Analysis of bioremediation respirometric data using wavelets
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | |
Tipo de documento: | Livro |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/86005 |
Resumo: | The study of biodegradation using respirometry generates an enormous quantity of data, with several millions of registers for each variable. We have been treating this enormous amount of information using several mathematical techniques. The first step is always the filtration of the data in order to eliminate anomalies strange to the process, such as voltage breakages. The length of the data can be reduced using conventional statistical methodologies or by using wavelets or by combination of both. We have been applying wavelet analysis to signals generated by the respirometry of biodegradation with three different purposes: (i) as a method of data filtration or denoising that keeps the inner core structure of the information without aliasing; (ii) as an interpretation tool; (iii) to detect variation patterns at smaller scales. The synthesized signals can be subsequently used to create digital data-driven mathematical models, either single input-single output or multiple input-multiple output, using the tools of the system identification theory. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Analysis of bioremediation respirometric data using waveletsCiências da terra e ciências do ambienteEarth and related Environmental sciencesThe study of biodegradation using respirometry generates an enormous quantity of data, with several millions of registers for each variable. We have been treating this enormous amount of information using several mathematical techniques. The first step is always the filtration of the data in order to eliminate anomalies strange to the process, such as voltage breakages. The length of the data can be reduced using conventional statistical methodologies or by using wavelets or by combination of both. We have been applying wavelet analysis to signals generated by the respirometry of biodegradation with three different purposes: (i) as a method of data filtration or denoising that keeps the inner core structure of the information without aliasing; (ii) as an interpretation tool; (iii) to detect variation patterns at smaller scales. The synthesized signals can be subsequently used to create digital data-driven mathematical models, either single input-single output or multiple input-multiple output, using the tools of the system identification theory.20082008-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/86005engMaria Cristina da Costa VilaAntónio Manuel Antunes Fiúzainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T13:42:57Zoai:repositorio-aberto.up.pt:10216/86005Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:46:25.623278Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Analysis of bioremediation respirometric data using wavelets |
title |
Analysis of bioremediation respirometric data using wavelets |
spellingShingle |
Analysis of bioremediation respirometric data using wavelets Maria Cristina da Costa Vila Ciências da terra e ciências do ambiente Earth and related Environmental sciences |
title_short |
Analysis of bioremediation respirometric data using wavelets |
title_full |
Analysis of bioremediation respirometric data using wavelets |
title_fullStr |
Analysis of bioremediation respirometric data using wavelets |
title_full_unstemmed |
Analysis of bioremediation respirometric data using wavelets |
title_sort |
Analysis of bioremediation respirometric data using wavelets |
author |
Maria Cristina da Costa Vila |
author_facet |
Maria Cristina da Costa Vila António Manuel Antunes Fiúza |
author_role |
author |
author2 |
António Manuel Antunes Fiúza |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Maria Cristina da Costa Vila António Manuel Antunes Fiúza |
dc.subject.por.fl_str_mv |
Ciências da terra e ciências do ambiente Earth and related Environmental sciences |
topic |
Ciências da terra e ciências do ambiente Earth and related Environmental sciences |
description |
The study of biodegradation using respirometry generates an enormous quantity of data, with several millions of registers for each variable. We have been treating this enormous amount of information using several mathematical techniques. The first step is always the filtration of the data in order to eliminate anomalies strange to the process, such as voltage breakages. The length of the data can be reduced using conventional statistical methodologies or by using wavelets or by combination of both. We have been applying wavelet analysis to signals generated by the respirometry of biodegradation with three different purposes: (i) as a method of data filtration or denoising that keeps the inner core structure of the information without aliasing; (ii) as an interpretation tool; (iii) to detect variation patterns at smaller scales. The synthesized signals can be subsequently used to create digital data-driven mathematical models, either single input-single output or multiple input-multiple output, using the tools of the system identification theory. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008 2008-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/86005 |
url |
https://hdl.handle.net/10216/86005 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
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1799135781512544256 |