On the use of kolmogorov–arnold networks for adapting wind numerical weather forecasts with explainability and interpretability: application to madeira international airport by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…Using the Kolmogorov-Arnold Network model led to a substantial reduction in wind speed and direction forecast errors, with a performance that reached a 48.5% improvement to the Global Forecast System 3 h nowcast, considering the mean squared error. …”
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A building operational carbon emissions database of 362 Chinese cities: Construction process and spatiotemporal characteristic analysis by Qi Wang, Xinyu Jia, Yang Zhao, Hao Zhou, Xinghui Zhang, Borong Lin, Cong Zhang

“…The existing calculation methods of city building carbon emissions based on energy audits, city statistics and energy balance sheets have problems such as time-consuming and labour-intensive, missing data and large errors, resulting in the lack of a complete and accurate database of city building carbon emissions in China. …”
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On the Optimum Linear Soft Fusion of Classifiers by Luis Vergara, Addisson Salazar

“…This allows us to predict the reduction in the post-fusion error probability relative to that of the best classifier. …”
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Abnormal sound detection method for coal mine belt conveyors based on convolutional autoencoder by SHEN Long, SHAN Haoran, PEI Wenliang, YANG Guixiang, WANG Yongli

“…Next, the normal operation audio features and the reconstructed normal operation audio features were input into the Mean Squared Error Loss function (MSELoss) to obtain the reconstruction error, with the maximum reconstruction error set as the reconstruction threshold for normal operation audio features. …”
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Evaluation of the PP6D5 Polymer as a Novel Non-Viral Vector in the Development of a CRISPR/nCas9-Based Gene Therapy for Tay–Sachs Disease by Jacky M. Guerrero-Vargas, Diego A. Suarez-Garcia, Andrés F. Leal, Ivonne L. Diaz-Ariza, León D. Pérez-Pérez, Angela J. Espejo-Mojica, Carlos J. Alméciga-Díaz

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Examining the impact of probiotic Lactiplantibacillus pentosus 6MMI on inhibiting biofilm formation, adhesion, and virulence gene expression in Listeria monocytogenes ATCC 19115 by Behrooz Alizadeh Behbahani, Mostafa Rahmati-Joneidabad, Morteza Taki

“…The residual errors showed a normal distribution, indicating reliable and consistent predictions. …”
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Gas Flow Characteristics through Irregular Particle Bed with the Vertical Confined Wall for Waste Heat Recovery by Sizong Zhang, Zhi Wen, Xunliang Liu, Yi Xing, Hui Zhang

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Low-overhead quantum computing with the color code by Felix Thomsen, Markus S. Kesselring, Stephen D. Bartlett, Benjamin J. Brown

“…Fault-tolerant quantum computation demands significant resources: large numbers of physical qubits must be checked for errors repeatedly to protect quantum data as logic gates are implemented in the presence of noise. …”
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Simulation of Drag Reducer Polymer (DRP) for Single and Annular Two Phase Flow in Horizontal Pipe by Cindy Dianita, Asep Handaya Saputra, Puteri Amelia Khairunissa

“…The final single phase flow equation model as the output of this study gives a value for onset drag reduction i.e 4.00 with an error up to 18%. While the proposed annular flow equation with and without drag reduction effect is only suitable when the condition of fluid film distribution is uniform and symmetrical with the error around 20%, i.e. for smaller diameter pipes. …”
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Illuminating the impact of economic policy uncertainty, renewable energy, and economic growth on environmental sustainability by Mohammed Albassam, Muhammad Aslam, Azhar Ali Janjua

“…The study also estimates the Driscoll–Kraay standard errors, panel corrected standard errors (PCSE), and feasible generalized least squares (FGLS), and uses the Dumitrescu–Hurlin panel Granger causality test. …”
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Increasing the Efficiency of Blind Decoding of the Steganographic Method with Code Control of Additional Information Embedding by Sokolov A.V., Ihnatenko O.O., Balandina N.M.

