Concept of Integrating a Hybrid Thermal Error Compensation Into an Existing Machine Tool Control Architecture by Alexander Geist, Muhammad Faisal Yaqoob, Christian Friedrich, Christian Naumann, Steffen Ihlenfeldt

“…Thermal error compensation via a numeric control (NC) system is a proven option for upgrading the precision of machine tools. …”
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Enterprise power emission reduction technology based on the LSTM–SVM model by Li Kun, Su Meng, Liu Qiang, Zhang Bin

“…The machine learning-based power data warning method proposed in this study has important practical application value and can effectively help enterprises achieve emission reduction and cost control goals.…”
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Dimensionality Reduction Optimization of High Subsonic Unmanned Aerial Vehicles Intake by Zeqi QI, Zheng GUO, Suqi CHEN, Ke YU

“…The results show that after dimensionality reduction through sensitivity analysis and PCA, the average error and coefficient of determination of the surrogate model were improved. …”
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Accelerating Energy Forecasting with Data Dimensionality Reduction in a Residential Environment by Rafael Gonçalves, Diogo Magalhães, Rafael Teixeira, Mário Antunes, Diogo Gomes, Rui L. Aguiar

“…Our results demonstrate that by selecting the optimal dimensionality reduction method and model architecture, it is possible to decrease the mean squared error (MSE) by up to 63% and accelerate training by up to 80%.…”
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Method for limiting the peak factor using an additional compensation signal in a system with orthogonal frequency division multiplexing for a Gaussian channel by Th. T. Pham, O. V. Tikhonova

“…The effect of the OFDM signal limitation level and the number of additional signals when using the limitation method with an additional compensation signal on the quality (reduction of transmission losses) of the OFDM signal is analyzed. …”
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Energy Efficient and High Speed Error Control Scheme for Real Time Wireless Sensor Networks by Ali Barati, Ali Movaghar, Masoud Sabaei

“…The theoretical results backed by simulation tests confirm that the solution put forward in this paper outperforms popular error control methods for WSNs in terms of error controllability, energy efficiency, and reduction of end-to-end delay.…”
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Analytical Reduction of Nonlinear Metabolic Networks Accounting for Dynamics in Enzymatic Reactions by Claudia López Zazueta, Olivier Bernard, Jean-Luc Gouzé

“…A simple example illustrates our approach and the resulting accuracy of the reduction method.…”
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Dimensionality Reduction using Hybrid Algorithms and Their Application to Remote Sensing Data by Maha Hasso, Mona Siddiq

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Fully-Gated Denoising Auto-Encoder for Artifact Reduction in ECG Signals by Ahmed Shaheen, Liang Ye, Chrishni Karunaratne, Tapio Seppänen

“…None of the present denoising methods preserve the morphology of ECG signals adequately for all noise types, especially at high noise levels. …”
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Insights into geometric deviations of medical 3d-printing: a phantom study utilizing error propagation analysis by Lukas Juergensen, Robert Rischen, Julian Hasselmann, Max Toennemann, Arne Pollmanns, Georg Gosheger, Martin Schulze

“…Methods The partial errors were analyzed employing surface deviation analyses. …”
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Study of the Noise Reduction of DF9S1600 Gearbox Reverse Gear by Li Haiqing

“…And according to the test,the effects of reverse gear noise is analyzed respectively from the speed,load and gear manufacturing errors,the structure is improved to achieve the purpose of the reverse gear damping noise reduction.…”
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Uncertainty evaluation of surface profile measurement error based on adaptive sparse grid polynomial chaos expansion by Ke Zhang, Xinya Zheng, Ruiyu Zhang

“…Numerical and experimental validations based on the car door outer surface demonstrate that compared to the ISO standard method, this method achieves a mean prediction error of less than 0.3% and a standard deviation relative error of less than 0.5% with a reduction of 99.6% in the number of sample calculation points. …”
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Correcting errors in PCR-derived libraries for rare allele detection by reconstructing parental and daughter strand information by Hyeonseob Lim, Soyeong Jun, Taehoon Kim, Ji Hyun Lee, Duhee Bang

“…Here, we present a sensitive genotyping method based on a peer-to-peer network-derived identifier for error reduction in amplicon sequencing (SPIDER-seq) and enable molecular identity tracking with PCR-derived libraries using overwritten barcodes. …”
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Optimizing Concrete Mix Design for Cost and Carbon Reduction Using Machine Learning by Angga T. Yudhistira, Arief S. B. Nugroho, Iman Satyarno, Tantri N. Handayani, Malindu Sandanayake, Rimba Erlangga, Jonathan Lianto, Alfa Rosyid Ernanto

“…The research findings indicate that the ML model provides satisfactory prediction values with an R2 value of 0.9043, root mean square error of 48.5147 and mean absolute percentage error of 0.0484. …”
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An Enhanced Error-Adaptive Extended-State Kalman Filter Model Predictive Controller for Supercritical Power Plants by Gang Chen, Shan Hua, Changhao Fan, Chun Wang, Shuchong Wang, Li Sun

“…This study introduces an Enhanced Error-Adaptive Extended-State Kalman Filter Model Predictive Control (EEA-ESKF-MPC) method to tackle strong coupling and inertia in supercritical power plants. …”
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A Polar-Coded PAPR Reduction Scheme Based On Hybrid Index Modulation by Si-Yu Zhang, Xinwei Yue, Behnam Shahrrava, Yuexia Zhang, Gongpu Wang

“…Therefore, the need for transmitting side information, which is a necessary process in probabilistic PAPR reduction schemes, can be eliminated. Further, to enhance detection accuracy, a construction method for frozen bit sets based on Hadamard matrix is proposed. …”
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Multi-stage deep learning artifact reduction for parallel-beam computed tomography by Jiayang Shi, Daniël M. Pelt, K. Joost Batenburg

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Analyzing the impact of curved tracks on wheel flange thickness reduction in railway systems by Namayanja Zainah, Nkundineza Celestin, Zewdie Behailu Mamo

“…The results of wear indices obtained using SIMPACK and VAMPIR closely matched with a small percentage error difference of 1.94%. The matching of these results validated the effectiveness of the methods used in this research to calculate wear. …”
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A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici... by Xinfu Pang, Wen Jia, Haibo Li, Qingzhong Gao, Wei Liu

“…Then, the Monte Carlo method was employed to simulate electric vehicle loads and to facilitate the generation of and reduction in scenario scenes. …”
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Improving Voice Spoofing Detection Through Extensive Analysis of Multicepstral Feature Reduction by Leonardo Mendes de Souza, Rodrigo Capobianco Guido, Rodrigo Colnago Contreras, Monique Simplicio Viana, Marcelo Adriano dos Santos Bongarti

“…Our comparative analysis demonstrates significant performance gains when dimensionality reduction methods are applied, underscoring their value in enhancing the security and effectiveness of voice biometric verification systems against emerging spoofing threats.…”
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