Accurate Conversion of Land Surface Reflectance for Drone-Based Multispectral Remote Sensing Images Using a Solar Radiation Component Separation Approach by Huasheng Sun, Lei Guo, Yuan Zhang

“…., lake water, slab stone, shrub, green grass, red grass, and dry grass), green grass has the highest error among the five multispectral bands with a mean absolute error (MAE) of 1.59%. …”
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Spatiotemporal wind speed forecasting using conditional local convolution and multidimensional meteorology features by Meng Wang, Juanle Wang, Mingming Yu, Fei Yang

“…Our model consistently achieves lower Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) values across various prediction intervals (3, 6, 9, and 12 h) compared to other models, supported by the meteorological station data from 2019 to 2021. …”
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Robust object counting through distribution uncertainty matching and optimal transport by Sabri Boughorbel, Fethi Jarray, Rachida Zegour, Nauman Ullah Gilal, Khaled Al Thelaya, Marco Agus, Jens Schneider

“…We provide a theoretical analysis and show that the generalization error bound of the proposed loss is tight. We extensively evaluate our model on benchmark datasets from three real-world applications: pathology cell counting, crowd counting and Vehicle Images Datasets. …”
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An Optimization Method for Indoor Pseudolites Anchor Layout Based on MG-MOPSO by Xiaohu Liang, Shuguo Pan, Shitong Du, Baoguo Yu, Shuang Li

“…Additionally, significant reductions are observed in average positioning error, maximum positioning error, and standard deviation across multiple test points. …”
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JEDAN: Joint Euclidean Distance and Autoencoder Network for Robust Out-of-Distribution Detection in Radar-Based Hand Gesture Recognition by Muhammad Ghufran Janjua, Kevin Kaiser, Thomas Stadelmayer, Stephan Schoenfeldt, Vadim Issakov

“…Traditional autoencoders often fall short in OOD detection because they prioritize minimizing reconstruction error over forming distinct clusters in the latent space. …”
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Hydrological performance of gridded meteorological products in Peruvian Altiplano basins by Efrain Lujano, Renny Daniel Diaz, Rene Lujano, Miguel Sanchez-Delgado, Apolinario Lujano

“…ABSTRACT Gridded meteorological datasets represent a valuable alternative for hydrometeorological applications, especially in areas with limited ground observations. …”
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Multi-Scale Spatiotemporal Feature Enhancement and Recursive Motion Compensation for Satellite Video Geographic Registration by Yu Geng, Jingguo Lv, Shuwei Huang, Boyu Wang

“…., which is a necessary preprocessing step for satellite video applications. In this paper, a multi-scale spatiotemporal feature enhancement and recursive motion compensation method for satellite video geographic alignment is proposed. …”
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Assessing artificial intelligence ability in predicting hospitalization duration for pleural empyema patients managed with uniportal video-assisted thoracoscopic surgery: a retrosp... by Issa Alnajjar, Baraa Alshakarnah, Tasneem AbuShaikha, Tareq Jarrar, Abed Al-Raheem Ozrail, Yousef Abu Asbeh

“…The first one had a mean absolute error of 4.56 days and a negative R2 value. The literature-informed model performed similarly, with a mean absolute error of 4.53 days and an R2 below zero. …”
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Artificial intelligence-based optimization and modeling of cadmium reduction via ultraviolet-assisted malathion/sulfite reaction mechanisms by Hossein Azarpira, Parsa Khakzad, Tayebeh Rasolevandi, Amir Sheikhmohammadi

“…In contrast, the SVR model showed better generalization to the test data, with lower error metrics and a consistent R2 of around 0.81 across both datasets. …”
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Automated tacholess rotational speed estimation on asynchronous motors for improved vibration analysis by Sietze Bruinsma, Rinze Geertsma, Richard Loendersloot, Tiedo Tinga

“…The proposed method determines the rotational speed with a root mean square error of 0.10 Hz or a specified maximum error of 0.0165 Hz for 90.1% of cases in the recent NLN-EMP dataset. …”
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Online Core Temperature Estimation for Lithium-Ion Batteries via an Aging-Integrated ECM-1D Coupled Model-Based Algorithm by Yiqi Jia, Lorenzo Brancato, Marco Giglio, Francesco Cadini

