Exact differential transform method and semi-analytic Chebyshev collocation method for ordinary differential equations by A. S. Mohamed

“…Abstract This article introduces two algorithms designed for solving differential equations: the differential transform method and the second-kind Chebyshev collocation method. …”
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Monitoring of Transformer Hotspot Temperature Using Support Vector Regression Combined with Wireless Mesh Networks by Naming Zhang, Guozhi Zhao, Liangshuai Zou, Shuhong Wang, Shuya Ning

“…Traditional methods typically measure only the surface temperature of transformers, whereas this study proposes a non-invasive thermal inversion algorithm based on a wireless mesh network that effectively predicts the internal hotspot temperature. …”
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Robust Fractional Low Order Adaptive Linear Chirplet Transform and Its Application to Fault Analysis by Junbo Long, Changshou Deng, Haibin Wang, Youxue Zhou

“…Based on the insensitive property of fractional low-order statistics for infinite variance and Gaussian processes, robust fractional lower order adaptive linear chirplet transform (FLOACT) and fractional lower order adaptive scaling chirplet transform (FLOASCT) methods are proposed to suppress the mixed complex noise in this paper. …”
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Vehicle Pose Estimation Method Based on Maximum Correntropy Square Root Unscented Kalman Filter by Shuyu Liu, Ying Guo

“…To improve the performance of the Square Root Unscented Kalman Filter SLAM (SRUKF-SLAM), this paper proposes the Maximum Correntropy Square Root Unscented Kalman Filter SLAM (MCSRUKF-SLAM) algorithm. The method first generates an estimate of the predicted state and covariance matrix through the Unscented Transform (UT), and then obtains the square root matrix of the covariance through Cholesky and QR decomposition to replace the original covariance, effectively preserving the positive definiteness of the covariance and improving the accuracy of the algorithm. …”
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Terminal-based method for efficient inter-turn fault localization and severity assessment in transformer windings by K. Lakshmi Prasanna, Manoj Samal, Mithun Mondal

“…Our approach leverages a non-iterative subspace identification algorithm to estimate the pole-zero-gain model from the measured Driving Point Impedance (DPI) frequency response, Zf(s), of a faulty transformer. …”
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Coherent DOA estimation based on low-rank matrix recovery with coprime arrays in nonuniform noise by Youzhen Yang, Jianhui Wang, Zhenyu Wang

“…Abstract In this paper, a novel low-rank matrix recovery-based direction of arrival estimation algorithm is proposed for coherent signals with coprime arrays under nonuniform noise conditions. …”
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Maximum Penalized-Likelihood Structured Covariance Estimation for Imaging Extended Objects, with Application to Radio Astronomy by Aaron Lanterman

“…Maximum-likelihood estimates of the covariance cannot be readily computed analytically; hence, we investigate an iterative algorithm originally proposed by Snyder, O’Sullivan, and Miller in the context of radar imaging. …”
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Advanced Human Pose Estimation and Event Classification Using Context-Aware Features and XGBoost Classifier by Wasim Wahid, Aisha Ahmed AlArfaj, Ebtisam Abdullah Alabdulqader, Touseef Sadiq, Hameedur Rahman, Ahmad Jalal

“…The system begins with preprocessing steps, including converting videos into image sequences, applying sliding window techniques, and converting images to grayscale, then extracting human silhouettes using binary masks. We use the GrabCut algorithm for human detection and perform skeletonization with Hough transform algorithm. …”
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Enhancing adaptive beamforming by enhanced MUSIC algorithm for urban environments in O-RAN architecture by Mustafa Mayyahi, Jordi Mongay Batalla, Constandinos X. Mavromoustakis

“…By leveraging the accuracy of the multiple signal classification (MUSIC) algorithm combined with predictive linear regression (LR) and support vector regression (SVR) models, our approach significantly enhances the MUSIC algorithm and accelerates the generation of beam weights for the beamforming system. …”
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Construction of a sugar and acid content estimation model for Miliang-1 kiwifruit during storage by LIU Li, YANG Tianyi, DONG Congying, SHI Caiyun, SI Peng, WEI Zhifeng, GAO Dengtao

