Secure performance analysis and detection of pilot attack in massive multiple-input multiple-output system by Xianyu Zhang, Daoxing Guo, Kefeng Guo, Hehao Niu

“…This article studies the physical layer security of massive multiple-input multiple-output system in time-division-duplex mode. …”
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Researches on the Excavation Disturbance of Shield Tunnel in Sandy Cobble Ground by Wei Wang, Jingjing Liu, Xueming Zhang, Jing Chen

“…The sandy cobble ground has loose structure, uneven particle size, and random distribution characteristics, which may lead to the local collapse of ground. …”
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Single-Shot Imaging Without Reference Wave Using Binary Intensity Pattern for Optically-Secured-Based Correlation by Wen Chen

“…Optical imaging without reference wave is applied based on double random phase encoding (DRPE), and the recorded intensity pattern is further compressed, which contains only two quantization levels (i.e., 0 and 1). …”
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Resilience Analysis of Multi-Modal Transportation Networks: A Case Study of the Beijing-Tianjin-Hebei Region by Shuyan Zheng, Ye Zhang, Yanyan Chen

“…The results show that the attack on key nodes brings more influence to MMTN than random attacks. More attention is suggested to be paid to the larger hub-type stations in operation and management. …”
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Multimodal Control by Variable-Structure Neural Network Modeling for Coagulant Dosing in Water Purification Process by Jun Zhang, Da-Yong Luo

“…Different with the normal neural network mode, PCA is used to optimize hidden-layer nodes and update the neural network structure at every computation. …”
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Pretreatment Methods for Enhancing Machine Learning Performance on Metabolomics Data by Rustam

“…The novelty of this paper lies in its comprehensive assessment of how these methods influence model-specific performance, particularly for Gradient Boosting Classifier, Multi-Layer Perceptron, Support Vector Classifier, and Random Forest. …”
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Mathematical description of deviation mechanisms positions of track chassis in motion with variable ground resistance by Goncharov K.A.

“…In reality, the ground is not homogeneous, and the coefficient of resistance to movement at each moment in time is a random variable located in a certain interval depending on the type of ground. …”
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Engineered surface nanocrystalline structures in SS304 via severe shot peening: Insights into microstructural evolution and mechanical property modulation by Yuefan Wei, Sankaranarayanan Seetharaman, Jing Jun Lee, Yakai Zhao, Aldrich Chua, Hong Fei Liu, Baisong Cheng, Cheng Cheh Tan

“…Phase transformation of γ austenite to α′martensite and grain refinement occurred during the mechanical peening process. Four layers with distinctly different microstructures were found after severe peening, which include i) martensitic phased nanocrystals with preferred orientation. ii) martensitic phased nanocrystals with random orientations. iii) transition layer with martensite phase partially transformed from austenite phase. iv) matrix phase. …”
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Drivers of soil carbon and nitrogen stock in topsoil and deep soil under grazing in two steppe ecosystems by Jiali Sun, Shichao Tian, Haihua Bai, Fei Li

“…In this study, we investigated the effects of grazing and steppe type on the SOC and TN concentrations, stocks, enzyme activities, and microbes in the top 1-meter soil layer of semi-arid steppe in Inner Mongolia. The results showed that grazing significantly reduced SOC and TN stocks in the 0–30 cm soil layer of the meadow steppe but significantly increased SOC and TN stocks in the 70–100 cm soil layer of both meadow and typical steppes. …”
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Brown-shell eggs shows high incidence of blood and meat spots accompanied by unique microbial distribution patterns by Junfeng Wu, Yiyuan Yan, Jiahua Chen, Junying Li, Guangqi Li, Guiqin Wu, Bin Wang, Gang Zheng, Yuqin Yang, Yushuang Du, Ling Lian

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First National Report on Soil Salinity Across Paraguay by Arnulfo Encina Rojas, Víctor Sevilla-Linares, Mario Guevara-Santamaría, Samuel Villarreal Villarreal, Carolina Olivera, Ronald Vargas, Federico Olmedo

“…The statistical model used to map soil salinity properties was the "quantile random forest." For validation and accuracy calculation, we utilized "cross-validation" with all soil sampling sites and a "Random" selection parameter. …”
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Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau by Wangping Li, Yadong Liu, Xiaodong Wu, Lin Zhao, Tonghua Wu, Guojie Hu, Defu Zou, Yongping Qiao, Xiaoying Fan, Xiaoxian Wang

