597 resultados para Two-nucleon spectra

em Queensland University of Technology - ePrints Archive


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Visible, near-infrared, IR and Raman spectra of magnesian gaspeite are presented. Nickel ion is the main source of the electronic bands as it is the principal component in the mineral where as the bands in IR and Raman spectra are due to the vibrational processes in the carbonate ion as an entity. The combination of electronic absorption and vibrational spectra (including near-infrared, FTIR and Raman) of magnesian gaspeite are explained in terms of the cation co-ordination and the behaviour of CO32– anion in the Ni–Mg carbonate. The electronic absorption spectrum consists of three broad and intense bands at 8130, 13160 and 22730 cm–1 due to spin-allowed transitions and two weak bands at 20410 and 30300 cm–1 are assigned to spin-forbidden transitions of Ni2+ in an octahedral symmetry. The crystal field parameters evaluated from the observed bands are Dq = 810; B = 800 and C = 3200 cm–1. The two bands in the near-infrared spectrum at 4330 and 5130 cm–1 are overtone and combination of CO32– vibrational modes. For the carbonate group, infrared bands are observed at 1020 cm–1(1 ), 870 cm–1 (2), 1418 cm–1 (3) and 750 cm–1 (4), of which3, the asymmetric stretching mode is most intense. Three well resolved Raman bands at 1571, 1088 and 331 cm–1 are assigned to 3, 1 and MO stretching vibrations.

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An approach to pattern recognition using invariant parameters based on higher-order spectra is presented. In particular, bispectral invariants are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale- and amplification-invariant. A minimal set of these invariants is selected as the feature vector for pattern classification. Pattern recognition using higher-order spectral invariants is fast, suited for parallel implementation, and works for signals corrupted by Gaussian noise. The classification technique is shown to distinguish two similar but different bolts given their one-dimensional profiles

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A new approach to pattern recognition using invariant parameters based on higher order spectra is presented. In particular, invariant parameters derived from the bispectrum are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale and amplification invariant, as well. A minimal set of these invariants is selected as the feature vector for pattern classification, and a minimum distance classifier using a statistical distance measure is used to classify test patterns. The classification technique is shown to distinguish two similar, but different bolts given their one-dimensional profiles. Pattern recognition using higher order spectral invariants is fast, suited for parallel implementation, and has high immunity to additive Gaussian noise. Simulation results show very high classification accuracy, even for low signal-to-noise ratios.

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An important component of current models for interstellar and circumstellar evolution is the infrared (IR)spectral data collected from stellar outflows around oxygen-rich stars and from the general interstellar medium [1]. IR spectra from these celestial bodies are usually interpreted as showing the general properties of sub-micron sized silicate grains [2]. Two major features at 10 and 20 microns are reasonably attributed to amorphous olivine or pyroxene (e.g. Mg2Si04 or MgSi03) on the basis of comparisons with natural standards and vapor condensed silicates [3-6]. In an attempt to define crystallisation rates for spectrally amorphous condensates, Nuth and Donn [5] annealed experimentally produced amorphous magnesium silicate smokes at 1000K. On analysing these smokes at various annealing times, Nuth and Donn [5] showed that changes in crystallinity measured by bulk X-ray diffraction occured at longer annealing times (days) than changes measured by IR spectra (a few hours). To better define the onset of crystallinity in these magnesium silicates, we have examined each annealed product using a JEOL 1OOCX analytical electron microscope (AEM). In addition, the development of chemical diversity with annealing has been monitored using energy dispersive spectroscopy of individual grains from areas <20nm in diameter. Furthermore, the crystallisation kinetics of these smokes under ambient, room temperature conditions have been examined using bulk and fourier transform infrared (FTIR)spectra.

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Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.

