Research and application of vibration loop triggering system for channel wave seismic detection by Hengcong WEN

“…In the trigger method of class synchronous, the trigger device of vibration loop is installed close to the firing point, and the starting delay is very short, eliminated the effect of uncertain delay error about detonator, forms the trigger effect of class synchronous, reduces the delay error, and realizes the accurate triggering of the channel wave earthquake.…”
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Expressions for the First Two Moments of the Range of Normal Random Variables with Applications to the Range Control Chart by Don G. Wardell

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Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated Navigation by WEN Sheng, LIU Caiyun, LUAN Tiantian, SUN Mingxiao

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An Adaptive Variance Adjustment Strategy for a Static Background Error Covariance Matrix—Part I: Verification in the Lorenz-96 Model by Lilan Huang, Hongze Leng, Junqiang Song, Dongzi Wang, Wuxin Wang, Ruisheng Hu, Hang Cao

“…Variational data assimilation relies on a static background error covariance matrix (<b>B</b>), yet its variance estimation is often inaccurate, affecting assimilation and forecast performance. …”
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Steroidomics via Gas Chromatography–Mass Spectrometry (GC-MS): A Comprehensive Analytical Approach for the Detection of Inborn Errors of Metabolism by Francesco Chiara, Sarah Allegra, Simona Liuzzi, Maria Paola Puccinelli, Giulio Mengozzi, Silvia De Francia

“…<b>Conclusions:</b> This GC-MS protocol enables comprehensive urinary steroid profiling and calculation of diagnostic ratios for inborn errors of steroid metabolism and endocrine disorders. …”
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Finite Volume Method and Its Applications in Computational Fluid Dynamics by Abdulkafi Mohammed Saeed, Thekra Abdullah Fayez Alfawaz

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On the estimation of ridge penalty in linear regression: Simulation and application by Khan M.S., Ali A., Suhail M.

“…A simulation study is used to evaluate the performance of proposed estimators based on minimum mean squared error (MSE) criterion. The simulative results reveal that, based on minimum MSE, ITPR2 was the most efficient estimator compared to the considered estimators in the study. …”
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Maximum-likelihood Regression with Systematic Errors for Astronomy and the Physical Sciences. II. Hypothesis Testing of Nested Model Components for Poisson Data by Massimiliano Bonamente, Dale Zimmerman, Yang Chen

“…The methods proposed in this paper provide a simple and accurate means of including systematic errors for hypothesis testing of nested model components in a variety of applications.…”
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Considerations on wrongful conviction based on forensic evidence: analysis by the Innocence Project, the National Registry of Exoneration and mechanisms for reducing forensic error... by Aline de Araújo Lourenço, Erick Simões da Camara e Silva

“…4) Are there criteria applicable to expert evidence that can be implemented in Brazil in order to reduce the chance of expert errors and misinterpretation by the judges? …”
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A Data Centric HitL Framework for Conducting aSsystematic Error Analysis of NLP Datasets using Explainable AI by Ahmed El-Sayed, Aly Nasr, Youssef Mohamed, Ahmed Alaaeldin, Mohab Ali, Omar Salah, Abdullatif Khalid, Shaimaa Lazem

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Error analysis and correction method of temperature and humidity profiles in the Three Gorges ground-based remote sensing vertical observation system by Ming ZHANG, Guirong XU, Yu DU, Dan YE

“…Above 6 km, the root mean square error (RMSE) of the humidity can reach 30% on cloudy and rainy days. (3) The correction method established after the regrouping of the 83 height layers can improve the temperature and humidity profile accuracy of the microwave radiometer. (4) The corrected temperature and humidity profiles of the microwave radiometer are closer to the reality in the case of a rain and snow event.…”
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Research on Multi-Parameter Error Model of Backcalculated Modulus Using Abaqus Finite Element Batch Modeling Based on Python Language by Chunlong Xiong, Jiangmiao Yu, Xiaoning Zhang, Chuanxi Luo

“…The error in modulus backcalculation is a crucial component in validating the rationality and reliability of results for engineering applications. …”
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InSAR Detection of Slow Ground Deformation: Taking Advantage of Sentinel-1 Time Series Length in Reducing Error Sources by Machel Higgins, Shimon Wdowinski

“…While analytical methods, weather models, and data exist to mitigate tropospheric error, most of these techniques are unsuitable for all InSAR applications (e.g., complex tropospheric mixing in the tropics) or are deficient in spatial or temporal resolution. …”
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Enhancing medication error reporting through interprofessional education: analysis of Medwatch reporting accuracy and completion rates between teams and individuals by Aline H. Saad, Rehab Bondok, Farah Sayeg, Brian J. Barnes, Caitlin E. Rukat, Candice Garwood, Diane L. Levine

