62 research outputs found
ARIA 2016: Care pathways implementing emerging technologies for predictive medicine in rhinitis and asthma across the life cycle
The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma a
Track D Social Science, Human Rights and Political Science
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd
Mineralogia e cristalografia da fração argila de horizontes coesos de solos nos tabuleiros costeiros
Contribution des informations expérimentales et expertes à l'amélioration des modÚles linéaires d'étalonnage multivarié en spectrométrie
(trad auto)The spectra contain information on sample composition. This information is extracted using a first family of chemometric tools, calibrations. A second family of tools, pre-processing, is designed to remove harmful spectral information. Calibrations and pre-processing are based on two types of information: (1) experimental information based on experience; (2) expert information based on a priori knowledge. The objective of the thesis is to study the complementarities and synergies between these two types of information. After a bibliographical study, a general model common to calibrations and pre-treatments is proposed. The useful or harmful information contained in a spectrum is obtained by orthogonal projection of this spectrum (according to a metric S) on a matrix P whose columns form a base of the vector space associated with the useful or harmful information. Depending on the case, useful information is kept while harmful information is eliminated. The general model is then implemented by two new methods. IDC-Improved Direct Calibration is a direct calibration method using both experimental and expert information. Then VODKA-PLSR is a generalization of PLSR. A vector r is highlighted, it allows to include expert information in the model. In conclusion, this work provides a more synthetic view of existing models, proposes two new calibration models and opens up many possibilities for creating new calibration and pre-treatment models"Les spectres contiennent de l'information sur la composition d'échantillons. Cette information est extraite au moyen d'une premiÚre famille d'outils chimiométriques, les étalonnages. Une deuxiÚme famille d'outils, les prétraitements, est destinée à enlever une information spectrale nuisible. Etalonnages et prétraitements sont construits à partir de deux types d'informations : (1) les informations expérimentales basées sur l'expérience; (2) les informations expertes basées sur la connaissance a priori. L'objectif de la thÚse est d'étudier les complémentarités et synergies entre ces deux types d'informations. AprÚs une étude bibliographique, un modÚle général commun aux étalonnages et prétraitements est proposé. L'information utile ou nuisible contenue dans un spectre est obtenue par projection orthogonale de ce spectre (selon un métrique S) sur une matrice P dont les colonnes constituent une base de l'espace vectoriel associé à l'information utile ou nuisible. Selon les cas, l'information utile est conservée alors que l'information nuisible est éliminée. Le modÚle général est ensuite implémenté par deux nouvelles méthodes. L'IDC-Improved Direct Calibration est une méthode d'étalonnage direct utilisant conjointement des informations expérimentales et expertes. Ensuite VODKA-PLSR est une généralisation de PLSR. Un vecteur r est mis en évidence, il permet d'inclure de l'information experte dans le modÚle. En conclusion ce travail permet une vision plus synthétique des modÚles existants, propose deux nouveaux modÚles d'étalonnage et ouvre de nombreuses possibilités pour créer de nouveaux modÚles d'étalonnage et de prétraitement
Contribution des informations expérimentales et expertes à l'amélioration des modÚles linéaires d'étalonnage multivarié en spectrométrie
(trad auto)The spectra contain information on sample composition. This information is extracted using a first family of chemometric tools, calibrations. A second family of tools, pre-processing, is designed to remove harmful spectral information. Calibrations and pre-processing are based on two types of information: (1) experimental information based on experience; (2) expert information based on a priori knowledge. The objective of the thesis is to study the complementarities and synergies between these two types of information. After a bibliographical study, a general model common to calibrations and pre-treatments is proposed. The useful or harmful information contained in a spectrum is obtained by orthogonal projection of this spectrum (according to a metric S) on a matrix P whose columns form a base of the vector space associated with the useful or harmful information. Depending on the case, useful information is kept while harmful information is eliminated. The general model is then implemented by two new methods. IDC-Improved Direct Calibration is a direct calibration method using both experimental and expert information. Then VODKA-PLSR is a generalization of PLSR. A vector r is highlighted, it allows to include expert information in the model. In conclusion, this work provides a more synthetic view of existing models, proposes two new calibration models and opens up many possibilities for creating new calibration and pre-treatment models"Les spectres contiennent de l'information sur la composition d'échantillons. Cette information est extraite au moyen d'une premiÚre famille d'outils chimiométriques, les étalonnages. Une deuxiÚme famille d'outils, les prétraitements, est destinée à enlever une information spectrale nuisible. Etalonnages et prétraitements sont construits à partir de deux types d'informations : (1) les informations expérimentales basées sur l'expérience; (2) les informations expertes basées sur la connaissance a priori. L'objectif de la thÚse est d'étudier les complémentarités et synergies entre ces deux types d'informations. AprÚs une étude bibliographique, un modÚle général commun aux étalonnages et prétraitements est proposé. L'information utile ou nuisible contenue dans un spectre est obtenue par projection orthogonale de ce spectre (selon un métrique S) sur une matrice P dont les colonnes constituent une base de l'espace vectoriel associé à l'information utile ou nuisible. Selon les cas, l'information utile est conservée alors que l'information nuisible est éliminée. Le modÚle général est ensuite implémenté par deux nouvelles méthodes. L'IDC-Improved Direct Calibration est une méthode d'étalonnage direct utilisant conjointement des informations expérimentales et expertes. Ensuite VODKA-PLSR est une généralisation de PLSR. Un vecteur r est mis en évidence, il permet d'inclure de l'information experte dans le modÚle. En conclusion ce travail permet une vision plus synthétique des modÚles existants, propose deux nouveaux modÚles d'étalonnage et ouvre de nombreuses possibilités pour créer de nouveaux modÚles d'étalonnage et de prétraitement
Etalonnage direct amélioré
International audienceRegression methods are often used for prediction of concentration of an interest analyte using NIR spectroscopy, the most popular method being PLS regression. Direct calibration methods were never employed since SBC was proposed. We propose another new method called IDC, based on Direct Calibration (DC) improvement
Pretreatments by means of orthogonal projections
This article describes several linear pretreatments based on orthogonal projections. The main differences of these pretreatments lie in the way the information to be removed are identified, using calibration dataset, pure spectra, experimental designs or mathematical models. Removing all the undesired spectral information yields spectra proportional to the net analyte signal, so it is important to collect the most complete information possible, using the complementarities of different approaches. The correction should then be processed with a single Euclidian orthogonal projection that gathers all the information, rather than with successive operations. By embedding Euclidian orthogonal projections into the calibration, it is not necessary to reapply them to new datasets
Improvement of Direct Calibration in spectroscopy
Several linear calibration methods have been proposed for predicting the concentration of a particular compound from a spectrum. Some methods are based on experimental data, such as Partial Least Square Regression. Other methods are based on expert data, e.g. Direct Calibration. This article proposes a new method, called Improved Direct Calibration, which uses expert and experimental information. It performs a projection onto the pure interest spectrum, after correcting it from inïŹuence factors. No calibration dataset is necessary to build this model. This method has been successfully applied to the quantiïŹcation of ethanol in musts during fermentation, using near infra-red spectrometry
Utilisation des paramétres physiques pour la caractérisation de la véraison des baies de raisin
National audienc
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