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195 articles for “Network adaptability”
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Survey of Predictive Models for Safe Route Predicting Using Machine Learning Techniques
Abstract: Safe route prediction is essential for the well-being and security of individuals in urban and rural environments. Machine learning techniques leverage historical data, real-time information, and algorithms to estimate the safety levels of different routes. The objective of safe route planning is to minimize risks, including crime-prone areas and accidents, reducing potential harm, property damage, and emotional distress. However, challenges arise from the complex and dynamic nature of urban environments, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 13–22 Read article
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Diet-Gene Interactions in Farm Animals: Molecular Dynamics, Gene Expressions, Signalling Pathways and Precision Nutrition for Sustainable Productivity
Abstract: Diet-gene interactions represent a central mechanism through which nutrition influences growth, health, and productivity in farm animals. Recent advances in molecular biology and genetics have revealed that nutrients act not only as metabolic substrates but also as signalling molecules capable of modulating gene expression, cellular pathways, and epigenetic regulation. This review synthesizes current knowledge on the molecular dynamics of nutrient utilization in farm animals, with emphasis on nutrigenomic responses, nutrient …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
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The Role and Functions of Computer Engineers
Abstract: Computer engineers play a crucial role in shaping the ever-evolving technological landscape by designing, developing, and optimizing computer systems and software. Their expertise spans various domains, including hardware design, embedded systems, software development, cybersecurity, and network architecture. These professionals contribute significantly to advancements across multiple industries, from healthcare and finance to telecommunications and artificial intelligence. This article delves into the diverse responsibilities of computer engineers, highlighting their involvement in problem-solving, …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 37–51 Read article
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New-Age E-voucher Utility: Redefining Peer-to-Peer Transactions in the Digital Economy
Abstract: This system introduces an innovative new-age e-voucher utility designed to facilitate peer-to-peer (P2P) intake through a person-pleasant cell platform. This revolutionary answer empowers people to create and list e-vouchers for numerous services, experiences, or bodily goods, circumventing conventional channels and fostering an extra direct financial machine. Operating on a decentralized architecture, the utility guarantees stable transactions through fee gateways and contains a recognition machine to set up acceptance as true …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 2, 2024 · pp. 36–46 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 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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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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Shell Programming with Sensor Systems and Applications for Human Cognition
Abstract: Shell programming provides a flexible interface to sensor systems, enabling robust scripting for real-time data acquisition and processing, as well as integration with perception components. Such sensors have human analogs—tactile, physiological, and behavioral—and are increasingly embedded within health, mobile, and smart environments to capture fine-grained details of human cognition. Using shell scripts, the system can automatically collect sensor data, fuse multimodal data, and perform adaptive behavioral monitoring, allowing researchers and …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 41–45 Read article
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Fused Deposition Modelling-based 3D Printing: A Systematic Literature Review Employing VOS Viewer
Abstract: Fused Deposition Modelling, also known as FDM, has emerged as a major technology in the field of 3D printing. It provides adaptability and cost-effectiveness in the process of materializing intricate designs. This paper intends to conduct a complete bibliometric analysis (BA) of 3D printing based on fused deposition modelling (FDM) in order to comprehend the trend and research field. After extracting data from the Scopus database using the titles, abstracts, …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 197–202 Read article
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A study on CMOS Operational Amplifier in Sensor Development
Abstract: CMOS operational amplifiers (op-amps) have emerged as pivotal components in modern sensor development, enabling the amplification and conditioning of weak signals with high precision and efficiency. Their inherent advantages low power consumption, compact size, and seamless integration with digital circuits make them ideal for advancing miniaturized, battery-powered sensor systems in fields ranging from biomedical devices to IoT networks. By delivering precision, power efficiency, and integration, CMOS op-amps are not just …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 01–07 Read article
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Reduce Traffic Congestion Using Automated Traffic Navigation System
Abstract: The concept of activity routing without reliance on traditional activity signals is gaining significant traction. This innovative approach aims to enhance urban vehicular movement by eliminating the need for conventional traffic signal systems. This summary delves into the intricate realm of signal-free activity routing, incorporating advanced technologies such as artificial intelligence, machine learning, and sensor networks. The benefits, including reduced congestion, increased fuel efficiency, and improved traffic flow, are thoroughly …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 34–40 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 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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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
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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Ramifications of Artificial Intelligence and Cyber Security
Abstract: Artificial intelligence (AI) has pros and cons for cyber security: AI can improve network security, anti-malware, and fraud detection. AI can simulate cyberattacks, automate responses, and analyse enormous databases. AI-powered phishing and deepfakes are cyber risks. AI can potentially be attacked and become a liability for corporations. AI has transformed cyber security, bringing both new opportunities and challenges. AI-powered tools discover abnormalities faster, automate threat responses, and improve threat detection …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 40–45 Read article
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A Review of Shell Programming Applications in Blockchain and Web3 Infrastructure
Abstract: Shell programming has long been an essential tool for automation and system management, but its role in emerging technologies like Blockchain and Web3 infrastructure has become increasingly prominent. This review explores how shell scripting supports various processes within decentralized ecosystems, including node management, smart contract deployment, data synchronization, and continuous integration workflows. As blockchain networks scale in complexity, shell scripts provide efficient solutions for orchestrating automation, security audits, and distributed …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
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IoT-Enabled Polymer–Gel PCM Composites for Intelligent Thermal Management in Solar Facade Applications
Abstract: The present study investigates the development of a multifunctional polymer–gel phase change composite designed for solar façade applications with integrated real-time thermal monitoring capability. A crosslinked polyvinyl alcohol–borax matrix was employed as a three-dimensional polymer scaffold to encapsulate paraffin-based phase change material, ensuring leakage-free operation and structural integrity under repeated thermal cycling. Graphite nanoplatelets were incorporated as thermally conductive nano-fillers to enhance heat transfer through the polymer composite via percolation-driven …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 99–111 Read article