The noise in sensor data has a substantial impact on the reliability and accuracy of (ML) algorithms. A comprehensive framework is proposed to analyze the effects of diverse noise inputs in sensor data on the accuracy of ML models. Through extensive experimentation and evaluation, this research examines the resilience of a LightGBM ML model to ten different noise models, namely, Flicker, Impulse, Gaussian, Brown, Periodic, and others. A thorough analytical approach with various statistical metrics in a Monte Carlo simulation setting was followed. It was found that the Gaussian and Colored noise were detrimental when compared to Flicker and Brown, which are identified as safe noise categories. It was interesting to find a safe threshold limit of noise intensity for the case of Gaussian noise, which was missing in other noise types. This research work employed the use case of changeover detection in (CNC) manufacturing machines and the corresponding data from the publicly funded research project (OBerA).
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10819623 | PMC |
| http://dx.doi.org/10.3390/s24020330 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Effects of Noise and Public Setting on Blood Pressure Readings : A Randomized Crossover Trial.
Ann Intern Med
January 2025
Department of Epidemiology and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore; and Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland (T.M.B.).
Background: Guidelines emphasize quiet settings for blood pressure (BP) measurement.
Objective: To determine the effect of noise and public environment on BP readings.
Design: Randomized crossover trial of adults in Baltimore, Maryland.
Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach.
JMIR Form Res
January 2025
Department of Computer Science, University of California, Irvine, Irvine, CA, United States.
Background: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsistencies in pain management. Multimodal pain assessment, integrating physiological and behavioral data, presents an opportunity to create more objective and accurate pain measurement systems.
View Article and Find Full Text PDFGeospatial and econometric approaches or older driver safety: Analysis of crash injury severity of regional highways.
PLoS One
January 2025
State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China.
This study tried to focus on the older drivers' group and explore the impact factors of injury severity involving older drivers from geo-spatial analysis. To reach the goal, a spatial analysis was proposed employing geographic information systems (GIS) with a case study application to two counties in Nevada. First, crash clusters were explored using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) approach to investigate the spatial crash pattern for older drivers, and determine high risk locations of injury severity.
View Article and Find Full Text PDFEstimation of stationary and non-stationary moving average processes in the correlation domain.
PLoS One
January 2025
Institute of Robotics and Cybernetics, Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava, Bratislava, Slovakia.
This paper introduces a novel approach for the offline estimation of stationary moving average processes, further extending it to efficient online estimation of non-stationary processes. The novelty lies in a unique technique to solve the autocorrelation function matching problem leveraging that the autocorrelation function of a colored noise is equal to the autocorrelation function of the coefficients of the moving average process. This enables the derivation of a system of nonlinear equations to be solved for estimating the model parameters.
View Article and Find Full Text PDFComparison of behind-the-ear vs. off-the-ear speech processors in cochlear implants: A systematic review and narrative synthesis.
PLoS One
January 2025
Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
Background: Cochlear implants (CI) with off-the-ear (OTE) and behind-the-ear (BTE) speech processors differ in user experience and audiological performance, impacting speech perception, comfort, and satisfaction.
Objectives: This systematic review explores audiological outcomes (speech perception in quiet and noise) and non-audiological factors (device handling, comfort, cosmetics, overall satisfaction) of OTE and BTE speech processors in CI recipients.
Methods: We conducted a systematic review following PRISMA-S guidelines, examining Medline, Embase, Cochrane Library, Scopus, and ProQuest Dissertations and Theses.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!