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781
Enhancing Image Denoising Performance of Bidimensional Empirical Mode Decomposition by Improving the Edge Effect
Published 2015-01-01“…This approach includes two steps, in which the first one is an extrapolation operation through the regression model constructed by the support vector machine (SVM) method with high generalization ability, based on the information of the original signal, and the second is an expansion by the closed-end mirror expansion technique with respect to the extrema nearest to and beyond the edge of the data resulting from the first operation. …”
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782
A predictive model for body water and fluid balance using 3D smartphone anthropometry
Published 2025-06-01“…Then, LASSO regression was used to develop new TBW and ECF prediction model in a subset of participants (n = 272), which was subsequently tested in the remaining participants (n = 66). …”
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783
MODELS AND METHODS FOR SYNTHESIS OF MANUFACTURING PROCESS STRUCTURE FOR MACHINING AT FLOW LINE OF STATIONARY MACHINES
Published 2016-09-01“…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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784
Full-waveform Small-footprint LiDAR Multi-target Echo Waveform Lightweight Detection by Spatio-temporal Coupling Models
Published 2025-06-01“…When integrated with four waveform decomposition methods, it improves processing efficiency by 2–3 times. …”
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785
Evaluation of a body height and weight harmony among university students
Published 2022-12-01“…A body weight value was evaluated using BMI model too. Correlation between results of these two evaluations was determined using the Pearson interclass correlation coefficient. …”
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786
Range–Null Space Decomposition With Frequency-Oriented Mamba for Spectral Superresolution
Published 2025-01-01“…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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787
Spectral Quadratic Variation Regularized Autoweighted Tensor Ring Decomposition for Hyperspectral Image Reconstruction
Published 2024-01-01“…The effectiveness of model-based reconstruction methods can be promoted. …”
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788
Unsteady Flow Field Analysis of a Compressor Cascade Based on Dynamic Mode Decomposition
Published 2024-12-01“…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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789
Dynamic Analysis of a Tapered Composite Thin-Walled Rotating Shaft Embedded with SMA Wires Using the Generalized Differential Quadrature Method
Published 2020-01-01“…A dynamical model is developed for the tapered composite thin-walled rotating shaft with shape memory alloy (SMA) wires embedded in. …”
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790
Research and Experiment on an Adaptive Feedforward Compensation Composite Control Strategy for an Electro-Hydraulic Servo System
Published 2025-01-01“…The servo working principle of the adaptive composite control based on feedforward compensation was analyzed, and the error function between the theoretical model and the actual model of the motor for motor speed control in the feedforward compensation control process was proposed. …”
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791
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792
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793
Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling
Published 2025-01-01“…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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794
Model Parameter Estimation Method on Multichannel Structural Response from Turbulence Flutter Test
Published 2022-01-01Get full text
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795
Transformer Failure Rate Model Based on DDgPCE Method and Oil Chromatography Datadd
Published 2023-12-01“…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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796
Methods of evaluation the quality of teaching in higher education institutions
Published 2019-01-01“…The aim of the study is to develop a methodology for assessing the quality of training for different groups of experts.Materials and methods. The method of quality assessment and the results of the study, based on the proposed pyramid model of quality assessment with the details of the components, included in its composition, and the designation of their values for evaluation are considered in the paper. …”
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797
A Composite Barrier Function Sliding Mode Control Method Based on an Extended State Observer for the Path Tracking of Unmanned Articulated Vehicles
Published 2025-02-01“…In this paper, a composite barrier function sliding mode control method based on an extended state observer is proposed to solve the problem of modeling uncertainty and unknown external disturbance in the path tracking control of unmanned articulated vehicles. …”
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798
Asymmetric Double-Sideband Composite Signal and Dual-Carrier Cooperative Tracking-Based High-Precision Communication–Navigation Convergence Positioning Method
Published 2025-05-01“…Experimental validation employs the 5G New Radio (NR) Time-Delay Line (TDL) channel model to simulate multipath propagation effects. …”
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799
Multiscale finite element procedure to predict the effective elastic properties of woven composites
Published 2024-10-01“…This paper integrates numerical and experimental approaches to predict the mechanical properties of a woven composite with carbon fiber-based fabrics. Initially, a multiscale modeling approach based on the finite element method ascertained the micro-scale properties of the composite tows, taking into account the effect of voids present in the epoxy resin. …”
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800
Evaluating the Impact of Frequency Decomposition Techniques on LSTM-Based Household Energy Consumption Forecasting
Published 2025-05-01“…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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