In this thesis, the conventional low voltage power line communication methods is investigated in the axis of automated meter reading applications and the classification and experimental verification of common noise types for low voltage power line communication network. The investigated system provides the real time transmission of electricity consumption data recorded by electricity meters, initially to a local computer via a low voltage line through a low speed PLC (Power Line Carrier) environment and subsequently to a corporate network through a high speed data transmission medium. The automated meter system provides a more effective tracking and data acquisition, a more detailed and vigorous knowledge about consumer behavior for subscriber assessment in electricity distribution in association with a brand new management and system supervision concept in electricity distribution control and management technology. The theoretical studies are experimentally verified for the Turkish low voltage power infrastructure through laboratory experiments performed in METU Electrical and Electronics Engineering Department, Electrical Machines and Drives Laboratory and R&amp / D Laboratories of MAKEL facilities in Hadimk&ouml / y. The single phase voltage of the mains line between the phase and neutral is monitored to exhibit the disturbing effects of various noise sources. The resulting voltage spectrum is logged by using digital data acquisition devices in time and frequency domain. The waveforms are converted to frequency domain using the Fast Fourier Transform (FFT) functions of the MATLAB. The experimental results are compared to the theoretical findings obtained through literature survey.

This study focuses on various aspects of nanocrystals embedded in a dielectric matrix. In the first part of this work, a new approach with the use of Fourier Transform Infrared spectroscopy (FTIR) in the nanocrystal analysis was developed and presented. Si and Ge nanocrystals embedded in SiO2 matrix were mainly studied. This new approach is based on the analysis of structural variations of SiO2 matrix during the formation of semiconductor nanocrystlas. It is shown that the chemical and structural variations of the host matrix are directly related to the precipitation of nanocrystals in it. This correlation provides valuable information about the presences of nanocrystals in the matrix. In the second part of this work, fabrication of SiC films with and without Si nanocrystals inclusions was studied. With this aim, stoichiometric SiC and Si rich SiC thin films were fabricated by using magnetron co-sputtering and Plasma Enhanced Chemical Vapor Deposition (PECVD) techniques. For SiC films, the structural and optical analyses were performed. For Si rich SiC films, the formation conditions of Si nanocrystals were investigated. Post annealing studies were carried out to track the evolution of the SiC matrix and formation of Si nanocrystals at different temperatures. Chemical and structural properties of the SiC host matrix were investigated with FTIR spectroscopy. Optimum conditions for the fabrication of stoichiometric SiC layers were determined. The crystallography of the nanocrystals was investigated by X-Ray Diffraction (XRD). The variation of the atomic concentrations and bond formations were investigated with X-Ray Photoelectron Spectroscopy (XPS). Raman spectroscopy and Transmission Electron Microscopy (TEM) were used to verify the formation of Si nanocrystals. We have shown that both single and multilayer Si nanocrystals can be fabricated in the amorphous SiC matrix for applications such as light emitting diodes and solar cells.

This thesis study focuses on the realization of an online cue based Motor Imagery (MI) Brain Computer Interface (BCI). For this purpose, some signal processing and classification methods are investigated. Specifically, several time-spatial-frequency methods, namely the Short Time Fourier Transform (STFT), Common Spatial Frequency Patterns (CSFP) and the Morlet Transform (MT) are implemented on a 2-class MI BCI system. Distinction Sensitive Learning Vector Quantization (DSLVQ) method is used as a feature selection method. The performance of these methodologies is evaluated with the linear and nonlinear Support Vector Machines (SVM), Multilayer Perceptron (MLP) and Naive Bayesian (NB) classifiers. The methodologies are tested on BCI Competition IV dataset IIb and an average kappa value of 0.45 is obtained on the dataset. According to the classification results, the algorithms presented here obtain the 4th level in the competition as compared to the other algorithms in the competition. Offline experiments are performed in METU Brain Research Laboratories and Hacettepe Biophysics Department on two subjects with the original cue-based MI BCI paradigm. Average prediction accuracy of the methods on a 2-class BCI is evaluated to be 76.26% in these datasets. Furthermore, two online BCI applications are developed: the ping-pong game and the electrical wheelchair control. For these applications, average classification accuracy is found to be 70%. During the offline experiments, the performance of the developed system is observed to be highly dependent on the subject training and experience. According to the results, the EEG channels P3 and P4, which are considered to be irrelevant with the motor imagination, provided the best classification performance on the offline experiments. Regarding the observations on the experiments, this process is related to the stimulation mechanism in the cue based applications and consequent visual evoking effects on the subjects.

