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122 articles for “feedback integration”
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A Review on Two-Wheeled Self-Balancing Robot Using Spartan-3E FPGA for Sensor Fusion and Real-Time Motor Control
Abstract: Two-wheeled self-balancing robots (TWSBR) are a popular application of embedded control and robotics because they operate on the inverted pendulum concept, which is naturally unstable. The main objective of such robots is to continuously maintain balance by estimating the tilt angle and applying corrective motor action in real time. In most practical systems, low-cost inertial sensors such as accelerometers and gyroscopes are used for tilt measurement. However, accelerometer readings are …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 17–27 Read article
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Overheating Prevention System to Improve the Solar Effcicency: Simulation in Logosoft
Abstract: This project aims to improve the efficiency and longevity of solar panels by preventing overheating through an automated cooling system. The system guarantees solar panels operate efficiently, reliably, and sustainably. The proposed system also includes a feedback-based control mechanism that assesses temperature changes on an ongoing basis to enhance cooling cycles and reduce superfluous water consumption. Using LOGO!Soft Comfort software for simulation, the system integrates a temperature sensor to monitor …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 Read article
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21st Century Cognitive Landscapes: Integrating ICT-Driven Pedagogies for Holistic, Inclusive Education
Abstract: The rapid advancement of Information and Communication Technology (ICT) has revolutionized digital pedagogies, reshaping modern education by improving accessibility, learner engagement, and academic outcomes. This review critically explores the psychological ramifications of digital learning environments while assessing the effectiveness of ICT tools in fostering inclusive and sustainable education. By integrating insights from contemporary research, this paper examines the impact of digital pedagogies on cognitive function, emotional health, and social interactions …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 75–81 Read article
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DR. REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care
Abstract: Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Assessment of Factors Affecting Telebirr (Mobile Money) Project Implementation in the Case of Ethio Telecom Sector
Abstract: Background: Mobile money services facilitate financial transactions through mobile devices, reducing dependence on physical cash and promoting financial inclusion. The Telebirr Mobile Money project by Ethio Telecom is a key initiative in this domain. Objective: This study aims to examine the factors influencing the successful implementation of the Telebirr Mobile Money project within Ethio Telecom. Methods: A census survey was conducted among 75 project team employees at the Lebu and …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 13–19 Read article
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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Persistent Atmospheric and Ecosystem Impacts of Enteric Methane Emissions from Intensive Livestock Production Systems
Abstract: Enteric methane emissions from intensive livestock production systems exert a significant long-lasting influence on atmospheric stability and ecosystem integrity. Recent observations confirm that global methane emissions continued to rise through the early 2020s, with total emissions exceeding 620 teragrams per year by 2024, driven by expanding ruminant production and associated feed systems. Anthropogenic sources accounted for more than 330 teragrams per year, reflecting sustained growth in agricultural and fossil fuel …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 18–38 Read article
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A Smart Stove System for cooking food: A study
Abstract: Traditional cooking methods often suffer from inconsistencies, safety concerns, and a lack of real- time feedback, leading to suboptimal culinary results, potential hazards, and inefficient energy consumption. This paper introduces the design and implementation of an innovative Smart Stove System engineered to address these challenges comprehensively. Leveraging Internet of Things (IoT) principles, the system integrates an array of precise sensors (e.g., temperature, flame/gas detection, weight) with a sophisticated microcontroller, smart …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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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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Implementing Smart Voting Systems: Challenges and Opportunities
Abstract: This article offers a detailed explanation of the process for creating an innovative electronic voting system that utilizes the flexibility and efficiency of the Raspberry Pi. This method aims to improve voting security, transparency, and user-friendliness by employing digital technology and a mechanism called the Voter Verified Paper Audit Trail (VVPAT). The proposed system comprises several components, including a Raspberry Pi for control, candidate selection buttons, a camera for voter …
Published in Journal of Microelectronics and Solid State Devices · Vol. 11, Issue 2, 2024 Read article
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A Next-Generation IoT-Enabled Smart Cane for the Visually Impaired: Integration of Advanced Navigation, Context-Aware Obstacle Detection, and Real-Time Voice Guidance
