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435 articles for “machine learning techniques”
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IoT-Based Industrial Safety Management Systems
Abstract: The integration of the Internet of Things (IoT) in industrial safety management has transformed workplace safety by enabling real-time monitoring, predictive analytics, and automated hazard mitigation. IoT-Based Industrial Safety Management Systems utilize interconnected sensors, wearable devices, and intelligent analytics platforms to proactively detect and respond to potential risks in high-risk environments such as manufacturing, oil and gas, and construction. These systems continuously monitor critical safety parameters, including temperature, pressure, gas …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 18–22 Read article
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Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms
Abstract: Within engineering software platforms that involve the design, simulation and characterization of composite materials, user experience (UX) design has become a key determinant for efficient use. This research aims to quantify how user experience design parameters relate to productivity in composite engineering workflows by analyzing the relationship between usability, learnability, accessibility, complexity of the UI, navigation efficiency and users engineering results satisfaction. Computational techniques in python were used in the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 341–366 Read article
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Innovative Approaches to Reactive Power Management and Optimization in Modern Power systems
Abstract: Reactive power management and optimization are necessary for the effective, stable, and reliable working of modern power systems. Without proper management, reactive power is responsible for additional losses in transmission, reduced capability of power transfer, and poor voltage stability conditions, thus forming a basis for developing advanced techniques of optimization. This paper discusses the innovative methods in Reactive Power Optimization (RPO) using met heuristic algorithms, namely the Self-Balanced Differential Evolution …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 44–50 Read article
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Identifying and Blocking of Non-productive Calls in Emergency Call System Using Machine Learning and IVRS Integration
Abstract: The Dial 100 emergency reaction gadget handles over 1,000,000 calls every day, with over 95% being unproductive, such as blank, machine-generated, and spoofed calls. These futile calls waste resources and put off responses to actual emergencies. This look presents a comprehensive solution integrating advanced name evaluation, system learning, and an interactive voice response system (IVRS) to filter out and prevent these calls. Our technique starts with studying incoming calls to …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 3, 2024 · pp. 20–28 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Implement Explainable Machine Learning to Improve Conductivity in Polymer-CNT Nanocomposites: Supporting Adaptive, Flexible, and Long-Lasting IoT Wrap-Around Electronics Applications
Abstract: The rapid growth of Internet of Things (IoT) technologies requires electronic components that are adaptable, lightweight, and durable, and that can continue to function well in diverse contexts and circumstances. Polymer–carbon nanotube (CNT) nanocomposites have become interesting choices for these kinds of uses because they are more flexible, conduct electricity better, and can be made to fit specific needs. However, improving conductivity in these heterogeneous systems remains a major challenge …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 238–254 Read article
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Holographic Beam Switching and Intelligent Routing for Terahertz Space-Air-Ground Integrated Networks
Abstract: The rapid evolution of sixth-generation (6G) and beyond communication technologies necessitates highly adaptive, ultra-high-capacity, and low-latency networking frameworks capable of supporting global connectivity across terrestrial and non-terrestrial domains. This study proposes a novel holographic beam switching and intelligent routing framework for terahertz (THz) Space-Air-Ground Integrated Networks (SAGINs). The proposed architecture leverages holographic beamforming techniques to dynamically manipulate electromagnetic wavefronts, enabling precise beam steering, reduced interference, and enhanced spectral efficiency in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Deep Guard: A Comprehensive Deep Learning System for Unmasking Suspicious Activities in Surveillance Footage
Abstract: These days, video surveillance is quite vital. Technology has evolved considerably as machine learning, artificial intelligence, and deep learning become increasingly widespread. There are several algorithms that assist in identifying distinct kinds of suspicious behaviour from live footage by combining the techniques. A person's behaviour is the most unpredictable thing, and it can be quite challenging to determine whether it is normal or suspicious. Video surveillance is automated to address …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 23–28 Read article
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Epilert: Epilepsy Tracker and Detector
Abstract: Epilepsy, affecting over 50 million individuals worldwide, necessitates innovative solutions for effective monitoring and intervention. Current systems face challenges such as inaccuracy, limited accessibility, and discomfort, leaving patients and caregivers vulnerable. Epilert, a wearable device, addresses these gaps by employing advanced sensors and machine-learning algorithms for real-time epilepsy detection and monitoring. The device integrates electromyography (EMG) and motion sensors to capture and analyze physiological and movement data. Preprocessing techniques ensure …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Advances in Medical Robotics: Surgical Automation and Rehabilitation Systems
Abstract: Medical robotics has emerged as a groundbreaking technology, transforming modern healthcare through advancements in surgical automation and rehabilitation systems. Robotic-assisted procedures machine learning (ML), and artificial intelligence (AI) have all been used to improve patient recovery consequences, reduce invasiveness, and increase surgical precision. These developments have redefined traditional medical techniques by opening the door for more effective, precise, and tailored therapies. By improved dexterity, stability, and vision, surgical robots has …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 31–38 Read article
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Comprehensive Review of the Fundamental and Functional Properties of Crystalline Materials
Abstract: Crystalline materials, characterized by their highly ordered atomic arrangements, serve as the backbone of modern engineering and technology. This review provides a detailed examination of their diverse properties, categorized into mechanical, thermal, electrical, and optical domains. We analyze fundamental mechanical parameters such as the elastic modulus, yield strength, and fracture toughness, alongside functional behaviors like fatigue and creep. The discussion extends to thermal transport and expansion, electrical conductivity and resistivity, …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 20–24 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Artificial Intelligence and the Future of Education
Abstract: Artificial Intelligence (AI) refers to the capability of a computer system to mimic human intelligence by performing tasks such as learning, reasoning, problem-solving, and decision-making. As a rapidly evolving and emerging technology, AI holds the potential to transform a wide range of sectors, including healthcare, transportation, business, and notably, education. Its application in the educational domain is gaining momentum, aiming to create more efficient, engaging, and personalized learning environments. Incorporating …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 39–44 Read article
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A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article