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Research status of channel estimation and signal detection techniques for orthogonal time frequency space modulation by WANG Yongchuan, ZHOU Ping, HUANG Ju

“…In order to obtain the time-frequency full diversity gain, a receiver with advanced channel estimation and signal detection algorithm is needed. …”
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A multi-modality ground-to-air cross-view pose estimation dataset for field robots by Xia Yuan, Kaiyang Wang, Riyu Qin, Jiachen Xu

“…The dataset uniquely integrates field environments and high-resolution LiDAR-aerial-ground data triplets, enabling rigorous evaluation of 3-DoF pose estimation algorithms for orientation alignment and coordinate transformation between perspectives.This resource supports development of robust localization systems for field robots in GNSS-denied conditions, emphasizing cross-view feature matching and multisensor fusion. …”
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Security state estimation based on signal reconstruction for multi‐vehicle systems under malicious attack by Jing Wang, Siyuan Wang, Shan Lu, Meng Zhou

“…First the reconstruction of attack signal is transformed into a sparse error correction problem by stacking the measurement information of adjacent vehicles, and is solved by orthogonal matching pursuit (OMP) algorithm. …”
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Method for estimating non-measurable parameters of gas turbine engines considering variations in technical condition by Sergiy Yepifanov, Oleksii Bondarenko

“…The practical value of the method lies in its applicability to both direct control algorithms based on non-measurable parameters, and onboard estimation and diagnostic algorithms that operate effectively with limited measurement data and under constrained computational resources.…”
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CNN-GRU Battery SOC Estimation Method Fused with Attention Mechanism for Electric Multiple Units by WANG Shenghui, TIAN Qin, LIU Lihao, FENG Enlai, YU Tianjian

“…Then, an attention mechanism-integrated gated recurrent unit (GRU) is adopted to capture long spatial distance dependencies of the extracted feature data, resulting in more precise battery SOC estimation. To precisely estimate the SOC of small-sample battery cycling data, this paper transforms the continuous regression model into a classification problem, discretizes the battery SOC ranges, and converts the final prediction result into discrete SOC values. …”
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High-fidelity pose estimation for real-time extended reality (XR) visualization for cardiac catheterization by Mohsen Annabestani, Sandhya Sriram, Alexandre Caprio, Sepehr Janghorbani, S. Chiu Wong, Alexandros Sigaras, Bobak Mosadegh

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The Time Difference of Arrival Estimation Method Utilizing an Inexact Reconstruction Within the Framework of Compressed Sensing by Shanhe Wang, Yu Xiang, Yuanyuan Gao, Yu Hua, Changjiang Huang, Xian Zhao

“…This paper introduces an incomplete reconstruction-based TDOA estimation method along with an improved variant. By selecting a partial Fourier transform matrix as the measurement matrix and a Fourier transform matrix as the projection matrix, the orthogonal matching pursuit (OMP) algorithm is employed to reconstruct the compressed measurement data. …”
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SpecTE: Parameter Estimation for LAMOST Low-resolution Stellar Spectra Based on Denoising Pretraining by Xirong Zhao, Xiangru Li, Hui Li, Xianqi Liu

“…The computed catalog demonstrates good consistency with APOGEE and GALAH. The estimated stellar catalog, code, pretrained model, and experimental data are released online for astronomical exploration and algorithm research.…”
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Efficient Gamma-Based Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement by Huitao Zhao, Shaoping Xu, Liang Peng, Hanyang Hu, Shunliang Jiang

“…To address this challenge, inspired by the state-of-the-art Zero-DCE approach, we introduce a novel method that transforms the low-light image enhancement task into a curve estimation task tailored to each individual image, utilizing a lightweight shallow neural network. …”
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A case study on entropy-aware block-based linear transforms for lossless image compression by Borut Žalik, David Podgorelec, Ivana Kolingerová, Damjan Strnad, Štefan Kohek

“…Abstract Data compression algorithms tend to reduce information entropy, which is crucial, especially in the case of images, as they are data intensive. …”
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