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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Spatial interpolation of cropland soil bulk density by increasing soil samples with filled missing values by Aiwen Li, Jinli Cheng, Dan Chen, Wendan Li, Yaruo Mao, Xinyi Chen, Bin Zhao, Wenjiao Shi, Tianxiang Yue, Qiquan Li

“…The RBFNN model, tailored for each sub-watershed, yielded the highest accuracy in filling missing BD, with an increase in coefficient of determination (R 2) by 19.54–37.36% and reductions in mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) by 8.91–14.81%, 9.02–16.22% and 7.71–13.61%, respectively. …”
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Prediction of Aluminum Alloy Surface Roughness Through Nanosecond Pulse Laser Assisted by Continuous Laser Paint Removal by Jingyi Li, Rongfan Liang, Han Li, Junjie Liu, Jingdong Sun

“…The SSA-BPNN model demonstrates high prediction accuracy, with a correlation coefficient (R²) of 0.98628, root mean square error (RMSE) of 0.024, mean absolute error (MAE) of 0.020 and mean absolute percentage error (MAPE) of 1.30% on the test set. …”
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…Key metrics, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Percentage Error (MAPE), were employed to evaluate model performance. …”
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Prediction of mechanical characteristics of shearer intelligent cables under bending conditions. by Lijuan Zhao, Dongyang Wang, Guocong Lin, Shuo Tian, Hongqiang Zhang, Yadong Wang

“…The results show that, compared to other predictive models, the proposed model achieves reductions in Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) to 0.0002, 0.0159, and 0.0126, respectively, with the coefficient of determination (R2) increasing to 0.981. …”
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Are Junior Residents Accurate at Predicting Fetal Weight? An Analysis of Junior Residents' Performance of Estimated Fetal Weight Using Ultrasound and Leopold's Maneuver by Kimberly Huynh, Alicia Lunardhi, Karren Lewis, Trevor Pickering, Hindi E. Stohl

“…Maternal body mass index and actual BW were associated with absolute percentage estimation error. After adjusting for these variables, there was a statistically significant decrease in error between PGY1 and PGY2 for Leopold's method in term births; ultrasound (term and preterm) showed more modest reductions in error during PGY2. …”
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Multi-scale attention-enhanced deep learning approach for detecting seven trunk pests and diseases in Shanghai’s urban plane trees by Tianyang Song, Guohua Hu, Tianci Yu, Xing Meng, Yanting Zhang, Ruiqing Yang, Benyao Wang, Xia Li

“…Traditional manual inspections are labor-intensive and error-prone. This study introduces an enhanced YOLOv8-based detection framework to address multi-scale variability in pest and disease datasets. …”
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DR Loss-Free Dithering-Based Digital Background Linearity Calibration for SAR-Assisted Multi-Stage ADCs With Digital Input-Interference Cancellation by Lizhen Zhang, Bo Gao, Kun-Woo Park, Kent Edrian Lozada, Raymond Mabilangan, Hyeongjin Kim, Jianhui Wu, Seung-Tak Ryu

“…By comparing the cases with and without the proposed IIC technique, a <inline-formula> <tex-math notation="LaTeX">$50\times $ </tex-math></inline-formula> reduction in convergence cycle could be achieved. The proposed calibration technique can be utilized to overcome the inherent DAC mismatch and residue gain errors to implement high-linearity ADCs, such as SAR-assisted ADCs in many different applications.…”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…Crucially, in-vivo application of the proposed method showed that the method generalizes well to in-vivo data, without introducing significant errors or artifacts. This generalization makes the presented method a promising candidate for use in clinical applications.…”
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Hole-Assisted Graded-Index Four-LP-Mode Fiber With Low Differential Mode Group Delay Over C+L Band by Jiajia Zhao, Borui Li, Ming Tang, Songnian Fu, Perry Ping Shum, Deming Liu

“…A tolerance analysis against manufacturing errors has been discussed, and we further propose a self-managed low DMGD transmission line solution with the controllable air-hole size.…”
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Replication of a GWAS signal near HLA-DQA2 with AML using a disease-only cohort and external population-based controls by Rose Laflamme, Véronique Lisi, Josée Hébert, Guy Sauvageau, Sébastien Lemieux, Vincent-Philippe Lavallée, Guillaume Lettre

