Random error
View article: Negative fluxes and cell-miss errors in the random ray method
Negative fluxes and cell-miss errors in the random ray method Open
View article: Three Methods of Fetal Weight Estimation Compared in Women With <scp>BMI</scp> ≥ 35 kg/m <sup>2</sup> at Term—A Prospective Observational Study
Three Methods of Fetal Weight Estimation Compared in Women With <span>BMI</span> ≥ 35 kg/m <sup>2</sup> at Term—A Prospective Observational Study Open
Objective To compare sonographic, maternal, and clinical estimations of fetal weight in women with severe and morbid obesity (BMI ≥ 35 kg/m 2 ) at term. Methods We conducted a prospective study on multiparous women with singleton term preg…
View article: A Systematic Analysis of Large Language Models with RAG-enabled Dynamic Prompting for Medical Error Detection and Correction
A Systematic Analysis of Large Language Models with RAG-enabled Dynamic Prompting for Medical Error Detection and Correction Open
Objective: Clinical documentation contains factual, diagnostic, and management errors that can compromise patient safety. Large language models (LLMs) may help detect and correct such errors, but their behavior under different prompting st…
View article: Comparative analysis of generalized least squares and generalized inverse regression models for predicting neonatal birth weight using maternal anthropometric measures
Comparative analysis of generalized least squares and generalized inverse regression models for predicting neonatal birth weight using maternal anthropometric measures Open
This research presents a comparative analysis of two advanced statistical methodologies for predicting neonatal birth weight using maternal anthropometric measures. We developed and evaluated both Generalized Least Squares (GLS) and Genera…
View article: Can discrete-time analyses be trusted for stepped wedge trials with continuous recruitment?
Can discrete-time analyses be trusted for stepped wedge trials with continuous recruitment? Open
In stepped wedge cluster randomized trials (SW-CRTs), interventions are sequentially rolled out to clusters over multiple periods. It is common practice to analyze SW-CRTs using discrete-time linear mixed models, in which measurements are …
View article: Can discrete-time analyses be trusted for stepped wedge trials with continuous recruitment?
Can discrete-time analyses be trusted for stepped wedge trials with continuous recruitment? Open
In stepped wedge cluster randomized trials (SW-CRTs), interventions are sequentially rolled out to clusters over multiple periods. It is common practice to analyze SW-CRTs using discrete-time linear mixed models, in which measurements are …
View article: Modelling the impact of quasar redshift errors on the full-shape analysis of correlations in the Lyman-α forest.
Modelling the impact of quasar redshift errors on the full-shape analysis of correlations in the Lyman-α forest. Open
In preparation for the first cosmological measurements from the full shape of the Lyman-α (Lyα) forest from DESI, we must carefully model all relevant systematics that might bias our analysis. It was shown in Youles et al. (2022) that rand…
View article: Pelvic Radiotherapy Immobilization: A Narrative Review of Vac-Lok and Thermoplastic Systems
Pelvic Radiotherapy Immobilization: A Narrative Review of Vac-Lok and Thermoplastic Systems Open
A BSTRACT Accurate patient positioning is critical in radiotherapy to ensure precise dose delivery and minimize setup errors. Immobilization devices such as thermoplastic molds, blue bags, and Vac-Lok systems are widely employed to achieve…
View article: Correction of gas chromatography–mass spectrometry long-term instrumental drift using quality control samples over 155 days
Correction of gas chromatography–mass spectrometry long-term instrumental drift using quality control samples over 155 days Open
Long-term instrumental data drift is a critical challenge for ensuring process reliability and product stability. In this study, we conducted 20 repeated tests on the smoke of six commercial tobacco products using gas chromatography-mass s…
View article: Imaging with super-resolution in changing random media
Imaging with super-resolution in changing random media Open
We develop an imaging algorithm that exploits strong scattering to achieve super-resolution in changing random media. The method processes large and diverse array datasets using sparse dictionary learning, clustering, and multidimensional …
View article: Performance Monitoring in Mathematics Learning and Assessment: Error Prediction, Feedback, and the Emotional Burden of Error
Performance Monitoring in Mathematics Learning and Assessment: Error Prediction, Feedback, and the Emotional Burden of Error Open
We learn from our mistakes, often through external feedback. However, there is little research into the intertwining of a student's neural error‐monitoring and their monitoring of external feedback ( feedback‐monitoring ), or how error fee…
View article: Exposure to heavy metals and neuropsychological performance in children with and without attention deficit hyperactivity disorder (ADHD)
Exposure to heavy metals and neuropsychological performance in children with and without attention deficit hyperactivity disorder (ADHD) Open
Heavy metal exposure can negatively impact the neuropsychological development of children and has been linked to ADHD. We investigated the association between heavy metal exposure and neuropsychological functions in children with and witho…
View article: Development of a parametrised atmospheric NO <sub> <i>x</i> </sub> chemistry scheme to help quantify fossil fuel CO <sub>2</sub> emission estimates
Development of a parametrised atmospheric NO <sub> <i>x</i> </sub> chemistry scheme to help quantify fossil fuel CO <sub>2</sub> emission estimates Open
Success of the Paris Agreement relies on rapid reductions in fossil fuel CO2 (ffCO2) emissions. Atmospheric data can verify the ffCO2 reductions pledged by nations in their nationally determined contributions. However, estimating ffCO2 fro…
