Noise annoyance and perceived environmental quality. Inventory 2003

The most annoying source of noise in the Netherlands is road traffic. Of the Dutch population aged 16 years and older 29% is severely annoyed by this type of noise. Second and third most annoying noise sources are air traffic and neighbours (both 12% severely annoyed). Mopeds are the most annoying source of road traffic noise. Nineteen percent of the Dutch population is severely annoyed by the noise of mopeds, followed by motorbikes (11% severely annoyed) and lorries (10% severely annoyed). The severe annoyance from mopeds, highways and building and demolition sites exhibits a rising trend since 1993. For military planes, cars and busses severe annoyance has declined since 1993. In addition to noise annoyance, mopeds are the most important source of sleep disturbance; 7% of the respondents report severe sleep disturbance by moped noise. The (loud and reckless) behaviour of moped drivers is also an important source of annoyance. These are some results from a periodic national survey on annoyance, sleep disturbance, risk perception and of the quality of the living environment. In general, Dutch inhabitants are satisfied with their homes and residential areas. The average score for satisfaction with the residential area is 7,7 on a scale from 0-10. People are most dissatisfied with parking facilities in the neighbourhood (18%), public transport (16%) and space for playgrounds in the neighbourhood (12%). In comparison with the last survey (in 1998), residential satisfaction has increased.Naar schatting zijn 3,7 miljoen Nederlanders van 16 jaar en ouder (29%) ernstig gehinderd door het geluid van wegverkeer. Na wegverkeer veroorzaken vliegverkeer en buren het vaakst ernstige hinder (beide 12%). Bromfietsen staan met 19% ernstige hinder op de eerste plaats in de top tien van meest hinderlijke geluidbronnen. Op de tweede en derde plaats volgen motoren (11% ernstige hinder) en vrachtauto's (10% ernstige hinder). Ernstige hinder door het geluid van bromfietsen, snelwegen en bouw- en sloopterreinen vertoont vanaf 1993 een stijgende trend. Voor militaire vliegtuigen, personenauto's en bussen is er sprake van een dalende trend. Brommers zijn naast geluidhinder ook de belangrijkste bron van slaapverstoring. Bij 7% van de respondenten wordt de slaap ernstig verstoord door het geluid van brommers. Naast geluid blijkt met name het (roekeloos en luidruchtig) gedrag van bromfietsrijders een belangrijke hinderbron. Dit zijn enkele bevindingen uit een periodiek landelijk onderzoek naar de verstoringen van de leefomgeving. Er is ook gevraagd naar de tevredenheid met de woonomgeving. Nederlanders zijn in het algemeen tevreden met hun woning en woonomgeving. Deze wordt beoordeeld met een gemiddelde van 7,7 op een schaal van 0-10. Het meest ontevreden is men over de parkeergelegenheden in de buurt (18%), het openbaar vervoer (16%) en de ruimte voor speelgelegenheid in de buurt (12%). Ten opzichte van de vorige peiling in 1998 is de tevredenheid over de woning en de woonomgeving toegenomen

CNN-based Landmark Detection in Cardiac CTA Scans

Fast and accurate anatomical landmark detection can benefit many medical image analysis methods. Here, we propose a method to automatically detect anatomical landmarks in medical images. Automatic landmark detection is performed with a patch-based fully convolutional neural network (FCNN) that combines regression and classification. For any given image patch, regression is used to predict the 3D displacement vector from the image patch to the landmark. Simultaneously, classification is used to identify patches that contain the landmark. Under the assumption that patches close to a landmark can determine the landmark location more precisely than patches further from it, only those patches that contain the landmark according to classification are used to determine the landmark location. The landmark location is obtained by calculating the average landmark location using the computed 3D displacement vectors. The method is evaluated using detection of six clinically relevant landmarks in coronary CT angiography (CCTA) scans : the right and left ostium, the bifurcation of the left main coronary artery (LM) into the left anterior descending and the left circumflex artery, and the origin of the right, non-coronary, and left aortic valve commissure. The proposed method achieved an average Euclidean distance error of 2.19 mm and 2.88 mm for the right and left ostium respectively, 3.78 mm for the bifurcation of the LM, and 1.82 mm, 2.10 mm and 1.89 mm for the origin of the right, non-coronary, and left aortic valve commissure respectively, demonstrating accurate performance. The proposed combination of regression and classification can be used to accurately detect landmarks in CCTA scans

