noise cleaning【计】 - PMC

Mélanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay

Nat Commun. 2022; 13: 1161. Published online 2022 Mar 4. doi: 10.1038/s41467-022-28818-3

PMCID:: PMC8897392

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Research Progress and Challenges in Laser-Controlled Cleaning of Aluminum Alloy Surfaces

Jian Deng, Guanrong Zhao, Jieheng Lei, Lin Zhong, Zeyong Lei

Materials (Basel) 2022 Aug; 15(16): 5469. Published online 2022 Aug 9. doi: 10.3390/ma15165469

PMCID:: PMC9410451

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Label Noise Cleaning with an Adaptive Ensemble Method Based on Noise Detection Metric

Wei Feng, Yinghui Quan, Gabriel Dauphin

Sensors (Basel) 2020 Dec; 20(23): 6718. Published online 2020 Nov 24. doi: 10.3390/s20236718

PMCID:: PMC7727820

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Motorboat noise disrupts co-operative interspecific interactions

Sophie L. Nedelec, Suzanne C. Mills, Andrew N. Radford, Ricardo Beldade, Stephen D. Simpson, Brendan Nedelec, Isabelle M. Côté

Sci Rep. 2017; 7: 6987. Published online 2017 Aug 1. doi: 10.1038/s41598-017-06515-2

PMCID:: PMC5539144

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Investigating audible and ultrasonic noise in modern animal facilities

Andrew Parker, Liane Hobson, Rasneer Bains, Sara Wells, Michael Bowl

Version 1. F1000Res. 2022; 11: 651. Published online 2022 Jun 14. doi: 10.12688/f1000research.111170.1

PMCID:: PMC9334837

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iCanClean Removes Motion, Muscle, Eye, and Line-Noise Artifacts from Phantom EEG

Ryan J. Downey, Daniel P. Ferris

Sensors (Basel) 2023 Oct; 23(19): 8214. Published online 2023 Oct 1. doi: 10.3390/s23198214

PMCID:: PMC10574843

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Effects of cleaning spray use on eyes, airways, and ergonomic load

Karin Lovén, Anders Gudmundsson, Eva Assarsson, Monica Kåredal, Aneta Wierzbicka, Camilla Dahlqvist, Catarina Nordander, Yiyi Xu, Christina Isaxon

BMC Public Health. 2023; 23: 99. Published online 2023 Jan 13. doi: 10.1186/s12889-022-14954-4

PMCID:: PMC9840290

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Research on the Effect of Molten Salt Ultrasonic Composite Cleaning for Paint Removal

Bao-cai Zhang, Xiu-jie Jia, Fang-yi Li, Yi-hang Sun

ACS Omega. 2019 Oct 15; 4(16): 17072–17082. Published online 2019 Oct 2. doi: 10.1021/acsomega.9b02880

PMCID:: PMC6796236

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The effect of time regime in noise exposure on the auditory system and behavioural stress in the zebrafish

Man Ieng Wong, Ieng Hou Lau, Flora Gordillo-Martinez, Raquel O. Vasconcelos

Sci Rep. 2022; 12: 15353. Published online 2022 Sep 12. doi: 10.1038/s41598-022-19573-y

PMCID:: PMC9468136

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A Conceptual Framework Proposal for a Noise Modelling Service for Drones in U-Space Architecture

Tommy Langen, Vimala Nunavath, Ole Henrik Dahle

Int J Environ Res Public Health. 2022 Jan; 19(1): 223. Published online 2021 Dec 25. doi: 10.3390/ijerph19010223

PMCID:: PMC8750543

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Novel Cleaning-in-Place Strategies for Pharmaceutical Hot Melt Extrusion

Martin Spoerk, Ioannis Koutsamanis, Josip Matić, Simone Eder, Carolina Patricia Alva Zúñiga, Johannes Poms, Jesús Alberto Afonso Urich, Raymar Andreína Lara García, Klaus Nickisch, Karin Eggenreich, Andreas Berghaus, Kathrin Reusch, Yorick Relle, Johannes Khinast, Amrit Paudel

Pharmaceutics. 2020 Jun; 12(6): 588. Published online 2020 Jun 24. doi: 10.3390/pharmaceutics12060588

PMCID:: PMC7356020

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Automated technique for high-pressure water-based window cleaning and accompanying parametric study

Youngjoo Lee, Daesung Kwon, Changmin Park, Myoungjae Seo, TaeWon Seo

PLoS One. 2020; 15(12): e0242413. Published online 2020 Dec 3. doi: 10.1371/journal.pone.0242413

PMCID:: PMC7714119

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Improving daily patient room cleaning: an observational study using a human factors and systems engineering approach

Anping Xie, Clare Rock, Yea-Jen Hsu, Patience Osei, Jennifer Andonian, Verna Scheeler, Sara C. Keller, Sara E. Cosgrove, Ayse P. Gurses, Centers for Disease Control and Prevention (CDC) Prevention Epicenter Program

IISE Trans Occup Ergon Hum Factors. Author manuscript; available in PMC 2019 Sep 25.

