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263 articles for “AI-Based algorithm”
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Employee Well-Being: Deep Learning Approaches to Stress Detection
Abstract: Stress has become a major concern for employee health, productivity, and overall well-being in today's fast-paced work environment. It is a growing global issue, affecting both individual employees and the productivity of organizations. Work-related stress occurs when the demands of a job surpass an individual's ability to manage, whether because of long hours, overwhelming responsibilities, or other pressures. Factors such as conflicts with coworkers or supervisors, constant changes, and job …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 52–58 Read article
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BATTERY MANAGEMENT SYSTEM (BMS)
Abstract: This review of the literature delves into the changes, structure, and the latest BMS (Battery Management Systems) technologies implemented in electric vehicles, smart grids, and energy storage, respectively. The studies emphasize the need for accurate battery modeling, advanced estimation algorithms, robust hardware design, and safety regulations. The research describes how contemporary BMSs perform integration of modeling, monitoring, control, cell balancing, and diagnostics in order to facilitate safe and energy- efficient …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 32–43 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Artificial Intelligence-Based Optimization of Mechanical and Biocompatible Properties in Polymer Composite Implants
Abstract: Artificial Intelligence (AI) has already become a ground-breaking tool of streamlining polymer composite implants to enhance both mechanical strength and biocompatibility simultaneously. This paper recommend an AI-based multi-objective optimization model, which integrates the selection of materials, structural modelling, and biological evaluation. The in vitro biocompatibility indicators, including cytotoxicity and cell adhesion, can be used to model mechanical behavior, e.g. stress-strain behavior and fatigue behavior. To arrive at an optimal material …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Optimization of Resin 3D Printing Process Parameters for Enhanced Dimensional Accuracy and Surface Roughness Using Hybrid Algorithm
Abstract: The advent of 3D printable dental resin has paved the way for minimally invasive dentistry, which helps to retain healthy tooth structure while yet producing pleasing aesthetic outcomes. However, printing these dental resins is being researched to improve their durability and therapeutic efficacy. Frontiers in dental restoration research can aim to fabricate occlusal appliances using resins with optimized parameters for enhanced functionalities. The present study aims to analyze the dimensional …
Published in Journal of Polymer & Composites · Vol. 11, Issue 3, 2023 · pp. 26–37 Read article
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Yoga Posture Detection and Correction
Abstract: Our project introduces a pioneering method for enhancing yoga practice through real-time pose correction, utilizing cutting-edge computer vision technology. Originating in India 5000 years ago, yoga offers profound benefits for both body and mind, yet with the modern lifestyle's increasing stress levels, its popularity has surged globally. While various avenues exist for learning yoga, including classes at yoga centers and self-learning through books and videos, many individuals struggle to identify …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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How Accurate is AI in Education? A Critical Examination of AI in School Education
Abstract: Artificial Intelligence (AI) is reshaping education by supporting personalized learning, streamlining administrative work, and offering intelligent tutoring systems, especially in K-12 and higher education. This research explores AI’s application in classroom instruction, student assessment, and adaptive learning, with a focus on its accuracy in school-based environments. AI tools like automated grading and intelligent tutors demonstrate strong performance in structured tasks such as multiple-choice assessments and content recommendations. However, they struggle …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 11–17 Read article
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Disease Prediction Using Machine Learning (ML)
Abstract: A technique called Machine Learning Disease Prediction uses symptoms reported by users or patients to forecast disease. The user-provided symptoms are entered into the system, and it outputs the disease probability. In disease forecasting, various popular supervised machine learning methods are known to be utilized. These algorithm estimates the likelihood of a disease occurrence. Precise analysis of medical information will support timely disease detection and management of patients based on …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 12, Issue 2, 2024 · pp. 40–48 Read article
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Atmospheric Remote Sensing: Bridging Technology and Environmental Challenges
Abstract: The rapid advancements in remote sensing technologies have revolutionized the field of atmospheric studies, offering unprecedented capabilities for detailed observation, analysis, and understanding of the Earth's atmosphere. These technological innovations have proven to be instrumental in tackling critical environmental challenges, providing scientists and researchers with the tools needed to monitor and analyze atmospheric phenomena with greater precision and depth.This article delves into the historical development, current state, and diverse applications …
