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660 articles for “learning environment”
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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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Development of Neuromorphic Polymer Composites Using IoT Sensing and Brain-Inspired Learning Algorithms
Abstract: This research aims to develop neuromorphic polymer composites by combining conductive sensing materials, IoT-based sensing data collection and brain-inspired learning models for adaptive response. Hybrid conductive polymer composites were developed by adding carbon nanofibers and graphene Nano platelets to a thermoplastic polymer. IoT sensors (strain, temperature) were employed to collect real-time sensing data that was combined with environmental data. A material-aware neuromorphic learning algorithm was created with event-driven spike coding …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 755–784 Read article
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Enhancing LAN Security Using Machine Learning
Abstract: The modern Local Area Network (LAN) is a critical component of any organization's infrastructure, facilitating communication, resource sharing, and access to the wider internet. However, this connectivity also brings inherent security risks. Traditional security measures, relying on signature-based detection and rule-based systems, are increasingly struggling to keep pace with the evolving sophistication of cyberattacks. This is where Machine Learning (ML) offers a powerful alternative, enabling proactive threat detection and enhanced …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 07–16 Read article
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SpecialMinds: Learning App for Visually Impaired Students
Abstract: This research aims to identify the challenges and barriers that visually impaired students encounter in the educational environment, with a focus on adaptive strategies and innovative solutions. Visually impaired students often experience difficulties in listening, speaking, reading, writing, conceptual understanding, and social communication. As one of the most excluded and discriminated groups in society, these students may feel isolated, which further impacts their learning. Given the significance of quality education …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 11–23 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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Virtual Design Studio-based Teaching and Learning in B.Arch. Program
Abstract: In Architecture education a new dimension is added in context to technology. If the person is equipped with technology learning will be infinite and multidisciplinary its future scope is also clarified by this means. Many parameters are crossed in learning through technology like countries, proximity to individuals; environment and other hostile conditions are avoided through technology. All the possible outcomes are available through technology like with the use of software’s, …
Published in Recent Trends in Civil Engineering & Technology · Vol. 12, Issue 3, 2022 · pp. 20–30 Read article
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Real-Time Object Detection and Tracking in Traffic Surveillance: Implementing Algorithms That Can Process Video Streams for Immediate Traffic Monitoring
Abstract: The rapid growth in urban development and traffic congestion calls for adopting high standards of traffic surveillance systems for monitoring. This paper reviews the current advancement and future trends of real-time object detection and tracking technology and its implications for traffic surveillance. Conventional approaches to traffic monitoring can provide more or less accurate data, but they are not easily scalable and cannot cope with rapidly changing conditions typical within urban …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 18–39 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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Radiation-Resilient AI: Next-Generation Robotic Systems with Adaptive Machine Learning for Nuclear Facility Management
Abstract: The increasing complexity of nuclear facility operations, decommissioning activities, and emergency response scenarios necessitates the development of advanced autonomous systems capable of functioning in highly radioactive environments. This paper presents a comprehensive review of radiation-resilient artificial intelligence systems integrated with next-generation robotic platforms, specifically designed for nuclear facility management applications. We examine the convergence of adaptive machine learning algorithms, radiation-hardened hardware architectures, and intelligent robotic systems that can operate autonomously …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 12–21 Read article
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Radiation-Resilient AI: Next-Generation Robotic Systems with Adaptive Machine Learning for Nuclear Facility Management
Abstract: The increasing complexity of nuclear facility operations, decommissioning activities, and emergency response scenarios necessitate the development of advanced autonomous systems capable of functioning in highly radioactive environments. This paper presents a comprehensive review of radiation-resilient artificial intelligence systems integrated with next-generation robotic platforms, specifically designed for nuclear facility management applications. We examine the convergence of adaptive machine learning algorithms, radiation-hardened hardware architectures, and intelligent robotic systems that can operate autonomously …
Published in Journal of Thermal Engineering and Applications · Vol. 15, Issue 2, 2025 · pp. 12–21 Read article
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Cyberattack Detection System in Private Cloud
Abstract: As cloud computing adoption in colleges continues to rise, the security of private cloud systems has become a paramount concern. Data breaches resulting from cyberattacks can inflict severe damage to a university's revenue and reputation. This research proposes a novel machine learning-based cyber threat detection system tailored to the university's private cloud environment. The system's main objective is to continuously monitor the cloud infrastructure and employ advanced machine learning algorithms …
