Browsing by Subject "Component Analysis"

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    Chemical characterization of Sinopean archaeological common ware
    (2004) Özal, Tuğba Arzu
    Chemical characterization of archaeological common wares is important in order to make quantitative explanations about history and trade relations of nations. Chemistry uses a microscopic point of view by applying spectroscopic methods rather than macroscopic studies that archaeologists usually deal in the structural analysis. The present study is done on the common ware samples which were made of raw clays from Demirci, Sinop, Black Sea Coast of Turkey, because of the geopolitical importance of this region having trade routes. Elemental and mineralogical analyses of the clay-originated common ware samples found in the archaeological excavations and of the clay taken from Demirci region, which locates at almost 15 km southern of Sinop, were made. While the elemental compositions of the samples were obtained by the spectroscopic method, X-Ray Fluorescence (XRF), the mineral structures were investigated by Powder XRay Diffraction (PXRD) and Fourier Transform Infra Red (FT-IR) spectroscopic method. Furthermore, the characteristic reactions (dehydroxylation, decomposition, transformation) that the clays experienced between the temperatures 50 and 1000 o C were determined by Thermal Gravimetric Analysis (TGA). Characterizations of the Sinopean samples were made and the similarity and differences between other samples from different regions were investigated. Besides the provenance characterization, the distinctions between the production and firing techniques were observed. In addition to the experimental studies, chemometric techniques using statistical methods such as the standard clustering method and principal component analysis (PCA) was also applied to identify the groupings in the set of samples. As a result of this study, it is observed that the raw clays and ceramic samples have minerals of montmorillonite, quartz, feldspars, pyroxene, calcite and hematite at different amounts. From the mineralogical and elemental data, it is concluded that the color variations are resulted from the calcium element occurring in pyroxene mineral. In the light colored samples, amount of this element and mineral is high whereas it is low in red colored ones. From the interpretation of elemental data by statistical methods, it is observed that a classification among the Demirci samples is possible according to the function of the pottery. In addition, classification among ceramics from two different regions is possible by the interpretation of chemical analysis, even though the ceramics have the same morphological properties of the same period.
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    Time-frequency component analyzer and its application to brain oscillatory activity
    (Elsevier, 2005-06-30) Özdemir, A. K.; Karakaş S.; Çakmak, E. D.; Tüfekçi, D. İ.; Arıkan, Orhan
    Currently, event-related potential (ERP) signals are analysed in the time domain (ERP technique) or in the frequency domain (Fourier analysis and variants). In techniques of time-domain and frequency-domain analysis (short-time Fourier transform, wavelet transform) assumptions concerning linearity, stationarity, and templates are made about the brain signals. In the time–frequency component analyser (TFCA), the assumption is that the signal has one or more components with non-overlapping supports in the time–frequency plane. In this study, the TFCA technique was applied to ERPs. TFCA determined and extracted the oscillatory components from the signal and, simultaneously, localized them in the time–frequency plane with high resolution and negligible cross-term contamination. The results obtained by means of TFCA were compared with those obtained by means of other commonly used techniques of ERP analysis, such as bilinear time–frequency distributions and wavelet analysis. It is suggested that TFCA may serve as an appropriate tool for capturing the localized ERP components in the time–frequency domain and for studying the intricate, frequency-based dynamics of the human brain. © 2004 Elsevier B.V. All rights reserved