Large Area Maskless Photopolymerization (LAMP) is a direct digital manufacturing technology being developed at Georgia Tech to produce ceramic molds for investment casting of turbine airfoils. In LAMP, UV light incident on a spatial light modulator is projected in the form of a structured black and white bitmap image onto a platform supporting slurry comprising a ceramic particle loaded photocurable resin. Curing of the resin is completed rapidly with exposures lasting 20~160ms. Three-dimensional parts are built layer-by-layer by sequentially applying and selectively curing resin layers of 25-100 micron thickness. In LAMP, diacrylate-based ceramic particle-loaded resins with photoinitiators sensitive in the range of spectral characteristics of the UV source form the basis for an ultra-fast photopolymerization reaction. At the start of the reaction, the monomer molecules are separated by van der Waals distance (~10⁴Å). As the reaction proceeds, these monomer molecules form a closely packed network thereby reducing their separation to covalent bond lengths (~ 1 Å). This results in bulk contraction in the cured resin, which accumulates as the part is fabricated layer-by-layer. The degree of shrinkage is a direct measure of the number of covalent bonds formed. Thus, shrinkage in LAMP is characterized by estimating the number of covalent bonds formed during the photopolymerization reaction. Polymerization shrinkage and accompanying stresses developed during photopolymerization of ceramic particle-loaded resins in LAMP can cause deviations from the desired geometry. The extent of deviations depends on the photoinitiator concentration, the filler loading, the degree of monomer conversion, and the operating parameters such as energy dose. An understanding of shrinkage and stresses built up in a part can assist in developing source geometry compensation algorithms and exposure strategies to alleviate these effects. In this thesis, an attempt has been made to understand the curing kinetics of the reaction and its relation to the polymerization shrinkage. Realtime Fourier Transform Infrared Spectroscopy (RTFTIR) is used to determine the conversion of monomers into polymer networks by analyzing the changes in the chemical bonds of the participating species of molecules. The conversion data can further be used to estimate the curing kinetics of the reaction and the relative volumetric shrinkage strain due to polymerization.

Atoms construct the molecules and molecules construct the material substances (with the exceptions as well, e.g.., metals, where atoms directly construct the material substances). Intermolecular interactions play an important role in most of the branches of sciences, ranging from material sciences to biological sciences. Van der Waals interactions are weak intermolecular interactions while hydrogen bonding varies in strength from weak to strong (1 to 40 kcal/mol). The present work focuses on applying some theoretical methods (ab initio and Atoms in Molecules theory) on these interactions to differentiate them with physically meaningful parameters such as hydrogen bond radii and atoms in molecules theory parameters. 1)Defining and calculating H-bond radii have been done using atoms in molecules theory approach which can explain ruling out the presence or absence of an H-bond in an intermolecular interaction. 2) A blue-shift of 200 cm-1 for a weakly bound complex is unprecedented. Our studies on weakly bound complexes showed the blue-shift of 200 cm-1 for H3C•••CIF and shift has been found to be purely from the mixing of normal modes and not because of an interaction. 3)Methane, a symmetric top molecule can act both as H-bond acceptor and donor. The present work shows that methane is rather a better H-bond acceptor than a donor and all the calculated parameters are in favor of this description. 4) Microwave spectrometer is an ultimate tool (at least at present) for structural characterization of the weakly bound complexes accurately. The rotational spectrum of the weakly bound isotopomer weakly bound complexes accurately. The rotational spectrum of the weakly bound isotopomer 13CC5H6•••Ar, which is a symmetric top and gives only “B” rotational constant. Moreover, the A rotational constant of the complex is the same as the rotational constant for 13CC5H6, which has no dipole moment. C2H2 molecule is an astrophysically important molecule as it is present in asymptotic giant branch and T-type stars (Teff<3000K). Due to its various infrared active vibrational modes, C2H2 is one of the most important sources in cool stars. The production of C2H2 infrared spectroscopic data at high temperature is therefore essential to trace back physical characteristics of these objects and to model the radiative transfer in their envelope. The databases such as “HITRAN”, do not have enough data available for stimulating high temperature spectra. Keeping all these objectives in mind, high temperature emission spectrum of acetylene has been recorded around 3µm region of acetylene.

