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463 articles for “network efficiency”
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Advancements and Challenges in Automated Guided Vehicles for Smart Industrial Automation
Abstract: Automated Guided Vehicles (AGVs) are increasingly central to modern industrial automation, enhancing operational efficiency in manufacturing, warehousing, and logistics. Traditionally reliant on fixed paths using magnetic tapes or wired tracks, AGVs were limited in flexibility. However, recent technological advances have enabled the development of autonomous AGVs equipped with sensor fusion, LiDAR, computer vision, and artificial intelligence (AI). These features support real-time obstacle detection, dynamic path planning, and robust performance in …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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A Decade of Research on Polymer Manufacturing and Industry 4.0 Integration: A Comprehensive Bibliometric Review of Industry
Abstract: The advent of Industry 4.0 has brought a transformative revolution to the manufacturing sector by integrating advanced polymer technologies with intelligent, interconnected, and data-driven production systems. These developments have significantly reshaped industrial operations by improving efficiency, enhancing production flexibility, and enabling innovative manufacturing practices. Smart polymer processing, supported by automation, artificial intelligence, the Internet of Things (IoT), and real-time data analytics, allows manufacturers to optimize resource utilization, reduce waste, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1897–1905 Read article
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Artificial Intelligence-Assisted Multi-Objective Optimization of Agricultural Biomass-Reinforced Polymer Composites
Abstract: Agricultural biomass can reduce the environmental burden of polymer composites, yet its heterogeneous structure creates competing effects on strength, moisture resistance, density, and process ability. This study developed an artificial intelligence-assisted framework for balanced composite formulation. Experimental data of agricultural biomass reinforced polymer composites were gathered, harmonized and validated using leakage controlled validation. The mechanical and physical properties were predicted by artificial neural networks and conventional regression models. Explainable analysis …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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A Comprehensive Study of various Multi-Area Hybrid Power Systems for Generation Control
Abstract: This paper is a detailed examination of multi-area hybrid power systems in the control of the generation taking into consideration the two area up to five area connected networks. As renewable energy sources are more and more integrated, and modern grids become more and more complex, the stability of the system itself and the frequency regulation have risen to a major issue. The study highlights the significance of Automatic Generation …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 28–42 Read article
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An Efficient LoRa-Enabled Fault Detection Using Self-Powered IoT Device
Abstract: This study describes a revolutionary internet of things (IoT) solution for effective defect detection in a variety of applications. By utilizing an IoT device that generates energy from the surroundings, the suggested solution gets around the drawbacks of conventional battery-operated gadgets. The suggested approach makes use of a self-sustaining IoT gadget that can capture energy from the surroundings to get beyond the drawbacks of conventional battery-powered IoT devices. Longer functioning …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–13 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Electronic Drones: Technology, Applications, and Future Directions
Abstract: Electronic drones, commonly referred to as Unmanned Aerial Vehicles (UAVs), have transitioned from exclusively military platforms to indispensable tools across commercial, scientific, industrial, and recreational domains. The rapid evolution of electronics, flight control systems, communication networks, onboard sensors, and artificial intelligence has reshaped drone capabilities, enabling high-precision remote sensing, autonomous navigation, swarm behavior, and integration into complex systems like the Internet of Drones (IoD). This paper examines the technological building …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 15–19 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 Read article
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Evolution of Kitchen Robots: A Review
Abstract: Robots are the machines designed and developed by humans which are more capable and efficient in doing such works and tasks which humans are unable to do or do with less efficiency. These machines are able to perform the tasks which are hard or impossible for humans. There are many robots which resemble like human, animal or even insects and are employed in different sectors. For example, dogs in bomb …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 1, 2024 · pp. 32–47 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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AI Driven IoT based Satellite remote sensing system: KSK Approach in Satellite Remote Sensing
Abstract: The convergence of the Internet of Things (IoT) and satellite remote sensing has traditionally been bottlenecked by massive data latency and limited downlink bandwidth. This paper proposes a decentralized framework for an "AI-Driven IoT-based Satellite Remote Sensing System," which shifts the paradigm from raw data transmission to onboard edge-intelligence. By integrating lightweight convolutional neural networks (CNNs) directly into satellite payloads, the system performs real-time feature extraction and anomaly detection before …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 50–57 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Advancing IoT Security through Blockchain-based Approaches
Abstract: The emergence of blockchain technology has revolutionized various industries, including the Internet of Things (IoT), by providing a decentralized and secure platform for data management and transaction processing. However, securing IoT devices and networks remains a significant challenge due to inherent vulnerabilities and the increasing sophistication of cyberattacks. Blockchain-based security approaches have shown promise in addressing these challenges, yet their adoption is hindered by a lack of comprehensive taxonomy and …
Published in Trends in Electrical Engineering · Vol. 15, Issue 1, 2025 · pp. 1–34 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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Design and Implementation of a Bidirectional Long-Range Communication System for Disaster Management Applications
Abstract: In times of natural disasters like earthquakes, floods, landslides and cyclones, the normal communication lines are frequently cut, thus reducing the ability of the affected people and the relief team to communicate vital information. Cellular networks and Internet-based communication systems could be compromised in the event of a loss of power, damage to infrastructure or network congestion. Thus, it is necessary to have a communication system that will be dependable, …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 2, 2026 Read article
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Determination of Free Chlorine Water Content in Jalandhar City Using Colorimeter
Abstract: Water is the ultimate source of life on this universe. Water is vital for the survival of humans, animals, and plants, and the issue of freshwater is becoming increasingly critical in society. With the human body composed of 64% water, contaminated water, inadequate waste disposal, and poor water management contribute to severe public health issues such as cholera, typhoid, and malaria annually. Globally, the quality and quantity of water are …
Published in Journal of Water Pollution & Purification Research · Vol. 11, Issue 1, 2024 · pp. 1–5 Read article
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Integration of AI and Machine Learning in Smart Environment Monitoring Systems
Abstract: The Internet of Things (IoT) plays an important role in our lives. Many real-time changes in logistics environment monitoring and location tracking can be measured using IoT. It uses a wireless sensor network to monitor important changes in the environment. In this article a comparative review study has been performed in which one side wireless sensor network is integrated with IoT only while on the other side wireless sensor network …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 15, Issue 2, 2024 · pp. 13–19 Read article
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Adaptive Traffic Control Systems: Enhancing Urban Mobility through Real-Time Traffic Management
Abstract: Traffic congestion is a ubiquitous challenge in urban areas, necessitating innovative solutions to improve transportation efficiency and alleviate gridlock. Traditional traffic signal control methods often prove inadequate in dynamically adapting to fluctuating traffic conditions, leading to increased travel times, fuel consumption, and emissions. In response, adaptive traffic control systems have emerged as a promising approach to mitigate congestion and enhance traffic flow in urban environments. These devices dynamically modify signal …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 37–45 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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Smart City Based Manhole Monitoring System
Abstract: Urban environments are increasingly reliant on complex underground infrastructure networks, with manholes serving as critical access points for maintenance, inspection, and drainage. However, traditional manhole monitoring methods, often manual and labour-intensive, can be inefficient and prone to human error. This can lead to serious safety and health hazards, such as accidents caused by open manholes, exposure to harmful gas leaks, and infrastructure damage from overflows due to undetected blockage This …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 27–34 Read article