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Risk assessment of Cryptosporidium p...

Janes, Kevin Robert.

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Risk assessment of Cryptosporidium parvum using neural networks.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Risk assessment of Cryptosporidium parvum using neural networks./
Author:	Janes, Kevin Robert.
Description:	96 p.
Notes:	Source: Masters Abstracts International, Volume: 46-03, page: 1607.
Contained By:	Masters Abstracts International46-03.
Subject:	Engineering, Biomedical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR33263
ISBN:	9780494332634

Risk assessment of Cryptosporidium parvum using neural networks.
Janes, Kevin Robert.

Risk assessment of Cryptosporidium parvum using neural networks. - 96 p.

Source: Masters Abstracts International, Volume: 46-03, page: 1607.

Thesis (M.Sc.)--University of Alberta (Canada), 2007.

Cryptosporidium parvum is a waterborne pathogen that has caused a significant number of outbreaks worldwide. A risk assessment of Cryptosporidium parvum exposure through drinking water requires consideration of oocyst concentrations at source waters, the effectiveness of drinking water treatment, tap water consumption, and the dose response relationship. In this thesis neural network models were developed to model tap water consumption and the disinfection of Cryptosporidium parvum using chlorine dioxide and ozone. These models were used for exposure assessment to determine daily doses of oocysts from tap water consumption. A dose response neural network model was developed for several strains of Cryptosporidium parvum. A risk characterization that considered a variety of exposure scenarios was completed using the tap water consumption, disinfection and dose response neural network models. The risk characterization produced point estimates for the daily probability of infection assuming exposure to Cryptosporidium parvum.

ISBN: 9780494332634Subjects--Topical Terms:

1017684
Engineering, Biomedical.

Risk assessment of Cryptosporidium parvum using neural networks.
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035 $a (UMI)AAIMR33263
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100 1 $a Janes, Kevin Robert. $3 1263013
245 1 0 $a Risk assessment of Cryptosporidium parvum using neural networks.
300 $a 96 p.
500 $a Source: Masters Abstracts International, Volume: 46-03, page: 1607.
502 $a Thesis (M.Sc.)--University of Alberta (Canada), 2007.
520 $a Cryptosporidium parvum is a waterborne pathogen that has caused a significant number of outbreaks worldwide. A risk assessment of Cryptosporidium parvum exposure through drinking water requires consideration of oocyst concentrations at source waters, the effectiveness of drinking water treatment, tap water consumption, and the dose response relationship. In this thesis neural network models were developed to model tap water consumption and the disinfection of Cryptosporidium parvum using chlorine dioxide and ozone. These models were used for exposure assessment to determine daily doses of oocysts from tap water consumption. A dose response neural network model was developed for several strains of Cryptosporidium parvum. A risk characterization that considered a variety of exposure scenarios was completed using the tap water consumption, disinfection and dose response neural network models. The risk characterization produced point estimates for the daily probability of infection assuming exposure to Cryptosporidium parvum.
590 $a School code: 0351.
650 4 $a Engineering, Biomedical. $3 1017684
650 4 $a Engineering, Sanitary and Municipal. $3 1018731
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710 2 0 $a University of Alberta (Canada). $3 626651
773 0 $t Masters Abstracts International $g 46-03.
790 $a 0351
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