SFMattingNet: A Trimap-Free Deep Image Matting Approach for Smoke and Fire Scenes by Shihui Ma, Zhaoyang Xu, Hongping Yan

“…Compared to the suboptimal approach, MODNet, our SFMattingNet method achieved an average error reduction of 12.65% in the smoke and fire matting task.…”
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A fast and fully automated system for segmenting retinal blood vessels in fundus images by Alqassab Ans Ibrahim Mahameed, Luque-Nieto Miguel-Ángel

“…Manual segmentation is time-consuming and prone to human error, leading to inconsistent results. Additionally, existing automated methods often struggle with low-quality images or variations in illumination, hindering their effectiveness. …”
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Tripability Analysis of Casing Strings in Directional Wells Using the Continuous Beam-Column and Buckling Theory by Gang Wang, Gang Liu, Kai Wang, Yichen Li, Yinan Hu

“…Through finite element method verification, the prediction was in line with the actual casing running operation and the improved model has the smallest prediction error, i.e., 6.58%, compared with the existing models. …”
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Assessing the Efficiency of Reduced Positional Games in Soccer: A Multivariate Analysis of Technical and Tactical Indicators According to Different Playing Systems by Mostafa Errama, Mustapha Bassiri, Jafaar Atifi, Said Lotfi

“…It seeks to determine how RPG optimize key indicators such as possession, passing, shooting, goals scored and error reduction, while exploring their influence on tactical synchronization and team cohesion. …”
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A Piezoelectric Micromachined Ultrasonic Transducer-Based Bone Conduction Microphone System for Enhancing Speech Recognition Accuracy by Chongbin Liu, Xiangyang Wang, Jianbiao Xiao, Jun Zhou, Guoqiang Wu

“…Compared with the original noisy speech, the enhanced speech achieves a character error rate reduction of over 20%, approaching the speech recognition accuracy of clean speech. …”
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An adaptive sliding mode fault-tolerant control of variable speed reaching law for steer-by-wire systems by Jinwen Yang, Yinquan Yu, Dequan Zeng, Yiming Hu, Junhui Liu, Kai Liu, Giuseppe Carbone, Shaohua Luo, Xiaofeng Zhu

“…The example information demonstrates that the proposed method reduces the root mean square (RMS) of tracking error by nearly 40% in three typical conditions compared to adaptive fault-tolerant control methods (ASMFTC), and the disturbances of the controller are relatively slighter. …”
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Improving WRF-Chem PM2.5 predictions by combining data assimilation and deep-learning-based bias correction by Xingxing Ma, Hongnian Liu, Zhen Peng

“…Throughout the initial 24-h period, compared with the control experiment, the results of WRF-Chem_DA_BC (WRF-Chem_DA, WRF-Chem_BC) showed an improvement in terms of root-mean-square error, with reduction proportions varying from 38.90 % to 48.86 % (18.88 % to 32.44 %, 30.10 % to 46.08 %). …”
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Reconstruction of Electrochemical Impedance Spectroscopy from Time-Domain Pulses of a 3.7 kWh Lithium-Ion Battery Module by Manuel Kasper, Manuel Moertelmaier, Hartmut Popp, Ferry Kienberger, Nawfal Al-Zubaidi R-Smith

“…In the proposed approach, the DRT directly utilizes measured current data instead of simulated current patterns, thereby enhancing robustness against current variations and data anomalies. The method is demonstrated with a simulation, a single cylindrical battery cell experiment, and an experimental EIS of a completely assembled module of 448 cells. …”
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Variable Structure Depth Controller for Energy Savings in an Underwater Device: Proof of Stability by João Bravo Pinto, João Falcão Carneiro, Fernando Gomes de Almeida, Nuno A. Cruz

“…In contrast to the conventional approach used in controller stability proofs for switched systems—which typically relies on the existence of multiple Lyapunov functions—the method developed in this paper adopts a different strategy. …”
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Temperature rise of high-speed bearing in gearbox of 5 MW wind turbine based on Bayesian-LightGBM and improved PSO-SVM troubleshooting by Minan Tang, Zhanglong Tao, Jiandong Qiu, Jinping Li, Mingyu Wang, Hongjie Wang, Chuntao Rao

