Factors Related to Superior and Inferior Hemifield Defects in Primary Open-Angle Glaucoma by Remi Takeuchi, Nobuko Enomoto, Kyoko Ishida, Ayako Anraku, Goji Tomita

“…Clinical data including visual acuity, refractive error, disc hemorrhage, VF indexes, and medical history were recorded. …”
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A Deep Learning Enabled Chest X-Ray Abnormality Detection Model for Radiology Assistance. by Ssempeebwa, Phillip, Ainembabazi, Patience

“…Traditional methods of interpretation rely heavily on manual inspection, which can be time-consuming and prone to human error. …”
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Research on the Multi-Objective Optimal Design of Adjusting Mechanisms Considering Force Transmission Performance by Qi Yang, Mingxin Shan, Yangli Tian, Boyang Guan, Jingyu Zhai, Wei Sun

“…Through case studies, significant reductions in motion precision errors and the peak stagnation force and maximum differences in stagnation force were achieved, validating the feasibility of this optimization design approach.…”
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Office blood pressure: overcoming the problems of diagnosis and control of arterial hypertension treatment by E. V. Platonova, E. Yu. Fedorova, V. M. Gorbunov

“…Some national guidelines since 2017 considered the most common method for diagnosing and controlling hypertension (HTN) (office blood pressure (OBP) measurement) as screening only. …”
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Software Defect Prediction Using Deep Q-Learning Network-Based Feature Extraction by Qinhe Zhang, Jiachen Zhang, Tie Feng, Jialang Xue, Xinxin Zhu, Ningyang Zhu, Zhiheng Li

“…In the data preprocessing phase, the undersampling method of BalanceCascade is applied to divide the original datasets. …”
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Machine Learning G-Code Optimization by Héctor Lasluisa-Naranjo, David Rivas-Lalaleo, Joaquín Vaquero-López, Christian Cruz-Moposita

“…A line-by-line analysis and rewriting of the G-code resulted in an average 24.36% reduction in time and 5% in material use, with minimal impact on quality, validated with the Taguchi method.…”
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Achieving Manufacturing Excellence Using Lean DMAIC by Rindi Kusumawardani, Ana, Moses Laksono Singgih

“…It identifies key inefficiencies, such as waiting times, overproduction, and document errors, using the DMAIC method, along with Root Cause Analysis (RCA) and Failure Mode and Effect Analysis (FMEA), to prioritize waste reduction. …”
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Dietary misreporting: a comparative study of recalls vs energy expenditure and energy intake by doubly-labeled water in older adults with overweight or obesity by Leinys S. Santos-Báez, Michele N. Ravelli, Diana A. Díaz-Rizzolo, Collin J. Popp, Dympna Gallagher, Bin Cheng, Dale Schoeller, Blandine Laferrère

“…Abstract Background Self-report methods are widely used to assess energy intake but are prone to measurement errors. …”
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Using automation to improve business process productivity by S. V. Trofimov

“…The study analyzed scientific publications by Russian authors, as well as studied examples of the implementation of robotic technologies that show a reduction in errors due to the rejection of manual checks. …”
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An efficient multiscale simulation framework integrating dynamic heterogeneity for accurate waterflooding prediction by Li Wu, Junqiang Wang, Deli Jia, Jiqun Zhang, Ruichao Zhang, Yiqun Yan, Yanfang Yin, Shuoliang Wang

“…SPE10 benchmark validation shows 95.07% reduction in total simulation time and 98.19% in linear solver time versus the fully implicit method, with errors < 5%. …”
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Evaluation of Decision-Making Processes and Impact Levels in Apparent Loss Management Using Analytic Hierarchy Process (AHP) and Fuzzy AHP by Furkan Acar, Cansu Bozkurt, Mahmut Fırat