“…Abstract Background Each year, the Food and Drug Administration receives over 2 million adverse event and medication error reports, which are likely underreported. Interprofessional education (IPE) is well positioned to provide team-based training regarding medication safety and related reporting tools. …”
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Study of Multivariate Background Error Characteristics of Convective System on Plateau Slope and Typhoon System Based on Convective-Scale Ensemble Samples by Wanli ZHANG, Yuanbing WANG, Rou LI, Yaodeng CHEN, Deming MENG, Xinyao QIAN, Xili JIN

“…The effective assimilation of observation data in the slope areas of the Qinghai-Xizang （Tibetan） Plateau and typhoon systems has a significant impact on the capabilities of weather forecasting in China， with background error being a key factor affecting the performance of data assimilation.The purpose of this study is to gain a deeper understanding of the characteristics of background errors in conventional control variables and hydrometeor control variables within convective systems on the slopes of the Qinghai-Xizang （Tibetan） Plateau and typhoon systems， so as to develop the data assimilation scheme which is applicable to the convective systems on the slopes of the Qinghai-Xizang （Tibetan） Plateau and typhoon systems.This study employs the Ensemble Transform Kalman Filter （ETKF） and the hybrid Ensemble-Variational data assimilation method to update the ensemble perturbation and the ensemble mean respectively to produce convective-scale ensemble forecast samples with 80 ensemble members and 4-kilometers resolution.This study focuses on cases of convective weather from the northeast slope of the Qinghai-Xizang （Tibetan） Plateau in mid-August 2022 and Typhoon "Meihua"， the 12th typhoon of 2022.Multivariate background error covariances， including those for multiphase hydrometeor and vertical velocity， were computed through physical transformation， vertical transformation， and horizontal transformation.Analyses of the spatial error characteristics， including the eigenvalues， eigenvectors， and characteristic length scales were conducted， and the results of the analyses indicate that background errors are more pronounced in the case of convective system on the slope of the Qinghai-Xizang （Tibetan） Plateau in comparison to the typhoon system.At the same time， the simulation of hydrometeor variables and vertical velocity is less precise in the case of convective system on the slope of the Qinghai-Xizang （Tibetan） Plateau compared to the typhoon system.In the context of data assimilation for these comparable convective systems， the analysis tends to be more aligned with observations and less so with the background， this feature highlights the necessity for high-quality and comprehensive observations in the slope areas of the Qinghai-Xizang （Tibetan） Plateau.In addition， the atmospheric characteristics and the horizontal scale of hydrometeor variables and vertical velocity in the case of convective system on the slope of the Qinghai-Xizang （Tibetan） Plateau display smaller and more localized features compared with those observed in the typhoon system.Moreover， hydrometeor control variables and the vertical velocity exhibit smaller horizontal scales and more pronounced localized characteristics compared to conventional control variables， therefore potentially leading to the influence range of observations and information related to hydrometeor control variables in the slope areas of the Qinghai-Xizang （Tibetan） Plateau relatively limited in the context of the subsequent assimilation analysis.…”
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New non-primitive codes formed from primitive BCH and Hamming codes and their norm evaluation by V. K. Konopelko, V. A. Lipnitski

“…Correction of such errors is called plus-decoding. It is shown that it is impossible to implement plus-decoding by known classical methods and algorithms, but only by the available and developing means of the theory of norms syndromes. …”
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Adjusting for covariates representing potential confounders, mediators, or competing predictors in the presence of measurement error: Dispelling a potential misapprehension and ins... by David M. Klurfeld, Nikhil V. Dhurandhar, Xiaoxin Yu, David B. Allison, Carmen D. Tekwe, Diana M. Thomas, Roger S. Zoh, Colby J. Vorland

“…Background Variables such as dietary intake are measured with error yet frequently used in observational epidemiology. …”
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On Polynomial <i>φ</i>-Contractions with Applications to Fractional Logistic Growth Equations by Abdelkader Moumen, Hayel N. Saleh, Hussien Albala, Khaled Aldwoah, Hicham Saber, E. I. Hassan, Taher S. Hassan

“…Furthermore, we derive explicit error estimates and convergence rates for the associated Picard iteration, providing practical insights into the speed of convergence. …”
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Development of a new statistical distribution with insights into mathematical properties and applications in industrial data in KSA by Badr Aloraini, Abdulaziz S. Alghamdi, Mohammad Zaid Alaskar, Maryam Ibrahim Habadi

“…This study presents the development of a novel distribution through a transformation involving error functions, namely the error function inverse Weibull model, along with an overview of the fundamental characteristics of the proposed model. …”
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Computation of separate ratio and regression estimator under Neutrosophic stratified sampling: an application to climate data by Abhishek Singh, Hemant Kulkarni, Florentin Smarandache, Gajendra Vishwakarma

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