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370 articles for “Network analysis”
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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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Advancements in Image Processing Techniques for Computer Vision Applications
Abstract: The fast-developing field of computer vision is transforming how people perceive and comprehend pictures and movies. Autonomous systems, robotics, healthcare, and surveillance are just a few of the many applications that have been made possible by recent significant advances in image and video processing. An overview of current developments in computer vision approaches, algorithms, and techniques for image and video analysis is given in this abstract. In conclusion, the analysis …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 27–32 Read article
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Developing a Comprehensive Framework for User and Entity Behavior Analytics (UEBA): Integrating Advanced Machine Learning and Contextual Insights
Abstract: User and Entity Behavior Analytics (UEBA) has emerged as a crucial approach in modern cybersecurity for detecting and mitigating insider threats, compromised accounts, and other malicious activities within organizational networks. However, existing UEBA frameworks often face challenges in scalability, detection accuracy, and response effectiveness. This research work proposes a novel framework for UEBA that aims to address these limitations and enhance threat detection and response capabilities. The framework integrates advanced …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 20–32 Read article
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Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article
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Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Utilizing Machine Learning for Waste Analysis
Abstract: The Internet of Things can be expanded to include any physical object with an IP address that allows data to be transmitted over a network by installing electronic devices such as networking hardware, sensors, and software. The Internet of Things (IoT) offers enhanced connectivity for an array of devices, services, protocols, and applications. It is further defined by its diverse nature. Not just in houses and smart cities has IoT …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Exploring the Intersection of AI Network Pharmacology and Ayurveda: Innovations in Traditional Medicine
Abstract: Integrative frameworks that integrate traditional medicine and modern computer research are increasingly important for advancing evidence-based, individualized healthcare. One interesting strategy is the combination of Ayurveda, network pharmacology, and artificial intelligence (AI). AI expands the capability by allowing for the quick analysis of biomedical big data, the identification of therapeutic trends, and the optimization of treatment plans. Ayurveda, with its long-standing emphasis on individualized care, holistic balance, and natural remedies, …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 3, 2025 · pp. 92–98 Read article
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Microstructural Characterisation and Analysis of Mechanical Behaviour of Hybrid AA 7075/7178 Fabricated Using Die Casting Technique
Abstract: AA are being increasingly used in the field of structural engineering owing to their desirable mechanical properties coupled with their recyclable and sustainable nature, thus contributing significantly towards reduction of carbon footprints and development of circular economy. Till date numerous research projects have been prompted to investigate the structural performance of aluminium alloy structures and develop alternatives with enhanced performance parameters. AA 7xxx (Al-Zn-Mg-Cu) are being widely used in variety …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 441–451 Read article
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Exploring the Viability and Implications of Quantum Communication in 6G Networks
Abstract: The development of telecommunication systems has brought us to the era of 6G, characterized by remarkable connectivity, speed and performance achievements. This article investigates the fusion of quantum communication into the architecture of 6G networks as a new approach to achieving security and efficiency. Using quantum mechanics principles, such as superposition and entanglement, quantum communication allows bloodless encryption and secure data transmission. The theoretical frameworks and quantum networks for 6G …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 1, 2024 · pp. 01–14 Read article
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Analysis of Power Quality Disturbances in Distribution Systems with Renewable Energy Integration
Abstract: The growing integration of renewable energy sources within the electrical distribution systems has greatly altered the working dynamics of the contemporary power grids. The introduction of intermittent and nonlinear sources (solar photovoltaic and wind energy systems) leads to a wide range of power quality disturbances, however. The current paper includes the in-depth examination of the problem of power quality in the distribution systems with the integration of renewable energy. The …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 Read article
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A Surgical Exploration of the Mechanism and Regulation of the Respiratory System: A Conceptual Analysis
Abstract: The respiratory system plays a vital role in facilitating the movement of air in and out of the body, comprising a complex network of anatomical pathways. It is conventionally divided into two primary sections: the upper respiratory tract and the lower respiratory tract. Within the upper respiratory tract lie structures extending from the nasal passages down to the vocal cords, crucial for phonation. These vocal cords, composed of mucous membrane …
Published in Research and Reviews : Journal of Surgery · Vol. 13, Issue 1, 2024 · pp. 56–63 Read article
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Monitoring and Modeling of Atmospheric Change Indices In Parts of Imo State Using GIS, MATLAB and ANN
Abstract: Geographic Information System (GIS) and Matrix Laboratory (MATLAB) Models were used to study air quality in parts of Imo State. Primary data were obtained by conducting relevant analysis using standard instrumental methods on open-air rainwater samples collected in the dry and the rainy seasons for two consecutive years. GIS showed that the pollutants were present throughout the year. Artificial Neural Network (ANN) of MATLAB 2015 was used to represent data …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 15, Issue 1, 2024 · pp. 25–74 Read article
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Improving Node Efficiency in Wireless Sensor Networks Using Advanced Clustering and Routing Techniques
Abstract: Many Internet of Things (IoT) applications, such as disaster relief, smart buildings, smart farming, and healthcare monitoring, have made use of wireless sensor networks (WSN). It is one of the alternatives to address different IoT difficulties in different contexts. One of the main problems with sensor networks is power efficiency. WSN operated on the Client-Server (CS) architecture in the past, however researchers suggested Mobile Agent (MA) based WSN to increase …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 · pp. 35–64 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Enhancing Power Conversion Efficiency in Tandem Solar Cells with Temporal Dynamic Graph Neural Network
Abstract: In modern homes, people want good comfort and also less electricity bill, so managing heating load and cooling load become very important. Heating Load (HL) and Cooling Load (CL) depend on many things like wall material, window size, sunlight, ventilation, and weather. Because of this many factors, calculation and optimization of HL and CL is little difficult and many time normal formulas give wrong or not perfect results. So in …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 Read article
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The DVB-H Standard: Comparative Analysis of the Results Obtained for Various Modulation Techniques and Different Code Rates
Abstract: DVB-H happens to be the technical specification for the transmission of digital TV to mobile telephones and PDAs—handheld receivers. Published as a formal standard, DVB-H is a physical layer specification designed to facilitate the proficient delivery of IP-encapsulated data over terrestrial networks. The making of DVB-H, which is closely associated with DVB-T, also entailed modifications of some other DVB standards dealing with data broadcasting, service Information, etc. It can be …
Published in Recent Trends in Electronics Communication Systems Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article