usefulness in fields like aviation, vehicle manufacturing, and electronic devices comes from customizable heat behavior alongside favorable mechanical traits. Yet variation in size due to heating or cooling remains a concern hard to dismiss. As conditions change, expansion occurs - sometimes enough to disrupt fit, alignment, or function within complex systems. This response to warmth …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 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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Design and Analysis of Smart Solar EV Charging System
Abstract: The rising demand for electric vehicles (EVs) has generated an urgent requirement for sustainable and advanced charging systems. This study delineates the design and analysis of an intelligent solar EV charging system intended to reduce dependence on the grid and optimize the utilization of renewable energy. The system incorporates a solar photovoltaic (PV) array, battery energy storage, and an IoT-enabled smart controller to optimize power delivery. A Maximum Power Point …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 1, 2026 · pp. 06–15 Read article
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Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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Zebrafish in Drug Research: Decoding Biological Mechanisms and Finding Novel Therapeutic Targets
Abstract: The zebrafish, scientifically known as Danio rerio, is a powerful model organism in biological research because of its favorable traits, which include rapid development, genetic tractability, and transparent embryos. Zebrafish were first identified for their use in studies of vertebrate development, but they have since spread to a variety of disciplines, such as pharmacology, clinical research as a disease model, and most notably, drug development. Zebrafish have emerged as a …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 · pp. 1–8 Read article