Published in International Journal of Atmosphere · Vol. 2, Issue 1, 2025 · pp. 14–19 Read article
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Integrate AI and IoT to Develop Sustainable Polymer Structural Materials Processing Optimization: Enabled Monitoring Strategies for Performance and Lifecycle Assessment
Abstract: The need for long-lasting structural polymer materials that are both environmentally friendly and highly mechanically effective is driving demand for these materials as the industrial sector continues to grow. Optimizing processes, saving energy, detecting faults, and monitoring structures are all hindered by conventional polymer manufacture. This study suggests an AI-IoT system for environmentally friendly production of structural polymer materials to get around these problems. Tools for evaluating system performance and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 169–192 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Proposed System: Quantum Computing Processor Based on Linear Number Relation
Abstract: This paper details the design and implementation of a specialized quantum processor tailored for efficiently evaluating custom mathematical formulas. Optimized to perform a specific set of arithmetic and logical operations, this processor delivers a stable and high-performance computing platform. Unlike general-purpose quantum processors, which are designed for versatility across a wide range of algorithms, this dedicated processor aims to enhance performance and accuracy for a targeted set of tasks. The …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 24–32 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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The Analysis of Deep Learning-Based Methods for Identifying Diabetic Retinopathy
Abstract: Diabetic retinopathy (DR) is a degenerative eye condition resulting from diabetes mellitus, where high blood glucose levels lead to lesions on the retina. This condition is considered the leading cause of blindness among working-age diabetic patients, particularly in developing countries. As the disease is irreversible, the treatment aims to preserve the patient’s current vision. Early detection is crucial for effective management of DR to maintain vision. One of the main …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 15–31 Read article
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Utilizing Image Processing Methods for Infrared (IR) Intensity Measurement across Spatial and Temporal Domains
Abstract: The research outlined in this investigation centres on employing image processing techniques to measure infrared (IR) intensity in spatial and temporal domains. The primary objective is to ascertain intensity levels at various spatial points over time, utilizing thermal imaging technology. To record the burning flare and produce radiometric data, the experimental setup makes use of a thermal camera. Additionally, a spectroradiometer is utilized to gauge intensity. To provide a particular …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 1, 2024 · pp. 1–1O Read article
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Artificial Neural Network Implementation in FPGA using Multiplexer-based Weight Updating for Efficient Resource Utilization
Abstract: This paper presents a novel scheme for field-programmable gate array (FPGA) implementation of an artificial neural network (ANN). The proposed implementation is aimed at reducing resource requirement, without compromising on the speed so that a complex ANN architecture could be realized on a single chip at a lower cost. The weight updating process in different layers of the ANN has been carried using a simple MUX-based architecture. Backpropagation algorithm which …
Published in Journal of Semiconductor Devices and Circuits · Vol. 2, Issue 1, 2015 · pp. 1–5 Read article
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IoT-based Patient Fall Detection and Alerting System for Patient Safety
Abstract: This paper presents an Internet of Things (IoT) based patient fall detection and alerting system designed to enhance patient safety in healthcare settings. Falls among patients, especially in hospitals or care facilities, can lead to severe injuries and complications. The proposed system utilizes wearable sensors integrated with IoT technology to continuously monitor the movements and activities of patients. Machine learning algorithms are employed to analyze sensor data in real time, …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 9–14 Read article
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Design and Validation of an Artificial Intelligence-Driven Digital Twin for Real-Time Monitoring and Control in Polymer Composite Manufacturing
Abstract: Polymer Matrix Composites (PMCs) have become indispensable in high-performance sectors such as aerospace and automotive engineering, offering exceptional strength-to-weight ratios that outperform traditional metals in many demanding applications. However, the reliability of manufacturing PMCs via Vacuum-Assisted Resin Transfer Molding (VARTM) is frequently undermined by stochastic process variabilities. Unpredictable fluctuations in thermal history, preform permeability, resin rheology, and ambient conditions often lead to some defects; namely voids, dry spots, and incomplete …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 224–233 Read article