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290 articles for “Continual learning”
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Reduce Traffic Congestion Using Automated Traffic Navigation System
Abstract: The concept of activity routing without reliance on traditional activity signals is gaining significant traction. This innovative approach aims to enhance urban vehicular movement by eliminating the need for conventional traffic signal systems. This summary delves into the intricate realm of signal-free activity routing, incorporating advanced technologies such as artificial intelligence, machine learning, and sensor networks. The benefits, including reduced congestion, increased fuel efficiency, and improved traffic flow, are thoroughly …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 34–40 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 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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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Design, Development, and Optimization of Autonomous Robots for Enhanced Performance
Abstract: Autonomous robots are transforming industries by executing complex tasks with minimal human intervention, improving efficiency, precision, and adaptability across various domains such as manufacturing, healthcare, logistics, and exploration. Their performance relies on a synergy of robust hardware design, intelligent control mechanisms, and advanced optimization techniques. This paper explores the key components of autonomous robots, including sensor integration, locomotion systems, control architectures, and decision-making frameworks that enable autonomous operation in dynamic …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 22–30 Read article
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Nuclear Reactor Safety Using Seismic and Natural Disaster Protection: A Study
Abstract: Nuclear energy has enormous power and is essential to the global effort to provide clean, sustainable electricity, but it also carries a huge responsibility: guaranteeing its complete safety. Nuclear energy is at a turning point. Nuclear power provides a potent, carbon-free answer as the globe struggles with climate change and the pressing need to decarbonize energy grids. However, public fear, primarily from past mishaps like Chernobyl and Fukushima, continues to …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 25–34 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
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Debris Flow Kinetics in Planetary Environments: A Systems Perspective
Abstract: Debris flow kinetics in planetary environments represent a critical intersection of geomorphology, fluid mechanics, and planetary science. These gravity-driven flow mixtures of solids, liquids, and gases play a key role in shaping planetary surfaces and recording environmental histories. This study adopts a systems perspective to analyze debris flow behavior across different planetary contexts, emphasizing the interconnected roles of material properties, energy transformations, and environmental forcing. By integrating rheological models with …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 08–17 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Randomized Latent Vectors for Enhanced Reinforcement Learning Exploration
Abstract: This paper investigates Random Latent Exploration (RLE), a novel reinforcement learning technique that enhances exploration using randomized latent vector conditioning. I evaluate RLE’s performance across various environments, including discrete control tasks (FourRoom), continuous control (IsaacLab), and complex visual domains (Atari games). The core approach augments traditional reward functions with intrinsic rewards, calculated as the dot product between state features and periodically resampled latent vectors. The policy and value networks are …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 19–25 Read article
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Autonomous Drones for Search and Rescue Opera-tions: State of the Art and Future Prospects
Abstract: Autonomous drones have significantly transformed search and rescue (SAR) operations by improving the speed, precision, and overall effectiveness with which rescuers are able to locate and provide assistance to individuals in need. By leveraging state-of-the-art technologies such as computer vision, artificial intelligence (AI), machine learning, and advanced navigation systems, drones have proven invaluable in carrying out complex rescue missions. These technologies enable drones to navigate hazardous environments autonomously, even in …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 9–13 Read article
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Evolving Face of Quality in The World Robotics Process Automation (RPA)
Abstract: Robotics Process Automation (RPA) is a technology that automates repetitive and rule-based tasks using software robots or "bots." These bots mimic human interactions with digital systems and perform tasks like data entry, validation, report generation, and system integration. RPA leverages AI and ML to improve operational efficiency and can be applied across industries and functions. Implementing RPA offers benefits such as error reduction, productivity enhancement, and cost savings. RPA is …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 1, 2023 · pp. 1–9 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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Virtual Assistant: JarvisAI Using Natural Language Processing
Abstract: This research presents the development of a voice-interactive virtual assistant built upon the JarvisAI framework, integrating advanced technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Speech Recognition. The goal is to enable seamless and intuitive human-computer interaction by allowing users to communicate through natural spoken and written language. The assistant is designed to understand, interpret, and respond to various user commands, aiding in tasks such as information …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 26–39 Read article
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article
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A Survey of Seasonal-based Movie Recommendations Using Machine Learning Through a Hybrid Approach with User Interest in Various OTT Platforms
Abstract: No matter their age, gender, race, color, or region, everyone enjoys watching films particularly during festival season. We are all, in the most basic sense, connected to one another through this beautiful medium, but what really grabs attention is the fact that, regardless of how unique our choices and combinations are in terms of picture show preference, one thing remains constant. Certain people have a preference for certain types of …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 24–29 Read article
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article