Published in Recent Trends in Parallel Computing · Vol. 10, Issue 2, 2023 · pp. 37–44 Read article
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AI-Driven Precision Nutrition: Advancing Personalized Dietary Systems for Public Health Equity in Resource-Constrained Environments
Abstract: The dual burden of malnutrition and diet-related non-communicable diseases (NCDs) represents a growing global public health challenge, particularly in low- and middle-income countries. Traditional dietary guidelines are largely population-based and fail to account for individual variability in genetics, metabolism, lifestyle, and environmental exposure. This limitation has led to the emergence of precision nutrition, an evolving field that integrates biological data and computational intelligence to deliver personalized dietary recommendations. This paper …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Virtual Reality Based Decentralized Educational Art Gallery
Abstract: One can experience the forefront of education by engaging with our virtual reality (VR) powered decentralized educational art gallery. This groundbreaking platform seamlessly integrates VR technology with decentralized networks, crafting an unmatched learning journey. Curated collections of art from diverse cultures and eras can be explored, accompanied by interactive educational modules that deepen one’s understanding of each piece. One can engage with fellow learners in real time, fostering collaboration and …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 31–37 Read article
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A Review Paper of Automated Driving & ADAS Technologies
Abstract: Automated driving and Advanced Driver Assistance Systems (ADAS) are transforming road mobility, promising enhanced safety, improved traffic efficiency, and greater accessibility. This review presents a comprehensive synthesis of core technologies, system architectures, sensor modalities, perception and decision-making algorithms, and evaluation methodologies underpinning contemporary ADAS and automated driving. We provide a detailed discussion of the functional components—sensors (camera, radar, LiDAR, ultrasonic), localization, perception, prediction, planning, control, and human–machine interfaces—and how these …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–8 Read article
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Optimizing Performance Characteristics, Thermal Stability, and Manufacturing Performance of Polymer Nanocomposites Using Artificial Intelligence
Abstract: Artificial intelligence (AI) has proven an efficient method to optimize the design and manufacture of polymer nanocomposites, allowing the proper prediction of the behavior of the materials and the results of the processing. This work proposes an AI-based framework to enhance the performance characteristics, thermal stability and manufacturing performance of advanced polymer nanocomposites. The input variables of the proposed framework are the material composition, the nanoparticle concentration, the particle size, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Effectiveness of Computer-assisted Instruction among Student Nurses
Abstract: Technology plays a major role in our teaching and learning strategies. Computer-assisted instruction (CAI) is an innovative resource for teaching content in a controlled environment focusing on individualized learning. So the study to evaluate the effectiveness of computer-assisted instruction developed on immunization program was conducted among student nurses of selected colleges of nursing of Delhi. It was an evaluative research with pre-test, post-test single group design. The study population included …
Published in Journal of Nursing Science & Practice · Vol. 3, Issue 3, 2013 · pp. 6–9 Read article
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Effectiveness of Computer-assisted Instruction among Student Nurses
Abstract: Technology plays a major role in our teaching and learning strategies. Computer-assisted instruction (CAI) is an innovative resource for teaching content in a controlled environment focusing on individualized learning. So the study to evaluate the effectiveness of computer-assisted instruction developed on immunization program was conducted among student nurses of selected colleges of nursing of Delhi. It was an evaluative research with pre-test, post-test single group design. The study population included …
Published in Journal of Nursing Science & Practice · Vol. 3, Issue 1, 2013 · pp. 6–9 Read article
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Optimization of Automatic Energy Management System Using Renewable Resources
Abstract: With the increasing demand for energy efficiency and sustainability, smart home energy management systems (SHEMS) have emerged as promising solutions to optimize residential energy consumption. This paper presents a comprehensive review of SHEMS technologies, focusing on their design, implementation, and impact. SHEMS integrates advanced sensors, real-time data analytics, and intelligent algorithms to monitor, control, and optimize energy usage within the home environment. By leveraging machine learning and predictive modelling techniques, …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
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Iot Based Environment Monitoring System
Abstract: Pollution combined with climate change is creating long-term problems for natural resources. Their impact on soil, air, and water cleanlinessis growing, requires smart, immediate solutions. In this paper, we report on an IoT-based Environment Monitoring System whose purpose is to monitor the air quality, temperature, humidity, and soil moisture content. It consists of an Arduino Uno, gas sensors (MQ135, MQ9, MQ6), a temperature sensor LM35, a soil moisture sensor, and …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 8–14 Read article
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article