Partial Discharge Type Identification of 10 kV T-Type Terminal Based on Empirical Mode Decomposition and Deep Convolution Neural Network by Shude Cai, Chunhua Fang, Yongyu Guo, Jialiang Liu, Gu Zhou

“…This method uses the partial discharge experimental platform of the T-type cable terminal to collect the partial discharge signal. …”
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Multi-Scale Ground Deformation in Beijing Plain Revealed by a Joint 2D-FFT and MGWR Decomposition of InSAR Observation by Nian Feng, Lei Xie, Wenbin Xu, Miao Yu

“…This article proposes a novel multiscale InSAR deformation decomposition method that integrates two-dimensional fast Fourier transform with a multiscale geographically weighted regression model. …”
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Convex Optimization of Markov Decision Processes Based on Z Transform: A Theoretical Framework for Two-Space Decomposition and Linear Programming Reconstruction by Shiqing Qiu, Haoyu Wang, Yuxin Zhang, Zong Ke, Zichao Li

“…We develop a Z-transformation-based dual-space decomposition method to reconstruct MDPs into a solvable linear programming form, resolving the inherent instability of traditional models caused by uncertain initial conditions and non-stationary state transitions. …”
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GPS Phase Integer Ambiguity Resolution Based on Eliminating Coordinate Parameters and Ant Colony Algorithm by Ning Liu, Shuangcheng Zhang, Xiaoli Wu, Yu Shen

“…When solving the float solution of ambiguity based on the double-difference model epoch by epoch, the common method for resolving the integer ambiguity needs to solve the coordinate parameter information, due to the influence of limited GNSS phase data observations. …”
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Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Met... by Amir Moslemi, Laurentius Oscar Osapoetra, Archya Dasgupta, Schontal Halstead, David Alberico, Maureen Trudeau, Sonal Gandhi, Andrea Eisen, Frances Wright, Nicole Look-Hong, Belinda Curpen, Michael Kolios, Gregory J. Czarnota

“…Additionally, we conducted a comparison of feature selection methods including mRMR, Relief, Rref QR decomposition, nonnegative matrix factorization and perturbation theory feature selection techniques. …”
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Multi-dimensional water quality indicators forecasting from IoT sensors: A tensor decomposition and multi-head self-attention mechanism. by Li Bo, Lv Junrui, Luo Xuegang

“…To overcome these limitations, we propose TGMHA (Tensor Decomposition and Gated Neural Network with Multi-Head Self-Attention), a novel hybrid model that integrates three key innovations: 1) Tensor-based Feature Extraction: We combine Standard Delay Embedding Transformation (SDET) with Tucker tensor decomposition to reconstruct raw time series into low-rank tensor representations, capturing latent spatio-temporal patterns while suppressing sensor noise. 2) Multi-Head Self-Attention for Inter-Indicator Dependencies: A multi-head self-attention mechanism explicitly models complex inter-dependencies among diverse water quality indicators (e.g., pH, dissolved oxygen, conductivity) via parallel feature subspace learning. 3) Efficient Long-Term Dependency Modeling: An encoder-decoder architecture with gated recurrent units (GRUs), optimized by adaptive rank selection, ensures efficient modeling of long-term dependencies without compromising computational performance. …”
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What explains differences in average wait time in the emergency department among different racial and ethnic populations: A linear decomposition approach by Hao Wang, Nethra Sambamoorthi, Richard D. Robinson, Heidi Knowles, Jessica J. Kirby, Amy F. Ho, Trevor Takami, Usha Sambamoorthi

“…We investigate factors contributing to longer wait times for NHB and Hispanic patients using a linear decomposition approach. Methods This retrospective observational study included patients presenting to one tertiary hospital ED from 2019 to 2021. …”
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A multivariate non-linear decomposition analysis of urban-rural disparities in overweight/obesity among men aged 20–49 in Ghana by Prince Tsekpetse, Samuel Salu, Joshua Shiuma, Brenda Nambozo, Brian Tonny Makoko, Bright Opoku Ahinkorah

“…A multivariate nonlinear decomposition model assessed the contributions of sociodemographic characteristics to urban–rural disparities in overweight/obesity. …”
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Temporal Evolution of the Hydrodynamics of a Swimming Eel Robot Using Sparse Identification: SINDy-DMD by Mostafa Sayahkarajy, Hartmut Witte