View article: Perbandingan Algoritma Random Forest dan Extreme Gradient Boosting (XGBoost) dalam Klasifikasi Penyakit Gagal Jantung
Perbandingan Algoritma Random Forest dan Extreme Gradient Boosting (XGBoost) dalam Klasifikasi Penyakit Gagal Jantung Open
Heart failure is a chronic condition where the heart is unable to pump blood optimally, posing a risk of serious complications and death. Early detection is crucial to reduce these risks and can be performed using classification methods wi…
View article: A Smart Blood Pressure Monitoring System Using Sensors and AI-Based Control
A Smart Blood Pressure Monitoring System Using Sensors and AI-Based Control Open
This paper presents a smart, non-invasive blood pressure monitoring system that integrates advanced sensors with artificial intelligence (AI) for continuous and accurate health tracking. Unlike traditional cuff-based devices, the proposed …
View article: A Smart Blood Pressure Monitoring System Using Sensors and AI-Based Control
A Smart Blood Pressure Monitoring System Using Sensors and AI-Based Control Open
This paper presents a smart, non-invasive blood pressure monitoring system that integrates advanced sensors with artificial intelligence (AI) for continuous and accurate health tracking. Unlike traditional cuff-based devices, the proposed …
View article: A Smart Blood Pressure Monitoring System Using Sensors and AI-Based Control
A Smart Blood Pressure Monitoring System Using Sensors and AI-Based Control Open
This paper presents a smart, non-invasive blood pressure monitoring system that integrates advanced sensors with artificial intelligence (AI) for continuous and accurate health tracking. Unlike traditional cuff-based devices, the proposed …
View article: Improved random coincidence estimation including triple coincidences for high quantitation accuracy in PET imaging
Improved random coincidence estimation including triple coincidences for high quantitation accuracy in PET imaging Open
View article: Spatio-temporal random forest-based estimation of monthly gridded carbon emissions using multi-source remote sensing data
Spatio-temporal random forest-based estimation of monthly gridded carbon emissions using multi-source remote sensing data Open
View article: Spatio-temporal random forest-based estimation of monthly gridded carbon emissions using multi-source remote sensing data
Spatio-temporal random forest-based estimation of monthly gridded carbon emissions using multi-source remote sensing data Open
View article: Effective refractive error coverage and quality gaps in Bhutan: evidence from rapid assessment of refractive error
Effective refractive error coverage and quality gaps in Bhutan: evidence from rapid assessment of refractive error Open
View article: A Simple and Effective Random Forest Modelling for Nonlinear Time Series Data
A Simple and Effective Random Forest Modelling for Nonlinear Time Series Data Open
In this paper, we propose Random Forests by Random Weights (RF-RW), a theoretically grounded and practically effective alternative RF modelling for nonlinear time series data, where existing RF-based approaches struggle to adequately captu…
View article: A Simple and Effective Random Forest Modelling for Nonlinear Time Series Data
A Simple and Effective Random Forest Modelling for Nonlinear Time Series Data Open
In this paper, we propose Random Forests by Random Weights (RF-RW), a theoretically grounded and practically effective alternative RF modelling for nonlinear time series data, where existing RF-based approaches struggle to adequately captu…
View article: D-J-Weston/RadiationBeltForecasting: VAMPIRE: Using a Random Forest to Forecast Earth's Outer Van Allen Radiation Belt
D-J-Weston/RadiationBeltForecasting: VAMPIRE: Using a Random Forest to Forecast Earth's Outer Van Allen Radiation Belt Open
View article: D-J-Weston/RadiationBeltForecasting: VAMPIRE: Using a Random Forest to Forecast Earth's Outer Van Allen Radiation Belt
D-J-Weston/RadiationBeltForecasting: VAMPIRE: Using a Random Forest to Forecast Earth's Outer Van Allen Radiation Belt Open
View article: Average Precision at Cutoff k under Random Rankings: Expectation and Variance
Average Precision at Cutoff k under Random Rankings: Expectation and Variance Open
Recommender systems and information retrieval platforms rely on ranking algorithms to present the most relevant items to users, thereby improving engagement and satisfaction. Assessing the quality of these rankings requires reliable evalua…
View article: Average Precision at Cutoff k under Random Rankings: Expectation and Variance
Average Precision at Cutoff k under Random Rankings: Expectation and Variance Open
Recommender systems and information retrieval platforms rely on ranking algorithms to present the most relevant items to users, thereby improving engagement and satisfaction. Assessing the quality of these rankings requires reliable evalua…
View article: Optimizing Panning Operating Parameters for Alluvial Gold Processing: The Case of the Wakaso Panning Plant
Optimizing Panning Operating Parameters for Alluvial Gold Processing: The Case of the Wakaso Panning Plant Open
The objective of this work is to determine the best configuration corresponding to the optimal rate of site handmade processing techniques. The experimental study allowed us to show that the gold yield depends on the case of the parameter …
View article: Instance-level Randomization: Toward More Stable LLM Evaluations
Instance-level Randomization: Toward More Stable LLM Evaluations Open
Evaluations of large language models (LLMs) suffer from instability, where small changes of random factors such as few-shot examples can lead to drastic fluctuations of scores and even model rankings. Moreover, different LLMs can have diff…
View article: Reliability Assessment of Systems with Multiple Performance Characteristic by Fusing Random Effects Wiener Processes with R-vine Copula
Reliability Assessment of Systems with Multiple Performance Characteristic by Fusing Random Effects Wiener Processes with R-vine Copula Open
#41