We present an efficient method to compute the electrostatic fields, torques and forces in dipolar systems, which is based on the fast Fourier transform for nonequispaced data (NFFT). We consider 3d-periodic, 2d-periodic, 1d-periodic as well as 0d-periodic (open) boundary conditions. The method is based on the corresponding Ewald formulas, which immediately lead to an efficient algorithm only in the 3d-periodic case. In the other cases we apply the NFFT based fast summation in order to approximate the contributions of the nonperiodic dimensions in Fourier space. This is done by regularizing or periodizing the involved functions, which depend on the distances of the particles regarding the nonperiodic dimensions. The final algorithm enables a unified treatment of all types of periodic boundary conditions, for which only the precomputation step has to be adjusted.

Hedeby Hochburg, borgen i Hedeby, har fått förhållandevis lite uppmärksamhet, jämfört med själva samhället i Hedeby. Utgrävningen från 2012 har dock väckt ett intresse, med ett antal frågor som behöver besvaras. I denna uppsats analyseras jordprover som samlats under utgrävningen, för att se om de kan visa något om den kronologiska relationen mellan borgvallen och gravarna i borgen. Tre metoder användes, FTIR (Fourier Transform Infrared Spectroscopy), röntgendiffraktion (XRD) och röntgenfluorescens (XRF). Resultaten från XRF och XRD visar på en rumslig relation mellan minst en av vallens konstruktionsfaser och nedsänkningen i ett lager innanför vallen. Relationen med gravarna är inte tydlig än, och analysen gav inga kronologiska ledtrådar. Resultatet kan användas som hypotes för vidare prövning i framti

The coherent properties of semiconductor nanostructures are inherently difficult to measure and one-dimensional spectroscopies are often unable to separate inhomogeneous and homogeneous linewidths. We have refined and improved a method of performing multidimensional Fourier transform spectroscopy based on four-wave mixing (FWM) experiments in the box geometry. We have modified our system with broadband beamsplitters in all interferometer arms, high-resolution translation stages and the ability to work in reflection geometry. By improving the phase-stability of our setup and scanning pulse delays with sub-optical cycle precision, we are able to reproduce 2DFT spectra of GaAs multiple quantum wells. With the FWM signal reflected from the sample surface instead of transmitted through, we show that very low pulse powers can be used to generate coherent 2D signals from colloidal PbS quantum dots. Dephasing times are particularly difficult to measure in small colloidal quantum dots due to environmental broadening effects from the colloidal growth. We show that low-temperature pure excitonic dephasing can be measured via time-integrated measurements as well as from the cross-diagonal linewidths of 2DFT spectra. Ultrafast sub-picosecond dephasing times are measured at 5 K in 3 nm PbS quantum dots, while excitation-density-dependence is investigated in these dots. By retrieving the global phase with an all-optical method, we are able to retrieve the real-part 2D spectra of PbS quantum dots.

