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Visar resultat 1 - 5 av 16 avhandlingar som matchar ovanstående sökkriterier.

1. 1. Exploration of Multivariate Evaluation Techniques in Surface Enhanced Raman Spectroscopy (SERS)

   Författare :Aamer Abbas; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; carotenoids; surface enhanced raman spectroscopy; orthogonal partial least squares; target orthogonal partial least squares; chemical imaging; OPLS; PLS; cytarbine; raman; hyperspectral; idarubicin; T-OPLS; doxorubicin; lymphocytes; multivariate analysis; 4-mercaptobenzonitrile; internal standard;

   Sammanfattning : .... LÄS MER

3. 2. Statistical Methods for Designed Experiments and Spectroscopic Data

   Författare :Tobias Adolfsson; Göteborgs universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; saturated orthogonal designs; multiple inference; step-down testing; partial least squares; principal components regression; multiple inference;

   Sammanfattning : This thesis consists of six papers related to saturated orthogonal designs, spectroscopic and high dimension data analysis. The first two papers deals with testing procedures for saturated orthogonal designs. Both the presented methods controls the multiple level of significance. LÄS MER

4. 3. Practical application of machine learning for analyses of biological matrices and environmental phenomena

   Författare :Alexandra Walsh; Göteborgs universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Machine learning; Surface enhanced Raman spectroscopy; Acute lymphatic leukaemia; Volatile halogenated organic carbons; Marine algae; Doxorubicin; Principal component analysis; Multivariate statistics; Design of experiments; Waterlogged archaelogical wood; Transposed orthogonal partial least squares;

   Sammanfattning : This thesis presents research aimed at forwarding an understanding of machine learning methods as a method of studying complex matrices and environmental phenomena. A number of machine learning methods in the form of linear projection algorithms and statistical experimental designs were applied for qualitative analysis of different matrices. LÄS MER

5. 4. Multivariate spectroscopic methods for the analysis of solutions

   Författare :Kent Wiberg; Sven Jacobsson; Lars Nørgaard; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Chemometrics; UV-Vis spectroscopy; Multivariate calibration; Lidocaine; Identity; Content; PLS; SIMCA; Non-column; Diode array UV spectroscopy; DAD; Control sample; High Capacity Analysis HCA ; Fluorescence spectroscopy; Albumin; Immunoglobulin G; HPLC-DAD; Prilocaine; Peak purity determination; PCA; PARAFAC; Partial separation; Curve resolution; Analytical chemistry; Analytisk kemi;

   Sammanfattning : In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. LÄS MER

7. 5. Novel variable influence on projection (VIP) methods in OPLS, O2PLS, and OnPLS models for single- and multi-block variable selection : VIPOPLS, VIPO2PLS, and MB-VIOP methods

   Författare :Beatriz Galindo-Prieto; Johan Trygg; Lennart Eriksson; Paul Geladi; Olav M. Kvalheim; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Variable influence on projection; VIP; MB-VIOP; orthogonal projections to latent structures; OPLS; O2PLS; OnPLS; variable selection; variable importance in multiblock regression; Computer Science; datalogi;

   Sammanfattning : Multivariate and multiblock data analysis involves useful methodologies for analyzing large data sets in chemistry, biology, psychology, economics, sensory science, and industrial processes; among these methodologies, partial least squares (PLS) and orthogonal projections to latent structures (OPLS®) have become popular. Due to the increasingly computerized instrumentation, a data set can consist of thousands of input variables which contain latent information valuable for research and industrial purposes. LÄS MER