scholarly journals Leq+X - Lärmexposition, Ereignishäufigkeiten und Belästigung: Re-Analyse von Daten zur Belästigung und Schlafstörung durch Fluglärm an deutschen und Schweizer Flughäfen

2020 ◽  
Author(s):  
Julia Haubrich ◽  
Sarah Benz ◽  
Ullrich Isermann ◽  
Beat Schäffer ◽  
Rainer Schmid ◽  
...  
Keyword(s):  
Noise Level ◽  
Regression Models ◽  
Aircraft Noise ◽  
Data Sets ◽  
Energy Equivalent ◽  
Impact Studies ◽  
Noise Impact ◽  
Multi Level ◽  
Continuous Noise ◽  
Noise Metrics

In this study, part of the data sets from 4 large Swiss and German aircraft noise impact studies are re-analysed using logistic multi-level regression models. The aim is to investigate the assumptions that the prediction of a) the percentage of persons highly annoyed by aircraft noise or b) the percentage of persons highly sleep disturbed by aircraft noise can be improved if (i) instead of the energy-equivalent continuous noise level alone, either additional or alternative, more frequency-based aircraft noise metrics and (ii) also airport-specific characteristics are used as predictors. The results support both assumptions; both regarding the percentage of persons highly annoyed and regarding the percentage of persons highly sleep disturbed.

Noise metrics analysis in schools near airports: A Brazilian case study

Noise Mapping ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 21-34
Author(s):  
Mariani Dan Taufner ◽  
Ana Paula Gama ◽  
Jules Ghislain Slama ◽  
Julio Cesar Boscher Torres
Keyword(s):  
Noise Level ◽  
Sound Level ◽  
Noise Mapping ◽  
Intermittent Behavior ◽  
Acoustic Simulation ◽  
Noise Impact ◽  
Average Noise Level ◽  
Noise Metrics ◽  
Brazilian Case

AbstractThis study compares metrics for environmental noise diagnosis in schools at airport vicinity. The goal is to analyze and identify the most suitable criteria for scaling aircraft noise impact over schools, during landing and take-off operations. A Brazilian case study is conducted, based on the noise mapping and sound level verification. The day-night average noise level (DNL) and the time above limit (TA) are investigated using acoustic simulation and noise mapping and in order to identify the critical receivers. Results of DNL and TA for two schools at airport surroundings show that the criteria adopted by the municipal and airport authorities to describe the airport noise are unsatisfactory and do not reflect the intermittent behavior of this type of noise. It was verified that individual receiver analysis, based on noise interruptions thought TA parameter is more suitable for evaluation of noise impact over schools at airport vicinity.

scholarly journals Physician-Related Variability in the Outcomes of an Invasive Treatment for Neck and Back Pain: A Multi-Level Analysis of Data Gathered in Routine Clinical Practice

2021 ◽  
Vol 18 (8) ◽  
pp. 3855
Author(s):  
Ana Royuela Vicente ◽  
Francisco M. Kovacs ◽  
Jesús Seco-Calvo ◽  
Borja M. Fernández-Félix ◽  
Víctor Abraira ◽  
...  
Keyword(s):  
Back Pain ◽  
Regression Models ◽  
Intraclass Correlation ◽  
Spinal Pain ◽  
Routine Clinical Practice ◽  
Invasive Treatment ◽  
Logistic Regression Models ◽  
Training Standards ◽  
Multi Level ◽  
Level Analysis

Neuro-reflexotherapy (NRT) is a proven effective, invasive treatment for neck and back pain. To assess physician-related variability in results, data from post-implementation surveillance of 9023 patients treated within the Spanish National Health Service by 12 physicians were analyzed. Separate multi-level logistic regression models were developed for spinal pain (SP), referred pain (RP), and disability. The models included all patient-related variables predicting response to NRT and physician-related variables. The Intraclass Correlation Coefficient (ICC) and the Median Odds Ratio (MOR) were calculated. Adjusted MOR (95% CI) was 1.70 (1.47; 2.09) for SP, 1.60 (1.38; 1.99) for RP, and 1.65 (1.42; 2.03) for disability. Adjusted ICC (95%CI) values were 0.08 (0.05; 0.15) for SP, 0.07 (0.03; 0.14) for RP, and 0.08 (0.04; 0.14) for disability. In the sensitivity analysis, in which the 6920 patients treated during the physicians’ training period were excluded, adjusted MOR was 1.38 (1.17; 1.98) for SP, 1.37 (1.12; 2.31) for RP, and 1.25 (1.09; 1.79) for disability, while ICCs were 0.03 (0.01; 0.14) for SP, 0.03 (0.00; 0.19) for RP, and 0.02 (0.00; 0.10) for disability. In conclusion, the variability in results obtained by different NRT-certified specialists is reasonable. This suggests that current training standards are appropriate.

