Master Degree / Yüksek Lisans Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/11147/3008

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Access Right: Open AccessSubject: search.filters.subject.Near infrared spectroscopy

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  • Master Thesis
    In-Depth Investigation of the Effects of Different Preprocessing Strategies on Infrared Spectroscopic Data
    (01. Izmir Institute of Technology, 2021) Deniz, Elin İlayda; Özdemir, Durmuş; Özdemir, Durmuş; 04.01. Department of Chemistry; 01. Izmir Institute of Technology; 04. Faculty of Science
    Whenever collecting experimental data, they may contain several spurious sources of variability which can hinder the extraction of the desired relevant information so that it is rarely the case that they can be processed as such by chemometrics approaches. In recent years, pre-processing techniques has become an integral part of chemometrics modeling with the purpose of providing better endmodels through fundamental knowledge for Near-Infrared (NIR) users. The aim of pre-processing techniques is to improve success of multivariate regression by reducing undesired physical phenomena in the spectra. This thesis describes the theory of present pre-processing techniques and compares the qualitative and quantitative results of their application. Mean centering, scatter-correction methods and spectral derivatives are the instances of those pre-processing techniques used in this thesis. Those techniques and combinations of them have been applied in order to find the best pre-processing strategy. To be able to observe the results and compare the effects of the applied methods, Partial Least Squares and Genetic Inverse Laast Squares are carried out as multivariate calibration methods. When comparing the calibration results of raw data with pre-processing techniques applied data, decreasement standard eror of prediction (SEP) values observed after appliying those techniques, which is good manner. However, better in comparison, t-Test: Paired Two Sample for Means applied. The results demontrates that there is no significant difference within 95% confidence level.
  • Master Thesis
    Development of Real Time Blood Vessel Imaging System for Early Diagnosis of Vascular Diseases
    (01. Izmir Institute of Technology, 2020) Gümüş, Abdurrahman; Gümüş, Abdurrahman; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Disorders in the circulatory system may cause various diseases and tissue damage. The early detection of abnormalities in blood circulation has an important role in terms of treatment and also raising awareness of the patient. Vascular imaging methods used by today's technology are invasive, and/ or radiation-based. As an alternative to high-cost near infrared (NIR) vascular imaging devices in the market, a microcomputer-based, real-time, non-contact and safe vascular imaging system has been developed with low- cost. Due to the higher absorption coefficient of blood than skin and fat and also the differences in the spectra of oxy and deoxyhemoglobin in blood, the vascular structures were obtained using light at NIR region. A device, which uses NIR LED light operated at 850 nm, was designed using optical and electronic components. Image and video analysis were performed using OpenCV, which is an open-source software library, and data visualization libraries. Tests were carried out to optimize the best imaging conditions for the device. To be able to show abnormalities in the vascular structures and to test the effectiveness of the device, "diabetes", which can cause various vascular disease complications, was selected. Superficial vascular structures were observed in the near infrared images captured from people at different stages of this disease. As expected, the vessel images captured from the participants revealed deterioration in vascular structures in diabetic patients compared to healthy people. In order to make a clear inference about the accuracy of the images, it is necessary to compare them to the angiography images of the individuals and be interpreted by vascular surgery specialist.
  • Master Thesis
    Monitoring the Esterification Reactions of Carboxylic Acids With Alcohols Using Near-Infrared Spectrocopy and Multivariate Calibration Methods
    (Izmir Institute of Technology, 2003) Öztürk, Betül; Öztürk, Betül; Özdemir, Durmuş; Özdemir, Durmuş; 04.01. Department of Chemistry; 04. Faculty of Science; 01. Izmir Institute of Technology
    Simultaneous determination of mixtures of alcohols, acids, esters, and water using near-infrared spectroscopy (NIR) and four different multivariate calibration methods were realized. The four multivariate calibration methods were Genetic Inverse Least Squares (GILS), Genetic Regression (GR), Principle Component Regression (PCR), and Partial Least Squares (PLS). Four different esterification reactions were investigated. These are methyl acetate, ethyl acetate, propyl acetate, and butyl acetate.The sample set contains 40 ternary mixtures of these esterification processes. Duplicate measurements were done for each sample and 80 NIR absorbance spectra that cover the range from 4000 to 10000 cm.1 were obtained. Of these 80 spectra, 50 were used as calibration set, 30 were reserved for the prediction purposes. Several calibration methods were built for each component of each esterification reactions. Standard error of calibration (SEC) and standard error of prediction (SEP) were calculated for each calibration model and comparison of these four multivariate calibration methods was done.
