scholarly journals Towards operational impact forecasting of building damage from winter windstorms in Switzerland

2021 ◽  
Vol 28 (6) ◽  
Author(s):  
Thomas Röösli ◽  
Christof Appenzeller ◽  
David N. Bresch
2020 ◽  
Vol 29 (4) ◽  
pp. 1944-1955 ◽  
Author(s):  
Maria Schwarz ◽  
Elizabeth C. Ward ◽  
Petrea Cornwell ◽  
Anne Coccetti ◽  
Pamela D'Netto ◽  
...  

Purpose The purpose of this study was to examine (a) the agreement between allied health assistants (AHAs) and speech-language pathologists (SLPs) when completing dysphagia screening for low-risk referrals and at-risk patients under a delegation model and (b) the operational impact of this delegation model. Method All AHAs worked in the adult acute inpatient settings across three hospitals and completed training and competency evaluation prior to conducting independent screening. Screening (pass/fail) was based on results from pre-screening exclusionary questions in combination with a water swallow test and the Eating Assessment Tool. To examine the agreement of AHAs' decision making with SLPs, AHAs ( n = 7) and SLPs ( n = 8) conducted an independent, simultaneous dysphagia screening on 51 adult inpatients classified as low-risk/at-risk referrals. To examine operational impact, AHAs independently completed screening on 48 low-risk/at-risk patients, with subsequent clinical swallow evaluation conducted by an SLP with patients who failed screening. Results Exact agreement between AHAs and SLPs on overall pass/fail screening criteria for the first 51 patients was 100%. Exact agreement for the two tools was 100% for the Eating Assessment Tool and 96% for the water swallow test. In the operational impact phase ( n = 48), 58% of patients failed AHA screening, with only 10% false positives on subjective SLP assessment and nil identified false negatives. Conclusion AHAs demonstrated the ability to reliably conduct dysphagia screening on a cohort of low-risk patients, with a low rate of false negatives. Data support high level of agreement and positive operational impact of using trained AHAs to perform dysphagia screening in low-risk patients.


2004 ◽  
Vol 58 (9) ◽  
pp. 1180-1185
Author(s):  
Randyr Reimer ◽  
Kanji Hagiwara

2013 ◽  
Vol 13 (2) ◽  
Author(s):  
Wisyanto Wisyanto

Tsunami which was generated by the 2004 Aceh eartquake has beenhaunting our life. The building damage due to the tsunami could be seenthroughout Meulaboh Coastal Area. Appearing of the physical loss wasclose to our fault. It was caused by the use dan plan of the land withoutconsidering a tsunami disaster threat. Learning from that event, we haveconducted a research on the pattern of damage that caused by the 2004tsunami. Based on the analysis of tsunami hazard intensity and thepattern of building damage, it has been made a landuse planning whichbased on tsunami mitigation for Meulaboh. Tsunami mitigation-based ofMeulaboh landuse planning was made by intergrating some aspects, suchas tsunami protection using pandanus greenbelt, embankment along withhigh plants and also arranging the direction of roads and setting of building forming a rhombus-shaped. The rhombus-shaped of setting of the road and building would reduce the impact of tsunamic wave. It is expected that these all comprehensive landuse planning will minimize potential losses in the future .


2019 ◽  
Vol 57 (9) ◽  
pp. 733-742
Author(s):  
Y. Maida ◽  
T. Mukai ◽  
H. Miyauchi

2020 ◽  
Vol 1 ◽  
pp. 36-51
Author(s):  
Licia Faenza ◽  
Alberto Michelini ◽  
Helen Crowley ◽  
Barbara Borzi ◽  
Marta Faravelli

2021 ◽  
Vol 11 (15) ◽  
pp. 7041
Author(s):  
Baoyintu Baoyintu ◽  
Naren Mandula ◽  
Hiroshi Kawase

We used the Green’s function summation method together with the randomly perturbed asperity sources to sum up broadband statistical Green’s functions of a moderate-size source and predict strong ground motions due to the expected M8.1 to 8.7 Nankai-Trough earthquakes along the southern coast of western Japan. We successfully simulated seismic intensity distributions similar to the past earthquakes and strong ground motions similar to the empirical attenuation relations of peak ground acceleration and velocity. Using these results, we predicted building damage by non-linear response analyses and find that at the regions close to the source, as well as regions with relatively thick, soft sediments such as the shoreline and alluvium valleys along the rivers, there is a possibility of severe damage regardless of the types of buildings. Moreover, the predicted damage ratios for buildings built before 1981 are much higher than those built after because of the significant code modifications in 1981. We also find that the damage ratio is highest for steel buildings, followed by wooden houses, and then reinforced concrete buildings.


2021 ◽  
Vol 13 (5) ◽  
pp. 905
Author(s):  
Chuyi Wu ◽  
Feng Zhang ◽  
Junshi Xia ◽  
Yichen Xu ◽  
Guoqing Li ◽  
...  

The building damage status is vital to plan rescue and reconstruction after a disaster and is also hard to detect and judge its level. Most existing studies focus on binary classification, and the attention of the model is distracted. In this study, we proposed a Siamese neural network that can localize and classify damaged buildings at one time. The main parts of this network are a variety of attention U-Nets using different backbones. The attention mechanism enables the network to pay more attention to the effective features and channels, so as to reduce the impact of useless features. We train them using the xBD dataset, which is a large-scale dataset for the advancement of building damage assessment, and compare their result balanced F (F1) scores. The score demonstrates that the performance of SEresNeXt with an attention mechanism gives the best performance, with the F1 score reaching 0.787. To improve the accuracy, we fused the results and got the best overall F1 score of 0.792. To verify the transferability and robustness of the model, we selected the dataset on the Maxar Open Data Program of two recent disasters to investigate the performance. By visual comparison, the results show that our model is robust and transferable.


2021 ◽  
Vol 150 ◽  
pp. 216-235
Author(s):  
Bruno Albert Neumann-Saavedra ◽  
Dirk Christian Mattfeld ◽  
Mike Hewitt

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