Annoyingness of Aircraft Noise in Relation to Cognitive Activity

1986 ◽  
Vol 63 (2) ◽  
pp. 599-616
Author(s):  
Malcolm D. Arnoult ◽  
Lynne G. Gillfillan ◽  
James W. Voorhees
Keyword(s):  
Test Anxiety ◽  
Cognitive Activity ◽  
Motor Task ◽  
Aircraft Noise ◽  
Cognitive Tasks ◽  
Performance Difference ◽  
Point Scale ◽  
Embedded Figures ◽  
Continuous Noise ◽  
The Individual

College students were exposed by means of headphones to two kinds of aircraft noise (helicopter and jet) at three levels of loudness (60, 70, and 80 dB) while engaging in two tests of intelligibility and 12 cognitive tasks. In addition, the annoyingness of the noise was rated on a seven-point scale for each source/loudness combination in each task. Individual-differences measures (embedded figures, locus-of-control, and test anxiety) were also obtained. No performance difference related to noise was obtained in any of the cognitive tasks, and using the individual-difference measures as co-variates made no difference. In a second experiment a limited set of five modified cognitive tasks was used, again without producing any significant results. Finally, a third experiment utilized four cognitive tasks, a perceptual-motor task (Rotary Tracking) and intermittent rather than continuous noise, and yielded the same results. It was concluded that the failure to find performance differences on the cognitive tasks was probably due to the fact that concern for the welfare of the subjects limited the stimuli to loudness levels that were too low to be effective.

COMPARISON OF OBSERVATIONS AND MACROCLIMATIC MODEL ESTIMATES OF MONTHLY WINTER SOIL TEMPERATURES AT OTTAWA

1985 ◽  
Vol 65 (1) ◽  
pp. 109-122 ◽  
Author(s):  
L. M. DWYER ◽  
H. N. HAYHOE
Keyword(s):  
Snow Cover ◽  
Predictive Models ◽  
Regression Models ◽  
Stepwise Regression ◽  
Regression Coefficients ◽  
Data Sets ◽  
Regression Equations ◽  
Grass Cover ◽  
Partial Regression ◽  
Soil Temperatures

Estimates of monthly soil temperatures under short-grass cover across Canada using a macroclimatic model (Ouellet 1973a) were compared to monthly averages of soil temperatures monitored over winter at Ottawa between November 1959 and April 1981. Although the fit between monthly estimates and Ottawa observations was generally good (R for all months and depths 0.10, 0.20, 0.50, 1.00 and 1.50 m was 0.90), it was noted that midwinter estimates were generally below observed temperatures at all soil depths. Data sets used in the development of the original Ouellet (1973a) multiple regression equations were collected from stations across Canada, many of which have reduced snow cover. It was found that the buffering capability of the snow cover accumulated at Ottawa during the winter months was underestimated by the pertinent partial regression coefficients in these equations. The coefficients were therefore modified for the Ottawa station during the winter months. The resultant regression models were used to estimate soil temperature during the winters of 1981–1982 and 1982–1983. Although the Ottawa-based models included fewer variables because of the smaller data base available from a single site, comparisons of model estimates and observations were good (R = 0.84 and 0.91) and midwinter estimates were not consistently underestimated as they were using the original Ouellet (1973a) model. Reliable monthly estimates of soil temperatures are important since they are a necessary input to more detailed predictive models of daily soil temperatures. Key words: Regression model, snowcover, stepwise regression, variable selection

Multi-level cognitive concept learning method oriented to data sets with fuzziness: a perspective from features

2019 ◽  
Vol 24 (5) ◽  
pp. 3753-3770
Author(s):  
Eric C. C. Tsang ◽  
Bingjiao Fan ◽  
Degang Chen ◽  
Weihua Xu ◽  
Wentao Li
Keyword(s):  
Concept Learning ◽  
Data Sets ◽  
Learning Method ◽  
Multi Level

Prediction and simulation of aircraft noise in the international Eskisehir Hasan Polatkan airport (LTBY)

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Halil Yalcin Akdeniz ◽  
Mehmet Ziya Sogut ◽  
Onder Turan
Keyword(s):  
Noise Level ◽  
Time Frame ◽  
Aircraft Noise ◽  
International Standards ◽  
Civil Aviation ◽  
Time Zone ◽  
Noise Emission ◽  
Night Time ◽  
Noise Mapping ◽  
Content Type

