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  1. 421

    Dynamic topology adaptability of adaptive multimodal transmission strategy based on environment perception in multi-hop routing of 5G vehicle network by Shengxia Tan, Xianshuang Zong, Feng Xiao

    Published 2025-04-01
    “…Abstract In multi-hop routing of 5G vehicle network, node movement and link failure often lead to frequent changes in network topology, which in turn cause delay and packet loss problems. …”
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  2. 422

    Estimating intercity human mobility flow from city attributes and intercity relations in physical space and cyberspace via graph attention network by Qingli Shi, Li Zhuo, Qiuping Li, Haiyan Tao

    Published 2025-08-01
    “…However, most GNN models rely more on city attributes but ignore intercity relations, especially in cyberspace, and they cannot explain or quantify how city attributes and intercity relations influence GNN outputs. To solve these problems, this study proposes a novel intercity flow estimation model that combines city attributes and intercity relations in physical space and cyberspace under graph attention network architecture (ARPC2F-GAT). …”
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  3. 423

    Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model by Lufeng Chen, Qingquan Chen, Zhimin Huang, Ling Yao, Jiajing Zhuang, Haibin Lu, Yifu Zeng, Jimin Fan, Ailing Song, Yixiang Zhang

    Published 2025-02-01
    “…Conclusions In Quanzhou, under COVID-19 quarantine management, the sleep quality of college students was affected to a certain extent, and their PSQI scores were higher than the national average in China. The artificial neural network model had the best performance, and it is expected to be used to provide early interventions to prevent sleep disorders.…”
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  4. 424

    An adaptive deep learning approach based on InBNFus and CNNDen-GRU networks for breast cancer and maternal fetal classification using ultrasound images by Mamuna Fatima, Muhammad Attique Khan, Anwar M. Mirza, Jungpil Shin, Areej Alasiry, Mehrez Marzougui, Jaehyuk Cha, Byoungchol Chang

    Published 2025-07-01
    “…Post-training features were extracted from the global average pooling and GRU layer and classified using neural network classifiers. …”
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  5. 425

    Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

    Published 2022-11-01
    “…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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  6. 426

    Predictive machine health monitoring using deep convolution neural network for noisy vibration signal of rotating machine using empirical mode decomposition by R. Pavithra, Prakash Ramachandran

    Published 2025-03-01
    “…Abstract In a noisy industry environment, to predict machine faults using vibration signals, a specially designed Deep Convolution Neural Network (DCNN) with an additional noisy layer has been recently demonstrated. …”
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  7. 427

    Physics‐Informed Neural Networks Trained With Time‐Lapse Geo‐Electrical Tomograms to Estimate Water Saturation, Permeability and Petrophysical Relations at Heterogeneous Soils... by C. Sakar, N. Schwartz, Z. Moreno

    Published 2024-08-01
    “…However, obtaining geoelectrical tomograms from raw measurements requires the inversion of an ill‐posed problem, which causes smoothing of the actual structure. …”
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  8. 428

    Secure Cooperative Dual-RIS-Aided V2V Communication: An Evolutionary Transformer–GRU Framework for Secrecy Rate Maximization in Vehicular Networks by Elnaz Bashir, Francisco Hernando-Gallego, Diego Martín, Farzaneh Shoushtari

    Published 2025-07-01
    “…In this paper, we investigate the problem of secrecy rate maximization in a cooperative dual-RIS-aided V2V communication network, where two cascaded RISs are deployed to collaboratively assist with secure data transmission between mobile vehicular nodes in the presence of eavesdroppers. …”
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  9. 429

    Research on multi dimensional feature extraction and recognition of industrial and mining solid waste images based on mask R-CNN and graph convolutional networks by Shuqin Wang, Na Cheng, Yan Hu

    Published 2025-04-01
    “…Abstract Aiming at the problems of traditional methods for multi-dimensional feature extraction of industrial and mining solid waste images, such as single feature extraction, difficult fusion, missing high-order features, weak generalization ability and low computational efficiency, an innovative solution combining Mask R-CNN with Graph Convolutional Networks (GCN) was proposed to achieve automatic, multi-dimensional and efficient feature extraction. …”
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  10. 430

    Engineering Circuit Analysis / by Hayt, William H. (William Hart), Jr., 1920-1999