“…The most significant result of the paper is a reduction in the number of decoding errors of the steganographic method with code control of the additional information embedding and blind decoding by 12.01% compared to the result known in the literature through a reasonable choice of codewords used to embed the additional information.…”
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Robust Parameter Inversion and Subsidence Prediction for Probabilistic Integral Methods in Mining Areas by Xinjian Fang, Rui Yang, Mingfei Zhu, Jinling Duan, Shenshen Chi

“…A critical challenge in subsidence prediction lies in the sensitivity of existing probabilistic integral parameter inversion methods to gross errors, leading to unstable predictions and compromised reliability. …”
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Usulan Perbaikan Sistem Kerja pada Proses Produksi Crumb Rubber Menggunakan Metode SHERPA di PT. Riau Crumb Rubber Factory by Ismu Kusumanto

“…Metode yang digunakan adalah Systematic Human Error Reduction and Prediction Approach (SHERPA) Berdasarkan hasil identifikasi tersebut selanjutnya ditelusuri penyebab terjadinya kesalahan untuk ditentukan pendekatan guna mengurangi kejadian kesalahan kerja operator. …”
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A clinical prediction model for blood pressure changes after renal denervation in patients with resistant hypertension by Yishuan Zhang, Ruiqing He, Chen Chen, Hong Zhang, Lingyan Li, Rongxue Xiao, Shuangyu Chen, Shuyi Wu, Zongjun Liu, Junqing Gao

“…In the prediction model on SBP change, compared to the OLS model, the Ridge regression exhibited lower prediction errors [mean absolute error [MAE]: 6.40 vs. 6.95; mean squared error [MSE]: 65.58 vs. 76.15] and a higher R² (0.79 vs. 0.72). …”
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Robust Monocular Visual-Inertial Odometry for Agricultural Vehicles Based on IMU-Augmented 3D Feature Point Correction by Quoc Duy Tran, Quoc Hung Hoang, Gon-Woo Kim

“…The effectiveness of the method is validated through real-time experiments across various scenarios, with the proposed system achieving approximately an 80% reduction in translation error and about a 60% reduction in rotation error compared to state-of-the-art methods. …”
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To What Extent Does Discounting ‘Hot’ Climate Models Improve the Predictive Skill of Climate Model Ensembles? by Abigail McDonnell, Adam Michael Bauer, Cristian Proistosescu

“…On regional scales, we find a heterogeneous pattern of error reduction in future regional precipitation. …”
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Modeling the arousal potential of epistemic emotions using Bayesian information gain: a framework for inquiry cycles driven by free energy fluctuations by Hideyoshi Yanagisawa, Shimon Honda

“…Conventional Gaussian models predict an infinite divergence in information gain (KLD and BS) as prediction error increases, which contradicts the known limits of human cognitive resources. …”
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Two-Stage Stochastic Scheduling of Virtual Power Plant Based on Transactive Control by Meng Song, Xiaoyuan Xu, Ciwei Gao, Zheng Yan, Mohammad Shahidehpour

“…Specifically, a two-stage VPP scheduling framework based on multi-time scale coordinated control of TCLs is proposed to address forecast errors of variable RES power output. In the first stage (hour time scale), TCLs are controlled as virtual generators to mitigate forecast errors between hour-ahead and day-ahead RES power. …”
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OPTIMASI PEMBACAAN SUHU KAMERA TERMAL MENGGUNAKAN REGRESI LINIER by Sevia Indah Purnama, Irmayatul Hikmah, Mas Aly Afandi, Elsa Sri Mulyani

“…The reduction in reading error also occurred by 5.27% at 37 ° C and 6.44% at 38 ° C. …”
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Improved Neutral Density Predictions Through Machine Learning Enabled Exospheric Temperature Model by Richard J. Licata, Piyush M. Mehta, Daniel R. Weimer, W. Kent Tobiska

“…The newly developed EXTEMPLAR‐ML model allows for exospheric temperature predictions at any location with one model and provides performance improvements over its predecessor. We achieve reductions in mean absolute error of 2 K on an independent test set while providing similar error standard deviation values. …”
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