Purpose In recent years, in parallel with the increasing air traffic and the number of passengers in air transport, the number of people exposed to aircraft-induced noise has increased significantly. Especially people living in the areas close to the airports are affected by noise emission during the landing, take-off, taxi and ground operations. Negative effects of noise such as sleep disturbance, lack of concentration, anxiety and high blood pressure cardiac diseases were determined directly or indirectly for human health. For this reason, examining the noise effect caused by aircraft and determining the necessary measures to be taken is very important for the sustainable development of aviation. In the International Eskisehir Hasan Polatkan Airport (LTBY), this paper aims to calculate a noise mapping following international standards in line with the directives of the International Civil Aviation Organization (ICAO). Also, Annex 8, “Airworthiness of Aircrafts” and Annex 16, “Environmental Protection Volume 1 Aircraft Noise”, which were taken at the International Civil Aviation Convention, were proposed to determine the exposure caused by aircraft noise. Design/methodology/approach In this paper, noise levels for the day (07.00–19.00), evening (19.00–23.00) and night (23.00–07.00) period around LTBY were predicted and calculated by the use of the IMMI software according to the “ECAC Doc. 29-Interim” method for the prediction and computation of the aircraft noise. Findings According to the calculated/mapped values, in the 24 hours (Lden), the noise level is 65 dB (A) and above. In the day time zone, the noise level is 63 dB (A) and above. When the calculations for the evening time zone are examined, the noise level is above 58 dB (A). When the calculations for the night time frame are examined, it is calculated that there is no dwelling that is affected by the noise level above 53 dB (A). Practical implications Along with future improvements, it is recommended to be applied to other civil airports. Originality/value To the best of the authors’ knowledge, there is no previous research in the literature on aircraft noise mapping of LTBY. Also, unlike the software commonly used in other works in the literature, IMMI software was used in this study. Such investigations should be carried out in other civil airports in the coming years to struggle with noise emissions and noise control. If noise boundary values are exceeded, action plans should be developed for a sustainable aviation concept. Along with future improvements, it is recommended to be applied to other civil airports.

scholarly journals Validating Aircraft Noise Models

Proceedings ◽  
2020 ◽  
Vol 59 (1) ◽  
pp. 12
Author(s):  
Ran Giladi ◽  
Eliav Menachi
Keyword(s):  
Noise Level ◽  
Health Hazard ◽  
Aircraft Noise ◽  
Noise Model ◽  
Aviation Industry ◽  
Noise Abatement ◽  
Statistical Variation ◽  
Huge Impact ◽  
Aircraft Type ◽  
Noise Models

Aircraft noise, especially at takeoffs and landings, became a major environmental nuisance and a health hazard for the population around metropolitan airports. In the battle for a better quality of life, wellbeing, and health, aircraft noise models are essential for noise abatement, control, enforcement, evaluation, policy-making, and shaping the entire aviation industry. Aircraft noise models calculate noise and exposure levels based on aircraft types, engines and airframes, aircraft flight paths, environment factors, and more. Validating the aircraft noise model is a mandatory step towards the model credibility, especially when these models play such a key role with a huge impact on society, economy, and public health. Yet, no validation procedure was offered, and it turns out to be a challenging task. The actual, measured, aircraft noise level is known to be subject to statistical variation, even for the same aircraft type at the same situation and flight phase, executing the same flight procedure, with similar environmental factors and at the same place. This study tries to validate the FAA’s AEDT aircraft noise model, by trying to correlate the specific flight path of an aircraft with its measured noise level. The results show that the AEDT noise model underestimates the actual noise level, and four validation steps should be performed to correct or tune aircraft noise databases and flight profiles.

Self-employment and Civic Inclination

2020 ◽  
Vol 63 (5) ◽  
pp. 719-737
Author(s):  
F. Carson Mencken ◽  
Bethany Smith ◽  
Charles M. Tolbert
Keyword(s):  
Regression Models ◽  
Political Activism ◽  
The Self ◽  
Data Sets ◽  
County Level ◽  
Cross Sectional ◽  
Individual Level ◽  
Self Employment ◽  
Level Data ◽  
Building Community

We test whether the self-employed have higher levels of civic inclination (trust, political activism, community closeness, community participation) compared to workers from the private sector. We examine the civic inclinations of the self-employed with two national cross-sectional data sets. We use a variety of discrete and continuous regression models. We find that the self-employed have higher levels of political activism, feel closer to neighbors and family, and have greater odds of engaging to solve community problems. We fail to detect differences in donating money, attending community events, and closeness to friends. Previous research has concluded with county-level data that the self-employed are important actors in building community and creating social capital. Our results add to this literature by showing that the self-employed have higher levels of civic inclination with individual-level data. Implications for theory and research are discussed.

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