Testing different function fitting methods for mobile eye-tracker calibration by Börn Severitt, Thomas Kübler, Enkelejda Kasneci

“…We found the commonly used polynomial regression via least-squares-error fit often lacks to find good mapping functions when compared to ridge regression. …”
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The Potential of a Laser-Aspiration Solution for Refractive Lens Exchange by D. E. Arakelyan, S. Yu. Kopaev, I. A. Il’inskaya, V. V. Pominova

“…This review presents the current knowledge about the methods of lens surgery for the correction of refractive errors in patients with presbyopia and other refractive errors. …”
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The Relative Role of Semantic and Sublexical Processes in Reading, Writing and Repetition: Evidence from a Follow-Up Study by Flavia Mattioli

“…The patient, examined twice, in a 10 month follow-up, showed a dissociation between preserved reading with respect to impaired other modalities as well as a qualitative change in errors' type. A reduction of neologisms and phonologically based errors, with a concurrent increase of semantic paraphasias in naming and repetition, as well as an amelioration in reading, with a reduction of stress assignment errors was exhibited at the follow-up. …”
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Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions by Yuxiang Guo, Qiang Han, Tan Li, Huichu Fu, Meng Liang, Siwei Zhang

“…However, traditional PV power forecasting models designed for distributed PV power stations often struggle with accuracy due to unpredictable meteorological variations, data noise, non-stationary signals, and human-induced data collection errors. To effectively mitigate these limitations, this work proposes a dual-stage feature extraction method based on Variational Mode Decomposition (VMD) and Principal Component Analysis (PCA), enhancing multi-scale modeling and noise reduction capabilities. …”
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Hybrid Improved PSO Algorithm for Soil Property Parameter Estimation by Mude Li, Aiping Shi, Yefan Shi, Tao Zhang, Cu Qu, Lihua Ye

“…For multimodal functions (e.g., F3), PSO-EDO significantly outperforms PSO-WOA (Particle Swarm Optimization-Whale Optimization Algorithm) with a 22.3% reduction in error. Simulation experiments further validate its engineering practicality: in soil parameter estimation, PSO-EDO completes 1000 iterations in just 1.95 s, with key parameters (e.g., sinkage coefficient n) controlled within a 7.32% error margin. …”
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Impact of Data Assimilation Frequency and Observation Location in Thermal Effluent Modeling for Coastal Waters by N. Alsulaiman, M. vanReeuwijk, M. D. Piggott

“…A series of observing system simulation experiments were conducted using the OpenDA toolbox to identify the optimal observation location and DA frequency. Significant reductions in temperature prediction errors were achieved using the EnKF for state estimation. …”
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The effect of transcranial random noise stimulation on the movement time and components of noise, co-variation, and tolerance in a perceptual-motor task by Fatemeh Salehi, Mohammadreza Doustan, Esmaeel Saemi

“…Moreover, the results indicate that tRNS elicited a significant reduction in both spatial error and movement execution time, (p ≤ 0.05). …”
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Vulnerability Testing and Analysis on Websites and Web-Based Applications in the XYZ Faculty Environment Using Acunetix Vulnerability by Mifthahul Rahmi, Yuhandri Yunus, Sumijan Sumijan

“…Following a recapitulation process, several web alerts were identified for optimization, including Cross-Site Scripting (XSS), Blind SQL Injection, Application error message, HTML form without CSRF protection, Development configuration file, Directory listing, Error message on page, and User credentials sent in clear text. …”
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One-Instant Flux Observer design for Three-Phase induction motor with reduced bound active load rejection speed controller by AKRAM HASHIM HAMEED, SHIBLY A. AL-SAMARRAIE, AMJAD JALEEL HUMAIDI

“…Abstract Latency in flux observation has an adverse effect on the performance of observer-based field-oriented speed control for three-phase induction motor (IM). The reduction of the convergent rate of estimation errors could improve the performance of speed-controlled IM based on flux observers. …”
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Physics-informed deep learning model for line-integral diagnostics across fusion devices by Cong Wang, Weizhe Yang, Haiping Wang, Renjie Yang, Jing Li, Zhijun Wang, Yixiong Wei, Xianli Huang, Chenshu Hu, Zhaoyang Liu, Xinyao Yu, Changqing Zou, Zhifeng Zhao

