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743 articles for “Network Model”
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Comparative Analysis of Forward and Backward Auxiliary Selective ASE Pumping for L-Band EDFA
Abstract: ABSTRACT An exhaustive quantitative and comparative study of eight DWDM EDFA amplifier configurations has been conducted using Selective Wavelength Auxiliary Pumping (SWAP) by Forward Amplified Spontaneous Emission (FASE) and Backward ASE (BASE) pumping schemes for L-band signal gain enhancement and noise figure (NF) improvement. 31 dB gain and 5.19 dB NF at 1570 nm can be achieved using suggested optimum pumping configuration in L-band EDFA. The proposed design model can …
Published in Trends in Opto-electro & Optical Communication · Vol. 2, Issue 3, 2012 · pp. 17–30 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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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Multi-objective Optimization Methods for Various Power System Problems
Abstract: This article discusses numerous features of multi-optimization approaches as applicable to challenges relating to the optimization of power systems, such as optimum power distribution network reconfiguration, optimal distributed generator placement and sizing (allocation), optimal D-STATCOM placement and sizing (allocation), simultaneous network reconfiguration and distributed generator allocation and simultaneous distributed generator and D-STACOM allocation, are discussed. The related objectives considered in these optimization problems are also discussed with respect to the …
Published in Journal of Microcontroller Engineering and Applications · Vol. 9, Issue 1, 2022 · pp. 35–39 Read article
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Wavelet based Adaptive Sliding Mode Control for Discrete Time Uncertain Nonlinear Systems
Abstract: This paper focuses on the development of a wavelet based adaptive sliding mode control strategy for a classof discrete time uncertain nonlinear systems. An adaptive sliding mode control is utilized to assure the stabletracking of uncertain nonlinear system under consideration. Wavelet neural network (WNN) is used to mimicthe uncertainties present in the system. Proposed scheme is derived to guaranty the necessary and sufficientreaching condition for sliding mode control in presence …
Published in Journal of Control & Instrumentation · Vol. 1, Issue 1-2-3, 2011 · pp. 59–68 Read article
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Predicting And Forecasting Stocks
Abstract: Stock value estimation may be a well-liked and vital topic in money and tutorial studies. Share Market is associate untidy place for predicting since there aren't any vital rules to estimate or predict the value of a share within the share market. Several ways like technical analysis, basic analysis, statistical analysis, and applied mathematics analysis, etc. area unit all want to conceive to predict the value within the share market …
Published in Journal of Electronic Design Technology · Vol. 13, Issue 1, 2022 · pp. 1–5 Read article
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Deep Learning Based Plant Disease Detection
Abstract: Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and recent advances in computer vision made possible by deep learning has paved the way for smartphone-assisted disease diagnosis. Using a public dataset of images of diseased and healthy plant leaves collected under controlled …
Published in Journal Of Network security · Vol. 8, Issue 2, 2020 · pp. 33–42 Read article
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Advancing Brain Tumor MRI Segmentation
Abstract: Segmentation of brain tumors in MRI scans is an integral part of neuroimaging carried out for diagnostic and therapeutic interventions. Given that manual segmentation is cumbersome and highly variable, there arises a need for automated, more precise segmentation solutions. This project, ‘Machine Learning and Deep Neural Networks to Advance Brain Tumor MRI Segmentation’ will develop a better, efficient, and accurate segmentation model to help clinicians identify brain tumors with greater …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 28–33 Read article
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Recipe-Fusion: Multimodal Food Recipe Recommendation System
Abstract: The food recipe recommendation system using data science is a software solution designed to help users discover new and delicious food options based on their food history and other relevant data. This system recommends various recipes based on the input given by the user and it helps to filter out the recipes on course type, diet type, and nature of the food (including non-veg, and veg) using a recommendation technique. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 82–91 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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Forecasting Climate-Driven Healthcare Demand in Agricultural Regions: A Multi-Modal AI Approach
Abstract: The rapidly increasing instability of world climatic regimes has made past meteorological thresholds irrelevant, especially in the agricultural areas where monetary stability and well-being of humans are closely intertwined with an environmental situation. The more the frequency of 1 in every 1000-year events, i.e., heatwaves and catastrophic flooding increase, the greater the rural healthcare systems are in crisis, i.e., unable to predict a surge in demand because of data scarcity, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 28–38 Read article
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Simulation of a Renewable Energy Hybrid MicroHydro-Wind-PV-Solar System for Electric Generation
