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309 articles for “support networks”
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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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Metro Systems' Role in Reducing CO2 Emissions in Urban Transport
Abstract: To better understand the impact of metro systems on reducing CO2 emissions in urban transport, a detailed analysis is required. This analysis should evaluate both the direct and broader effects of metro networks on the overall urban transportation system. It is crucial to quantify the actual contribution of metro systems in cutting CO2 emissions by considering the entire transport network. The evaluation should include not only the emissions generated by …
Published in Trends in Transport Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 19–22 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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IOT Based design and implementation of home automation using Blynk application.
Abstract: The increasing advancement in communications technology has sparked significant interest in home automation systems. It concentrates on the evolution of an IOT-based prototype home automation system which is capable of remotely controlling various household components with the help of the internet anytime and anywhere, as well as being programmable to operate based on ambient conditions. This paper represents prototype design implementation and performance testing of Home Automation System of low …
Published in Journal of Microcontroller Engineering and Applications · Vol. 10, Issue 3, 2023 · pp. 16–22 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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Direct Determination of the Frequency-Dependent Transmission Constants of Non-Uniform Two-Port Networks
Abstract: Due to space constraints and the expansion of electricity networks, transmission lines that cross close to one another are now commonplace. Power networks also commonly install higher operational voltage lines that share transmission corridors with lower voltage lines. Overhead transmission lines are the primary method for transmitting electrical energy across vast distances. This paper presents an efficient and direct technique for identifying the four frequency-dependent ABCD transmission constants of arbitrary …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 1–8 Read article
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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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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article