“…Because genotypes were generated using different technologies in the 2 data sets (eg, low- vs high-coverage whole-genome sequencing), we applied stringent quality-control filters to minimize type 1 errors. We showed, using data reduction methods (eg, principal component analysis and uniform manifold approximation and projection), that our approach successfully integrated the Leucegene and CaG genetic data. …”
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Explosion characteristics and overpressure prediction of hydrogen-doped natural gas under ambient turbulence conditions by Ranran Li, Zhongmo Xu, Mingzhi Li, Shuhong Li, Zhenyi Liu, Zihao Xiu, Qiqi Liu

“…The proposed model achieves a root mean square error of 0.140 kPa under various wind speed conditions, demonstrating good predictive accuracy.…”
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Electric Vehicle charging station load forecasting with an integrated DeepBoost approach by Joveria Siddiqui, Ubaid Ahmed, Adil Amin, Talal Alharbi, Abdulelah Alharbi, Imran Aziz, Ahsan Raza Khan, Anzar Mahmood

“…For the dataset of Adaptive Charging Networks (ACN), the Mean Absolute Error (MAE) of DeepBoost improves by 9.4%, 32.7% and 88% as compared to CatBoost, XgBoost and LSTM networks, respectively.…”
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Unraveling overestimated exposure risks through hourly ozone retrievals from next-generation geostationary satellites by Siwei Li, Ge Song, Jia Xing, Jiaxin Dong, Maolin Zhang, Chunying Fan, Shiyao Meng, Jie Yang, Lechao Dong, Wei Gong

“…Here, we utilize a next-generation geostationary satellite with ultraviolet capabilities to retrieve hourly O3 concentrations, achieving high accuracy (R2 = 0.94) and improving daily maximum 8-hour estimates, particularly in semi-urban areas (R2 + 0.10, error reduction >7 μg/m³). Our analysis reveals a 30% drop in O3-related health risks compared to traditional polar-orbit estimates, with the greatest impact in semi-urban and rural areas where satellite data plays an important role due to the lack of ground measurements. …”
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Wavefront Detection and Event Segmentation Method for Partial Discharge Signal Analysis by Francisco de A. Oliveira Nascimento, Rodrigo De A. Coelho, George V. R. Xavier, Pedro D. Alvim, Almir C. Dos Santos Junior, Hugerles S. Silva

“…Experimental results showed substantial improvements in signal-to-noise ratio (SNR), high cross-correlation between the original and denoised signals, and a significant reduction in normalized mean squared error, confirming the robustness of the method under low-SNR conditions.…”
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FASQuiC: Flexible Architecture for Scalable Spin Qubit Control by Mathieu Toubeix, Eric Guthmuller, Adrian Evans, Antoine Faurie, Tristan Meunier

“…The hardware for a single channel is very compact, 2&#x0025; of ZCU111 logic resources for one DAC lane in the default configuration, leaving significant circuit resources for integrated feedback, calibration, and quantum error correction.…”
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Five Strategies for Efficient and Effective Training of Japanese Resident Physicians Under the Japanese Work Style Reform by Nishizawa T, Ishizuka K, Miyagami T, Kondo K, Takai S, Fukushima K, Katto D, Nishizaki Y, Shimizu T

“…However, studies indicate that excessive DH is associated with reduced sleep, worsened mental health, and increased risk of medical errors without significant improvement in clinical competence. …”
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MODELLING OF STRESS STATE OF DENTAL HARD TISSUES WHILE CARIOUS CAVITIES OF I CLASS RESTORATION by Yu.V. Lakhtin, Yu.V. Smeyanov, B.V. Nishta

“…It concerns technical errors during treatment, methods of forming carious cavities. …”
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CRIM-negative infantile Pompe disease, long-term observation of the effect of enzyme replacement therapy: a clinical case by D. R. Sabirova, D. I. Sadykova, A. A. Kucheryavaya, A. A. Kashina, L. A. Sabirova

“…Awareness of physicians about Pompe disease will prevent the growth in diagnostic errors and neglected cases. In case of early confirmation, the effectiveness of currently available ERT increases: the possibility to stop the disease progression, to reverse its individual clinical manifestations, and to improve the patient’s quality of life.…”
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Surrogate-based model parameter optimization in simulations of the West African monsoon by M. Fischer, P. Knippertz, C. Proppe

“…To further enhance the accuracy of climate simulations and potentially improve weather predictions, it is crucial to prioritize the refinement of the overall physical models, including the reduction in inherent structural errors, rather than solely adjusting the uncertain parameters in existing model parametrizations. …”
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