Abstract: This project is based on the development of a renewable energy hybrid tri-system made up of a photovoltaic device, a small wind turbine and a micro hydraulic turbine to generate electricity in places where these renewable energy resources are available. The system pursues the reduction of energy dependence on local electric network as well as the greenhouse gases emission. The project will be theoretically modelled and verified in a small …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 13, Issue 2, 2022 · pp. 37–50 Read article
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Harnessing Artificial Intelligence for Precision Physics: A Machine Learning Framework for Data Reconstruction in Support of India's Deep-Tech Missions
Abstract: India's emergence as a global leader in deep-tech innovation is driven by ambitious scientific megaprojects, including the Laser Interferometer Gravitational-Wave Observatory (LIGO)-India, the X-ray Polarimeter Satellite (XPoSat), the Aditya-L1 solar observatory, and the National Quantum Mission (NQM). However, the unprecedented scale and complexity of the observational data generated by these missions present severe computational bottlenecks. Traditional analytical frameworks struggle with non-stationary noise transients, diffusion blurring, and the exponential scaling limits …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 2, 2026 · pp. 48–55 Read article
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Zero Trust Implementation Challenges in Legacy and Wireless Network Systems
Abstract: This article titled "Zero Trust Implementation Challenges in Legacy Systems and Wireless Network Systems" delves into the evolving landscape of cybersecurity, emphasizing the inadequacy of traditional perimeter-based security models in the face of modern cyber threats. The Zero Trust Security framework is highlighted as an essential advancement in this scenario, emphasizing the core idea of "never trust, always verify." This paradigm shift underscores the importance of continuous verification, least privilege …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 1, 2025 · pp. 39–50 Read article
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Comparative Between (LiNbO3) and (LiTaO3) in Detecting Acoustics Microwaves Using Classification
Abstract: AbstractOur work is mainly about detecting acoustics microwaves in the type of BAW (Bulk acoustic waves), where we compared between Lithium Niobate (LiNbO3) and Lithium Tantalate (LiTaO3), during the propagation of acoustic microwaves in a piezoelectric substrate. In this paper, we have used the classification by Probabilistic Neural Network (PNN) as a means of numerical analysis in which we classify all the values of the real part and the imaginary …
Published in Journal of Microwave Engineering and Technologies · Vol. 5, Issue 3, 2018 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 45–54 Read article
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Implementing Blockchain to Enhance Security in the Pharmaceutical Industry and Combat Drug Counterfeiting
Abstract: Drug counterfeiting has emerged as a critical threat to public health, as it has enabled inferior and counterfeit drugs to flood many markets around the world thereby eroding trust in healthcare systems and patient safety. This paper seeks to address the glaring need for adequate security safeguards to curb the circulation of counterfeit drugs by proposing a blockchain model designed specifically for the pharmaceutical industries. In general, the idea of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 1, 2025 · pp. 33–46 Read article
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Design and Simulation of Artificial Neural Network (ANN) Based Speed Control for an Induction Motor Taking Core Loss and Stray Load Losses into Account
Abstract: Indirect field oriented control scheme has been preferred due to its superior performance for Induction Motor. Core Loss and stray load losses are generally neglected in the mathematical model of induction motor. But it should be consider in the mathematical model of induction motor to precisely control the torque and flux. Conventional PI controller has overshoot effect at the transient period of the speed response curve. Artificial Neural Network (ANN) …
Published in Journal of Control & Instrumentation · Vol. 6, Issue 3, 2015 · pp. 13–22 Read article
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Oceanmind Systems: AI-Driven Marine Life Intelligence for Climate Prediction and Ocean Ecosystem Stability
Abstract: Oceans regulate global climate systems, support biodiversity, and serve as critical carbon sinks, yet they remain under-monitored relative to their ecological importance. Traditional oceanographic methods rely heavily on satellite sensing, buoy networks, and periodic marine surveys, which often fail to capture real-time biological dynamics at micro-ecosystem levels. This paper introduces OceanMind Systems, an artificial intelligence (AI)-driven marine intelligence framework that integrates marine life behavior, oceanographic data, and computational modeling to …
Published in International Journal of Marine Life · Vol. 3, Issue 2, 2026 Read article
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Optimizing Routing and Placement of VLSI Circuits with Differential Algorithms and Neural Networks
Abstract: The performance of modern VLSI systems is heavily influenced by power constraints, necessitating precise power estimation and effective optimization techniques. Traditional methods, such as gate-level simulations, are often slow and computationally intensive. This paper introduces DRPENN (Differential Algorithm for Routing and Placement Optimization using Neural Networks), an innovative solution that combines a Switching Activity Estimator (SAE) with a neural network-assisted differential algorithm. By leveraging toggle rates from simulations to train …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article