CNN-based Landmark Detection in Cardiac CTA Scans

Fast and accurate anatomical landmark detection can benefit many medical image analysis methods. Here, we propose a method to automatically detect anatomical landmarks in medical images. Automatic landmark detection is performed with a patch-based fully convolutional neural network (FCNN) that combines regression and classification. For any given image patch, regression is used to predict the 3D displacement vector from the image patch to the landmark. Simultaneously, classification is used to identify patches that contain the landmark. Under the assumption that patches close to a landmark can determine the landmark location more precisely than patches further from it, only those patches that contain the landmark according to classification are used to determine the landmark location. The landmark location is obtained by calculating the average landmark location using the computed 3D displacement vectors. The method is evaluated using detection of six clinically relevant landmarks in coronary CT angiography (CCTA) scans : the right and left ostium, the bifurcation of the left main coronary artery (LM) into the left anterior descending and the left circumflex artery, and the origin of the right, non-coronary, and left aortic valve commissure. The proposed method achieved an average Euclidean distance error of 2.19 mm and 2.88 mm for the right and left ostium respectively, 3.78 mm for the bifurcation of the LM, and 1.82 mm, 2.10 mm and 1.89 mm for the origin of the right, non-coronary, and left aortic valve commissure respectively, demonstrating accurate performance. The proposed combination of regression and classification can be used to accurately detect landmarks in CCTA scans

Noise annoyance and perceived environmental quality. Inventory 2003

Naar schatting zijn 3,7 miljoen Nederlanders van 16 jaar en ouder (29%) ernstig gehinderd door het geluid van wegverkeer. Na wegverkeer veroorzaken vliegverkeer en buren het vaakst ernstige hinder (beide 12%). Bromfietsen staan met 19% ernstige hinder op de eerste plaats in de top tien van meest hinderlijke geluidbronnen. Op de tweede en derde plaats volgen motoren (11% ernstige hinder) en vrachtauto's (10% ernstige hinder). Ernstige hinder door het geluid van bromfietsen, snelwegen en bouw- en sloopterreinen vertoont vanaf 1993 een stijgende trend. Voor militaire vliegtuigen, personenauto's en bussen is er sprake van een dalende trend. Brommers zijn naast geluidhinder ook de belangrijkste bron van slaapverstoring. Bij 7% van de respondenten wordt de slaap ernstig verstoord door het geluid van brommers. Naast geluid blijkt met name het (roekeloos en luidruchtig) gedrag van bromfietsrijders een belangrijke hinderbron. Dit zijn enkele bevindingen uit een periodiek landelijk onderzoek naar de verstoringen van de leefomgeving. Er is ook gevraagd naar de tevredenheid met de woonomgeving. Nederlanders zijn in het algemeen tevreden met hun woning en woonomgeving. Deze wordt beoordeeld met een gemiddelde van 7,7 op een schaal van 0-10. Het meest ontevreden is men over de parkeergelegenheden in de buurt (18%), het openbaar vervoer (16%) en de ruimte voor speelgelegenheid in de buurt (12%). Ten opzichte van de vorige peiling in 1998 is de tevredenheid over de woning en de woonomgeving toegenomen.The most annoying source of noise in the Netherlands is road traffic. Of the Dutch population aged 16 years and older 29% is severely annoyed by this type of noise. Second and third most annoying noise sources are air traffic and neighbours (both 12% severely annoyed). Mopeds are the most annoying source of road traffic noise. Nineteen percent of the Dutch population is severely annoyed by the noise of mopeds, followed by motorbikes (11% severely annoyed) and lorries (10% severely annoyed). The severe annoyance from mopeds, highways and building and demolition sites exhibits a rising trend since 1993. For military planes, cars and busses severe annoyance has declined since 1993. In addition to noise annoyance, mopeds are the most important source of sleep disturbance; 7% of the respondents report severe sleep disturbance by moped noise. The (loud and reckless) behaviour of moped drivers is also an important source of annoyance. These are some results from a periodic national survey on annoyance, sleep disturbance, risk perception and of the quality of the living environment. In general, Dutch inhabitants are satisfied with their homes and residential areas. The average score for satisfaction with the residential area is 7,7 on a scale from 0-10. People are most dissatisfied with parking facilities in the neighbourhood (18%), public transport (16%) and space for playgrounds in the neighbourhood (12%). In comparison with the last survey (in 1998), residential satisfaction has increased.Berg M van den VROM-DGM-LM

Cross-sectional associations of objectively measured physical activity, cardiorespiratory fitness and anthropometry in european adults

Objective: To quantify the independent associations between objectively measured physical activity (PA), cardiorespiratory fitness (CRF), and anthropometry in European men and women. Methods: 2,056 volunteers from 12 centers across Europe were fitted with a heart rate and movement sensor at 2 visits 4 months apart for a total of 8 days. CRF (ml/kg/min) was estimated from an 8 minute ramped step test. A cross-sectional analysis of the independent associations between objectively measured PA (m/s2 /d), moderate and vigorous physical activity (MVPA) (%time/d), sedentary time (%time/d), CRF, and anthropometry using sex stratified multiple linear regression was performed. Results: In mutually adjusted models, CRF, PA, and MVPA were inversely associated with all anthropometric markers in women. In men, CRF, PA, and MVPA were inversely associated with BMI, whereas only CRF was significantly associated with the other anthropometric markers. Sedentary time was positively associated with all anthropometric markers, however, after adjustment for CRF significant in women only. Conclusion: CRF, PA, MVPA, and sedentary time are differently associated with anthropometric markers in men and women. CRF appears to attenuate associations between PA, MVPA, and sedentary time. These observations may have implications for prevention of obesity