Zobrazeno 1 - 10
of 122
pro vyhledávání: '"Nina S N Lam"'
Publikováno v:
Environmental Research Communications, Vol 5, Iss 6, p 065013 (2023)
AI fairness is tasked with evaluating and mitigating bias in algorithms that may discriminate towards protected groups. This paper examines if bias exists in AI algorithms used in disaster management and in what manner. We consider the 2017 Hurricane
Externí odkaz:
https://doaj.org/article/6babf93b716b4948b08b65ff40d91d0b
Publikováno v:
PLoS ONE, Vol 7, Iss 10, p e47935 (2012)
We analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of business
Externí odkaz:
https://doaj.org/article/7e7f5388189f4882925e1ac7093a0c4e
Publikováno v:
PLoS ONE, Vol 4, Iss 8, p e6765 (2009)
BACKGROUND: Empirical observations on how businesses respond after a major catastrophe are rare, especially for a catastrophe as great as Hurricane Katrina, which hit New Orleans, Louisiana on August 29, 2005. We analyzed repeated telephone surveys o
Externí odkaz:
https://doaj.org/article/34f97e6a5c72449a9965e8b424d1d561
Autor:
Misbah Ul Hoque, Kisung Lee, Jessica L. Beyer, Sara R. Curran, Katie S. Gonser, Nina S. N. Lam, Volodymyr V. Mihunov, Kejin Wang
Publikováno v:
IEEE Access, Vol 10, Pp 72879-72894 (2022)
The abundance of available information on social media can provide invaluable insights into people’s responses to health information and public health guidance concerning COVID-19. This study examines tweeting patterns and public engagement on Twit
Externí odkaz:
https://doaj.org/article/fbc79e75829549d0a387ef1fe3c9585f
Autor:
Zheye Wang, Nina S. N. Lam, Mingxuan Sun, Xiao Huang, Jin Shang, Lei Zou, Yue Wu, Volodymyr V. Mihunov
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 11, Iss 11, p 570 (2022)
Hurricane Harvey in 2017 marked an important transition where many disaster victims used social media rather than the overloaded 911 system to seek rescue. This article presents a machine-learning-based detector of rescue requests from Harvey-related
Externí odkaz:
https://doaj.org/article/9bcbc01cb6324293b84fa43ddb01f843
Publikováno v:
Remote Sensing, Vol 14, Iss 11, p 2720 (2022)
In the wake of increasingly frequent extreme weather events and population growth in hazard-prone areas worldwide, human communities are faced with growing threats from natural hazards [...]
Externí odkaz:
https://doaj.org/article/60229988c57f4fdebf8219a8c4a69103
Publikováno v:
Journal of Homeland Security and Emergency Management. 20:133-168
We present findings from our 2018 survey of organizations involved in emergency management in areas affected by Hurricanes Sandy and Isaac to gain insight into their social media use throughout the four phases of emergencies – preparedness, respons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3be59b87d6af47781eba06a76b24b78
https://doi.org/10.1515/jhsem-2021-0031
https://doi.org/10.1515/jhsem-2021-0031
Publikováno v:
Annals of GIS. 29:1-20
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31552478d4e14f58e62e2cf11aeaa217
https://doi.org/10.1080/19475683.2023.2165545
https://doi.org/10.1080/19475683.2023.2165545
Publikováno v:
International Journal of Disaster Risk Science. 13:729-742
Twitter can supply useful information on infrastructure impacts to the emergency managers during major disasters, but it is time consuming to filter through many irrelevant tweets. Previous studies have identified the types of messages that can be fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c9d95a15d1f6d19d118aa00f29e86d3
https://doi.org/10.1007/s13753-022-00442-1
https://doi.org/10.1007/s13753-022-00442-1
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 10, Iss 3, p 116 (2021)
Disaster resilience is the capacity of a community to “bounce back” from disastrous events. Most studies rely on traditional data such as census data to study community resilience. With increasing use of social media, new data sources such as Twi
Externí odkaz:
https://doaj.org/article/025129d833734662a87c8e6a6544a126