MODELS AND METHODS FOR SYNTHESIS OF MANUFACTURING PROCESS STRUCTURE FOR MACHINING AT FLOW LINE OF STATIONARY MACHINES by N. N. Guschinsky, O. Battaia, A. Dolgui

“…A problem of design of a flow line composed of stationary machines is considered. Mathematical models and methods for synthesis of manufacturing process structure are proposed. …”
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Full-waveform Small-footprint LiDAR Multi-target Echo Waveform Lightweight Detection by Spatio-temporal Coupling Models by Zhen XIAO, Yanfeng GU, Yanze JIANG, Xian LI

“…When integrated with four waveform decomposition methods, it improves processing efficiency by 2–3 times. …”
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Range–Null Space Decomposition With Frequency-Oriented Mamba for Spectral Superresolution by Meimei Weng, Jianjun Liu, Jinlong Yang, Zebin Wu, Liang Xiao

“…Spectral superresolution (SSR) is a technique aimed at reconstructing hyperspectral images (HSIs) from images with low spectral resolution. Previous methods combining mathematical models with deep learning have shown promising performance for HSI reconstruction. …”
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Spectral Quadratic Variation Regularized Autoweighted Tensor Ring Decomposition for Hyperspectral Image Reconstruction by Xinwei Wan, Dan Li, Fanqiang Kong, Yanyan Lv, Qiang Wang

“…The effectiveness of model-based reconstruction methods can be promoted. …”
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Unsteady Flow Field Analysis of a Compressor Cascade Based on Dynamic Mode Decomposition by Xiaoxiong Wu, Yuming Du

“…This study applies the Dynamic Mode Decomposition (DMD) method to perform reduced-order modeling of unsteady flow fields over an airfoil and a compressor cascade. …”
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On Holt Winters Algorithm with Decomposition for Forecasting Financial Time Series with Complex Seasonal Patterns by منى نزيه على عبد البارى

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Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…We first propose a novel block-successive convex approximation algorithm based on a regularized model-fitting objective where the normal flows are modeled as low-rank tensors and anomalies as sparse. …”
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Model Parameter Estimation Method on Multichannel Structural Response from Turbulence Flutter Test by Shiqiang Duan, Hua Zheng, Ziwei Zhang, Jianzhu Wang, Guanyu Fang

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Transformer Failure Rate Model Based on DDgPCE Method and Oil Chromatography Datadd by CHEN Li juan, WU Jian jun, WANG Gang, DAI Zi kuo, LIU Zhen dong, TAN Yu hua, ZHOU Yul ong

“…Thirdly, considering the health status and service life of transformer, the distribution model of transformer failure rate is established by data-driven generalized polynomial chaos method. …”
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Evaluating the Impact of Frequency Decomposition Techniques on LSTM-Based Household Energy Consumption Forecasting by Maissa Taktak, Faouzi Derbel

“…This study presents a novel methodological method that systematically decomposes energy consumption signals into low-frequency components representing gradual trends and daily routines and high-frequency components capturing transient events, such as appliance switching, before applying predictive modeling. …”
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Overlapping social structures behind Brazil's cesarean section births: A decomposition analysis. by Surbhi Shrivastava, Heeju Sohn

“…We applied the Karlson-Holm-Breen (KHB) decomposition method to multivariate logistic regression models. …”
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Kinetic Analysis of Cement–Asbestos Materials’ Thermal Decomposition Process by an Ex Situ Technique by Robert Kusiorowski, Anna Gerle, Magdalena Kujawa

“…At the same time, scientists are looking for alternatives to this type of “disposal” of asbestos by developing methods for degrading the harmful fibers. Particular attention has been paid to methods based on the thermal treatment of this waste, which results in hazardous asbestos fibers being thermally decomposed. …”
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Gender, work, and satisfaction: a decomposition approach to job satisfaction gaps in Egypt and Tunisia by Mesbah Fathy Sharaf, Abdelhalem Mahmoud Shahen

“…To explain gender gaps in job satisfaction, we apply the Blinder–Oaxaca decomposition method, both with and without correcting for sample selection bias.ResultsOur results show that conclusions about the existence and direction of the gender gap depend critically on accounting for selection effects. …”
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Spatial and Temporal Evolution of Regional Energy Efficiency in China and Its Influencing Factors by Jinqiu Li, Yufeng Hu, Hui Zhang

“…To scientifically study the evolution trend in regional energy efficiency in China, this study uses convergence analysis, a spatial Gini coefficient decomposition model (no spatial consideration), and a spatial Markov chain model and spatial measurement model (spatial consideration). …”
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Facial recognition targeted attack algorithm based on multiscale frequency decomposition and meta-learning by CAI Jun, HUANG Tianqiang, ZHENG Aokun, YE Feng, XU Chao

“…To address this issue, a facial recognition targeted attack algorithm based on multiscale frequency decomposition and meta-learning was proposed. This algorithm initially devised a multiscale frequency decomposition module that meticulously partitioned the target facial image into frequency bands comprising distinct components. …”
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Multi-Scale Graph Attention Network Based on Encoding Decomposition for Electricity Consumption Prediction by Sheng Huang, Huakun Que, Lukun Zeng, Jingxu Yang, Kaihong Zheng

“…Traditional forecasting methods typically focus on sequential features of the data, which may lead to an over-smoothing issue for the fluctuations. …”
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Asynchronous time integration while achieving zero interface energy by Radim Dvořák, Radek Kolman, Jan Falta, Michaela Neühauserová

“…The numerical model is partitioned into individual subdomains using the domain decomposition method by means of localized Lagrange multipliers. …”
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Analyzing the dihedral scattering component of P-band SAR signals for trunk permittivity estimation – a concept study by Anke Fluhrer, Hamed Alemohammad, Thomas Jagdhuber

“…A new retrieval method, based on a hybrid decomposition technique and the extended (x-) Fresnel model, is proposed for estimating trunk permittivity from polarimetric P-band SAR observations. …”
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Fuzzy Solutions of Fuzzy Fractional Parabolic Integro Differential Equations by Deepak Pachpatte, Nagwa Saeed

“…This work primarily investigates the numerical solution of fuzzy fractional parabolic integro-differential equations of the Volterra type with the time derivative defined in the Caputo sense using the fuzzy Adomian decomposition method. Fuzzy fractional partial integro-differential equations pose significant mathematical challenges due to the interplay between fuzziness and fractional-order dynamics, while at the same time, there is a growing need for accurate and efficient methods to model real-world phenomena involving uncertainty in physics, biology, and engineering. …”
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Development of improved deep learning models for multi-step ahead forecasting of daily river water temperature by Mehdi Gheisari, Jana Shafi, Saeed Kosari, Samaneh Amanabadi, Saeid Mehdizadeh, Christian Fernandez Campusano, Hemn Barzan Abdalla

“…This study addresses the limited use of signal decomposition in hybrid WT prediction models by proposing three methods: namely ensemble empirical mode decomposition (EEMD) on AdaBoost, long short-term memory (LSTM), and gated recurrent unit (GRU). …”
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