Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…ObjectiveThree-dimensional (3D) slope reliability analysis encounters two primary challenges: (1) the stochastic modeling of soil properties involves intricate spatial variability, necessitating extensive data processing and imposing prohibitive computational burdens; and (2) brute-force trial-and-error methods for locating critical failure surfaces are computationally inefficient, impeding real-world implementation despite the imperative for precise stability evaluations in civil infrastructure. …”
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Possibilities and reserves of using electronic medical records data in health information systems on the example of assessing the causes of visits to outpatient clinics and death i... by I. V. Samorodskaya, R. N. Shepel, I. V. Klyuchnikov, M. M. Lukyanov, S. Yu. Martsevich, E. P. Kakorina, O. M. Drapkina

“…In 92 (3,9%) patients, MI was the reason for visiting in 2020-2021 and the initial cause of death in 2021, while in 1404 (59,6%) patients who did not visit for CAD or MI in 2020-2021, MI was the initial cause of death in 2021. Following data recording errors were revealed: only in 28 (12,7%) of 219 cases after MI were codes recommended in the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) for recording cases of post-infarction cardiosclerosis (I25.8) indicated; in 326 (16,5%) cases among those who died from MI, codes I22.0-9 were used, which are not recommended to be indicated as the underlying cause of death. …”
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Data-Driven Multi-Scale Channel-Aligned Transformer for Low-Carbon Autonomous Vessel Operations: Enhancing CO₂ Emission Prediction and Green Autonomous Shipping Efficien... by Jiahao Ni, Hongjun Tian, Kaijie Zhang, Yihong Xue, Yang Xiong

“…Traditional models face limitations in real-time multi-source data analysis and dynamic cross-variable dependency modeling, hindering data-driven decision-making for sustainable autonomous shipping. …”
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Bayesian Estimation for Zero-Truncated Bivariate Poisson Regression Model by Prapaporn Rerngchaiyaphum, Monthira Duangsaphon

“…The performance of the Bayes estimators was compared with that of the bootstrap estimators and the maximum likelihood estimators via a Monte Carlo simulation analysis, focusing on mean square error. The performance of intervals was evaluated based on coverage probability and average length. …”
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Monthly Load Forecasting in a Region Experiencing Demand Growth: A Case Study of Texas by Jeong-Hee Hong, Geun-Cheol Lee

“…This study focuses on the Texas power grid, where electricity consumption has surged due to rising industrial activity and the increased construction of data centers driven by growing demand for AI. Based on an extensive exploratory data analysis, we identify key characteristics of monthly electricity demand in Texas, including an accelerating upward trend, strong seasonality, and temperature sensitivity. …”
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A Deep Learning-Based Framework for Bearing RUL Prediction to Optimize Laser Shock Peening Remanufacturing by Yuchen Liang, Yuqi Wang, Anping Li, Chengyi Gu, Jie Tang, Xianjuan Pang

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Improving the quality of payment fraud detection by using a combined approach of transaction analysis by Світлана Гавриленко, Олексій Абдуллін

“…The results of the experiment showed a different influence of features on subclass belonging, which allows for a more detailed analysis of the data to identify hidden structures in the data. …”
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HAMF: A Novel Hierarchical Attention-Based Multi-Modal Fusion Model for Parkinson’s Disease Classification and Severity Prediction by Anitha Rani Palakayala, P. Kuppusamy, D. Kothandaraman, Gunakala Archana, Jaideep Gera

“…A comprehensive approach is a multi-modal framework that overcomes these limitations by integration of brain Magnetic Resonance Imaging (MRI) data, gait analysis, and speech signals for enhanced classification and severity estimation of PD. …”
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Review of construction and reasoning methods for knowledge graphs in coal mining domain by LUO Xiangyu, HUA Ying, WANG Xiping, XIE Panshi, WU Yongping

“…Knowledge from diverse data sources in the coal mining domain is extracted to construct a knowledge network. …”
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Rice Identification and Spatio-Temporal Changes Based on Sentinel-1 Time Series in Leizhou City, Guangdong Province, China by Kaiwen Zhong, Jian Zuo, Jianhui Xu