“…The main heading of data measurement and management has the highest weight (0.5048 with the AHP method and 0.3489 with the BAHP method). When the sub-component weights are examined, 9 of the first 11 components in the ranking created according to the weight coefficients obtained with the AHP and FAHP methods are the same. …”
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Spatial interpolation of cropland soil bulk density by increasing soil samples with filled missing values by Aiwen Li, Jinli Cheng, Dan Chen, Wendan Li, Yaruo Mao, Xinyi Chen, Bin Zhao, Wenjiao Shi, Tianxiang Yue, Qiquan Li

“…The RBFNN model, tailored for each sub-watershed, yielded the highest accuracy in filling missing BD, with an increase in coefficient of determination (R 2) by 19.54–37.36% and reductions in mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) by 8.91–14.81%, 9.02–16.22% and 7.71–13.61%, respectively. …”
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…Key metrics, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Percentage Error (MAPE), were employed to evaluate model performance. …”
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A deep learning framework for prediction of crop yield in Australia under the impact of climate change by Haydar Demirhan

“…The reductions in average root mean squared error are 19%, 25%, 37%, and 29% over the benchmark methods. …”
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A Combination of Classification Robust Adaptive Kalman Filter with PPP-RTK to Improve Fault Detection for Integrity Monitoring of Autonomous Vehicles by Hassan Elsayed, Ahmed El-Mowafy, Amir Allahvirdi-Zadeh, Kan Wang, Xiaolong Mi

“…Epoch-wise weighting adjustments in the robustness test create a more accurate stochastic model, aided by an adaptive unit weight variance (UWV) calculated with a sliding window, achieving a 7–28% UWV reduction. Three test scenarios with up to four simultaneous faults in code and phase observations, ranging from 1 to 200 m and 0.4 to 20 m, respectively, demonstrated successful identification and de-weighting of faults, resulting in maximum positioning errors of 6 mm (horizontal) and 11 mm (vertical). …”
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Physics-Informed Neural Networks for Enhanced State Estimation in Unbalanced Distribution Power Systems by Petros Iliadis, Stefanos Petridis, Angelos Skembris, Dimitrios Rakopoulos, Elias Kosmatopoulos

“…Notably, the PINN achieves up to a 97% reduction in current estimation errors while maintaining high voltage prediction accuracy. …”
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Flight Trajectory Prediction Based on Automatic Dependent Surveillance-Broadcast Data Fusion with Interacting Multiple Model and Informer Framework by Fan Li, Xuezhi Xu, Rihan Wang, Mingyuan Ma, Zijing Dong

“…The experiments are conducted using real flight surveillance data received from automatic dependent surveillance-broadcast (ADS-B) sensors to validate the effectiveness of the proposed method. The results demonstrate that the IMM-Informer framework has notable prediction error reductions and significantly outperforms the prediction accuracies of the standalone sequence prediction network models.…”
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Neural Implicit Monocular Visual SLAM for 3D Reconstruction in Planetary Environments by C. Liu, R. Huang, R. Huang, H. Xie, H. Xie, T. Tao, Y. Feng, Y. Feng, X. Tong, X. Tong

“…The results demonstrate that our method significantly outperforms OV²SLAM in localization accuracy, achieving an 85.16% reduction in absolute trajectory errors and maintaining translation errors within 1 m across the entire trajectory. …”
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TREATMENT OF SPASTICITY AND DEGENERATIVE-DYSTROPHIC CHANGES IN MUSCLES IN CHILDREN WITH CEREBRAL PALSY by О. Данилов, О. Шульга

“…A central focus of multidisciplinary rehabilitation of patients with CP is the reduction muscle spasticity. One of the most effective methods for achieving this is the administration of botulinum toxin type A. …”
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A data mining approach for proposing a relationship to predict self-compaction concrete crack width after the self-healing period by Saeid Hosseini, Ali Seyedkazemi, Abdullah Davoudi-Kia, Saman Soleimani Kutanaei

“…In this study, three powerful soft computing methods, including Group Method of Data Handling (GMDH), Response Surface Methodology (RSM), and Gene Expression Programming (GEP), were used to evaluate the effects of fly ash (FA), limestone powder (LP), silica fume (SF), and initial crack width (CWB) on the crack width after the self-healing period (CWA) and to propose a relationship for its prediction. …”
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