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1180 articles for “FEA”
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Nitro IDE: Exploring Integrated Development Environments: Current Trends and Innovations
Abstract: Integrated Development Environments (IDEs) have become essential in modern software development, offering a centralized platform that brings together source code management, debugging tools, version control, and compilation features. This study offers an in-depth analysis of various IDE platforms, with a particular focus on Eclipse as a widely used open-source integration environment. It also explores specialized IDEs tailored for embedded systems and enterprise-level Java (J2EE) application development. Additionally, the study examines …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 35–40 Read article
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AutoGen Bike: A Self-Sustaining Smart Electric Bike with Integrated AI Safety Systems
Abstract: This is the paper which gives the information about the self-sustaining electric bike. This also tells the idea about how energy is produced during its usage. The “Auto gen bike” is the most useful aspect that can change the future of the electric bikes. This also helps in the conservation of natural resources and nature. This also helps in the accidents happening to the two-wheel vehicle. This is achieved by …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 41–49 Read article
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Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Innovative Applications of AI and Machine Learning in Voice-Driven Systems: Friday AI 2.0
Abstract: The development of artificial intelligence (AI) has enabled the development of increasingly sophisticated models that can understand and react to human questions. This study introduces Friday AI-2.0, a cutting-edge AI model that improves user engagement by using natural language processing (NLP) and voice synthesis technologies to produce text-based and audio-based responses. By increasing engagement through an intuitive and engaging interface, Friday AI-2.0 seeks to improve the user experience. By describing …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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Smart Home Automation Systems: AI Approaches for Monitoring and Reducing Power Consumption
Abstract: This study comprehends a Bluetooth controlled home automation system that users can control remotely through a specific Android platform. Technology advancements lead to homes that acquire greater intelligence. Remote-controlled switches continue replacing standard wall switches because they operate as part of system-wide central control gear in contemporary homes. Today's users must operate wall-mounted manual switches in every room of the house. Members of both these populations face an additional obstacle …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 10–17 Read article
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Robotic Arm Using Color Sorting Algorithm
Abstract: *Author for CorrespondenceDeokar AdityaE-mail: adityadeokar0007@gmail.com1Dean Academics, Department of Computer Technology, Sanjivani K.B.P. Polytechnic, Kopargaon, Maharashtra, India2Research Scholar, Department of Computer Technology, Sanjivani K. B. P. Polytechnic, Kopargaon, Maharashtra, IndiaReceived Date: April 03, 2025Accepted Date: April 22, 2025Published Date: May 09, 2025Citation: K.P. Jadhav, Deokar Aditya, Dushing Sushant, Gaikwad Om, Garbhe Prathamesh. Robotic Arm Using Color Sorting Algorithm. Journal of Mechatronics and Automation. 2025; 12(2): 8–16p.Industrial and commercial applications form part …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 8–16 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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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Analysis of Friction Stir Welding Utilizing ANSYS: A Study Based on Simulation
Abstract: Friction Stir Welding (FSW) represents a sophisticated solid-state welding methodology that has attracted considerable scholarly attention due to its efficacy in amalgamating high-strength, lightweight substrates including aluminium, magnesium, and titanium alloys. FSW enables the fabrication of defect free products with a substantial amount of mechanical and wear properties. The process is highly sensitive to various parameters that significantly influence the quality and strength of the final product. Studies have shown …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 62–77 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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Machine Learning Framework for Optimizing Polymer–Metal Oxide Composites as Charge Selective Layers in Perovskite Solar Cells
Abstract: To achieve high-performance and stability of perovskite solar cells (PSCs), it was important to incorporate innovative interfacial materials to tune the balanced charge extraction, low recombination, and enhanced operational lifespan. On this note, polymer composites with metal oxides have been proposed as promising candidates as charge selective layers (CSLs), whereby they present a rare combination of tunable energy levels, improved film forming abilities, and better interface engineering capabilities. In this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1073–1098 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Smart Attendance Management System: Design and Implementation
Abstract: The Smart Attendance Management System (SAMS) is an all-in-one, role-specific digital platform created to transform how educational institutions manage both attendance and academic content. Designed with modern technological standards, SAMS simplifies and streamlines the tracking of student attendance while also facilitating effective course administration. The system supports a wide range of features such as automatic attendance recording, detailed reports for individual subjects, and consolidated overviews of overall class attendance. In …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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IoT Based Smart Plant Watering System
Abstract: Effective water management in plant irrigation is essential for resource conservation and sustaining robust plant development in the age of smart technologies. This project introduces a NodeMCU microcontroller-based Internet of Things (IoT) smart plant pump control system designed to automate irrigation procedures based on real-time environmental data. A soil moisture sensor built within the system continuously checks the soil's moisture content. The NodeMCU activates the water pump to irrigate the …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 3, 2025 · pp. 8–13 Read article
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NOVA: The Virtual Desktop Assistant
Abstract: This research work details the design, development, and implementation of a voice-controlled desktop assistant aimed at streamlining everyday tasks and boosting user productivity. The assistant seamlessly integrates with various desktop applications and core operating system functions to automate routine operations, deliver relevant contextual information, and provide personalized suggestions based on observed user behavior and preferences. A standout feature of the system is its ability to monitor user activity levels and …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 19–25 Read article
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Innovative Polymer Nanocomposites: Bridging Sustainability and Advanced Material Performance
Abstract: This study examines the evolution of bio-based polymer nanocomposites using eco-friendly synthesis methods to improve mechanical, thermal, and barrier properties. It involves the combination of sustainable synthetic polymers with natural polymers in the presence of nanofillers in a green and compatible fashion to generate durable nanocomposites. Optimal alignment of nanofillers with the polymer matrices can be achieved using solvent casting, melt blending, and in-situ polymerization as fabrication methods. Consequently, the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1671–1679 Read article