“…In this paper, a combined modelling wind turbine gearbox high-speed bearing temperature rise prediction method based on Bayesian-LightGBM and improved PSO-SVM is proposed with a 5 MW wind turbine as the research object. …”
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Learning on Bandwidth Constrained Multi-Source Data With MIMO-Inspired DPP MAP Inference by Xiwen Chen, Huayu Li, Rahul Amin, Abolfazl Razi

“…Extensive experiments verify the superiority of our scalable method over the most commonly used data selection methods, including GreeDi, Greedymax, random selection, and stratified sampling by a substantial gain of at least 12% reduction in Relative Diversity Error (RDE). …”
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An enhanced deep learning approach for speaker diarization using TitaNet, MarbelNet and time delay network by Muzamil Ahmed, Riad Alharbey, Ali Daud, Hikmat Ullah Khan, Javeria Nawal, Ghazia Arshad

“…We evaluate the proposed approach on two standard datasets of VoxConverse and VoxCeleb, comparing clustering-based methods with the proposed Neuro-TM Diarizer using three metrics: Diarization Error Rate (DER), false alarm rate, and missed detection rate. …”
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A Pedaling Torque Observation Approach for Sensorless Electric Bicycles by Riccardo Mandriota, Niklas Konig, Emanuele Grasso, Matthias Nienhaus

“…Also, an online low-computational effort road slope estimation method based on Kalman filtering, that accounts for cornering effect errors, is proposed. …”
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Time-series characterization of various honey types under different storage conditions based on total polyphenol content and fluorescence properties by Takumi Murai, Teruki Tobari, Sota Kudo, Yoshito Saito

“…These findings demonstrate the potential of fluorescence spectroscopy as a non-destructive method for evaluating honey quality changes during storage, particularly under high-temperature conditions.…”
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Machine Learning Models Informed by Connected Mixture Components for Short- and Medium-Term Time Series Forecasting by Andrey K. Gorshenin, Anton L. Vilyaev

“…For geophysical spatiotemporal data, the decrease in Root Mean Square Error (RMSE) was up to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>27.7</mn><mo>%</mo></mrow></semantics></math></inline-formula>, and the reduction in Mean Absolute Percentage Error (MAPE) was up to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>45.7</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared with ML models without probability informing. …”
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Spatio-temporal graph neural networks for power prediction in offshore wind farms using SCADA data by S. Daenens, S. Daenens, S. Daenens, T. Verstraeten, T. Verstraeten, T. Verstraeten, P.-J. Daems, P.-J. Daems, A. Nowé, J. Helsen, J. Helsen, J. Helsen

“…The results show that both the spatial and the spatio-temporal GNN models outperform traditional data-driven power curve methods, achieving reductions in the mean absolute error (MAE) of approximately 22.6 % and 30.3 %, respectively, and in the mean absolute percentage error (MAPE) of around 20.7 % and 30.5 %, respectively. …”
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Parental acceptance of novel children's medical syringes and their influencing factors by Su Wen Luo, Peng Rui Yang

“…Technology anxiety and time and error reduction emerge as key factors influencing perceived risks.ConclusionsThis study offers product designers crucial insights into purchasing factors for children's medical products, aims to enhance product development and iteration efficiency, and promotes more accurate innovation, decision-making, and communication. …”
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Fuzzy decision support system for english language teaching with corpus data by Meilin Huang

“…This system focuses on identifying and providing solutions for lexical placement errors. Focusing on the progression of English teaching with high-quality outputs, lexical arrangement, and error reduction is pursued. …”
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Development of an upper limb muscle strength rehabilitation assessment system using particle swarm optimisation by Chuangan Zhou, Siqi Wang, Meiyi Wu, Wei Lai, Junyu Yao, Xingyue Gou, Hui Ye, Jun Yi, Dong Cao

“…Model performance was evaluated using R-squared (R2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Bias Error (MBE).ResultsThe system successfully collected electromyographic and kinematic data. …”
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Power Assessment and Performance Comparison of Wind Turbines Driven by Multivariate Environmental Factors by Bubin Wang, Bin Zhou, Denghao Zhu, Mingheng Zou, Zhao Rao, Haoxuan Luo, Weihao Ji

“…Samples are segmented based on rated wind speed to reflect differences in control strategies, and turbine-specific operational parameters are excluded to ensure unbiased comparisons among turbines. The proposed method achieves substantial improvements in predictive accuracy, with decreases of 9.39% in mean absolute error (MAE) and 11.75% in root mean square error (RMSE), compared to conventional binning approaches. …”
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