Prediction of coalbed methane productivity based on neural network models by JIN Yi, ZHENG Chenhui, SONG Huibo, MA Jiaheng, YANG Yunhang, LIU Shunxi, ZHANG Kun, NI Xiaoming

“…The prediction accuracy is significantly higher than the BP model.ConclusionsThe model has good stability and high prediction accuracy. …”
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Prediction of Clavien Dindo Classification ≥ Grade III Complications After Epithelial Ovarian Cancer Surgery Using Machine Learning Methods by Aysun Alci, Fatih Ikiz, Necim Yalcin, Mustafa Gokkaya, Gulsum Ekin Sari, Isin Ureyen, Tayfun Toptas

“…We used 49 predictors to develop the best algorithm. Mean absolute error, root mean squared error, correlation coefficients, Mathew’s correlation coefficient, and F1 score were used to determine the best performing algorithm. …”
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Imputation and Missing Indicators for Handling Missing Longitudinal Data: Data Simulation Analysis Based on Electronic Health Record Data by Molly Ehrig, Garrett S Bullock, Xiaoyan Iris Leng, Nicholas M Pajewski, Jaime Lynn Speiser

“…We evaluated imputation quality using normalized root-mean-square error for continuous variables and percent falsely classified for categorical variables. …”
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Evaluating User Experience and Satisfaction in a Concussion Rehabilitation App: Usability Study by Michael G Hutchison, Alex P Di Battista, Kyla L Pyndiura

“…Future iterations of the app will aim to improve time efficiency and streamline error recovery processes to further enhance the user experience.…”
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Mathematical Modelling and Optimization Methods in Geomechanically Informed Blast Design: A Systematic Literature Review by Fabian Leon, Luis Rojas, Alvaro Peña, Paola Moraga, Pedro Robles, Blanca Gana, Jose García

“…Results: High-fidelity simulations delimit blast-induced damage with ≤0.2 m mean absolute error; extensions of the Kuznetsov–Ram equation cut median-size mean absolute percentage error (MAPE) from 27% to 15%; Gaussian-process and ensemble learners reach a coefficient of determination (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup><mo>></mo><mn>0.95</mn></mrow></semantics></math></inline-formula>) while providing closed-form uncertainty; Pareto optimisers lower peak particle velocity (PPV) by up to 48% without productivity loss. …”
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Modeling of trends in the development of demand for long-distance passenger transport, taking into account the peculiarities of its formation in the Russian Federation regions by E. A. Makarova, K. V. Surzhin, S. B. Elizarov, S. S. Morozov

“…The accuracy of prediction was made together with conclusions about the performance of the proposed models. …”
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Should We Reconsider RNNs for Time-Series Forecasting? by Vahid Naghashi, Mounir Boukadoum, Abdoulaye Banire Diallo

“…Our model also utilizes a feed-forward layer right after the GRU module to represent temporal dependencies, and aggregates it with the GRU layers to predict future values of a given time-series. (3) Results and conclusions: Our extensive experiments conducted on different real-world datasets show that our inverted GRU (iGRU) model achieves promising results in terms of error metrics and memory efficiency, challenging or surpassing state-of-the-art models on various benchmarks.…”
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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…For the homogeneous case, the computed seepage exit point (8.401 m) shows merely 3.7% relative error relative to experimental measurements, representing a significant accuracy improvement (&gt;45%) over literature-reported values. …”
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An experimental study and prediction of dynamic deformation of wind turbine blade based on DIC by Jing Jia, Liru Zhang, Wei Gao, Tong Qiu, YuQi Hou, Jianwen Wang

“…The accuracy of the blade dynamic fluctuation deformation prediction model is verified by experiments and error analysis, and the study’s conclusions provide a reference for the design and safe operation of wind turbines.…”
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Enhancing Intermittent Spare Part Demand Forecasting: A Novel Ensemble Approach with Focal Loss and SMOTE by Saskia Puspa Kenaka, Andi Cakravastia, Anas Ma’ruf, Rully Tri Cahyono

“…The approach was empirically validated by comparing the model’s Mean Squared Error (MSE) performance and Area Under the Curve (AUC). …”
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A Two-Step Approach to Uncertainty Quantification of Core Simulators by Artem Yankov, Benjamin Collins, Markus Klein, Matthew A. Jessee, Winfried Zwermann, Kiril Velkov, Andreas Pautz, Thomas Downar

“…For the multiple sources of error introduced into the standard computational regime for simulating reactor cores, rigorous uncertainty analysis methods are available primarily to quantify the effects of cross section uncertainties. …”
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HIV-phyloTSI: subtype-independent estimation of time since HIV-1 infection for cross-sectional measures of population incidence using deep sequence data by Tanya Golubchik, Lucie Abeler-Dörner, Matthew Hall, Chris Wymant, David Bonsall, George Macintyre-Cockett, Laura Thomson, Jared M. Baeten, Connie L. Celum, Ronald M. Galiwango, Barry Kosloff, Mohammed Limbada, Andrew Mujugira, Nelly R. Mugo, Astrid Gall, François Blanquart, Margreet Bakker, Daniela Bezemer, Swee Hoe Ong, Jan Albert, Norbert Bannert, Jacques Fellay, Barbara Gunsenheimer-Bartmeyer, Huldrych F. Günthard, Pia Kivelä, Roger D. Kouyos, Laurence Meyer, Kholoud Porter, Ard van Sighem, Mark van der Valk, Ben Berkhout, Paul Kellam, Marion Cornelissen, Peter Reiss, Helen Ayles, David N. Burns, Sarah Fidler, Mary Kate Grabowski, Richard Hayes, Joshua T. Herbeck, Joseph Kagaayi, Pontiano Kaleebu, Jairam R. Lingappa, Deogratius Ssemwanga, Susan H. Eshleman, Myron S. Cohen, Oliver Ratmann, Oliver Laeyendecker, Christophe Fraser, the HPTN 071 (PopART) Phylogenetics protocol team, the BEEHIVE consortium and the PANGEA consortium

