Design of an Iterative Method for Time Series Forecasting Using Temporal Attention and Hybrid Deep Learning Architectures by Yuvaraja Boddu, A. Manimaran

“…This method improves the focus on relevant information and achieves a 10% average reduction in mean absolute error (MAE) compared to models devoid of such mechanisms. …”
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Modelagem estatística da precipitação mensal e anual e no período seco para o estado de Minas Gerais Statistical modeling of monthly, annual and dry season mean precipitation for t... by Carlos R. de Mello, Antônio M. da Silva

“…Coefficient of determination adjusted (r²), mean absolute error (%), prediction bias (%) and estimated parameters significance were considered for evaluation of models. …”
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Evaluation of Depth Anything Models for Satellite-Derived Bathymetry by E. Günaydın, İ. Yakar, T. Bakırman, M. O. Selbesoğlu

“…The predicted depth maps were also scaled to obtain Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The RMSE and MAE values for Depth Anything V1 are 0.4135 m and 0.34 m, respectively, while the RMSE and MAE values for V2 are 0.2681 m and 0.2089 m, respectively. …”
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Concurrent Validity of a Custom Method for Markerless 3D Full-Body Motion Tracking of Children and Young Adults Based on a Single RGB-D Camera by Nikolas Hesse, Sandra Baumgartner, Anja Gut, Hubertus J. A. van Hedel

“…Our method achieved a mean per joint position error over all joints of 11.7 mm compared to the Vicon system, and 98.4% of the estimated joint positions had an error of less than 50 mm. …”
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Improving Event Data in Football Matches: A Case Study Model for Synchronizing Passing Events with Positional Data by Alberto Cortez, Bruno Gonçalves, João Brito, Hugo Folgado

“…Spatial differences in OSD were also compared to the RSD data and to the original data from the provider. Root mean square error (<i>RMSE</i>) and mean absolute error (<i>MAE</i>) were utilized to assess the accuracy of both procedures. …”
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Exploring the Dynamics of Dietary Self-Monitoring Adherence Among Participants in a Digital Behavioral Weight Loss Program: Model Development Study by Hui Lin, Min Yang, Zhiheng Zhou, Yu Zhang, Ning Deng

“…Model performance was evaluated using mean square error, root mean square error (RMSE), and goodness of fit. …”
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Spatiotemporal inhomogeneity of accuracy degradation in AI weather forecast foundation models: A GNSS perspective by Junsheng Ding, Wu Chen, Junping Chen, Jungang Wang, Yize Zhang, Lei Bai, Yuyan Wang, Xiaolong Mi, Tong Liu, Duojie Weng

“…We calculated the mean deviation, mean absolute error, and root mean square error of these data. …”
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Prediction of the thermophysical properties of Ag-reduced graphene oxide-water/ethylene-glycol hybrid nanofluids using different machine learning methods by Huaguang Li, Ali B.M. Ali, Rasha Abed Hussein, Narinderjit Singh Sawaran Singh, Barno Abdullaeva, Zubair Ahmad, Soheil Salahshour, Mohammadreza Baghoolizadeh, Mostafa Pirmoradian

“…Such properties make them suitable candidates for many industrial applications such as solar systems and thermal management. …”
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Self-adaptive evolutionary neural networks for high-precision short-term electric load forecasting by Muhammad Abbas, Yanbo Che, Sarmad Maqsood, Muhammad Zain Yousaf, Mustafa Abdullah, Wajid Khan, Saqib Khalid, Mohit Bajaj, Mohammad Shabaz

“…Experimental results demonstrate that SADE-KAN reduces mean absolute percentage error (MAPE) by up to 35% and root mean squared error (RMSE) by 38% compared to MLP models, while requiring 35% fewer learnable parameters. …”
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Robust Initialization of Active Shape Models for Lung Segmentation in CT Scans: A Feature-Based Atlas Approach by Gurman Gill, Matthew Toews, Reinhard R. Beichel

“…The proposed initialization method can be generalized to other applications employing ASM-based segmentation.…”
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Analysis of 2D heat transfer of shear wall thermal bridges influencing on the exterior wall by Yan Zhou, Xiaoyu Jin, Yihui Wang, Difang Wei

“…In addition, the maximum error of replacing K2D with K1D discussed in this paper was 3.56%, which can be neglected in engineering applications in hot summer and cold winter climate zones. …”
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Detection and recognition of natural sounds by Kim ABOUCHACRA, Tomasz ŁĘTOWSKI, Jessica GOTHIE

“…Therefore, the design and selection of audio signals for specific applications should be based on the detectability and recognizability of the signals in the intended environments and on the meaningful connotations of the individual sounds. …”
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Spinner Innovation: Integrated Model for the Development and Prediction of Innovation by Figueiredo Ronnie

“…For numerous SMEs, innovation resembles a trial-and-error endeavor, often leading to feelings of anxiety and frustration, as resources are seemingly squandered. …”
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Resolver Decoding Method Using Hilbert Transform and ATO by Jiliang Yi, Xuechun Zhou, Huabing Tan, Zhongqi Li

“…The results show that the proposed method can control the decoding error within 0.5° when the SNR is 30 dB, which provides a high-precision and low-cost decoding scheme for practical applications.…”
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A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction by Jian Wang, Yi‐ran Liu, Ya‐fei Shi

“…Abstract In order to achieve more accurate spatial reconstruction of ionospheric total electron content (TEC) and promote improved satellite positioning and ranging applications, a high accuracy spatial reconstruction (HASR) method for TEC is proposed based on the surface theory. …”
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Research on Multi-crane Cooperative Micro-motion Control of Combined Gantry Cranes for Turnout Laying and Replacement of High-speed Railways Based on Self-learning by LYU Maoyin, NIU Xuexin, CHEN Qishen, ZHAN Taiping

“…The experimental results from field operations showcases adopting the control method proposed in this article, stable and reliable rotation and longitudinal movement by the combined gantry cranes, with an operational error of less than 10 mm, achieving full compliance with the requirements of engineering applications demonstrates.…”
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Wavelet Packet Transform based Speech Enhancement via Two-Dimensional SPP Estimator with Generalized Gamma Priors by Pengfei SUN, Jun QIN

“…Although various speech enhancement techniques have been developed for different applications, existing methods are limited in noisy environments with high ambient noise levels. …”
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CPrecNet: Enhanced Nowcast of High‐Resolution Short‐Term Precipitation Using Deep Learning by Jun Park, Changhoon Lee

“…These findings highlight the potential of deep learning based on physical considerations to enhance high‐resolution precipitation nowcasting for better decision‐making in weather‐sensitive applications.…”
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Transfer Reinforcement Learning-Based Power Control for Anti-Jamming in Underwater Acoustic Communication Networks by Liejun Yang, Yi Chen, Hui Wang

“…Underwater acoustic communication networks (UACNs) play a critical role in ocean environmental monitoring, maritime rescue, and military applications. However, they are highly susceptible to performance degradation due to narrow bandwidths, long propagation delays, and severe multipath effects, especially adversarial jamming attacks. …”
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Ozone trends in homogenized Umkehr, ozonesonde, and COH overpass records by I. Petropavlovskikh, I. Petropavlovskikh, J. D. Wild, J. D. Wild, K. Abromitis, K. Abromitis, P. Effertz, P. Effertz, K. Miyagawa, L. E. Flynn, E. Maillard Barras, R. Damadeo, G. McConville, G. McConville, B. Johnson, P. Cullis, S. Godin-Beekmann, G. Ancellet, R. Querel, R. Van Malderen, D. Zawada

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