“…In this study, we employ machine learning strategies to investigate the temporal evolution of the system and discover a data-driven model. Three methods were studied, including dynamic mode decomposition (DMD), sparse system identification (SINDy using PySINDy package), and autoencoder neural network (AE NN), as a general function approximator. …”
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In vivo estimation of motor unit intrinsic properties in individuals with spinal cord injury by Zhihao Duan, Asta Kizyte, Emelie Butler Forslund, Elena M. Gutierrez-Farewik, Pawel Herman, Ruoli Wang

“…This study proposed an integrated approach using high-density electromyography (HD-EMG) decomposition and motor neuron (MN) modelling to estimate the intrinsic properties of MUs in vivo and investigated alterations of these properties in persons with SCI. …”
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Decomposition and comparative analysis of urban-rural disparity in attitude towards advance care planning among Chinese adults: A nationwide study by Xue Wang, Yibo Wu, Lina Ge, Meizhen Zhao, Yi Ma, Shuang Zang

“…Methods Data were derived from Psychology and Behavior Investigation of Chinese Residents (PBICR) including 19,738 participants, representative of Chinese adults. …”
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A Three-Level Meta-Frontier Framework with Machine Learning Projections for Carbon Emission Efficiency Analysis: Heterogeneity Decomposition and Policy Implications by Xiaoxia Zhu, Tongyue Feng, Yuhe Shen, Ning Zhang, Xu Guo

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Sustainable Renewable Biofuel Production Toward Pyrolysis of Fibers Biowaste Agave Americana L. and Thermodynamics Mechanisms Kinetic Parameters Triplet Assessment by Imen Lalaymia, Ahmed Belaadi, Hassan Alshahrani, Djamel Ghernaout, Herbert Mukalazi

“…Non-isothermal thermogravimetric analysis (TGA) was conducted at heating rates of 30, 40, and 50 °C/min. Kinetic modeling using the Coats – Redfern method evaluated 36 solid-state reaction models to determine the activation energy-Ea and pre-exponential factor (lnA). …”
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Analysis of the Impact of Global Oil Prices On GDP (on the Example of the Azerbaijan Republic) by N. S. Ayyubova

“…In particular, the method of vector error correction model VECM is used. …”
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Numerical Investigation of Tar Formation Mechanisms in Biomass Pyrolysis by Shuiting Ding, Yifei Wu, Xiaojun Yang, Zongwei Zhang

“…This study achieves the particle-resolved modeling of biomass pyrolysis via a novel approach of integrating the Discrete Element Method (DEM) with a semi-detailed chemical kinetic mechanism. …”
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Improved and Optimized GNSS-IR Sea Surface Height Retrieval Based on Noise Elimination and Lightweight Airborne Multi-GNSS Multi-UAV Fusion by Naiquan Zheng, Ying Xu, Fuxi Zhao, Mingzhen Xin, Fanlin Yang

“…The inversion accuracy of the improved model is better, which confirms the effectiveness of the improved GNSS-IR model based on intelligent extraction, decomposition and reconstruction of δSNR data. …”
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Gearbox Status Recognition based on TMD-SVD and POS-BP Networks Under Strong Interference by Lei He, Suqi Liu

“…On the basis of existing methods， a method based on two-layer-mode decomposition （TMD） and singular value decomposition （SVD） is proposed， combined with particle swarm （POS）-BP neural network for fault diagnosis. …”
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A State Estimation of Dynamic Parameters of Electric Drive Articulated Vehicles Based on the Forgetting Factor of Unscented Kalman Filter with Singular Value Decomposition by Tianlong Lei, Mingming Hou, Liaoyuan Li, Haohua Cao

“…In this paper, a state estimation method of distributed electric drive articulated vehicle dynamics parameters based on the forgetting factor unscented Kalman filter with singular value decomposition (SVD-UKF) is proposed. …”
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Impact of Phase Angle Jump on a Doubly Fed Induction Generator under Low-Voltage Ride-Through Based on Transfer Function Decomposition by Peiru Feng, Jiayin Xu, Zhuang Wang, Shenghu Li, Yuming Shen, Xu Gui

“…Firstly, the differential-algebraic equations of the DFIG are linearized to propose their transfer function model. Secondly, considering its high-order characteristic, a model reduction method for the transfer function of the DFIG using the Schur decomposition is proposed, and the analytical expression of the output variables of the DFIG with the phase angle jump is derived by the inverse Laplace transformation to judge the necessity of the LVRT measures. …”
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Predictive machine health monitoring using deep convolution neural network for noisy vibration signal of rotating machine using empirical mode decomposition by R. Pavithra, Prakash Ramachandran

“…An ablation study shows that the proposed method is highly susceptible to impulse noise as well. …”
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