“…HIV-phyloTSI provides a continuous measure of TSI up to 9 years, with a mean absolute error of less than 12 months overall and less than 5 months for infections with a TSI of up to a year. …”
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The Impact of Paragliding on Human Health - Literature Review by Maksymilian Wiśniowski, Klaudia Kulig, Kacper Buczek, Michal Popiel, Kamil Dziekoński, Ada Wiśniowska, Aneta Redner, Julia Głowacz, Dominik Stanibuła, Patrycja Zwierzchlewska, Kamila Smala

“…Epidemiological studies show regional variations in accident rates, with fatalities often linked to pilot error and weather conditions. Conclusions: While paragliding offers health benefits, its risks necessitate strict safety measures, training, and protective gear. …”
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Predicting communities with high tuberculosis case-finding efficiency to optimise resource allocation in Pakistan: comparing the performance of a negative binomial spatial lag mode... by Hasan Tahir, Frank Cobelens, Christina Mergenthaler, Mirjam I Bakker, Tanveer Ahmed, Jake D Mathewson, Daniella Brals, Abdullah Latif, Stephanie Lako, Andreas Werle van der Merwe, Matthys Potgieter, Vincent Meurrens, Zia Samad, Ente Rood

“…While the BML had a slightly lower root mean squared error (1.02 vs 1.03) the NBR had a slightly better fit based on the Akaike information criterion.Conclusions Statistical models can be effective in predicting TB hotspots for ACF planning, and the relatively simpler NBR model was nearly as effective as a more complex BML model. …”
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Tissue Distribution and Pharmacokinetic Characteristics of Aztreonam Based on Multi-Species PBPK Model by Xiao Ye, Xiaolong Sun, Jianing Zhang, Min Yu, Nie Wen, Xingchao Geng, Ying Liu

“…Finally, the cross-species validation was performed using the average fold error (AFE) and absolute relative error (ARE). <b>Results</b>: The cross-species validation showed that the model predictions were highly consistent with the experimental data (AFE < 2, ARE < 30%), but the deviation of the volume of distribution (<i>V_ss</i>) in dogs and monkeys suggested the need to supplement the species-specific parameters to optimize the prediction accuracy. …”
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Quantitative Mapping of Posterior Eye Curvature in Children Using Distortion-Corrected OCT: Insights into Temporal Region Morphology by Takahiro Hiraoka, MD, PhD, Masato Tamura, MS, Yoshikiyo Moriguchi, PhD, Riku Kuji, MS, Toshihiro Mino, PhD, Masahiro Akiba, PhD, Yosuke Takahashi, OD, Kenichi Yoshino, MD, PhD, Yoshimi Sugiura, MD, PhD, Toshifumi Mihashi, PhD, Tetsuro Oshika, MD, PhD

“…Significant correlations were noted between mean curvature and AL, refractive error, and ChT in the superior, macular, and inferior regions. …”
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Insomnia, Cognitive Impairment, or a Combination of Both, Alter Lipid Metabolism Due to Changes in Acylcarnitine Concentration in Older Persons by Selma Karime Castillo-Vazquez, Berenice Palacios-González, Marcela Vela-Amieva, Isabel Ibarra-González, Ricardo Morales, Paola García-delaTorre, Sergio Sánchez-García, Carmen García-Peña, Ricardo Reyes-Chilpa, Raúl Hernán Medina-Campos, Jessica Hernández-Pineda, Juan Carlos Gomez-Verjan, Nadia Alejandra Rivero-Segura

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Experimental study on the influence mechanism of ambient temperature on the seismic performance of steel tube confined concrete columns by Wang Li, Hu Qi, Pan Qiren, Gu Haowei, Zhai Qiyuan, Yu Lusong, Kang Ercong

“…Under high and low temperature conditions, the maximum relative error between the calculated value of the existing formula and the experimental value can reach 21.73%. …”
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Unlocking Gait Analysis Beyond the Gait Lab: High-Fidelity Replication of Knee Kinematics Using Inertial Motion Units and a Convolutional Neural Network by Stefano A. Bini, MD, Nicholas Gillian, PhD, Thomas A. Peterson, PhD, Richard B. Souza, PhD, PT, Brooke Schultz, MS, ACE-CPT, Wojciech Mormul, MS, Marek K. Cichoń, MS, Agnieszka Barbara Szczotka, MS, Ivan Poupyrev, PhD

“…Model performance was assessed using mean absolute error. Results: The convolutional neural network models exhibited high accuracy in replicating motion capture-derived kinematic variables. …”
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The Channel Fading Influence of the Receiver Operating Characteristics of the TT&C Receiver Based on the Dual-Sequence Frequency Hopping by Guangkai Liu, Jie Guo, Weizheng Xin, Cheng Cheng, Lu Wang

“…Thirdly, the detection probability, false alarm probability, ROC, and system bit error rate (BER) of the DSFH signals enhanced by SR under the Rayleigh fading conditions are obtained, under the minimum BER criterion. …”
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