“…This study achieves reductions in reconstruction errors, and accelerates the development of surrogate models in fusion research.…”
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Evaluating Predictive Accuracy of Regression Models with First-Order Autoregressive Disturbances: A Comparative Approach Using Artificial Neural Networks and Classical Estimators by Rauf I. Rauf, Masad A. Alrasheedi, Rasheedah Sadiq, Abdulrahman M. A. Aldawsari

“…The analysis is structured into three phases: the first phase examines predictive accuracy across methods using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE); the second phase evaluates the efficiency of parameter estimation based on standard errors across methods; and the final phase visually assesses the closeness of predicted values to actual values through scatter plots. …”
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NUMERICAL MODELING OF SWASH ZONE MORPHOLOGICAL PROCESSES IN COARSE-GRAINED BEACHES WITH XBEACH OPEN-SOURCE MODEL by S. Maleki Taghiabad, M. Adjami, A. Ahmadi

“…The results of this research indicate that the XBeach model has an acceptable performance in modeling hydrodynamic and morphodynamic processes in the Swash region, and simulation with the NH module performs better compared to the SB module (with a reduction in modeling error of over in various models). …”
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Pain Induced during Both the Acquisition and Retention Phases of Locomotor Adaptation Does Not Interfere with Improvements in Motor Performance by Jason Bouffard, Laurent J. Bouyer, Jean-Sébastien Roy, Catherine Mercier

“…Pain did not interfere with global performance during the acquisition or the retention phases but was associated with a shift in movement error center of gravity to later in the swing phase, suggesting a reduction in anticipatory strategy. …”
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Filtering and Overlapping Data for Accuracy Enhancement of Doppler-Based Location Method by Rafał Szczepanik, Jan M. Kelner

“…Each of the analyzed filters with an appropriately selected cutoff frequency provides a comparable reduction in localization error at the level of about 30%. …”
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Nonlinear Adaptive Fuzzy Hybrid Sliding Mode Control Design for Trajectory Tracking of Autonomous Mobile Robots by Yung-Hsiang Chen

“…The controller is systematically derived from the trajectory-tracking error dynamics between the AMR and the desired trajectory (DT). …”
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Deep learning-based dual monitoring system for power forecasting and fault detection in nuclear power applications by Mingzhe Lyu, Helin Gong, Zhang Chen, Jiangyu Wang, Mingxiao Zhong, Zhiyong Wang, Qing Li, Zefei Pan

“…In the most informative case, the model achieves a 56.6% reduction in root mean square error and a 36.8% reduction in mean absolute error, with a coefficient of determination (R2) of 0.9924—significantly outperforming the next-best benchmark. …”
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Quality improvement project to reduce length of stay for patients with urinary tract infections in an NHS hospital trust by Molly Crawford

“…White-topped urine sample errors reduced by 50% following the process change. …”
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PEMFC Thermal Management Control Strategy Based on Dual Deep Deterministic Policy Gradient by Zhi Zhang, Yunde Shen, Kai Ou, Zhuwei Liu, Dongji Xuan

“…Specifically, the D-DDPG PID achieves a temperature error reduction of up to 75.4% and shortens the average tuning time by up to 25.6% compared to PSO-PID. …”
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Embedded Parallel Implementation of LDPC Decoder for Ultra-Reliable Low-Latency Communications by Mhammed Benhayoun, Mouhcine Razi, Anas Mansouri, Ali Ahaitouf

“…The reached decoding latency on the parallel processing platform is 150 μs for 288 bits with a bit error ratio of 3.410–9.…”
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A weighted and distributed algorithm for multi-hop localization by Juan Cota-Ruiz, Rafael Gonzalez-Landaeta, Jose David Diaz-Roman, Boris Mederos-Madrazo, Ernesto Sifuentes

“…The hop-weighted localization approach generates spatial locations around position estimates of unknown sensors and computes local functions that minimize distance errors among hop-weighted and static neighboring sensors. …”
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