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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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“…These outdated updates hinder the convergence of the global model during aggregation.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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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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Multiscale Image Representation and Texture Extraction Using Hierarchical Variational Decomposition by Liming Tang, Chuanjiang He

“…In order to achieve a mutiscale representation and texture extraction for textured image, a hierarchical (BV,Gp,L2) decomposition model is proposed in this paper. We firstly introduce the proposed model which is obtained by replacing the fixed scale parameter of the original (BV,Gp,L2) decomposition with a varying sequence. …”
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Modeling of changes in particle size distribution of solids in multistage separation systems by Lagereva E.A.

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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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POLAND AND UKRAINE IN THE LIGHT OF PARADYSZ'S PERIOD FERTILITY MODEL by J. Paradysz, K. Paradysz

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Strengthening of Deficient Steel Sections using CFRP Composite under Combined Loading by Amir Hamzeh Keykha

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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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Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…<p>This paper presents a brand-new hybrid solar photovoltaic (PV) power forecasting model called empirical mode decomposition (EMD)-particle swarm optimisation (PSO)-adaptive neuro-fuzzy inference system (ANFIS). …”
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An analysis of the decomposition and driving force of carbon emissions in transport sector in China by Jing Gu, Shuhua Jiang, Jing Zhang, Jinde Jiang

“…It first calculates the China’s transport carbon emissions by IPCC carbon emission factor method, and then applies the Logarithmic Mean Divisia Index (LMDI) model for decomposition analysis. …”
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Combined wideband speech enhancement method based on statistical model and EMD by Xuan ZHOU, Chang-chun BAO, Bing-yin XIA

“…A combined wideband speech enhancement method based on statistical model and empirical mode decomposition (EMD) was proposed.First,statistical model was used to eliminate the main noise component in noisy speech.Then,the residual noise was further suppressed by a post-processing module which is a speech enhancement algorithm with voice activity detection (VAD) based on EMD.The advantages of the two methods were combined effectively.The performance of the proposed method was evaluated under the standard of ITU-T G160.The experimental results indicate that the algorithm is more effective for improving the SNR in the different noise environments than classical statistical model approach.Meanwhile,in low SNR conditions,musical noise is reduced effectively,and the speech sounds more comfortable.…”
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Transformer network for time series prediction via wavelet packet decomposition by Zhichao Wu, Aiye Shi, Yan Ping Tao

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Synergistic and Antagonistic Effects of Mixed-Leaf Litter Decomposition on Nutrient Cycling by Vestine Mukamparirwa, Salim M. S. Maliondo, Canisius Patrick Mugunga

“…Specifically, we expected mixtures containing nutrient-rich species to exhibit synergistic effects, resulting in faster decay rates and sustained nutrient release, while mixtures with nutrient-poor species would demonstrate antagonistic effects, slowing decomposition. We conducted a mesocosm experiment using a custom wooden setup filled with soil, and the litterbag method was used to test various leaf litter mixtures. …”
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Compressive SAR Imaging Based on Modified Low-Rank and Sparse Decomposition by Jeong-Il Byeon, Wookyung Lee, Jihoon Choi

“…In this paper, we propose a novel imaging method for synthetic aperture radar (SAR) systems with compressive sensing (CS) by modifying the existing low-rank and sparse decomposition (LRSD) scheme. …”
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Overhead Transmission Line Modeling Strategies for EMT-Based Traveling-Wave Analysis and Fault Location by Adrian Wilmer Diaz Sarmiento, Jaimis Sajid Leon Colqui, Jose Pissolato Filho

“…The results show that: 1) uniform soil resistivity assumptions introduce negligible errors in TW arrival times despite minor amplitude variations; 2) shield wires significantly affect modal structure, compromising the effectiveness of Clarke transformation for ground quasi-mode decoupling while preserving aerial quasi-mode reliability; 3) exact eigenvector-based decomposition improves ground mode identification but remains impractical for field applications; 4) the classical two-terminal fault location method maintains high accuracy across all modeling configurations; and 5) simplified OHTL modeling uniformly distributed sections at both terminals achieves an optimal balance between accuracy and computational efficiency for simulating TWs. …”
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3D Multi-Domain MFS Analysis of Sound Pressure Level Reduction Between Connected Enclosures by Luıs GODINHO, Fernando G. BRANCO, Paulo AMADO MENDES

“…It is important to note that, for such a configuration, a tra- ditional single-domain approach using methods like the MFS or the BEM would lead to undetermined equation systems, and thus the proposed model makes use of a domain decomposition technique.…”
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Logarithmic Mean Divisia Index Analysis and Dynamic Back Propagation Neural Network Prediction of Transport Carbon Emissions in Henan Province by Changjiang Mao, Jian Luo, Shengyang Jiao, Bin Zhao

“…This study applied the LMDI decomposition method and a BP neural network model to thoroughly analyse the factors influencing carbon emissions in Henan Province’s transportation sector and forecast future trends. …”
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Effect of compositions and hardness on wheel-rail contact analysis and wear behavior of wheel materials using finite element method: a case study of Addis Ababa light rail transit by Leul Fenta Demisie, Matiwos Getachew Wedajeneh, Aychew Asratie Ejigu

“…A three-dimensional finite element analysis model of a wheel-rail system was created, and stress at a contact patch is calculated by applying a load. …”
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Managing Soil Biota-Mediated Decomposition and Nutrient Mineralization in Sustainable Agroecosystems by Joann K. Whalen

“…Next, it explores experimental approaches to measure the physical, chemical, and biological barriers to decomposition and nutrient mineralization. Methods are proposed to determine the rates of decomposition and nutrient release from organic residues. …”
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