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404 articles for “network performance”
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Synthesis of Graphene-CeO2 Nanocomposite with Enhanced Electrochemical Properties
Abstract: For the fabrication of graphene–cerium oxide (CeO₂G) composites, 99 mg of cerium oxide (CeO₂, 99.9%) was uniformly dispersed in 100 mL of deionized water via ultra-sonication (40 kHz) to achieve a stable suspension, followed by the incorporation of 1 mg of synthesized graphene. The resulting mixture was maintained at ambient temperature (25 ± 2 °C) under continuous magnetic stirring at 500 rpm for 2 h to promote effective interfacial interaction …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1355–1373 Read article
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Real-Time System Monitoring and Resource Optimization Using Shell Scripts in UNIX/Linux Environments
Abstract: Real-time system monitoring is a fundamental aspect of system administration in UNIX/Linux environments, as it ensures optimal system performance, reliability, and continuous availability of services. In modern computing infrastructures, systems are expected to operate efficiently under varying workloads, and any degradation in performance, such as CPU overload, memory exhaustion, disk bottlenecks, or network congestion, can significantly impact user experience and system stability. Regular observation and prompt action are crucial for …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 1, 2026 · pp. 08–15 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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Analysis and Simulation of VLAN Using Cisco Packet Tracer
Abstract: The acronym for Virtual Local Area Network, or Virtual LAN, is VLAN. We build this unique network from one or more pre-existing LANs. In order to provide scalable, dependable, and secure services regardless of location, today's networks must always be accessible from anyplace. Reducing users and workgroups that are separated is the main objective of a network. Each system must have the ability to interact with other systems and transmit …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 2, 2023 · pp. 28–33 Read article
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Advancing Conductive Ink Formulations for DIW with Graphene and Hybrid Nanostructures
Abstract: The development of solvent-based conductive inks for direct ink writing (DIW) has gained significant attention as a pathway toward flexible, wearable, and scalable electronic devices. This review critically examines conductive fillers, binders, solvent systems, and hybrid ink strategies reported in recent literature. Graphene and carbon nanotubes (CNTs) remain the most studied fillers due to their high intrinsic conductivity and unique dimensionality, but challenges such as restacking, bundling, and high viscosity …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 36–49 Read article
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Smart Polymer Composites with Multifunctional Capabilities Integrating Electroactive Polymers Conductive Nanofillers and Flexible Electronics for Advanced Sensing and Actuation Systems
Abstract: Smart polymer composites have gained significant attention to their ability to integrate polymer matrices with conductive nanofillers, offering tunable electrical, mechanical, and electroactive properties. These composites are highly responsive to external stimuli such as electrical fields, mechanical stress, and temperature variations, making them ideal for applications in flexible electronics, soft robotics, and adaptive sensing systems. This research investigates the effect of nanofiller dispersion on the performance of polymer composites, optimizing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 946–965 Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
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Advancements and Challenges in Computer Hardware Technology Management: Innovations, Performance, and Future Directions
Abstract: Modern computing systems depend on computer hardware technology for performance, efficiency, and innovation. Processing units, memory storage, input/output devices, and networking hardware are covered in this article. It emphasizes how multi-core processors, SSDs, and integrated circuits have increased computational power and speed. The essay also discusses quantum computing, edge computing, and the IoT, which will change hardware. Finally, the essay discusses hardware design challenges such power consumption, heat control, and …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 1–8 Read article
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Image-Based Crack Morphology Characterisation for Electrical Failure Analysis in Conductive Polymer Composites
Abstract: Electrical performance in conductive polymer composites is strongly governed by crack-network evolution, yet failure analysis typically relies on qualitative image inspection or electrical anomaly detection in isolation. This work proposes an end-to-end framework that converts optical/SEM crack imagery into a standardised crack morphology signature and quantitatively links it to electrical degradation indicators. A two-stage learning strategy is adopted: crack-representation pretraining using the public Concrete Crack Images for Classification dataset, followed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1375-1386 Read article
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Smart Biopolymer–PCM Composite Modules with Embedded Wireless Thermal Sensing for Autonomous Energy Storage Applications
Abstract: The development of multifunctional polymer composite systems for intelligent thermal energy storage has gained significant attention due to the increasing demand for sustainable and autonomous thermal management technologies. In the present study, a wireless-integrated biopolymer–phase change material (PCM) composite module embedded with thermal feedback sensors was successfully fabricated and experimentally investigated for advanced thermal energy storage applications. Polylactic acid (PLA) was employed as the biodegradable polymer matrix, while paraffin wax …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 193–205 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Hybrid Best-Response Algorithms for Mobile Computing Offloading: A Comprehensive Review
Abstract: The exponential growth of mobile applications with intensive computational requirements has necessitated innovative offloading strategies in mobile computing ecosystems. This comprehensive review examines hybrid best-response offloading algorithms integrated with game-theoretic optimization frameworks to address resource allocation challenges in mobile edge computing (MEC) environments. The proliferation of Internet of Things (IoT) devices and bandwidth-intensive applications has created unprecedented demands on mobile network infrastructure, compelling researchers to develop sophisticated offloading mechanisms that …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 20–26 Read article