Improving pluvial flood simulations with a multi-source digital elevation model super-resolution method by Y. Zhu, Y. Zhu, P. Burlando, P. Y. Tan, C. Geiß, C. Geiß, S. Fatichi

“…Compared to conventional methods (e.g. bicubic interpolation), the simulation results demonstrated that our approach significantly improved the accuracy of flood simulations, with a reduction in the mean absolute error of floodwater depth of about 13.1 % and an increase in the intersection over union (IoU) for inundation area predictions of about 46 %. …”
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Free Iron Determination in Soil by Flame Atomic Absorption Spectrometry by Sui’an ZHANG, Zhongrui YANG, Yuyu DUAN, Kaiqi YANG, Zhijie HU, Chun YANG, Sha HOU

“…The detection limit (3σ) of this method is 0.05g/kg, the quantification limit is 0.20g/kg, the linear correlation coefficient of the standard curve is 0.9995, the precision (RSD, n=6) is 1.95%−3.76%, and the standard error is less than 5%, which meets the analysis requirements of soil investigation. …”
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A pilot study for assessing NAO humanoid robot assistance in shoulder rehabilitation by Alessandra Raso, Martina Pulcinelli, Emiliano Schena, Alfio Puglisi, Giovanni Pioggia, Arianna Carnevale, Umile Giuseppe Longo

“…Performance was evaluated by mean absolute error (MAE) for ROM and execution time, with smoothness assessed through Log Dimensionless Jerk analysis. …”
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Is there a competitive advantage to using multivariate statistical or machine learning methods over the Bross formula in the hdPS framework for bias and variance estimation? by Mohammad Ehsanul Karim, Yang Lei

“…This study aimed to systematically evaluate and compare the performance of traditional statistical methods and machine learning approaches within the hdPS framework, focusing on key metrics such as bias, standard error (SE), and coverage, under various exposure and outcome prevalence scenarios.…”
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Enhanced power sharing and voltage regulation for islanded nano-satellite DC microgrids in spinning flight scenarios by Khalil Louassaa, Josep M. Guerrero, Baseem Khan, Muhammad Zain Yousaf, Mohamed Ali Zdiri, Liu Zhang, Rajkumar Sivanraju

“…Comprehensive validation through stability analysis, simulations, and experimental testing demonstrates superior performance versus conventional methods, with significant improvements in transient response speed, steady-state error reduction, and disturbance rejection capability. …”
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Photospectral Data Obtaining with the Unmanned Aerial Spectrometry Vehicle by A. A. Lamaka, A. V. Gutarau, N. G. Shcherbakou, P. V. Ivuts

“…This led to the timing error standard deviation reduction from 142 ms to 15 ms. …”
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How Does Assimilating SMAP Soil Moisture Improve Characterization of the Terrestrial Water Cycle in an Integrated Land Surface‐Subsurface Model? by Haojin Zhao, Carsten Montzka, Johannes Keller, Fang Li, Harry Vereecken, Harrie‐Jan Hendricks Franssen

“…The assimilation improves the median correlation between simulated and measured soil moisture from 0.72 ∼ 0.79 to 0.79 ∼ 0.83 and decreases the median unbiased Root Mean Square Error (ubRMSE) from 0.063 ∼ 0.060 cm3/cm3 to 0.050 ∼ 0.045 cm3/cm3. …”
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Steering-Angle Prediction and Controller Design Based on Improved YOLOv5 for Steering-by-Wire System by Cunliang Ye, Yunlong Wang, Yongfu Wang, Yan Liu

“…Numerical simulations and experiments have shown that the proposed method provides a 39.16% better root mean squared error (RMSE) score than traditional backstepping control, and it achieves good estimation performance for angles, angular velocity, and unknown disturbances.…”
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Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…The significance of this research lies in its ability to automate and accelerate complex structural analysis using Adaptive Neuro-Fuzzy Inference Systems (ANFISs), achieving an average error of less than 2% in multi-variable prediction scenarios. …”
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A preliminary attempt to harmonize using physics-constrained deep neural networks for multisite and multiscanner MRI datasets (PhyCHarm) by Gawon Lee, Dong Hye Ye, Se-Hong Oh

“…PhyCHarm was evaluated using the structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and normalized-root-mean square error (NRMSE) for the Quantitative Maps Generator, and using SSIM, PSNR, and volumetric analysis for the Harmonization network, respectively. …”
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Reduced‐Order Probabilistic Emulation of Physics‐Based Ring Current Models: Application to RAM‐SCB Particle Flux by Alfredo A. Cruz, Rashmi Siddalingappa, Piyush M. Mehta, Steven K. Morley, Humberto C. Godinez, Vania K. Jordanova

