Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1522
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dc.contributor.authorAncuta, Paul-Nicolae-
dc.contributor.authorAtanasescu, Anca-
dc.contributor.authorSorea, Sorin-
dc.contributor.authorStanciu, Danut Iulian-
dc.contributor.authorLucaciu, Irina-
dc.contributor.authorStoica, Catalina-
dc.contributor.authorNita-Lazar, Mihai-
dc.contributor.authorBanciu, Alina-
dc.date.accessioned2019-10-22T09:33:41Z-
dc.date.available2019-10-22T09:33:41Z-
dc.date.issued2019-
dc.identifier.issn1454-8658-
dc.identifier.urihttp://hdl.handle.net/123456789/1522-
dc.descriptionControl Engineering and Applied Informatics, vol. 21, nr. 2, pag. 54-63, 2019en_US
dc.description.abstractEuropean organizations involved in updating water management regulations (WHO, OECD) insist in recent years on the need to improve methods for assessing and managing microbiological , physical and chemical safety of drinking water . Data obtained as a result of water quality monitoring should become a starting point for risk management actions. The paper is mainly focused on presenting a highly efficient software application used to implement a more rapid microbiological method to detect pathogenic bacteria for human health, based on bacterial specific antibody-antigen interaction (Ag-Ab) , namely immunofluorescence technique , and microscopic digital image processing. Laboratory tests have proven that the proposed solution is reliable, stable and time-efficient for preventing microbiological contamination of drinking water. This application software, the method and related instrumentation that the paper presents are parts of a demonstrative modular model which monitors water quality. The first module consists of instrumentation and software that serve a methodology applied to detect pathogenic bacteria in drinking water samples. The second module performs data transmission and storage in a relational database and enables real-time data visualization.en_US
dc.description.sponsorshipThis paper was supported by a grant of the Romanian National Authority for Scientific Research and Innovation CNCS/CCCDI-UEFISCDI, project number PN-III-P2-2.1-PED-2016-0965 within PNCDI III.en_US
dc.language.isoen_USen_US
dc.subjectWater qualityen_US
dc.subjectDigital image processingen_US
dc.subjectDigital filtersen_US
dc.subjectImage segmentationen_US
dc.titleBacterial Monitoring of Drinking Water Sources Using Immunofluorescence technique, Image Processing Software and Web-based Data Visualisationen_US
dc.typeArticleen_US
item.grantfulltextopen-
item.languageiso639-1en_US-
item.openairetypeArticle-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptNational Research and Development Institute for Industrial Ecology, ECOIND-
crisitem.author.deptNational Research and Development Institute for Industrial Ecology, ECOIND-
crisitem.author.deptNational Research and Development Institute for Industrial Ecology, ECOIND-
crisitem.author.deptNational Research and Development Institute for Industrial Ecology, ECOIND-
crisitem.author.orcid0000-0001-6413-3003-
crisitem.author.orcid0000-0003-1352-157X-
crisitem.author.orcid0000-0002-5099-1311-
crisitem.author.orcid0000-0002-2347-508X-
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