  • Master Thesis
    Spectroscopic Determination of Major Nutrients (n, P, K) of Soil
    (Izmir Institute of Technology, 2003) Şen, İlknur; Şen, İlknur; Ertürk, Handan; Ertürk, Handan; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    The aim of this study was to determine the major soil nutrients (nitrogen, phosphorus and potassium) which mainly affect the raw material quality of food, using near infrared reflectance spectroscopy (1000-2500 nm). Genetic inverse least squares and partial least squares were used to predict the concentrations of major soil nutrients.The soil samples, collected from Menemen Application and Research Farms, were prepared for the near infrared analysis by using two different methods. According to the first method, two experiments were performed. The soil samples of which were oven dried and screened through a 2 mm sieve, were mixed with NPK fertilizer in the concentration range of 1-15% (wt/wt) (first experiment), and with NH4NO3 and TSP fertilizers in the concentration range of 0.075-0.3% (wt/wt) (second experiment). Using genetic inverse least squares method, regression coefficients of 0.9820, 0.9779 and 0.9906 were obtained for the prediction of nitrogen, phosphorus and potassium concentrations in samples containing NPK fertilizer, respectively. In the second experiment, prediction of nitrogen concentration in samples containing NH4NO3 fertilizer was done reliable with a regression coefficient of 0.8409 using genetic inverse least squares method. On the other hand, regression coefficient of 0.6005 was obtained for the prediction of phosphorus concentration in samples containing TSP fertilizer with the same statistical method.The second method differed from the first one by eliminating the drying of soil samples and moisturizing step following the addition of fertilizers into soil samples. The aim was to prevent baseline shifts in the spectra arising from the moisture changes in the samples. Five types of fertilizer [KNO3, CaNO3, TSP, (NH4)2SO4, NPK] were used in the preparation of samples in the concentration range of 0.02-0.5% (wt/wt). Using genetic inverse least squares method, calibration models produced between the reflectance spectra and the nutrient concentrations had regression coefficients greater than 0.80, however the prediction ability of the models was poor (R2<0.50) except for the samples containing (NH4)2SO4 and NPK fertilizers. The regression coefficients for the prediction of nitrogen and sulfur concentrations in (NH4)2SO4 containing samples were found as 0.8620 and 0.8555, respectively. For the prediction of nitrogen, phosphorus and potassium concentrations in NPK containing samples, the regression coefficients were found as 0.6737, 0.7633 and 0.8724, respectively. The partial least squares method was also used for the prediction of nutrient concentrations in the samples prepared according to the second method. Except samples containing (NH4)2SO4 fertilizer, nitrogen, phosphorus and potassium amounts could not be predicted in the other samples using partial least squares method (R2<0.20). The regression coefficients obtained for the prediction of nitrogen and sulfur amounts in (NH4)2SO4 containing samples were 0.9301.An additional work was carried out with laboratory analyzed soil samples collected from several points of two agricultural fields in Menemen Application and Research Farms. Total nitrogen, extractable phosphorus and exchangeable potassium amounts were determined by Agricultural Engineering Department of Ege University according to the Kjeldahl method, Bingham method and ammonium acetate method, respectively.Predictions of these nutrient concentrations by genetic inverse least squares method were poor (R2< 0.20). Using partial least squares method, the nutrient concentrations could not be predicted (factor number . 0).The results of this study indicate that, near infrared reflectance technique provided rapid, non-destructive and simultaneous determination of nitrogen, phosphorus and potassium concentrations in soil- fertilizer mixtures depending on the sample preparation steps, fertilizer types and concentrations and multivariate calibration methods (genetic inverse least squares and partial least squares methods).