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Semi-conducting phase I CuTCNQ (TCNQ = 7,7,8,8-tetracyanoquinodimethane), which is of considerable interest as a switching device for memory storage materials, can be electrocrystallized from CH3CN via two distinctly different pathways when TCNQ is reduced to TCNQ˙− in the presence of [Cu(MeCN)4]+. The first pathway, identified in earlier studies, occurs at potentials where TCNQ is reduced to TCNQ˙− and involves a nucleation–growth mechanism at preferred sites on the electrode to produce arrays of well separated large branched needle-shaped phase I CuTCNQ crystals. The second pathway, now identified at more negative potentials, generates much smaller needle-shaped phase I CuTCNQ crystals. These electrocrystallize on parts of the surface not occupied in the initial process and give rise to film-like characteristics. This process is attributed to the reduction of Cu+[(TCNQ˙−)(TCNQ)] or a stabilised film of TCNQ via a solid–solid conversion process, which also involves ingress of Cu+via a nucleation–growth mechanism. The CuTCNQ surface area coverage is extensive since it occurs at all areas of the electrode and not just at defect sites that dominate the crystal formation sites for the first pathway. Infrared spectra, X-ray diffraction, surface plasmon resonance, quartz crystal microbalance, scanning electron microscopy and optical image data all confirm that two distinctly different pathways are available to produce the kinetically-favoured and more highly conducting phase I CuTCNQ solid, rather than the phase II material.

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Theoretical calculations of the C3HO potential surface at the CCSD(T)/aug-cc-pVDu/B3LYP/6-31G* level indicate that the three radicals HCCCO, CCCHO, and (cyclo-C3H)=O are stable, with HCCCO being the most stable of the three. A fourth isomer, CCHCO, is unstable with respect to cyclization to (cyclo-C3H)=O. Two isomers have been prepared by neutralization of charged precursors, formed as follows: (i) HCCCO, by HC drop C-C(O)-O+(H)(Me) --> HC3O+ + MeOH, and (ii) C2CHO, by (a) Me3SiC drop C-CHO + HO- --> C- drop C-CHO + Me3SiOH and (b) C- drop C-CH(OH)-C drop CH --> C- drop C-CHO + C2H2. A comparison of the CR and -NR+ spectra of -C2CHO indicate that C2CHO is (partially) rearranging to an isomer that shows significant formation of CO.(+) in the -NR+ spectrum of the anion. Ab initio calculations indicate that HCCCO is the product of the isomerism and that a proportion of these isomerized neutrals dissociate to CO and C2H. The neutral HCCCO may be formed by (i) synchronous rearrangement of C2CHO and/or (ii) stepwise rearrangement of C2CHO through (cyclo-C3H)=O. The second of these processes should have the higher rate, as it has the lower barrier in the rate-determining step and the higher Arrhenius pre-exponential A factor.

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We investigated the effects of handling and fixation processes on the two-photon fluorescence spectroscopy of endogenous fluorophors in mouse skeletal muscle. The skeletal muscle was handled in one of two ways: either sectioned without storage or sectioned following storage in a freezer. The two-photon fluorescence spectra measured for different storage or fixation periods show a differential among those samples that were stored in water or were fixed either in formalin or methanol. The spectroscopic results indicate that formalin was the least disruptive fixative, having only a weak effect on the two-photon fluorescence spectroscopy of muscle tissue, whereas methanol had a significant influence on one of the autofluorescence peaks. The two handling processes yielded similar spectral information, indicating no different effects between them.

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Two-photon fluorescence spectroscopy has been performed on rat skeletal muscles to investigate the effect of fixation processes on the micro-environments of the endogenous fluorophors in rat skeletal muscles. The two-photon fluorescence spectra measured for different fixation periods show a differential among those samples that were fixed in water, formalin and methanol, respectively. The results imply that two-photon fluorescence spectroscopy can be a potential technique for identification of healthy and malignant biological tissues.

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The effect of the nonuniformity of the electron density on the dispersion properties of surface waves propagating in a direction transverse to an external magnetic field is studied for the model of a two-layer plasma structure bounded by a metal. It is shown that the spectra of the waves can be effectively controlled by varying the degree of nonuniformity of the density and the dimensions of the layers.

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The Raman spectra at 77 K of the hydroxyl stretching of kaolinite were obtained along the three axes perpendicular to the crystal faces. Raman bands were observed at 3616, 3658 and 3677 cm−1 together with a distinct band observed at 3691 cm−1 and a broad profile between 3695 and 3715 cm−1. The band at 3616 cm−1 is assigned to the inner hydroxyl. The bands at 3658 and 3677 cm−1 are attributed to the out-of-phase vibrations of the inner surface hydroxyls. The Raman spectra of the in-phase vibrations of the inner-surface hydroxyl-stretching region are described in terms of transverse and longitudinal optic splitting. The band at 3691 cm−1 is assigned to the transverse optic and the broad profile to the longitudinal optic mode. This splitting remained even at liquid nitrogen temperature. The transverse optic vibration may be curve resolved into two or three bands, which are attributed to different types of hydroxyl groups in the kaolinite.