    Published 2012
    Table of Contents: “…Mesh Analysis: A Comparison -- 4.6.Computer-Aided Circuit Analysis -- Summary And Review -- Reading Further -- Exercises -- ch. 5 Handy Circuit Analysis Techniques -- 5.1.Linearity and Superposition -- 5.2.Source Transformations -- 5.3.Thevenin and Norton Equivalent Circuits -- 5.4.Maximum Power Transfer -- 5.5.Delta-Wye Conversion -- 5.6.Selecting an Approach: A Summary of Various Techniques -- Summary And Review -- Reading Further -- Exercises -- ch. 6 The Operational Amplifier -- 6.1.Background -- 6.2.The Ideal Op Amp: A Cordial Introduction -- 6.3.Cascaded Stages -- 6.4.Circuits for Voltage and Current Sources -- 6.5.Practical Considerations -- 6.6.Comparators and the Instrumentation Amplifier -- Summary And Review -- Reading Further -- Exercises -- ch. 7 Capacitors And Inductors -- 7.1.The Capacitor -- 7.2.The Inductor -- 7.3.Inductance and Capacitance Combinations -- 7.4.Consequences of Linearity -- 7.5.Simple Op Amp Circuits with Capacitors -- 7.6.Duality -- 7.7.Modeling Capacitors and Inductors with PSpice -- Summary And Review -- Reading Further -- Exercises -- ch. 8 Basic Rl And Rc Circuits -- 8.1.The Source-Free RL Circuit -- 8.2.Properties of the Exponential Response -- 8.3.The Source-Free RC Circuit -- 8.4.A More General Perspective -- 8.5.The Unit-Step Function -- 8.6.Driven RL Circuits -- 8.7.Natural and Forced Response -- 8.8.Driven AC Circuits -- 8.9.Predicting the Response of Sequentially Switched Circuits -- Summary And Review -- Reading Further -- Exercises -- ch. 9 The Rcl Circuit -- 9.1.The Source-Free Parallel Circuit -- 9.2.The Overdamped Parallel RLC Circuit -- 9.3.Critical Damping -- 9.4.The Underdamped Parallel RLC Circuit -- 9.5.The Source-Free Series RLC Circuit -- 9.6.The Complete Response of the RLC Circuit -- 9.7.The Lossless LC Circuit -- Summary And Review -- Reading Further -- Exercises -- ch. 10 Sinusoidal Steady-State Analysis -- 10.1.Characteristics of Sinusoids -- 10.2.Forced Response to Sinusoidal Functions -- 10.3.The Complex Forcing Function -- 10.4.The Phasor -- 10.5.Impedance and Admittance -- 10.6.Nodal and Mesh Analysis -- 10.7.Superposition, Source Transformations and Thevenin's Theorem -- 10.8.Phasor Diagrams -- Summary And Review -- Reading Further -- Exercises -- ch. 11 Ac Circuit Power Analysis -- 11.1.Instantaneous Power -- 11.2.Average Power -- 11.3.Effective Values of Current and Voltage -- 11.4.Apparent Power and Power Factor -- 11.5.Complex Power -- Summary And Review -- Reading Further -- Exercises -- ch. 12 Polyphase Circuits -- 12.1.Polyphase Systems -- 12.2.Single-Phase Three-Wire Systems -- 12.3.Three-Phase Y-Y Connection -- 12.4.The Delta (A) Connection -- 12.5.Power Measurement in Three-Phase Systems -- Summary And Review -- Reading Further -- Exercises -- ch. 13 Magnetically Coupled Circuits -- 13.1.Mutual Inductance -- 13.2.Energy Considerations -- 13.3.The Linear Transformer -- 13.4.The Ideal Transformer -- Summary And Review -- Reading Further -- Exercises -- ch. 14 Complex Frequency And The Laplace Transform -- 14.1.Complex Frequency -- 14.2.The Damped Sinusoidal Forcing Function -- 14.3.Definition of the Laplace Transform -- 14.4.Laplace Transforms of Simple Time Functions -- 14.5.Inverse Transform Techniques -- 14.6.Basic Theorems for the Laplace Transform -- 14.7.The Initial-Value and Final-Value Theorems -- Summary And Review -- Reading Further -- Exercises -- ch. 15 Circuit Analysis In The s-Domain -- 15.1.Z(s) and Y(s) -- 15.2.Nodal and Mesh Analysis in the s-Domain -- 15.3.Additional Circuit Analysis Techniques -- 15.4.Poles, Zeros, and Transfer Functions -- 15.5.Convolution -- 15.6.The Complex-Frequency Plane -- 15.7.Natural Response and the s Plane -- 15.8.A Technique for Synthesizing the Voltage Ratio H(s) = V out/V in -- Summary And Review -- Reading Further -- Exercises -- ch. 16 Frequency Response -- 16.1.Parallel Resonance -- 16.2.Bandwidth and High-Q Circuits -- 16.3.Series Resonance -- 16.4.Other Resonant Forms -- 16.5.Scaling -- 16.6.Bode Diagrams -- 16.7.Basic Filter Design -- 16.8.Advanced Filter Design -- Summary And Review -- Reading Further -- Exercises -- ch. 17 Two-Port Networks -- 17.1.One-Port Networks -- 17.2.Admittance Parameters -- 17.3.Some Equivalent Networks -- 17.4.Impedance Parameters -- 17.5.Hybrid Parameters -- 17.6.Transmission Parameters -- Summary And Review -- Reading Further -- Exercises -- ch. 18 Fourier Circuit Analysis -- 18.1.Trigonometric Form of the Fourier Series -- 18.2.The Use of Symmetry -- 18.3.Complete Response to Periodic Forcing Functions -- 18.4.Complex Form of the Fourier Series -- 18.5.Definition of the Fourier Transform -- 18.6.Some Properties of the Fourier Transform -- 18.7.Fourier Transform Pairs for Some Simple Time Functions -- 18.8.The Fourier Transform of a General Periodic Time Function -- 18.9.The System Function and Response in the Frequency Domain -- 18.10.The Physical Significance of the System Function -- Summary And Review -- Reading Further -- Exercises.…”
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  11. 431