“…Furthermore, we extracted the distribution range of early and late rice in Leizhou City from 2017 to 2021 using a U-Net model with a minimum relative error accuracy of 3.56%. Our analysis indicated an increasing trend in both overall rice planting area and early rice planting area, accounting for 44.74% of early rice and over 50% of late rice planting area in 2021. …”
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Analysis and spatial mapping of antimicrobial prescription completeness and legibility in a public community pharmacy by Friedemann BERGER, Fabrícia Benda OLIVEIRA, Sérgio Henriques SARAIVA, Ariadne Marra SOUZA, Carlos Henrique OLIVEIRA, Larissa COUTO-ROSA, Genival Araujo SANTOS-JÚNIOR

“… Objective The phenomenon of resistance of antimicrobials is associated with inappropriate use. The analysis of antimicrobial prescriptions, evaluating their legibility and completeness, is interesting because it aims to identify possible errors that may compromise the proper use. …”
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The Effectiveness of Electronic Differential Diagnoses (DDX) Generators: A Systematic Review and Meta-Analysis. by Nicholas Riches, Maria Panagioti, Rahul Alam, Sudeh Cheraghi-Sohi, Stephen Campbell, Aneez Esmail, Peter Bower

“…<h4>Background</h4>Diagnostic errors are costly and they can contribute to adverse patient outcomes, including avoidable deaths. …”
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The analysis of dynamic evaluation of online shopping satisfaction based on the recurrent neural network model by Cheng Zhao, Yi Xun

“…Experimental evaluations of the prediction model are conducted on an Amazon shopping dataset. Comparative analysis reveals that the DW-GRU model outperforms the standard RNN model, showing lower errors with accuracy, precision, and recall values of 0.871, 0.667, and 0.667, respectively. …”
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Key Factors of Effectiveness of Developing an Activity Based Cost Accounting and Analysis System at an Enterprise by Y. V. Trifonov, A. N. Vizgunov

“…It helps to eliminate the errors connected with using wrong data as an information base for accounting. …”
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Machine learning enhanced formation pressure prediction using integrated well logging and mud logging by Jiwen Liang, Ming Luo, Wentuo Li, Bo Sun, Chuanliang Yan, Zhongying Han, Yuanfang Cheng

“…The IWM model significantly reduces the prediction error of formation pore pressure, achieving an average improvement of 8.32% enhancement in prediction accuracy compared to traditional data models. …”
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Nonlinear Regression with High-Dimensional Space Mapping for Blood Component Spectral Quantitative Analysis by Xiaoyan Ma, Yanbin Zhang, Hui Cao, Shiliang Zhang, Yan Zhou

“…This paper proposes a nonlinear regression method with high-dimensional space mapping for blood component spectral quantitative analysis. Kernels are introduced to map the input data into high-dimensional space for nonlinear regression. …”
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Algorithm for Reproducible Analysis of Semiconducting 2D Nanomaterials Based on UV‐VIS Spectroscopy by Nico Kubetschek, Claudia Backes, Stuart Goldie

“…Existing UV‐VIS extinction spectroscopy‐based metrics, particularly those related to thickness, have shown promise but rely on manual data processing, which can introduce irreproducibility and user errors. …”
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Analysis of the Influence of CT Imaging Conditions on the CT Image Features of Pulmonary Nodule Phantoms by Jing Li, Daidi Zhong, Shuo Wang, Chunjing Tao, Hao Wang

“…The texture features (GLCM, GLRLM, GLSZM, GLDM, NGTDM) of CT images of pulmonary nodules were extracted using the PyRadiomics package in Python, and the five main texture features were selected using the LASSO method. To analyze the data, correlation analysis and non-parametric tests were applied, with a correction method used to control errors in multiple comparisons. …”
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Comparative Analysis and Optimal Selection of Calibration Functions in Pure Rotational Raman Lidar Technique by Yinghong Yu, Siying Chen, Wangshu Tan, Rongzheng Cao, Yixuan Xie, He Chen, Pan Guo, Jie Yu, Rui Hu, Haokai Yang, Xin Li

“…Conclusions based on the simulation results are validated with actual data, and the factors influencing calibration errors are discussed. …”
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Robust Analysis and Parameters Identification of the Nonlinear Multistage Dynamical System in Batch Fermentation of Glycerol by Xu Zhang, Xinying Wang, Enmin Feng, Zhilong Xiu

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