Enhanced bearing health indicator extraction using slope adaptive signal decomposition for predictive maintenance by Dev Bhanushali, Pooja Kamat, Harsh Dhiman

“…This study introduces the Slope Adaptive Signal Decomposition (SASD) algorithm, a novel method for extracting enhanced intrinsic machine health indicators from vibration data. …”
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A survey of model compression techniques: past, present, and future by Defu Liu, Yixiao Zhu, Zhe Liu, Yi Liu, Changlin Han, Jinkai Tian, Ruihao Li, Wei Yi

“…To meet the urgent demand for efficient deployment, we delve into several compression methods—such as quantization, pruning, low-rank decomposition, and knowledge distillation—emphasizing their fundamental principles, recent advancements, and innovative strategies. …”
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A decomposition of Fisher’s information to inform sample size for developing or updating fair and precise clinical prediction models for individual risk—part 1: binary outcomes by Richard D. Riley, Gary S. Collins, Rebecca Whittle, Lucinda Archer, Kym I. E. Snell, Paula Dhiman, Laura Kirton, Amardeep Legha, Xiaoxuan Liu, Alastair K. Denniston, Frank E. Harrell, Laure Wynants, Glen P. Martin, Joie Ensor

“…However, more guidance is needed for targeting precise and fair individual-level risk estimates. Methods We propose a decomposition of Fisher’s information matrix to help examine sample sizes required for developing or updating a model, aiming for precise and fair individual-level risk estimates. …”
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Analysis of Flow-induced Vibration Characteristics of Fuel Rods Using POD and DMD Methods by MIN Guangyun1, JIANG Naibin1, 2

“…Leveraging the snapshot matrix derived from the extensive database, a high-fidelity reduced-order model (ROM) was developed. Two data-driven methodologies, namely proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) methods, were employed to construct the ROM. …”
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Homotopy Analysis Transform Method for Solving Systems of Fractional-Order Partial Differential Equations by Fang Wang, Qing Fang, Yanyan Hu

“…Additionally, when the convergence parameter <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>ℏ</mo><mo>=</mo><mo>−</mo><mn>1</mn></mrow></semantics></math></inline-formula>, both the homotopy perturbation method and the Adomian decomposition method emerge as special cases of the proposed method. …”
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Finite-Time Cluster Synchronization of Fractional-Order Complex-Valued Neural Networks Based on Memristor with Optimized Control Parameters by Qi Chang, Rui Wang, Yongqing Yang

“…Finally, a numerical example and a comparative experiment are both provided to verify the theoretical results and optimization method.…”
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Multisource Heterogeneous Data Fusion Methods Driven by Digital Twin on Basis of Prophet Algorithm by Min Li

“…However, the current data fusion methods still have problems, such as low accuracy of fused data, insufficient data integrity, poor data fusion efficiency, and poor scalability of fusion methods. …”
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Numerical Methods for Fractional-Order Fornberg-Whitham Equations in the Sense of Atangana-Baleanu Derivative by Naveed Iqbal, Humaira Yasmin, Akbar Ali, Abdul Bariq, M. Mossa Al-Sawalha, Wael W. Mohammed

“…The results demonstrated that the future method is easy to implement, highly methodical, and very effective in analyzing the behavior of complicated fractional-order linear and nonlinear differential equations existing in the related areas of applied science.…”
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Life Prediction Method of Remanufactured Machinery Equipment Based on Vibration Signal Feature Extraction by Bin Li, Le Kui, Jingdong Luo, Shiyong Chen

“…Using amplitude spectrum analysis, Hilbert envelope demodulation and wavelet packet decomposition method, and other vibration signal processing methods, preliminary extraction of multiple statistical feature parameters are given. …”
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Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System by Minghong She, Pengju Zhao

“…For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. …”
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FedSVD: Asynchronous Federated Learning With Stale Weight Vector Decomposition by Giwon Sur, Hyejin Kim, Seunghyun Yoon, Hyuk Lim

“…These outdated updates hinder the convergence of the global model during aggregation. To address this staleness problem, we propose FedSVD, a method that leverages vector decomposition of stale weights. …”
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A New Prediction Model of Dam Deformation and Successful Application by Shuangping Li, Bin Zhang, Meng Yang, Senlin Li, Zuqiang Liu

“…In view of the poor accuracy of the monitoring data, which reflect the overall deformation response in the current dam monitoring practices, this paper proposes an innovative solution of ensemble empirical mode decomposition and a wavelet noise reduction method. A high-precision prediction model considering spatial correlation is constructed. …”
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Computer-Visualized Sound Parameter Analysis Method and Its Application in Vocal Music Teaching by Zhenming Yu

“…In addition, based on the short-term periodicity and short-term stationarity of speech signals, an analytical synthesis model based on harmonic decomposition is proposed. …”
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POLAND AND UKRAINE IN THE LIGHT OF PARADYSZ'S PERIOD FERTILITY MODEL by J. Paradysz, K. Paradysz

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Cross-Attention U-Net for Elastic Wavefield Decomposition in Anisotropic Media by Youngjae Shin

“…Elastic wavefield separation in anisotropic media is essential for seismic imaging but remains challenging due to complex interactions among multiple wave modes. Traditional methods often rely on solving the Christoffel equation, which is computationally expensive, particularly in heterogeneous models. …”
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PCCNN: A CNN classification model integrating EEG time-frequency features for stroke classification by Teng Wang, Fenglian Li, Jia Yang, Wenhui Jia, Fengyun Hu

“…This paper proposes a stroke classification method using multi-channel electroencephalography (EEG) data. …”
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Application effect of short-term traffic flow prediction method based on CNNBLSTM algorithm. by Guozhu Sui, Meixia Song, Ke Bian, Mingzhen Zhang, Xiaogang Zhang, Yiru Wang

“…The method firstly identifies, repairs and decomposes the abnormal traffic flow data by smoothing the estimation threshold and adaptive noise integration empirical modal decomposition method to improve the data quality and stability. …”
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Progressive Domain Decomposition for Efficient Training of Physics-Informed Neural Network by Dawei Luo, Soo-Ho Jo, Taejin Kim

“…This study proposes a strategy for decomposing the computational domain to solve differential equations using physics-informed neural networks (PINNs) and progressively saving the trained model in each subdomain. The proposed progressive domain decomposition (PDD) method segments the domain based on the dynamics of residual loss, thereby indicating the complexity of different sections within the entire domain. …”
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Surrounding Object Material Detection and Identification Method for Robots Based on Ultrasonic Echo Signals by Bo Zhu, Tao Geng, Gedong Jiang, Zheng Guan, Yang Li, Xialun Yun

“…This method primarily adopts the 16-dimensional feature vector extracted from intrinsic mode functions that we gain from empirical mode decomposition as inputs of machine learning algorithms to recognize different materials, and we use K-nearest neighbor, decision tree, and support vector machine algorithms on the feature vector set to decide the best classifier, and its acoustic theoretical model is established additionally. …”
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Monthly Runoff Prediction Based on STL-CEEMDAN-LSTM Model by WANG Hai, SHEN Yanqing, QI Shansheng, PAN Hongzhong, HUO Jianzhen, WANG Zhance

“…According to the nonlinear and non-stationary characteristics of monthly runoff sequences, the quadratic decomposition method was combined with machine learning to construct a model for predicting monthly runoff. …”
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