    Interaction Among Smartphone Addiction, Behavioral Inhibition/Activation Systems and Mental Health Factors Among Chinese Undergraduate Student: A Study Using Network Analysis by Zhang M, Wang X, Zhang B

    Published 2025-04-01
    “…The new insight will help to enhance mental health and facilitating proper smartphone use management to avoid the aggravation of addiction problems among undergraduate student.Keywords: smartphone addiction, psychological health, college students, network approaches…”
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  12. 432

    Personalized learning path optimization based on enhanced deep neural network: higher education teaching model integrating learner behavior and cognitive style by Xiaomei Ding, Huaibao Ding, Fei Zhou, Lihong Zhao

    Published 2025-08-01
    “…To address the above problems, this paper designs an effective model for optimizing personalized learning paths using Enhanced Deep Neural Networks (EDNN). …”
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  13. 433

    The longitudinal relationship between loneliness and problematic social networking site use in college students: the mediating role of trait- and state-fear of missing out by Yuhua Wang, Yufei Sun, Taiping Li

    Published 2025-03-01
    “…Overall, 417 college students (45.08% male and 54.92% female, with an average age of 19.87 ± 1.05) completed measures of loneliness and PSNSU at the first time point (T1), and measures of trait-FoMO, state-FoMO, and PSNSU 12 months later (T2).Results(1) There were significant positive correlations among loneliness, trait-FoMO, state-FoMO, and PSNSU; (2) Trait-FoMO and state-FoMO fully mediated the relationship between loneliness and PSNSU; (3) there were two paths of loneliness that influenced PSNSU: loneliness was associated with PSNSU through the mediating role of trait-FoMO alone and the chain mediating role of trait- and state-FoMO.ConclusionThis study highlights the need to accurately distinguish between trait-FoMO and state-FoMO, considering their different underlying mechanisms in addressing problematic network problems among college students.…”
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  14. 434

    Artificial intelligence assisted common maternal fetal planes prediction from ultrasound images based on information fusion of customized convolutional neural networks by Fatima Rauf, Muhammad Attique Khan, Hussain M. Albarakati, Kiran Jabeen, Shrooq Alsenan, Ameer Hamza, Sokea Teng, Yunyoung Nam

    Published 2024-10-01
    “…Artificial intelligence is becoming increasingly significant in medical imaging and can assist in resolving many problems related to the classification of fetal organs. …”
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  15. 435

    Multi-Objective Optimization of Pressure-Reducing Valves Operation in Extreme Water Consumption Scenarios (Case Study: Najaf Abad Urban Water Distribution Network) by Seyed Pedram Jazayeri Farsani, Ramtin Moeini

    Published 2024-10-01
    “…A simultaneous optimization model was developed to determine nodal average pressure, residual chlorine concentration, and network combined reliability. …”
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  16. 436

    Optimized integration of photovoltaic systems and distribution static compensators in distribution networks using a novel discrete-continuous version of the adaptive JAYA algorithm... by Paolo Iván Cubillo-Leyton, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña

    Published 2025-06-01
    “…This document addresses the problem regarding the optimal siting and sizing of photovoltaic generators (PVs) and distributed static compensators (D-STATCOMs) in electrical distribution networks, with annualized investment and operating costs minimization as the objective function, incorporating a 10% investment recovery rate and a 2% annual energy cost increase. …”
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  17. 437

    Multi-Step Temperature Prognosis of Lithium-Ion Batteries for Real Electric Vehicles Based on a Novel Bidirectional Mamba Network and Sequence Adaptive Correlation by Hongyu Shen, Yuefeng Liu, Qiyan Zhao, Guoyue Xue, Tiange Zhang, Xiuying Tan

    Published 2024-10-01
    “…First, a two-step hybrid model of trajectory piecewise–polynomial regression and exponentially weighted moving average is created and used to an operational dataset of EVs in order to handle the problem of noisy and incomplete time-series data. …”
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  18. 438

    Variable granularity service function chain mapping algorithm based on microservice architecture by Xiaochun WU, Chen HONG, Yue ZHANG, Junnan ZHANG, Jingjing ZHOU

    Published 2022-12-01
    “…For the problem that the end-to-end delay of the service function chain (SFC) cannot meet the demand of delay-sensitive applications in 5G environment, a variable granularity service function chain mapping (VG-SFCM) algorithm based on microservice architecture was proposed by splitting the traditional virtualized network function (VNF) into mapping units of varying granularity.Firstly, the traditional coarse-grained VNF was decoupled into fine-grained microservice units, and then the instantiation of microservice units was reduced through the consolidation of redundant microservice units within SFC and the reuse of microservice units between SFC, thus reducing the processing time of SFC.The simulation results show that the algorithm reduces the end-to-end delay of SFC by 14.81% compared to the traditional mapping algorithm while reducing the average deployment network cost.…”
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