Enhancing Binary Convolutional Neural Networks for Hyperspectral Image Classification by Xuebin Tang, Ke Zhang, Xiaolei Zhou, Lingbin Zeng, Shan Huang

“…The leading model for classifying hyperspectral images, which relies on convolutional neural networks (CNNs), has proven to be highly effective when run on advanced computing platforms. …”
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Physical Reservoir Computing for Real‐Time Electrocardiogram Arrhythmia Detection Through Controlled Ion Dynamics in Electrochemical Random‐Access Memory by Kyumin Lee, Dongmin Kim, Jongseon Seo, Hyunsang Hwang

“…Through material and process engineering, it is identified that higher ionic conductivity (σion) in the electrolyte layer and lower ionic diffusivity (Dion) in the channel layer are crucial for achieving non‐linear dynamics and fading memory characteristics. …”
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Assessing Water Resource Planning Policies in the Sefidroud Irrigation and Drainage Network Using the Water-Land-Food Nexus Approach by S. Ashkevari, S. Janatrostami, A. Ashrafzadeh

“…To understand the behavior of the network and create a simulation model of the system, a dynamic systems modeling approach was employed, and the simulation was conducted using MATLAB/Simulink. …”
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Graph learning-based spatial-temporal graph convolutional neural networks for traffic forecasting by Na Hu, Dafang Zhang, Kun Xie, Wei Liang, Meng-Yen Hsieh

“…In this paper, we propose a graph learning-based spatial-temporal graph convolutional neural network (GLSTGCN) for traffic forecasting. To capture the dynamic spatial dependencies, we design a graph learning module to learn the dynamic spatial relationships in the traffic network. …”
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Vehicular Crowdsensing with High-Mileage Vehicles: Investigating Spatiotemporal Coverage Dynamics in Historical Cities with Complex Urban Road Networks by L. L. L. Starace, F. Rocco Di Torrepadula, S. Di Martino, N. Mazzocca

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Multi-Source Data-Driven Local-Global Dynamic Multi-Graph Convolutional Network for Bike-Sharing Demands Prediction by Juan Chen, Rui Huang

“…The prediction of bike-sharing demand plays a pivotal role in the optimization of intelligent transportation systems, particularly amidst the COVID-19 pandemic, which has significantly altered travel behaviors and demand dynamics. In this study, we examine various spatiotemporal influencing factors associated with bike-sharing and propose the Local-Global Dynamic Multi-Graph Convolutional Network (LGDMGCN) model, driven by multi-source data, for multi-step prediction of station-level bike-sharing demand. …”
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EEG Emotion Recognition Using AttGraph: A Multi-Dimensional Attention-Based Dynamic Graph Convolutional Network by Shuai Zhang, Chengxi Chu, Xin Zhang, Xiu Zhang

“…Methods: To address these challenges, this paper proposes a multi-dimensional attention-based dynamic graph convolutional neural network (AttGraph) model. …”
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Design and Performance Verification of Dynamic Load Aware Geographic Routing Protocol in IEEE 802.15.4a Networks by Young-Duk Kim, Soon Kwon, Joon-Woo Son, Dongkyun Kim

“…In order to verify the performance of the proposed protocol, we conduct simulation verification experiments and the results show that the proposed protocol provides better performance than the legacy geographical routing schemes in terms of packet delivery ratio, end-to-end delay, network lifetime, and so forth.…”
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Ties that bind: exploring corporate networks, decision-making dynamics in the financial market, labor-management relations, and organizational performance by Emerson Jorge da Silva, Fernando Maciel Ramos, Priscila Cembranel, Cleonice Witt

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Discovery of novel TACE inhibitors using graph convolutional network, molecular docking, molecular dynamics simulation, and Biological evaluation. by Muhammad Yasir, Jinyoung Park, Eun-Taek Han, Jin-Hee Han, Won Sun Park, Mubashir Hassan, Andrzej Kloczkowski, Wanjoo Chun

“…Moreover, molecular docking and molecular dynamics simulation were conducted to validate these findings, using BMS-561392 as a reference TACE inhibitor. …”
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Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks by Honghao Gao, Kang Zhang, Jianhua Yang, Fangguo Wu, Hongsheng Liu

“…In this article, improved particle swarm optimization is introduced into the quality service evaluation of dynamic service composition to meet the mobility requirements of hybrid networks. …”
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The potential mechanism of Huangqin for treatment of systemic lupus erythematosus based on network pharmacology, molecular docking and molecular dynamics simulation by Shuting Zheng, Hui Yang, Jialing Wu, Ou Jin, Xi Zhang

“…Method Employing the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database to identify the active chemical components of Huangqin, searching for target genes related to SLE through GeneCards and the KEGG database, extracting the SLE expression gene profile from the GEO database to identify SLE-related targets, and identifying Huangqin-SLE interaction targets using Venny diagrams; Constructing protein interaction networks using the STRING database, identifying core targets with Cytoscape software, and conducting protein clustering analysis; Importing the common targets into the Database for Annotation, Visualization and Integrated Discovery (DAVID) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. …”
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Power selection of a static symmetrical device under dynamically changing load conditions by A. V. Petrov, V. E. Martusenko, R. A. Magayayev, V. E. Martusenko

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Evaluation and optimization of carbon emission for federal edge intelligence network by Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI

“…In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.…”
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Echoes of Strain: A Two-Year Longitudinal Study on the Impact of China’s Zero-COVID Policy on College Students’ Insomnia and Depressive Symptoms by Wang S, Zou X, Tang Q, Zhang L, Liu X, Liu G, Tao Y

“…There is a pressing need for a more comprehensive evaluation of the implementation of restrictive public policies, taking into account their potential long-term consequences.Keywords: insomnia, depression, dynamic zero-COVID policy, network analysis…”
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Evolutionary Dynamics and Functional Conservation of <i>amh</i> Signaling in Teleost Lineages by Lingqun Zhang, Qingke Zhang, Kai Hu, Wei Lu, Weigang Li, Fengchi Wang, Jie Cheng

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An evolution model for urban rail transit hyper networks based on allometric growth relationship by Zehua Zhang, Ruining Wei, Shumin Feng, Lei Xu, Fan Yang, Hao Liu, Yiqiang Jiang

“…We construct a URT hyper network (stations as nodes, lines as hyper edges) and derive dynamic equations for node hyper degree and hyper edge hyper degree. …”
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Service capability evaluation of electric vehicle public charging network based on analytic hierarchy process by PAN Ying, CAO Xiaoli

“…Therefore, the analytic hierarchy process is used to dynamically evaluate the service capacity of the network. …”
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Stream Network Dynamics of Non‐Perennial Rivers: Insights From Integrated Surface‐Subsurface Hydrological Modeling of Two Virtual Catchments by F. Zanetti, G. Botter, M. Camporese

“…In this work, CATchment HYdrology, an integrated surface–subsurface hydrological model (ISSHM), is used to simulate the stream network dynamics of two virtual catchments with the same, spatially homogeneous, subsurface characteristics (hydraulic conductivity, porosity, water retention curves) but different morphology. …”
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Application of Artificial Neural Network for Predicting Shaft and Tip Resistances of Concrete Piles by Ehsan Momeni, Ramli Nazir, Danial Jahed Armaghani, Harnedi Maizir

“…Axial bearing capacity (ABC) of piles is usually determined by static load test (SLT). However, conducting SLT is costly and time-consuming. High strain dynamic pile testing (HSDPT) which is provided by pile driving analyzer (PDA) is a more recent approach for predicting the ABC of piles. …”
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