Evaluating the impact of built environment on shared electric bicycle connectivity in kunming’s public transport system by Chaodong Gou, Churan Feng, Shucheng Tan, Miqi Guo, Rongwei Li, Fei Zhao

“…For the selection of feature factors, the XGBoost machine learning algorithm is harnessed to compare the importance indices of relevant factors. …”
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Developing real-time IoT-based public safety alert and emergency response systems by Han Zhang, Runze Zhang, Jiamanzhen Sun

“…Abstract This paper presents the design and evaluation of a real-time IoT-based emergency response and public safety alert system tailored for rapid detection, classification, and dissemination of alerts during critical incidents. …”
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An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks by Jin Wang, Yu Gao, Wei Liu, Arun Kumar Sangaiah, Hye-Jin Kim

“…In this article, we present an intelligent data gathering schema with data fusion called IDGS-DF. …”
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Memory‐constrained implementation of lattice‐based encryption scheme on standard Java Card platform by Ye Yuan, Kazuhide Fukushima, Junting Xiao, Shinsaku Kiyomoto, Tsuyoshi Takagi

“…Abstract The lattice‐based encryption scheme has high efficiency and reliability, and it can be run on small devices with limited memory capacity and computational resources such as sensor nodes or smart cards. The first implementation is presented of the original ring–learning‐with‐errors‐based encryption scheme on a standard Java Card platform by combining the number theoretic transform with improved Montgomery modular multiplication. …”
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Enhancing biometric identification using 12-lead ECG signals and graph convolutional networks by Maram Al Alfi, Pedro Peris-Lopez, Carmen Camara

“…This index is used to construct a graph representation, where nodes correspond to ECG features and edges reflect their relationships based on MI values. …”
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Knowledge graph based entity selection framework for ad-hoc retrieval by Pankaj Singh, Plaban Kumar Bhowmick

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Robust collaborative mesh networking with large-scale distributed wireless heterogeneous terminals in industrial cyber-physical systems by Tao Wang, Jun Liu, Lianglun Cheng, Hong Xiao

“…First, moderate redundancy of network deployment is introduced to guarantee two-connectivity for each mesh router and two-coverage for each wireless terminal, and an improved metric for evaluating the overall network robustness is presented. Second, the robustness-aware collaborative mesh networking problem is formulated with a multi-objective optimization model, and an improved multi-objective particle swarm optimization algorithm based on self-adaptive evolutionary learning is exploited to search out the Pareto optimal particles with better distribution and diversity. …”
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Power Quality State Estimation for Distribution Grids Based on Physics-Aware Neural Networks—Harmonic State Estimation by Patrick Mack, Markus de Koster, Patrick Lehnen, Eberhard Waffenschmidt, Ingo Stadler

“…Monitoring all relevant nodes is operationally infeasible and costly. State estimation methods provide knowledge about unmeasured locations by learning a physical system’s non-linear relationships. …”
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Comparison of ensemble and correlation graphs in the task of classifying brain states based on fMRI data by Vlasenko, Daniil Vladimirovich, Ushakov, Vadim Gennadevich, Zaikin, Aleksei Anatolevich, Zakharov, Denis Gennadevich

“…Methods. This paper presents a novel method for representing fMRI data in graph form based on ensemble learning. …”
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Spatio-Temporal AI Modeling for Urban Traffic Calibration: A SUMO-Based Approach by Pablo Manglano-Redondo, Alvaro Paricio-Garcia, Miguel A. Lopez-Carmona

“… Urban traffic management is a critical challenge in modern cities, necessitating innovative solutions to optimize traffic flow and reduce congestion. This research presents the development of an AI engine leveraging spatio-temporal learning techniques for urban traffic calibration. …”
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Wasserstein GAN for moving differential privacy protection by Enze Liu, Zhiguang Chu, Xing Zhang

“…Abstract Training machine learning models often requires large datasets, but using sensitive data for training poses risks of privacy leakage. …”
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Aerodynamic Drag Coefficient Prediction of a Spike Blunt Body Based on K-Nearest Neighbors by Jonathan Arturo Sánchez Muñoz, Christian Lagarza-Cortés, Jorge Ramírez-Cruz

“…The parametric study of the spike blunt body was performed considering body diameter, spike length, and freestream Mach number as input variables. The algorithm presents proper predictions, with errors less than 5% for the drag coefficient and considering a minimum of three neighbor nodes. …”
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Soil Parameter Inversion in Dredger Fill Strata Using GWO-MLSSVR for Deep Foundation Pit Engineering by Changrui Chen, Sifan Li, Jinbi Ye, Fangjian Chen, Yibin Wu, Jin Yu, Yanyan Cai, Jinna Lin, Xianqi Zhou

“…Additionally, the influence of construction stages, input layer nodes, and training sample size on inversion performance is investigated. …”
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The digital university is a solution for the sustainable functioning and developing of higher education institutions in war and post-war times by Oleh Zakhozhai, Dmytro Marchenko, Oleksandr Menyaylenko

“…Particular attention is paid to solutions that allow to ensure the sustainable functioning and development of educational institutions in war and post-war times. The presented approach to building a «digital university» is based on the use of a hybrid server park for minimize financial costs for support while simultaneously ensuring a high level of availability of the educational institution’smain services and the introduction of an improved mode of synchronous learning, which is called «distributed synchronous mode». …”
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Intrusion Detection in IoT Networks Using Dynamic Graph Modeling and Graph-Based Neural Networks by William Villegas-Ch, Jaime Govea, Alexandra Maldonado Navarro, Pablo Palacios Jativa

“…In this model, devices are represented as nodes and communications as weighted edges, integrating features such as communication frequency, transmitted data volume, and protocol type. …”
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Resource Optimization Method Based on Spatio-Temporal Modeling in a Complex Cluster Environment for Electric Vehicle Charging Scenarios by Hongwei Wang, Wei Liu, Chenghui Wang, Kao Guo, Zihao Wang

“…In intelligent cluster systems, the spatio-temporal complexity of agent data collection and resource allocation, as well as the problems in collaborative organizations, present substantial challenges to efficient resource distribution. …”
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Smart Maritime Transportation-Oriented Ship-Speed Prediction Modeling Using Generative Adversarial Networks and Long Short-Term Memory by Xinqiang Chen, Peishi Wu, Yajie Zhang, Xiaomeng Wang, Jiangfeng Xian, Han Zhang

“…To overcome this difficulty and further optimize the accuracy of ship-speed prediction, this research proposes a new deep learning framework to predict ship speed by combining GANs (Generative Adversarial Networks) and LSTM (Long Short-Term Memory). …”
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The relationship between cognitive and global function in patients with schizophrenia and mood disorders: a transdiagnostic network analysis by Yuanyuan Zhu, Rongrong Zhang, Longyan Ni, Zhaoyang Xie, Shuiping Lu, Shiping Xie, Xiangrong Zhang

“…ObjectiveCognitive deficits present transdiagnostic characteristic and partly explain the poor functional outcomes of patients with mental disorders. …”
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Dynamic Path Flow Estimation Using Automatic Vehicle Identification and Probe Vehicle Trajectory Data: A 3D Convolutional Neural Network Model by Can Chen, Yumin Cao, Keshuang Tang, Keping Li

“…Therefore, in this paper, the dynamic path flow estimation is based on these two data sources and transformed into a feature learning problem. To fuse the two data sources belonging to different detection ways at the data level, the virtual AVI points, analogous to the real AVI points (turning movements at nodes with AVI detectors), are defined and selected to statically observe the dynamic movement of the probe vehicles. …”
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Urban Functional Zone Mapping by Integrating Multi-Source Data and Spatial Relationship Characteristics by Daoyou Zhu, Xu Dang, Wenjia Shi, Yixiang Chen, Wenmei Li

“…This framework leverages the OpenStreetMap (OSM) road network to partition the study area into functional units, employs a graph model to represent urban functional nodes and their intricate spatial topological relationships, and harnesses the capabilities of Graph Convolutional Network (GCN) to fuse these multi-dimensional features through end-to-end learning for accurate urban function discrimination. …”
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