Published in final edited form as: IISE Trans Occup Ergon Hum Factors. 2018; 6(3-4): 178–191. Published online 2018 Sep 25. doi: 10.1080/24725838.2018.1487348

PMCID:: PMC6760906

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An assessment of ambient noise and other environmental variables in a nonhuman primate housing facility

Alexander R. McLeod, Jane A. Burton, Chase A. Mackey, Ramnarayan Ramachandran

Lab Anim (NY) Author manuscript; available in PMC 2023 Aug 1.

Published in final edited form as: Lab Anim (NY). 2022 Aug; 51(8): 219–226. Published online 2022 Jul 27. doi: 10.1038/s41684-022-01017-9

PMCID:: PMC9511702

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Noise annoyance during COVID-19 lockdown: A research of public opinion before and during the pandemic

Ayça Şentop Dümen, Konca Şaher

J Acoust Soc Am. 2020 Dec; 148(6): 3489–3496. Published online 2020 Dec 8. doi: 10.1121/10.0002667

PMCID:: PMC7857498

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Being a Fair Neighbor—Towards a Psychometric Inventory to Assess Fairness-Related Perceptions of Airports by Residents—Development and Validation of the Aircraft Noise-Related Fairness Inventory (fAIR-In)

Dominik Hauptvogel, Dirk Schreckenberg, Tobias Rothmund, Marie-Therese Schmitz, Susanne Bartels

Int J Environ Res Public Health. 2023 Jun; 20(12): 6113. Published online 2023 Jun 13. doi: 10.3390/ijerph20126113

PMCID:: PMC10297952

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PMC Images search for noise cleaning【计】

Figure 1

Flowchart of label noise cleaning with an adaptive ensemble method based on a noise detection metric.

Label Noise Cleaning with an Adaptive Ensemble Method Based on Noise Detection Metric

Sensors (Basel). 2020 Dec;20(23):6718.
Fig. 6.

Classification results (SegNet) before and after CRF noise cleaning mapped to (x,y) view. Panels show: (a) ground truth, (b) results prior to CRF noise cleaning, and (c) results after CRF noise cleaning. Colors are green (lipid), red (calcium), and white (guidewire).

Automated plaque characterization using deep learning on coronary intravascular optical coherence tomographic images

Biomed Opt Express. 2019 Dec 1;10(12):6497-6515.
Figure 6

A-line classification results before and after CRF noise cleaning mapped to (x, y) domain. Panels are: (A) results prior to noise cleaning and (B) results after noise cleaning. For each figure, the inner ring is the ground truth label, and the outer ring is the predicted result. Colors are green (fibrolipidic), red (fibrocalcific), blue (other), and white (guidewire).

Fully automated plaque characterization in intravascular OCT images using hybrid convolutional and lumen morphology features

Sci Rep. 2020;10:2596.
FIGURE 2

Example output plots produced by Zapline‐plus for 50 Hz line noise. Shown is a 9 min MEG data set from MEG study I (Section ), with 50 Hz predefined as the noise to remove. For a detailed explanation of the individual subplots, see section 2.6. (a) Power spectrum centered around the noise frequency. (b) Number of components removed by Zapline for each chunk. Chunks were defined as periods in which the noise was spatially stable. (c) Specific noise frequencies are detected within each chunk. (d) Component scores, sorted in descending strength. Red line: threshold for rejection based on outlier detection. (e) Same as (a), but after removal of the noise components. (f) Full power spectrum, depicting both the line noise and (sub‐)harmonics. (g) Same as (e), but showing clean and noise data separately. The x‐axis expresses frequency relative to the removed noise frequency, where 1 indicates the noise frequency. (h) Power spectrum of 10 Hz range below the noise frequency, indicating to what extent non‐noise frequencies were affected by the cleaning

Zapline‐plus: A Zapline extension for automatic and adaptive removal of frequency‐specific noise artifacts in M/EEG

Hum Brain Mapp. 2022 Jun 15;43(9):2743-2758.