Abstract: The rapid growth of Internet of Things (IoT) technologies, combined with advances in embedded systems and artificial intelligence, has opened new possibilities for developing assistive mobility solutions tailored to the needs of individuals with visual impairments. This paper introduces an IoT- enabled smart cane designed to enhance independent mobility through intelligent environmental interpretation and context-aware navigation. Unlike traditional canes that rely solely on tactile feedback, the proposed system incorporates multiple …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 12–17 Read article
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Leveraging Artificial Intelligence (AI) and Digitalization of Community Health Screening in Unani Medicine: Bridging Tradition with Technology – A Perspective Review
Abstract: AI and digitalization bring a great opportunity for reforming and even improvement of traditional healthcare systems in Unani physiology. This review, therefore, observes the important role played by AI and digital health solutions in modernizing health screening and diagnostic procedures in Unani medicine, thereby bridging traditional healing practices with contemporary technological advancement. AI refers to the advantages that may accrue via wearable health devices and telemedicine in real-time monitoring, early …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 2, 2025 · pp. 20–31 Read article
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Design of Disturbance Observer for Third- Order Interval Plants
Abstract: This paper outlines the development of a disturbance observer (DOB) specifically tailored for third-order interval plants, which are distinguished by uncertainties in their parameters. Utilizing an interval-based modeling approach, this design effectively captures variations in system dynamics, providing robust control solutions for plants with parameter uncertainties. The key focus is creating a disturbance observer capable of real-time estimation and compensation for external disturbances and model uncertainties. The proposed DOB is …
Published in Trends in Electrical Engineering · Vol. 14, Issue 3, 2024 Read article
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Smart Crop Recommendation Using IoT Sensor for Precision Agriculture
Abstract: This study addresses precision agriculture, which leverages modern technologies to enhance farming efficiency and sustainability. This study proposes a Smart Crop Recommendation System using IoT sensors to optimize crop selection based on real-time environmental conditions. The system integrates multiple sensors, including a temperature sensor, flame sensor, soil sensor, moisture sensor, and LDR sensor, to monitor crucial parameters such as temperature, soil moisture, light intensity, and fire hazards. An Arduino microcontroller …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 3, 2025 · pp. 29–41 Read article
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Ethical Considerations in AI-Driven Rehabilitation Robotics: Balancing Innovation and Responsibility
Abstract: Artificial intelligence (AI) is transforming robotics rehabilitation by introducing advanced capabilities such as adaptive therapy, real-time feedback, and personalized assistance, significantly improving outcomes for individuals with neurological and physical impairments. These AI-powered systems offer high levels of precision and consistency in therapy delivery, making them especially beneficial in pediatric and adult rehabilitation settings where engagement and tailored interventions are crucial. However, the integration of AI in healthcare also presents critical …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 24–29 Read article
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A Real-time Visualization Framework to Enhance Prompt Accuracy and Result Outcomes Based on the Number of Tokens
Abstract: In the rapidly evolving domain of artificial intelligence (AI), the efficacy of user-generated prompts has emerged as a critical factor influencing the quality of model-generated responses. Current methodologies for prompt evaluation predominantly rely on post-hoc analysis, which often leads to iterative prompting and increased computational overhead. Furthermore, the challenge of “prompt hallucinations,” where AI models produce irrelevant or nonsensical responses, persists as a significant impediment to effective AI utilization. The …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 45–53 Read article
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A Novel Frontier On Biofeedback Enhanced Psychological Wellbeing For Metabolic Health In Human
Abstract: This article explores the emerging field of biofeedback and its application in optimizing metabolic health. Biofeedback involves the use of technology to monitor physiological processes and provide real-time feedback to individuals, empowering them to regulate their bodily functions. We delve into various biofeedback modalities and their potential benefits in managing metabolic disorders such as diabetes, obesity, and metabolic syndrome. Additionally, we discuss the underlying mechanisms of biofeedback, its effectiveness in …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 56–69 Read article
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Developing Techniques for Controlling Different Aspects of Text Generation Such as Tone and Contents
Abstract: Large Language Models (LLMs) have shown excellent text creation quality in Natural Language Processing (NLP). However, LLMs have to satisfy ever-more-complex standards in real-world applications. LLMs are supposed to meet specific user goals, like as mimicking specific writing styles or producing material with poetic richness, in addition to eliminating inaccurate or objectionable content. Controllable Text Generation (CTG) techniques were developed in response to these diverse demands. They guarantee that outputs …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 34–39 Read article
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Graphene Based Electronic Skin for Wearable Health Monitoring and Human– review on Machine Interaction, Materials, Structures and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article