On the data library transfer in Laser-Induced Breakdown Spectroscopy applications
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F18%3APU130615" target="_blank" >RIV/00216305:26620/18:PU130615 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
On the data library transfer in Laser-Induced Breakdown Spectroscopy applications
Popis výsledku v původním jazyce
Laser-Induced Breakdown Spectroscopy (LIBS) serves as an exceptional platform for a fast sample analysis. Detected laser-induced plasma (LIP) spectrum is composed of unique information (i.e. chemical fingerprint) characterizing the sample from which it originates. Multivariate Data Analysis (MVDA) algorithms are becoming an inevitable part of the spectroscopic analysis. A successful MVDA implementation is based on the well-balanced data pre-processing (outlier filtering, signal standardization, variable down-selection, etc.). This is consecutively followed by the model creation and further classification and a quantitative analysis. Nevertheless, data and related statistical models are not transferable among LIBS instruments. This is the main drawback of LIBS; in other words, it is not possible to create a model using a data from one system and classify/quantify unknown data obtained using another system. In this project, we focus on the development of a protocol that will enable data library transfe
Název v anglickém jazyce
On the data library transfer in Laser-Induced Breakdown Spectroscopy applications
Popis výsledku anglicky
Laser-Induced Breakdown Spectroscopy (LIBS) serves as an exceptional platform for a fast sample analysis. Detected laser-induced plasma (LIP) spectrum is composed of unique information (i.e. chemical fingerprint) characterizing the sample from which it originates. Multivariate Data Analysis (MVDA) algorithms are becoming an inevitable part of the spectroscopic analysis. A successful MVDA implementation is based on the well-balanced data pre-processing (outlier filtering, signal standardization, variable down-selection, etc.). This is consecutively followed by the model creation and further classification and a quantitative analysis. Nevertheless, data and related statistical models are not transferable among LIBS instruments. This is the main drawback of LIBS; in other words, it is not possible to create a model using a data from one system and classify/quantify unknown data obtained using another system. In this project, we focus on the development of a protocol that will enable data library transfe
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
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OECD FORD obor
10406 - Analytical chemistry
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2018
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů