Variable Speed Limit Strategies Based on the Macro Hierarchical Control Traffic Flow Model by Shubin Li, Tao Wang, Hualing Ren, Baiying Shi, Xiangke Kong, Jianyong Chai, Xuejuan Wang

“…The dynamic OD estimation model is used to produce the real traffic information, which is loaded to the traffic network. Then, the prediction information of traffic variables and the VSL strategy are introduced to macro hierarchical control traffic flow model. …”
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Tailoring orthotropic mechanical and thermal properties in nonlinear contact, vibration and thermal problems via kriging-based optimization by Yicong Zhou, Jinyan Duan, Guoxin Mao, Jun Hong

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PointNet++ (MSG-DSLS): A Classification Framework With Dynamic Step-Size Loop-Sampling for High-Density Tree Point Clouds by Zhen Liu, Ying Quan, Bin Wang, Jianyang Liu, Mingze Li

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Dispatching strategy of shared bicycles for morning peak tidal travel based on spatial distribution by Xiangyu Lei, Jiaqi Yang

“…The study identifies the spatial distribution characteristics of the tidal phenomenon by analyzing the riding order and electronic fence data and combining them with the KD-Tree algorithm; subsequently, a demand prediction model based on the XGBoost algorithm and a hierarchical scheduling model based on the greedy algorithm are constructed to dynamically optimize the spatial distribution of the bicycle resources with the demand fluctuation as the guide. …”
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A Semi-Supervised Attention-Temporal Ensembling Method for Ground Penetrating Radar Target Recognition by Li Liu, Dajiang Yu, Xiping Zhang, Hang Xu, Jingxia Li, Lijun Zhou, Bingjie Wang

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Servo Control of Shunt-Active Power Filters Using Kalman Filter With DC-Link Reference by Vijay Kumar C. V., Srinivasa Rao Gundala, Sri Kavya G., Pavan K., Murali R., Meerimatha G.

“…This reference approach may autonomously regulate adapting dc-link voltage anticipating current at most permissible source reference under varying load circumstances. Predictive modelling does this. MATLAB/Simulink integrates SAPF with the control algorithm. …”
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Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition by Yuyang Li, Xia Wang, Min Zhang, Ruiqiang Li, Qiyang Sun

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GRRIS: A Real-time Intrasite Observation Scheduling Scheme for Distributed Survey Telescope Arrays by Yajie Zhang, Ce Yu, Chao Sun, Yi Hu, Zhaohui Shang, Jizeng Wei, Xu Yang

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Signature of pre-pregnancy microbiome in infertile women undergoing frozen embryo transfer with gestational diabetes mellitus by Wenzheng Guan, Tian Zhou, Jiao Jiao, Liwen Xiao, Zhen Wang, Siyuan Liu, Fujie Yan, Fangqing Zhao, Xiuxia Wang

“…A model based on ten bacteria and ten metabolites simultaneously was used to predict the risk of GDM developing in the pre-pregnancy state with the ROC value of 0.712. …”
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Intelligent design of mixture proportions of manufactured sand concrete from environmental, economical and mechanical perspectives by Junfei Zhang, Changhai Xu, Lei Zhang, Ling Wang

“…This study proposes a multi-objective optimization (MOO) method based on machine learning (ML) and the non-dominated sorting genetic algorithm II (NSGA-II) to optimize MSC mixtures. The results indicate that the extremely randomized trees (ERT) model exhibits the best predictive performance for UCS, with an R value of 0.988 on the test set. …”
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An Intelligent Fault Diagnosis Model for Rolling Bearings Based on IGTO-Optimized VMD and LSTM Networks by Xianglong Luo, Fengrong Yu, Jing Qian, Biao An, Nengpeng Duan

“…This approach provides a valuable reference for predictive maintenance and fault detection systems in industrial applications.…”
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Comparative effects of metformin and varying intensities of exercise on miR-133a expression in diabetic rats: Insights from machine learning analysis by Elahe Alivaisi, Sabrieh Amini, Karimeh Haghani, Hori Ghaneialvar, Fatemeh Keshavarzi