“…Validation under extreme conditions (high-rate cycling, aging, and ISCs) demonstrates 60% lower core temperature RMSE during high-rate cycling, a maximum estimation error below 0.9 K, and 58.9% reduction in SOC estimation error under aging conditions versus existing methods. …”
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Reading Dye-Based Colorimetric Inks: Achieving Color Consistency Using Color QR Codes by Ismael Benito-Altamirano, Laura Engel, Ferran Crugeira, Miriam Marchena, Jürgen Wöllenstein, Joan Daniel Prades, Cristian Fàbrega

“…This indicator was formulated for Modified Atmosphere Packaging (MAP) applications. To verify the method, the sensors were exposed to several environmental conditions (both in gas composition and light conditions). …”
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Development of Hybrid Exemplar based DLSRGAN model for Restoration of the Distorted Signals by Tammineni Shanmukha Prasanthi, Swaraiya Madhuri Rayavarapu, Gottapu Sasibhushana Rao, Rajkumar Goswami

“…Initial results indicate significant improvements in signal clarity and detail recovery, outperforming conventional methods in metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Mean Squared Error (MSE). This hybrid approach not only restores signals more effectively but also preserves essential features, making it a valuable tool for applications in telecommunications and audio processing. …”
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Acoustic Emission-Based Method for IFSS Characterization in Single-Fiber Fragmentation Tests by Felipe Romero, Franco Méndez, Javiera González, Víctor Tuninetti, Carlos Medina, Meylí Valin, José Valin, Alexis Salas, Cristián Vicuña

“…Results indicate that this approach achieves an IFSS determination error of 14.16% at a 95% confidence level. This study demonstrates the feasibility of using AE for IFSS characterization in SFFT and contributes to future research on AE applications in composite materials.…”
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Probabilistic distribution model of grain boundary α phase length in titanium alloys by Huizhi Peng, Wan Ye, Jianwen Liu, Shun Wu, Yichi Zhang, Yichi Zhang, Yuman Zhu, Alberto Boretti, Aijun Huang

“…Additionally, based on limited characterization inputs, the probabilities of GB-α having specific lengths are predicted by our model within an error margin of 4 %. Furthermore, this model is extended to the size of crept-induced voids in Inconel 718 superalloy, demonstrating its potential applicability to microstructure features governed by similar physical process.…”
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Enhancing LEO direct-to-satellite channel modeling with the shadowing effect via K-distribution by Tomás B. Núñez-González, Cesar A. Azurdia-Meza, Raydel Ortigueira, Samuel Montejo-Sánchez, Javier A. Ordenes-Pinto, Melissa E. Diago-Mosquera, Sandra Céspedes

“…This enhancement captures the combined effects of multipath fading and shadowing, providing a more accurate representation of the channel conditions experienced in DtS-IoT applications. Simulation results show that the enhanced model aligns closely with analytical bit error rate (BER) predictions, particularly at higher signal-to-noise ratios (SNRs), with less than 1% deviation from theoretical values. …”
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Leveraging advanced deep learning and machine learning approaches for snow depth prediction using remote sensing and ground data by Haytam Elyoussfi, Abdelghani Boudhar, Salwa Belaqziz, Mostafa Bousbaa, Karima Nifa, Bouchra Bargam, Abdelghani Chehbouni

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An Asymptotic Model for Solving Mixed Integral Equation in Position and Time by A. R. Jan

“…Also the error estimate, in each case, is computed.…”
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Weld seam location with adaptive fracture repair on minor-caliber pipe by Yong Yan, Jingyu Zhang, Lingjiang Guo, Heming Zhao, Fan Zhang

“…Positioning experiment of pipeline welds validates the algorithm effectiveness by a maximum positional error of 3.6 pixels and an average error of 0.98 pixel. …”
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Advanced State-of-Health Estimation for Lithium-Ion Batteries Using Multi-Feature Fusion and KAN-LSTM Hybrid Model by Zhao Zhang, Runrun Zhang, Xin Liu, Chaolong Zhang, Gengzhi Sun, Yujie Zhou, Zhong Yang, Xuming Liu, Shi Chen, Xinyu Dong, Pengyu Jiang, Zhexuan Sun

“…Notably, temperature variations were primarily caused by seasonal changes, enabling the experiments to more realistically simulate the battery’s performance in real-world applications. By enhancing dynamic modeling capabilities and capturing long-term temporal associations, experimental results demonstrate that the method achieves highly accurate SOH estimation under various charging conditions, with low mean absolute error (MAE) and root mean square error (RMSE) values and a coefficient of determination (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>) exceeding 97%, significantly improving prediction accuracy and efficiency.…”
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