Improved Liu Estimator for the Beta Regression Model: Methods, Simulation and Applications by Nimra Ilyas, Muhammad Amin, Muhammad Nauman Akram, Syeda Maryam Siddiqa

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Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter by ZHAN Yanhao, YANG Jiawei, LU Qingsong

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Application of Improved EEMD-NNBR Coupling Model in Annual Runoff Prediction by ZHENG Fangfang, WANG Wensheng, ZHANG Lanting

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Automated Symbolic Upscaling: 1. Model Generation for Extended Applicability Regimes by Kyle Pietrzyk, Ilenia Battiato

“…In Part 1 of this two part series, we present a strategy for expanding the applicability of classical homogenization theory by generalizing the assumed closure form. …”
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Research on crosstalk problem of SiC MOSFET module and countermeasures in application by LIU Min'an, LUO Haihui, LU Shengwen, WANG Xu, LI Cheng

“…In view of the crosstalk problem in the application of SiC MOSFET module, this paper first conducted a comparison of the parameters and measured waveform of three types of measuring differential probes to effectively reduce measurement error. …”
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Exploration and application of deep learning based wellbore deformation forecasting model by Hui LIU, Guoqiang LI, Xiaojun ZHU, Pengfei ZHANG, Hua CHENG, Jinzheng WANG, Peishuai LI

“…In response to the tilting and damage disasters of deep vertical shafts in thick water-bearing loose layers, the tilting and deformation monitoring of shafts was carried out by taking the deep vertical shaft (800 m) of a mine in Lunan as the research object, studying the spatial and temporal change characteristics of shaft tilting, and analyzing the main influencing factors of shaft tilting; based on this, based on the deep learning theory, four types of deep learning method, namely, recurrent neural network (RNN), long and short-term memory network (LSTM), gated recurrent unit (GRU), and one-dimensional convolutional neural network (1DCNN), were used. unit (GRU), and one-dimensional convolutional neural network (1DCNN) to construct a wellbore tilt deformation prediction model, and compare the prediction results with the measured values to analyze the accuracy of the wellbore deformation prediction model, validate the reliability of the model, studied overall wellbore and critical area prediction effects, and carry out engineering applications. The study shows that: ① The wellbore tilt mainly occurs in the loose layer, the tilt value decreases linearly from shallow to deep, and is biased towards the side of the extraction zone, with a maximum of 352 mm, and the deformation of the bedrock layer is smaller, with a maximum of 88 mm; the increase in the range of deformation propagation in the thick loose layer caused by the mining, and the change of seepage hydrophobicity of the aquifer at the bottom along the wall of the well and the seepage field of the groundwater are the main causes of the tilted deformation of the wellbore. ② The Spearman correlation coefficient between the model and the measured value is 0.978 at the maximum and 0.867 at the minimum;the maximum difference between the four models and the field measured offsets is 0.043 m, the mean absolute error EMA is within 0.003–0.009 m, and the root mean square error ERMS is within 0.004–0.011 m. …”
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The Application of Kernel Ridge Regression for the Improvement of a Sensing Interferometric System by Ana Dinora Guzman-Chavez, Everardo Vargas-Rodriguez

“…Here, these features were the wavelength positions and maximum amplitudes of some peaks of the interference spectrum of the sensing system. To sustain the application of the method, four kernel functions were used to estimate the values of the response variable. …”
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Application of improved clustering algorithm in mixed teaching of modern educational technology by Lei Shu, Guirong Li

“…With advances in algorithm optimization and computational capabilities, cluster analysis holds broad potential for educational applications. Specifically, the improved clustering algorithm increased the silhouette score from 0.51 (K-means) and 0.58 (DBSCAN) to 0.68 and reduced the clustering error from 0.27 to 0.18. …”
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Application of SWAT Model for Runoff Calculation in Small Watershed of Zhejiang Province by LAN Xuechun, WANYAN Sheng, ZHANG Zhenqi

“…To verify the applicability of the SWAT model in runoff calculation in small watershed of Zhejiang province,this paper collects daily records for the past 20 years from Wenling meteorological station,topographic map,land use and soil data,and establishes the SWAT model of the Human reservoir by using the SWAT2012 module loaded with Arcgis 10.2 software.In calibration period (1999—2008),R² (correlation coefficient) is 0.89 and E_NS (Nash-Sutcliffe efficiency) is 0.88;in validation period (2009—2018),R² is 0.93 and E_NS is 0.91.With an error of 1.3%,the simulated annual average flow is 0.8 m³/s and the observed flow is 0.79 m³/s,which indicating a high accuracy of the model.The sensitivity test of input parameters shows that the SOL_AWC.sol (available water capacity of soil) and CN2.mgt (runoff coefficient of different land use) are significant to simulated results.The model can be further used for forecasting the flood process and peak flow of Human reservoir,as well as optimizing the reservoir operation scheme and formulating the protection program of water source.…”
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MZAP—Mobile Application for Basketball Match Tracking and Digitalization of Endgame Reports by Predrag Pecev, Branko Markoski

“…This paper presents MZAP, a mobile application designed to digitalize basketball match tracking and generate secure, searchable endgame reports. …”
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Comparing Outlier Detection Methods: An Application on Indonesian Air Quality Data by Anwar Fitrianto, Amalia Kholifatunnisa, Anang Kurnia

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An Application of Quasi Newton Algorithm and Improvement of Sliding Surface for Robot Control by Chi-Ngon Nguyen, Thanh Tung Pham

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Generating Automatically Print/Scan Textures for Morphing Attack Detection Applications by Juan E. Tapia, Maximilian Russo, Christoph Busch

“…A larger and more diverse dataset representing passport application scenarios, including various devices and resulting printed, scanned, or compressed images, is needed to enhance the detection capabilities and identify such morphing attacks. …”
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Application of deep learning for rice leaf disease detection in the Mekong Delta by Duc Luu Ngo, Thi Thuy Diem Le, Thi Phuong Anh Ha

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Application of deep learning for rice leaf disease detection in the Mekong Delta by Duc Luu Ngo, Thi Thuy Diem Le, Thi Phuong Anh Ha

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Application of Homogenization Method in Free Vibration of Multi-Material Auxetic Metamaterials by Kadir Gunaydin, Orhan Gülcan, Aykut Tamer

“…Different additive manufacturing modalities enable the production of multi-material components which can be used in a wide range of industrial applications. The prediction of the mechanical properties of these components via finite element modelling rather than through testing is critical in terms of cost and time. …”
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Application of Mathematical Models for Blood Flow in Aorta and Right Coronary Artery by Monica Minniti, Vera Gramigna, Arrigo Palumbo, Gionata Fragomeni

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Design and Application of an Energy Management System Based on Artificial Intelligence Technology by Hongye Lin, Xuanying Bai, Chun Li, Shenghan Xu, Haibin Xu, Zne-Jung Lee, Yun Lin, Qunshan Zhou, Jingxun Cai

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Advanced Applications of Artificial Intelligence in Pharmacovigilance: Current Trends and Future Perspectives by Yogesh S Ahire, Jayesh H Patil, Harshita N Chordiya, Rashmi A Deore, Vinod A Bairagi

“…For artificial intelligence-driven systems to be accurate, dependable, and applicable, ongoing validation, monitoring, and improvement efforts are essential. …”
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Design and Application of Full-Time Dimension Dispatching Schedule Safety Check by Di WU, Zhengfeng WANG, Hang LIU

“…The system has been successfully applied in Anhui Power Grid, and the application results show that the proposed method is effective and can meet the needs of power grid safety check.…”
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