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914 articles for “SHC–stochastic algorithm”
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Development Of Ai-Driven Systems for Real-Time Joint Movement Detection and Correction in Frozen Shoulder Therapy Using Sensor-Based Shoulder Rehabilitation Devices
Abstract: Frozen shoulder, or adhesive capsulitis, is a common musculoskeletal disorder characterized by progressive pain, stiffness, and restricted range of motion that significantly impairs functional ability and quality of life. Recent advancements in artificial intelligence and sensor-based technologies have enabled the development of intelligent rehabilitation systems capable of real-time joint movement detection and correction. Wearable sensors such as inertial measurement units, electromyography sensors, and flexible strain sensors capture continuous biomechanical data …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Literature Review and Research Gaps in Power Quality Enhancement: From Conventional Methods to Intelligent Solutions
Abstract: Power quality (PQ) has become a critical concern in modern electrical power systems due to the rapid integration of renewable energy sources, proliferation of power electronic devices, and increasing sensitivity of loads. This paper presents a comprehensive literature review and research gap analysis of power quality enhancement techniques, ranging from conventional approaches to emerging intelligent solutions. Traditional methods, including passive filters, capacitor banks, and synchronous condensers, have been widely employed …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 38–80 Read article
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A Technical Blueprint for AI-Driven Localization in 6G Mobile Networks
Abstract: The advent of sixth-generation (6G) wireless systems promises unprecedented spatial resolution, ultra-low-latency, and pervasive connectivity, turning mobile localization from a peripheral service into a core enabler of immersive extended reality (XR), autonomous logistics, and digital twins. Yet, the sheer scale of dense terahertz (THz) deployments, the stochastic nature of reconfigurable intelligent surfaces (RIS), and the dynamic interference landscape render traditional model-based positioning techniques inadequate. This work investigates how artificial intelligence …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 26–34 Read article
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Optimized Receivers for Underwater Visible Light Communication
Abstract: For uses like ocean exploration, environmental monitoring, and underwater data transfer, wireless communication under water is crucial. Conventional acoustic and radio frequency communication methods suffer from low bandwidth, high latency, and severe signal attenuation in underwater environments. With its high data rate and low propagation delay, Visible Light Communication (VLC) provides a promising alternative. In this work, an underwater VLC system is implemented using Light Emitting Diodes (LEDs) with intensity …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
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Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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Analysis of Machine Learning in Metal Processing: A Novel Prospect
Abstract: Metal is processed by a wide range of procedures, from forming and casting to machining and riveting. Metal processing is a crucial part of modern manufacturing. The application of machine learning (ML) is driving a significant change in the sector, which has historically depended on empirical knowledge and trial-and-error techniques. Increased production, improved product quality, and resource optimization are expected outcomes of this action. This study aims to explore the …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 40–51 Read article
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Technology with a Human Face: Reimagining Progress through Universal Ethical Principles
Abstract: Technological progression is mostly considered as a tool of human evolution. In this digital era, however, quick novelty has revealed complex ethical gaps in the modelling and implement of technology. Technologies namely artificial intelligence, algorithmic systems, and digital surveillance progressively effect social life, economic activity, and political decision-making. While these technologies provide proficiency and progress, they also advance moral concerns connected to discretion, disparity, liability, and human dignity. The technique …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 30–36 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
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Stock Market Prediction Using Machine Learning: Techniques, Challenges, and Future Directions
Abstract: The continuous advancement of machine learning (ML) technologies has significantly transformed the field of financial forecasting, particularly in the area of stock market prediction. The ability to accurately forecast stock price movements and market trends plays a crucial role in supporting informed investment strategies and effective risk management. This paper provides a comprehensive review of recent developments in the application of ML techniques for predicting stock market behavior. It classifies …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 10–16 Read article
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Predictive Learning Powered by AI and Sophisticated Student Engagement Techniques
Abstract: The contemporary landscape of education has witnessed a paradigm shift in integrating advanced technologies that have revolutionized the learning experience. Innovative methodologies have emerged to address longstanding challenges, such as enhancing student engagement, accurately predicting academic performance, and personalizing the learning journey. However, despite the numerous benefits that technology brings to education, there remains a crucial hurdle - sustaining student motivation and engagement. Traditional teaching methodologies often struggle to generate …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 127–140 Read article
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Design and Performance Analysis of Microwave Filters and Resonators for High-Frequency Systems
Abstract: Microwave filters and resonators are fundamental components in high-frequency systems, playing a crucial role in signal selection, interference suppression, and frequency stabilization. This review presents a detailed analysis of design methodologies and performance characteristics of microwave filters and resonators used in modern communication and radar applications. Various filter topologies, including low-pass, high- pass, band-pass, and band-stop configurations, are examined with respect to their frequency response, insertion loss, selectivity, and bandwidth. …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 1, 2026 · pp. 8–16 Read article
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IoT-Based Automated Crop Protection System for Smart Farming
Abstract: The development of current technological advancements produces expanded capabilities for agricultural farming production alongside pest management techniques. The Automatic Crop Protection System requires an Arduino controller and Blynk IoT application for monitoring and managing essential environmental parameters including temperature along with humidity as well as soil moisture and pest behavior. Real-time environmental and soil data obtained by the suggested system's sensor array gets analyzed and controlled by an Arduino controller. …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 1–8 Read article
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Experimental Investigation and Optimization of Machining Parameters for Al6351 Alloy Using a Modified Taguchi Approach
Abstract: Machining processes encompass both conventional and non-conventional techniques and optimizing machining parameters is crucial for achieving high-quality outcomes. However, simplifying these processes remains a significant challenge. This study focuses on determining the optimal machining parameters—cutting speed, feed rate, and depth-of-cut to enhance performance characteristics in Al6351 alloy plates. The parameters evaluated include surface roughness (Ra), material removal rate (MRR), resultant forces (RF), and temperature at the tool- workpiece interface (Temp). …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1463–1481 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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A Low-Cost Multi-Sensor IoT System for Real-Time Segregation of Polymer Waste
Abstract: Segregation of solid waste is a critical aspect of waste management, especially in settings where technical and financial constraints limit the adoption of sophisticated technologies. The proposed low cost, sensor-driven smart waste sorting system combines a variety of sensing technologies with an integrated decision-making system. The system employs an inductive sensor, moisture sensor and capacitive sensor to measure the physical properties of waste items, allowing segregation into metal, wet and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 90–`107 Read article
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AI-Integrated Graphene-Modified Polymer Interfaces for Real-Time Crack Detection and Autonomous Healing in Smart Concrete Structures
Abstract: This study presents the design and development of a graphene-reinforced multifunctional polymer composite interface engineered for structural reinforcement, self-sensing, and autonomous healing applications in cementitious systems. A thermosetting polymer matrix embedded with graphene nanoplatelets (0.25–1.5 wt.%) was developed to establish a conductive polymer nano-composite network. Electrical characterization confirmed a distinct percolation threshold at ~0.6–0.8 wt.%, beyond which a sharp increase in conductivity was observed due to the formation of interconnected …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 30–42 Read article