“…In terms of spatial distribution, clay and silt are higher in the southeast and lower in the northwest in each standard layer, while sand is just the opposite. The random forest regression model showed that vegetation condition was a controlling factor of soil particle size. …”
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A machine learning-based approach for constructing a 3D apparent geological model using multi-resistivity data by Jordi Mahardika Puntu, Ping-Yu Chang, Haiyina Hasbia Amania, Ding-Jiun Lin, M. Syahdan Akbar Suryantara, Jui-Pin Tsai, Hwa-Lung Yu, Liang-Cheng Chang, Jun-Ru Zeng, Lingerew Nebere Kassie

“…Notably, in the proximal fan, gravel layers predominate, whereas the middle fan primarily consists of sandy clay layers. …”
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A comparative study of machine learning in predicting the mechanical properties of the deposited AA6061 alloys via additive friction stir deposition by Qian Qiao, Quan Liu, Jiong Pu, Haixia Shi, Wenxiao Li, Zhixiong Zhu, Dawei Guo, Hongchang Qian, Dawei Zhang, Xiaogang Li, C. T. Kwok, L. M. Tam

“…Furthermore, analysis suggests that the feed rate (24.8%/24.1%) and layer thickness (25.6%/26.6%) indicate a higher contribution that affects the mechanical properties.…”
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Microplastics Abundance and Spatial Distribution in Bayinbuluk Alpine Swamp Meadow by Yuxin Tian, Maidinuer Abulaizi, Yunpeng Hu, Yang Hu, Mo Chen, Yuanbin Jia, Tianle Kou, Jianqin Zhou, Hongtao Jia

“…Polyethylene (PE) was found to be a major component of soil microplastics in the study area through random sampling using Raman spectroscopy. Correlation analysis showed that the change in soil layer had a significant effect (<i>p</i> < 0.05) on the number, color, and particle size of microplastics. …”
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Controlled Fabrication of Native Ultra‐Thin Amorphous Gallium Oxide From 2D Gallium Sulfide for Emerging Electronic Applications by AbdulAziz AlMutairi, Aferdita Xhameni, Xuyun Guo, Irina Chircă, Valeria Nicolosi, Stephan Hofmann, Antonio Lombardo

“…The results demonstrate the ability to form ultrathin native oxide (GaSxOy), 4 nm in thickness, upon exposure to 10 W of O2, resulting in a GaSxOy/GaS heterostructure where the GaS layer beneath remains intact. By integrating such structures between metal electrodes and applying electric stresses as voltage ramps or pulses, their use for resistive random‐access memory (ReRAM) is investigated. …”
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Comparative analysis of visible and near-infrared (Vis-NIR) spectroscopy and prediction of moisture ratio using machine learning algorithms for jujube dried under different conditi... by Seda Günaydın, Necati Çetin, Cevdet Sağlam, Kamil Sacilik, Ahmad Jahanbakhshi

“…Also, the MR was predicted by the MC, and the drying rate (DR), drying times, and final thickness were predicted using the multi-layer perceptron (MLP), gaussian process (GP), k-nearest neighbors (KNN), random forest (RF), and support vector regression (SVR) algorithms. …”
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Deformation Influencing Factor Analysis for Shield Tunnelling under Micro-shallow Gas Strata by YANG Xin, HONG Yi, WANG Lizhong

“…The importance of shield tunneling parameters on land subsidence during shield construction in gas-bearing soil layers is analyzed based on a random forest model. …”
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PRECISION AND STABILITY OF THE PREDICTION FORMULA FOR BURST STRENGTH OF PRESSURE-BEARING CYLINDER by LIU Cen, YANG Fan, WU SengLin, HONG Kai, ZHANG Shu, LIU XiaoNing

“…The researching results shown that:（ 1） It is the basic conditions for selecting formulas or extending their applied ranges that stability and precision not reduced.（ 2） For pressure-bearing single-layer cylinder,the applied range of the Mid-diameter formula for measured burst pressure specified by the standard,it can be extended from no more than 105 MPa to no more than 329. 6 MPa,the stability of the Mid-diameter formula is obviously improved and the precision is not reduced. …”
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Soil water dynamics in a 450-year-old natural landslide-dammed valley farmland: Insights into precipitation responses by Zhao Jin, Huifeng Wu, Hao Han, Yunchong Fu, Jing Zhang, Guofan Cao, Keyan Xu

“…Based on HYDRUS-1D model calculations, the soil water storage of NLDF remained stable under low precipitation but showed a sharp rise and decline when precipitation exceeded 9.8 mm. We employed a random forest model to assess the factors influencing the soil layers’ response rates to rainfall and their soil moisture expansion potential during extreme rainfall events. …”
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