“…We used the CatBoost algorithm to develop a predictive model for miR-133a expression based on metabolic parameters. …”
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Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction by Ander Biguri, Subhadip Mukherjee, Xuzhi Zhao, Xi Liu, Xinyi Wang, Rui Yang, Yi Du, Yahui Peng, Mikael Brudfors, Mark Graham, Hyungon Ryu, Oliver Kutter, Andreas Hauptmann, Mustafa Al-Rubaye, Miika T. Nieminen, Mikael A. K. Brix, Austin Yunker, Rajkumar Kettimuthu, John C. Roeske, Sasidhar Alavala, Subrahmanyam Gorthi, Carola-Bibiane Schonlieb

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Eye Collateral Channel Characteristic Analysis and Identification Model Construction of Mild Cognitive Impairment by WU Tiecheng, CAO Lei, YIN Lianhua, HE Youze, LIU Zhizhen, YANG Minguang, XU Ying, WU Jinsong

“…Eligible subjects were matched on a 1∶1 propensity score according to sex, age, and years of education and were divided into MCI group and normal cognition group, with 158 cases in each group. …”
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Stroke aftercare in Germany: findings from an online survey in the outpatient setting of a neurovascular network by John-Ih Lee, Robin Jansen, Jan F. Cornelius, Hubert Schelzig, Bernd Turowski, Rüdiger J. Seitz, Til Menge, Philipp Albrecht, Philipp Albrecht, Sebastian Jander, Jan Sobesky, Hans-Jürgen von Giesen, Marcel Dihné, Lars Wojtecki, Lars Wojtecki, Tristan Kölsche, Sajjad Muhammad, Tobias Ruck, Sven G. Meuth, Michael Gliem

“…The evidence-based acute treatment of stroke patients in Germany is carried out according to standardized algorithms in more than 300 certified stroke units, and its quality is repeatedly assured by the German Stroke Society (DSG) and others. …”
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Understanding discrepancies in soil moisture from SMAP and AMSR2: insights into performance and dry-down behavior by Zhiqing Peng, Tianjie Zhao, Jiancheng Shi, Lu Hu, Thomas J. Jackson, Michael H. Cosh, Hui Lu, Xiaodong Gao, Jingyao Zheng, Panpan Yao, Qian Cui, Peng Guo, Peilin Song, Zushuai Wei, Mengjia Wang, Anmin Fu

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Spatiotemporal estimation of ambient forest phytoncides: Unveiling patterns through geospatial-based machine learning approach by Aji Kusumaning Asri, Hao-Ting Chang, Chia-Pin Yu, Wan-Yu Liu, Yinq-Rong Chern, Rui-Hao Xie, Shih-Chun Candice Lung, Kai Hsien Chi, Yu-Cheng Chen, Sen-Sung Cheng, Gary Adamkiewicz, John D. Spengler, Chih-Da Wu

“…The results showed that RF and XGB were the most effective algorithms, explaining approximately 83.3% and 98.4% of the spatiotemporal variability in camphene and α-pinene, respectively. …”
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A Distributed Energy Optimized Routing Using Virtual Potential Field in Wireless Sensor Networks by Haifeng Jiang, Yanjing Sun, Renke Sun, Wei Chen, Shanshan Ma, Jing Gao

“…We adopt the social welfare function from social sciences to predict equality of residual energy of neighbors after selecting different next nodes, which is used to compute the potential value in energy balance potential field. …”
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3D Volumetric Strain Distribution of the Cerro Prieto Geothermal Field Inferred From Inverse Modeling of InSAR and Leveling Data by Luis A. Gallardo, Olga Sarychikhina, Ewa Glowacka, Braulio Robles

“…We present and release a conjugate‐gradient inversion code that searches for the three‐dimensional distribution of the volumetric strain that predicts simultaneously any observed InSAR, leveling and GPS surface displacement. …”
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Local Entropy Optimization–Adaptive Demodulation Reassignment Transform for Advanced Analysis of Non-Stationary Mechanical Signals by Yuli Niu, Zhongchao Liang, Hengshan Wu, Jianxin Tan, Tianyang Wang, Fulei Chu

“…This method provides strong support for mechanical fault diagnosis, condition monitoring, and predictive maintenance, making it particularly suitable for real-time analysis of multi-component and cross-frequency signals.…”
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