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309 articles for “support networks”
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Significant Advances in Cloud Computing in Information and Communications Technology
Abstract: The critical advances in information and communications technology (ICT) over the last half-century have led to the increasingly common vision that computing will one day become the 5th utility. This computing utility will provide the essential level of computing service considered basic to meet the everyday needs of the general public. To convey this vision, a number of computing models have been proposed, with the most recent being cloud computing. …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 33–38 Read article
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Evaluation of composite material based on different phases of Face recognition System
Abstract: Composite materials can indeed play a crucial role in various phases of a face recognition system, offering advantages such as lightweight construction, durability, and tailored mechanical properties. Let's explore how composite materials can be utilized in different phases of a face recognition system. A composite material based different phases of Face recognitions System is software that recognizes or verifies a person based on a digital image or a frame from …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 195–204 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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SkinSight: Design and Implementation of an Intelligent Skin Type Detection System
Abstract: Identifying an individual’s skin type accurately is essential for creating personalized dermatological treatments and formulating skincare products that genuinely meet user needs. In this project, a real- time skin type classification system is developed using a combination of convolutional neural networks (CNNs) and modern computer vision techniques. The system processes live video streams, isolates the facial region through Haar cascade–based detection, and applies a series of preprocessing steps to enhance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 35–45 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Energy Efficiency and Awareness in Edge Computing: A Critical Review of Challenges, Strategies, and Future Directions"
Abstract: Edge computing enhances distributed systems by processing data near its source, yet its rapid growth, driven by IoT, 5G, and smart applications, escalates energy consumption across billions of devices. This study critically analyzes energy-saving techniques across hardware, software, and network layers, highlighting the role of AI tools and user education in promoting energy awareness. It explores trade offs between energy efficiency and system performance, identifies scalability challenges in large-scale deployments, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 32–36 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Optimized Hardware Realization of AES for High-Throughput FPGA Platforms
Abstract: The Advanced Encryption Standard (AES) is the predominant symmetric-key cryptographic algorithm used for securing digital communication across embedded systems, IoT devices, cloud infrastructures, and defense networks. Although software-based AES implementations offer flexibility, they often fail to meet the high-speed, low-latency, and energy-efficient requirements of modern real-time applications. Reconfigurable hardware platforms such as Field-Programmable Gate Arrays (FPGAs) provide a powerful alternative by enabling architectural customization, intrinsic parallelism, and optimized hardware acceleration. …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 11–22 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
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Electric Vehicle Range Prediction
Abstract: The introduction of new energy vehicles has emerged as a new trend in the automotive industry inresponse to growing energy and environmental issues. The electric vehicle (EV) is the driving force behind newenergy vehicles. The one major problem electric vehicles have always been the distance(range) of the travel and mapto the nearby charging stations. For range prediction in the present study, four machine learningalgorithms—multiple linear regression, random forest regression, polynomial …
Published in Trends in Electrical Engineering · Vol. 13, Issue 3, 2023 · pp. 24–32 Read article
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AI-Driven IoT Ecosystems for Real-Time Thermo-Chemical Decision Making
Abstract: The efficient management of thermo-chemical processes is a critical challenge in modern industry, where maintaining precision, operational safety, and energy efficiency directly influences productivity and sustainability. The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) has transformed conventional industrial systems into intelligent, data-driven environments capable of continuous monitoring, predictive analysis, and autonomous decision-making. By integrating interconnected sensors, edge computing, cloud platforms, and advanced machine learning algorithms, industries …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 2, 2026 · pp. 10–15 Read article
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Hybrid Material Systems for Flexible Electronics Electro-Mechanical Performance and Future Prospects
Abstract: Flexible electronics are transforming the landscape of modern electronic systems, enabling devices that are lightweight, stretchable, and adaptable to complex surfaces. These technologies are particularly impactful in applications such as wearable health monitors, soft robotics, energy harvesting systems, and implantable biomedical devices. At the heart of this evolution are hybrid material systems—engineered composites that combine organic polymers and inorganic nanomaterials to achieve synergistic electro-mechanical properties. These materials address the limitations …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 7–12 Read article
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Securing Healthcare 5.0: A Review of Applications, Security Challenges, and Future Perspectives
Abstract: Healthcare 5.0 represents a revolutionary shift in the healthcare sector, focusing on individualized, patient-centric care through the integration of different cutting-edge technologies such as internet of things, artificial intelligence, big data analytics, blockchain, and cloud computing to enable healthcare services such as real-time health monitoring, personalized treatments, and access to expert advice regardless of geographic barriers. Potentially, Healthcare 5.0 supports more engaged and effective care and help through a focus …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 22–36 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Experimental Studies and in silico Analysis on Quarum Sensing and System Simulation in Pseudomonas aeruginosa
Abstract: Pseudomonas aeruginosa is the most common pathogenic bacterium present in human microbial flora, biofilms, soil and water associated and support self microbial communications and survilance. The present study shows estimated protein concentration present in two days grown in Mullar hinton broth was resulted around 32.5 mg/ml. The studies in protein interaction on X-ray film with aqueous fruit and vegetable extracts showed good results with apple, straw berry, cucumber, grape, orrange, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 7, Issue 1, 2018 · pp. 1–8 Read article
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Reactive Power Pricing Technique in A Competitive Market
Abstract: For maintaining voltages of each bus within specific range, proper reactive power support is mandatory. Reactive power is considered as an ancillary service in the restructured electricity market, hence it is price based service and controlled by ISO. Here, a modified optimal power flow (OPF) optimization method is proposed over the bids received from Gencos and to maintain the system security and stability subject to the constraints imposed by different …
Published in Trends in Electrical Engineering · Vol. 6, Issue 3, 2016 · pp. 89–100 Read article
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Random Forrest Based Man-in-the-Middle Attack Detection in Advanced Metering Infrastructure
Abstract: Advanced metering infrastructure (AMI) plays a central role in the operation of modern smart grid (SG) systems by enabling continuous, two-way communication between utility providers and consumers. Through this communication, AMI supports real-time monitoring, dynamic pricing, and efficient energy management. However, the same connectivity that makes AMI effective also increases its exposure to cyber threats. One of the most critical threats is the man-in-the-middle (MITM) attack, in which an attacker …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 1–8 Read article