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742 articles for “Network Model”
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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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Cyclist Safety Enhancement: A Multi-Modal Hazard Detection System
Abstract: This study presents a multi-modal hazard detection system to enhance cyclist safety in urban environments. Lever- aging a combination of computer vision, object tracking, and predictive modeling, the system offers a comprehensive approach to identifying and mitigating potential risks. Key contributions include improved depth estimation through object size priors, multi-class tracking utilizing KCF and Brisk, and a novel recurrent neural network architecture for predicting bicycle movement. The system’s collision detection …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 1, Issue 2, 2023 · pp. 35–83 Read article
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Pipeline Integrity Optimal Maintenance Techniques and Its Reliability
Abstract: This study is aimed at determining the optimal maintenance model for utilizing both preventive and corrective costs control system. It was assumed that operating conditions and pipeline diameters were uniform following the cumulated results and computational analysis. The research included an estimation which shows that the average cost for the installation and of course the maintenance of a healthy and operational pipeline is within $1,989,992 per km. Considering the failure …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 9, Issue 1, 2022 · pp. 23–29 Read article
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Health Risk and Evaluation of Atmospheric Pollutants in Owerri Metropolis and Sub-Urban Areas of Imo State, Nigeria Using Chemometric Models
Abstract: Concern about health risk from atmospheric pollutants; Particulate Matter (PM10), Sulphur dioxide (SO2), Nitrogen dioxide (NO2) and Carbon Monoxide (CO) prompted atmospheric monitoring and inhalation health risk assessment for residents of Owerri Metropolis and its Sub-urban areas. Field measurements were carried out in 35 select locations within Imo State. Monitoring was carried out using Chemometric methods as Matrix Laboratory (MATLAB) and Artificial Neural Network (ANN). According to the experiment results, …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 1, 2024 · pp. 47–79 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Artificial Neural Network Based Prediction of Impact Loads and Thickness in CFRP and GFRP Composite Laminates
Abstract: Recent technological advancements, particularly the integration of neural networks, have facilitated a predictive approach to complex engineering problems, especially those involving composite materials with directional properties. The scarcity of literature on predicting impact damage using experimental and ultrasonic flaw detection data motivated this study. Experimental assessment of impact damage on carbon fiber/epoxy (CFRP) and glass fiber/epoxy (GFRP) composites was conducted using low-velocity drop weight impact testing. Damage assessment employed an …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 34–45 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Performance Optimizing of a Simulated Model of a Fabry-Perot based Tunable Laser Operating at 1550 nm
Abstract: AbstractThe paper presents data for an optimized Fabry-Perot tunable laser, with a wavelength tuning range of 56.3 nm, with a high output power of 17.4307 dBm. Incentive for this research has been due to the cause that Fabry–Perot semiconductor laser diodes have been fine contenders as transmitters to be used in WDM optical networks. The proposed system is capable of modulating a maximum bit rate of 26.58 Gb/s, with an …
Published in Trends in Opto-electro & Optical Communication · Vol. 4, Issue 3, 2014 · pp. 23–31 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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YOLOv8 in Focus: A Review of its Application in Driver Monitoring Systems
Abstract: This research presents a novel Driver Monitoring System (DMS) that utilises Convolutional Neural Networks (CNNs) to achieve remarkable results. Specifically, the YOLOv8 (You Only Look Once version 8) detection technique is used. The main goal is to increase road safety by using cutting-edge computer vision techniques to analyse driver behaviour in real-time. The YOLOv8 detection method, a cutting-edge CNN model renowned for its precision and effectiveness in object recognition, is …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 3, 2023 · pp. 35–40 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing Read article
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 9–25 Read article
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Neural Network Based Fractional Order PID Controller for Harmonic Mitigation of Induction Motor Drive System
Abstract: Torque produced in IM (induction Motor) is collected fundamental torque, however, due to core saturation, air gap irregularity, and winding distribution; stator and rotor slotting harmonics torque are produced. This reduces the quality of the power system, life span, and performance of the motor and the controller device. In this paper, a neural network, based fractional order proportional integral derivative (NNFOPID) controller is designed to compensate the harmonics of the …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 23–41 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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Research on Selection Method of the Optimum Alternative Using Improved AHP Method in NSDL Environment
Abstract: In this paper, we have considered the development of a decision-making tool to optimize the design of the ship-roll fin stabilizer using improved analytical hierarchy process (AHP) in a network-oriented system description language (NSDL) environment developed by combining the advantages of Petri nets and object-oriented programming languages. First, we have considered the network-oriented system description language NSDL, a new software development tool that combines the advantages of Petri nets and …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 1, 2025 · pp. 46–56 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
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Monoclonal Antibodies in Next Generation Animal Nutrition: Mapping Nutrient Immune Interaction Networks in Livestock Systems
Abstract: Sustainable livestock production is increasingly constrained by disease pressure, antimicrobial resistance, and declining feed efficiency under intensifying environmental stressors. Conventional nutritional strategies, while essential, remain insufficient to precisely regulate immune function and metabolic resilience. This review explores the emerging role of Monoclonal antibodies as advanced biologics in next generation animal nutrition, with a focus on mapping nutrient immune interaction networks in livestock systems. It synthesizes current knowledge on how nutrients …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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A Study On Power Losses And Reduction of Power Losses In Power System
Abstract: Now the world's power supply system is a large unit, large grid, high voltage as the main characteristics of the centralized single system. Although the power load of the world's number is powered by such a single large power grid, the demand for quality and safety reliability of energy and power supply is increasing in today's society, and the large power grid cannot meet this requirement because of its own …
Published in Journal of Microelectronics and Solid State Devices · Vol. 8, Issue 3, 2021 · pp. 16–25 Read article
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Enhancing Image Classification Performance with Deep Neural Networks
Abstract: Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 13–23 Read article