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Toward Utilizing Similarity in Hydrologic Data Assimilation
Published 2024-10-01“…This signifies the importance of accounting for the phase error in order to reduce the error in the amplitude estimate of the sine function. …”
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191
The mean point of vergence is biased under projection
Published 2019-09-01“…We show that the mean point of vergence is generally biased for centrally symmetric errors and that the bias depends on the horizontal vs. vertical error distribution of the tracked eye positions. …”
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192
GNSS-R-Based wildfire detection: a novel and accurate method
Published 2024-12-01“…Results show high agreement between predicted and actual fire areas, with CNN outperforming Random Forest (RF) by 3.3% in prediction accuracy and achieving a 17.4% increase in model fitting. Error analysis indicates no systematic errors, with CNN exhibiting lower fire detection errors and better spatial alignment with actual conditions than RF, which tends to overestimate. …”
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The Predictability of Idealized Tropical Cyclones in Environments With Time‐Varying Vertical Wind Shear
Published 2017-12-01“…The most significant error desaturation occurs in TCs previously exposed to shallow‐upper level shear. …”
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A Vessel Position Precision Analysis Based on a Two-Star Combined Approach
Published 2024-12-01“…This study reveals the error influence mechanism based on the dual-star combination approach, which has significant implications for practical vessel navigation using small-field-of-view star sensors.…”
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Patient Safety in Medication Nomenclature: Orthographic and Semantic Properties of International Nonproprietary Names.
Published 2015-01-01“…The interplay between the different WHO INN naming principles should be further examined, to better understand their implications for the problem of LASA errors.…”
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196
Engineering qubit dynamics in open systems with photonic synthetic lattices
Published 2025-06-01“…We experimentally validate this method by simulating common noise processes, such as phase errors and depolarization. Besides providing a practical solution for quantum state purification, this work demonstrates a versatile approach for the simulation of open qubit dynamics, with potential implications for quantum error correction and environment-induced quantum phase transitions.…”
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Analysis of new approaches used in portfolio optimization: a systematic literature review
Published 2020-08-01“…Implications for theory and practice Robust optimization, Fuzzy logic, and prediction are examples of techniques used to reduce estimation errors. …”
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Maintaining Professional Relations with Patients When Unexpected Things Happen: The Case for Service Recovery
Published 2025-12-01“…It also happens that patients do not always live up to dentist’s expectations.Methods A large general literature shows that service recovery can vary from the protracted and expensive to well-managed cases where patients and professionals emerge with even more positive relationships than they had before the error occurred.Results Five steps in managing service recovery are presented: (a) have a policy of prevention and preparation, (b) clarify your role, (c) listen, (d) agree on the best available mutual path forward, and (e) learn from the experience.Conclusions Available service recovery strategies range from practice development to service recovery, to mediation, to arbitration, to litigation, and even to loss of license.Practical Implications The ultimate service recovery strategy accepts some errors as inevitable and manages these through continuous quality improvement.…”
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On the effect of military spending on education in Africa: what role does institutional quality play?
Published 2025-06-01“…The Fixed Effects with Driscoll-Kraay standard error method was used to obtain reliable standard errors and inferences from the estimated coefficients of the fixed effects model. …”
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Estimating Maize Leaf Water Content Using Machine Learning with Diverse Multispectral Image Features
Published 2025-03-01“…The results indicate that the RFR model performs optimally during the seedling stage, with a root relative mean square error (RRMSE) of 2.99%, whereas estimation errors are larger during the tasseling stage, with an RRMSE of 4.13%. …”
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