“…This ROPE offers accurate predictions of omnidirectional flux at a single energy with no pitch angle information, providing robust predictions on the test set with an error score below 11% and calibration scores under 8% with bias under 2% providing a significant speed up as compared to the full RAM‐SCB run.…”
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How have unintended pregnancies and contraceptive use among adolescent girls and young women changed in Uganda? Evidence from the 2014 and 2019 PMA national surveys. by Simon P S Kibira, Mary Nakafeero, Mathew Amollo, Ronald Ssenyonga, Rawlance Ndejjo, Phil Anglewicz, Melody Kukundakwe, Mabel Luzze, Samuel Kagongwe, Victor Guma, Vivian Zalwango, Fredrick Edward Makumbi

“…A weighted comparison of the prevalence of unintended pregnancies was made between the surveys, and statistical significance determined at a 5% type-1 error rate. All analyses were conducted with Stata version15 using svy surveyset methodology accounting for complex survey design. …”
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Predicting the passive control of fluid forces over circular cylinder in a time dependent flow using neuro-computing by Atif Asghar, Rashid Mahmood, Afraz Hussain Majeed, Hammad Alotaibi, Ahmed Refaie Ali

“…These results show that the mean square error values are very close to zero, indicating a strong correlation between the fluid force coefficients obtained from CFD and those predicted by the ANN. …”
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The combined impact of AI and VR on interdisciplinary learning and patient safety in healthcare education: a narrative review by Emmanuel Aoudi Chance

“…Strategic implementation can contribute to error reduction, improved patient outcomes, and a culture of safety. …”
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Tomato Yield Estimation Using an Improved Lightweight YOLO11n Network and an Optimized Region Tracking-Counting Method by Aichen Wang, Yuanzhi Xu, Dong Hu, Liyuan Zhang, Ao Li, Qingzhen Zhu, Jizhan Liu

“…For fruit counting, the results showed that the proposed region tracking-counting method achieved a mean counting error (MCE) of 6.6%, representing a reduction of 5.0% and 2.1% compared to the Bytetrack and cross-line counting methods, respectively. …”
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Aspect-Oriented Approach of Non-Functional Requirements for Embedded System-Based IoT Applications by Anirban Bhar, Sabnam Sengupta, Sankhayan Choudhury

“…Designing high-performance embedded devices is usually time consuming and error-prone due to conflicting non-functional requirements (NFRs) like performance, timeliness, and sustainability. …”
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Assessment of Sensitivity and Validity Hydrodynamic Model in Cisadane Using Delft3d Flow Model by Gumilang Ramadhan Pasma, Hamzah Haru Radityo Suharyanto, Hanah Khoirunnisa, Reni Wijayanti, Gugum Gumbira, Reno Arief Rachman

“…The validation formulation used Normalization Root Mean Square Error (NRMSE), resulting in 5.3 - 9.6% for all the manning values and domains. …”
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Evaluating the effect of digital elevation model resolution in lahar hazard simulations: insights from the 1877 Cotopaxi scenario, Ecuador by Francisco J. Vasconez, Francisco J. Vasconez, Jeremy C. Phillips, S. Daniel Andrade, Mark J. Woodhouse

“…Normalized Root Mean Square Error (NRMSE) values computed over overlapping areas remain below 5% for maximum depth, speed and impact pressure. …”
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Azanza garckeana Extract Alleviates Lead-Induced Testicular Toxicity: A Histological and Oxidative Stress Analysis by Maureen Osemudiamen Oromaiwele, Daniel E. Odiase

“…Statistical analysis was done using the GraphPad Prism software V9, and data was expressed as mean with standard error of mean (SEM). A one-way analysis of variance (ANOVA), followed by Fisher’s multiple comparisons post-hoc test, was performed to determine statistical significance ([Formula: see text] values <0.05). …”
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The Impact of Sportsmetrics™ Neuromuscular Training on Injury Risk Factors and Athletic Performance: A Systematic Review by E Shakiba, H Mohammadi, M.H Alizadeh

“…The majority of studies reported a significant reduction in injury risk and a significant improvement in athletic performance.Conclusion:In addition to reducing dynamic knee valgus and landing error, and improving the alignment of the lower limbs, Sportsmetrics™ increase power, speed, agility and core stability. …”
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