In the past, we could rely on technology scaling and new micro-architectural techniques to improve the performance of processors. Nowadays, both of these methods are reaching their limits. The primary concern in future architectures with billions of transistors on a chip and limited power budgets is power/energy efficiency. Full-custom design of application-specific cores can yield up to two orders of magnitude better power efficiency over conventional general-purpose cores. However, a tremendous design effort is required in integrating a new accelerator for each new application. In this dissertation, we present the design of specialized compute fabrics that maintain the efficiency of full custom hardware while providing enough flexibility to execute a whole class of coarse-grain operations. The broad vision is to develop integrated and specialized hardware/software solutions that are co-optimized and co-designed across all layers ranging from the basic hardware foundations all the way to the application programming support through standard linear algebra libraries. We try to address these issues specifically in the context of dense linear algebra applications. In the process, we pursue the main questions that architects will face while designing such accelerators. How broad is this class of applications that the accelerator can support? What are the limiting factors that prevent utilization of these accelerators on the chip? What is the maximum achievable performance/efficiency? Answering these questions requires expertise and careful codesign of the algorithms and the architecture to select the best possible components, datapaths, and data movement patterns resulting in a more efficient hardware-software codesign. In some cases, codesign reduces complexities that are imposed on the algorithm side due to the initial limitations in the architectures. We design a specialized Linear Algebra Processor (LAP) architecture and discuss the details of mapping of matrix-matrix multiplication onto it. We further verify the flexibility of our design for computing a broad class of linear algebra kernels. We conclude that this architecture can perform a broad range of matrix-matrix operations as complex as matrix factorizations, and even Fast Fourier Transforms (FFTs), while maintaining its ASIC level efficiency. We present a power-performance model that compares state-of-the-art CPUs and GPUs with our design. Our power-performance model reveals sources of inefficiencies in CPUs and GPUs. We demonstrate how to overcome such inefficiencies in the process of designing our LAP. As we progress through this dissertation, we introduce modifications of the original matrix-matrix multiplication engine to facilitate the mapping of more complex operations. We observe the resulting performance and efficiencies on the modified engine using our power estimation methodology. When compared to other conventional architectures for linear algebra applications and FFT, our LAP is over an order of magnitude better in terms of power efficiency. Based on our estimations, up to 55 and 25 GFLOPS/W single- and double-precision efficiencies are achievable on a single chip in standard 45nm technology. / text

The accurate and safe diagnosis of breast cancer is a significant societal issue, with annual disease incidence of 48,000 women and around 370 men in the UK. Early diagnosis of the disease allows more conservative treatments and better patient outcomes. Microcalcifications in breast tissue are an important indicator for breast cancers, and often the only sign of their presence. Several studies have suggested that the type of calcification formed may act as a marker for malignancy and its presence may be of biological significance. In this work, breast calcifications are studied with FTIR, synchrotron FTIR, ATR FTIR, and Raman mapping to explore their disease specific composition. From a comparison between vibrational spectroscopy and routine staining procedures it becomes clear that calcium builds up prior to calcification formation. Raman and FTIR indicate the same size for calcifications and are in agreement with routine staining techniques. From the synchrotron FTIR measurements it can be proven that amide is present in the centre of the calcifications and the intensity of the bands depends on the pathology. Special attention is paid to the type of carbonate substitution in the calcifications relating to different pathology grades. In contrast to mammography, Raman spectroscopy has the capability to distinguish calcifications based on their chemical composition. The ultimate goal is to turn the acquired knowledge from the mapping studies into a clinical tool based on deep Raman spectroscopy. Deep Raman techniques have a considerable potential to reduce large numbers of normal biopsies, reduce the time delay between screening and diagnosis and therefore diminish patient anxiety. In order to achieve this, a deep Raman system is designed and after evaluation of its performance tested on buried calcification standards in porcine soft tissue and human mammary tissue. It is shown that, when the calcification is probed through tissue, the strong 960 cm-1 phosphate band can be used as a pseudo marker for carbonate substitution which is related to the pathology of the surrounding tissue. Furthermore, the first study in which human breast calcifications are measured in bulk tissue with a thickness of several millimetres to centimetres is presented. To date, measurements have been performed at 41 specimens with a thickness up to 25 mm. Measurements could be performed through skin and blue dye. The proposed deep Raman technique is promising for probing of calcifications through tissue but will need refinement before being adopted in hospitals.