Analysis of Receiver Operating Characteristic Curves for Cure Survival Data and Mismeasured Biomarkers by Li-Pang Chen

“…On the other hand, while a large body of estimation methods have been proposed, they rely on an implicit assumption that the variables are precisely measured. In applications, measurement errors are generally ubiquitous and ignoring measurement errors can cause unexpected bias for the estimator and lead to the wrong conclusion. …”
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Modeling the violation of reward maximization and invariance in reinforcement schedules. by Giancarlo La Camera, Barry J Richmond

“…In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. …”
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Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer by Zuriani Mustaffa, Mohd Herwan Sulaiman, Muhammad ‘Arif Mohamad

“…Evaluation using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the coefficient of determination (R2) demonstrates the superior performance of DL optimized by BMO, showing minimal errors.…”
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Utilizing soil–water characteristic curve parameters in custom artificial neural network models to predict the unsaturated hydraulic conductivity by Bashar Alibrahim, Maan Habib, Ahed Habib

“…Analysis of mean absolute error (MAE) and root mean square error (RMSE) values revealed variability in predictive performance across soil textures, with sandy soils showing higher errors due to their unique hydraulic properties and testing method discrepancies. …”
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Evaluation of statistical methods applied in theses and dissertations in an Open, Distance and e-Learning University. by Legesse Kassa Debusho, Mahlageng Retang Mashabela, Phuti Naphtaly Sebatjane, Sthembile Sithole, Busisiwe Tabo, Eeva-Maria Rapoo

“…The appropriate application of research methods and statistical analyses used in the studies directly affects the quality of scientific studies. …”
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Enhanced Software Testing Model Under Software Warranty Policy Considering Debugger Learning and Time Postponement Factors by Wang Li, Chih-Chiang Fang

“…However, striving for perfect and error-free software is often impractical due to constraints in budget, time, and testing resources. …”
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Working mode detection method based on bidirectional LSTM for pipe jacking inertial automatic guidance system by Yutong Zu, Lu Wang, Yuanbiao Hu, Gansheng Yang, Boning He, Zheng Zhou

“…However, since its guidance information is obtained by gyroscope integration, the accrued error is significant, which limits its application. …”
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Learning Online MEMS Calibration with Time-Varying and Memory-Efficient Gaussian Neural Topologies by Danilo Pietro Pau, Simone Tognocchi, Marco Marcon

“…To compensate for these drifts, the traditional calibration method based on a linear model is applicable, and unfortunately, it does not work with nonlinear errors. …”
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Memory Monitoring Recognition Test (MMRT), a new measurement of stimular source monitoring: Software and comprehension. by Pedro C Martínez-Suárez, José Alejandro Valdevila Figueira, Joselyn M Luna-Cambi, Carlos E Guerrero-Granda, Rocío Valdevila Santiesteban

“…<h4>Conclusion</h4>Preliminary applications suggest its usefulness in identifying early cognitive markers of schizophrenia, facilitating the measurement of reality monitoring through attribution errors. …”
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Performance Comparison of Monolithic and Microservices Architectures in Handling High-Volume Transactions by Mastura Diana Marieska, Arya Yunanta, Harisatul Aulia, Alvi Syahrini Utami, Muhammad Qurhanul Rizqie

“…The selected performance metrics were response time and error rate. The experimental results reveal that under high-load conditions, microservices outperform monolithic architectures, demonstrating 36% faster response times and 71% fewer errors. …”
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Artificial Intelligence in the Identification of Germinated Soybean Seeds by Hiago H. R. Zanetoni, Lucas G. Araujo, Reynaldo P. Almeida, Carlos E. A. Cabral

“…The results derived from the analysis of the graphs and comparisons to the conventional methodology of seed classification showed the effectiveness of YOLO for classifying seeds as germinated or nongerminated, reaching 95% accuracy in seed classification, beyond the range of 0–0.110 of the prediction errors, determined by the application of the methodology of mean square error, highlighting the efficiency of YOLO.…”
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Optimizing PEMFC parameter identification using improved pufferfish algorithm and CNN by Ji Li, Changiz Bastani

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Command-Filtered Yaw Stability Control of Vehicles with State Constraints by Lizhe Wu, Zhenhua Liu, Dingxuan Zhao

“…Meanwhile, a command-filtered control strategy is introduced to reduce computational complexity, and an error compensation mechanism is incorporated to mitigate the adverse effects of filter-induced errors on system performance. …”
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Uncertainty in Ecohydrological Modeling in an Arid Region Determined with Bayesian Methods. by Junjun Yang, Zhibin He, Jun Du, Longfei Chen, Xi Zhu

“…We determined that model-structural uncertainty constituted the largest error; the model did not capture the extremes of low soil moisture in the desert-oasis ecotone (DOE), particularly below 40 cm soil depth. …”
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A Capillary-Based Micro Gas Flow Measurement Method Utilizing Laminar Flow Regime by Yuheng Zheng, Dailiang Xie, Zhengcheng Qin, Zhengwei Huang, Ya Xu, Da Wang, Hong Zheng

“…This study proposes a novel micro gas flow measurement method based on a single capillary laminar flow element, which simplifies the structure and enhances applicability in the field of micro gas flow. Through structural optimization with precise control of the capillary length–diameter ratios and theoretical error correction based on computational analysis, nonlinear errors were effectively reduced while improving the measurement accuracy in the field of micro gas flow. …”
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An Online‐Learned Neural Network Chemical Solver for Stable Long‐Term Global Simulations of Atmospheric Chemistry by Makoto M. Kelp, Daniel J. Jacob, Haipeng Lin, Melissa P. Sulprizio

“…There are however large regional biases for ozone and NOx under remote conditions where chemical aging leads to error accumulation. These regional biases remain a major limitation for practical application, and ML emulation would be more difficult in a more complex mechanism.…”
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Wpływ Osłabienia Pręta na Siłę Krytyczną w Zakresie Sprężysto-Plastycznym by M. Wnuk, M. Życzkowski

“…It is found that in the case of small parameter 8 the errors are much smaller than those of the Dinnik formula (Table 2). …”
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LiMMCov: An interactive research tool for efficiently selecting covariance structures in linear mixed models using insights from time series analysis. by Perseverence Savieri, Lara Stas, Kurt Barbé

“…Incorrect covariance structure specification can lead to inflated type I error rates, reduced statistical power, and inefficient estimation, ultimately compromising the reliability of statistical inferences. …”
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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

“…These constraints make the errors of OCR vary between 10 and 30%, affecting the efficiency of the terminals and necessitating higher manual interventions. …”
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Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism. by Yutong Liu, Shile Zhang

“…This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with a dependency self-attention mechanism, to automatically detect and correct textual errors in the translation process. The model aims to strengthen the understanding of sentence structure, thereby improving both the accuracy and efficiency of error correction. …”
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