Auflistung nach Autor:in "Kohout, J."
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- KonferenzbeitragHuman and Ecological Risk Assessment, Expert Systems(Informatics for Environmental Protection - Networking Environmental Information, 2005) Dušek, L.; Holoubek, I.; Jarkovský, J.; Koptíková, J.; Kohout, J.; Šmíd, R.; Pavliš, P.; Mužík, J.; Hřebíček, J.The aim of this article is to introduce topic of conference tutorial focused on human and ecological risk assessment. Educational part of the tutorial is designed as methodical overview of risk assessment studies, exposure assessment and analyses of toxic biological effects. Data processing and associated information flow will be demonstrated in practical examples from environmental and epidemiological monitoring. All methodical aspects will be demonstrated and trained in two model case studies, prepared over representative and already published data. Both studies will be supported by information and expert systems that make data sources readily accessible for analyses. First case study is focused on environmental risk assessment and monitoring of surface water quality. Czech nationally distributed expert system TRITON® will be presented as a model solution for processing of very heterogeneous abiotic and biotic data. Seasonally repeated monitoring of physical environment and biological communities from more than 400 river profiles will be used to demonstrate advantages and limits of multivariate analog modelling (searching for and typology of reference sites, calibration of environmental gradient data, etc.). This case study will introduce educational block oriented on processing of biodiversity data. Second case study will address the problems of population human risk assessment and epidemiological studies. Cancer epidemiology was selected as a model system due to its societal importance. The study will be based on Czech national expert system (SVOD®) developed to process representative national cancer registry (standardized representative database collected since 1977) that allows quantitative evaluation of long-term epidemiological trends. Processing of population data using modern technologies (multivariate modelling and artificial intelligence techniques) will be demonstrated.