122 resultados para visible spectra


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The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.

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There is a need for an accurate real-time quantitative system that would enhance decision-making in the treatment of osteoarthritis. To achieve this objective, significant research is required that will enable articular cartilage properties to be measured and categorized for health and functionality without the need for laboratory tests involving biopsies for pathological evaluation. Such a system would provide the capability of access to the internal condition of the cartilage matrix and thus extend the vision-based arthroscopy that is currently used beyond the subjective evaluation of surgeons. The system required must be able to non-destructively probe the entire thickness of the cartilage and its immediate subchondral bone layer. In this thesis, near infrared spectroscopy is investigated for the purpose mentioned above. The aim is to relate it to the structure and load bearing properties of the cartilage matrix to the near infrared absorption spectrum and establish functional relationships that will provide objective, quantitative and repeatable categorization of cartilage condition outside the area of visible degradation in a joint. Based on results from traditional mechanical testing, their innovative interpretation and relationship with spectroscopic data, new parameters were developed. These were then evaluated for their consistency in discriminating between healthy viable and degraded cartilage. The mechanical and physico-chemical properties were related to specific regions of the near infrared absorption spectrum that were identified as part of the research conducted for this thesis. The relationships between the tissue's near infrared spectral response and the new parameters were modeled using multivariate statistical techniques based on partial least squares regression (PLSR). With significantly high levels of statistical correlation, the modeled relationships were demonstrated to possess considerable potential in predicting the properties of unknown tissue samples in a quick and non-destructive manner. In order to adapt near infrared spectroscopy for clinical applications, a balance between probe diameter and the number of active transmit-receive optic fibres must be optimized. This was achieved in the course of this research, resulting in an optimal probe configuration that could be adapted for joint tissue evaluation. Furthermore, as a proof-of-concept, a protocol for obtaining the new parameters from the near infrared absorption spectra of cartilage was developed and implemented in a graphical user interface (GUI)-based software, and used to assess cartilage-on-bone samples in vitro. This conceptual implementation has been demonstrated, in part by the individual parametric relationship with the near infrared absorption spectrum, the capacity of the proposed system to facilitate real-time, non-destructive evaluation of cartilage matrix integrity. In summary, the potential of the optical near infrared spectroscopy for evaluating articular cartilage and bone laminate has been demonstrated in this thesis. The approach could have a spin-off for other soft tissues and organs of the body. It builds on the earlier work of the group at QUT, enhancing the near infrared component of the ongoing research on developing a tool for cartilage evaluation that goes beyond visual and subjective methods.

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Using interview data on LGBT young people’s policing experiences, I argue policing and security works as a program of government (Dean 1999; Foucault 1991; Rose 1999) that constrains the visibilities of diverse sexuality and gender in public spaces. While young people narrated police actions as discriminatory, the interactions were complex and multi‐faceted with police and security working to subtly constrain the public visibilities of ‘queerness’. Same sex affection, for instance, was visibly yet unverifiably (Mason 2002) regulated by police as a method of governing the boundaries of proper gender and sexuality in public. The paper concludes by noting how the visibility of police interactions with LGBT young people demonstrates to the public that public spaces are, and should remain, heterosexual spaces.

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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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Photocatalytic synthesis using visible light is a desirable chemical process because of its potential to utilize sunlight. Supported gold nanoparticles (Au-NPs) were found to be efficient photocatalysts and the effects of the supports were identified including CeO2, TiO2, ZrO2, Al2O3, and zeolite Y. In particular Au/CeO2 exhibited the high catalytic activity to reduce nitroaromatics to azo compounds, hydrogenate azobenzene to hydroazobenzene, reduce ketones to alcohols, and deoxygenate epoxides to alkenes at ambient temperatures, under irradiation of visible light (or simulated sunlight). The reac-tive efficiency depends on two primary factors: one is the light adsorption of catalysts and another is the driving ability of catalysts corresponding to the reactants. The light absorption by Au-NPs is due to surface plasmon resonance effect or inter-band electron transition; this is related to the reduction ability of the photocatalysts. Irradiation with shorter wavelengths can excite the conduction electrons in Au-NPs to higher energy levels and as a result, induce reduction with more negative reduction potentials. It is known when irradiated with light the Au-NPs can abstract hydrogen from isopropanol forming Au-H species on the Au-NP surface. Hence, we proposed that the active Au-H species will react with the N=O, N=N, C=O double bonds or epoxide bonds, which are weakened by the interaction with the excited electrons in the Au-NPs, and yield the final reductive products. The reacting power of the Au-H species depends on the energy of the excited electrons in Au-NPs: the higher the electronic energy, the stronger the reduction ability of the Au-H species. This finding demonstrates that we can tune the reduction ability of the photocatalysts by manipulating the irradiation wavelength.

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Determining the properties and integrity of subchondral bone in the developmental stages of osteoarthritis, especially in a form that can facilitate real-time characterization for diagnostic and decision-making purposes, is still a matter for research and development. This paper presents relationships between near infrared absorption spectra and properties of subchondral bone obtained from 3 models of osteoarthritic degeneration induced in laboratory rats via: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACL); and (iii) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group (N = 36). After 8 weeks, the animals were sacrificed and knee joints were collected. A custom-made diffuse reflectance NIR probe of diameter 5 mm was placed on the tibial surface and spectral data were acquired from each specimen in the wavenumber range 4000–12 500 cm− 1. After spectral acquisition, micro computed tomography (micro-CT) was performed on the samples and subchondral bone parameters namely: bone volume (BV) and bone mineral density (BMD) were extracted from the micro-CT data. Statistical correlation was then conducted between these parameters and regions of the near infrared spectra using multivariate techniques including principal component analysis (PCA), discriminant analysis (DA), and partial least squares (PLS) regression. Statistically significant linear correlations were found between the near infrared absorption spectra and subchondral bone BMD (R2 = 98.84%) and BV (R2 = 97.87%). In conclusion, near infrared spectroscopic probing can be used to detect, qualify and quantify changes in the composition of the subchondral bone, and could potentially assist in distinguishing healthy from OA bone as demonstrated with our laboratory rat models.

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Fourteen new complexes of the form cis-\[RuIIX2(R2qpy2+)2]4+ (R2qpy2+ = a 4,4′:2′,2″:4″,4‴-quaterpyridinium ligand, X = Cl− or NCS−) have been prepared and isolated as their PF6− salts. Characterisation involved various techniques including 1H NMR spectroscopy and +electrospray or MALDI mass spectrometry. The UV–Vis spectra display intense intraligand π → π∗ absorptions, and also metal-to-ligand charge-transfer (MLCT) bands with two resolved maxima in the visible region. Red-shifts in the MLCT bands occur as the electron-withdrawing strength of the pyridinium groups increases, while replacing Cl− with NCS− causes blue-shifts. Cyclic voltammograms show quasi-reversible or reversible RuIII/II oxidation waves, and several ligand-based reductions that are irreversible. The variations in the redox potentials correlate with changes in the MLCT energies. A single-crystal X-ray structure has been obtained for a protonated form of a proligand salt, \[(4-(CO2H)Ph)2qpyH3+]\[HSO4]3·3H2O. Time-dependent density functional theory calculations give adequate correlations with the experimental UV–Vis spectra for the two carboxylic acid-functionalised complexes in DMSO. Despite their attractive electronic absorption spectra, these dyes are relatively inefficient photosensitisers on electrodes coated with TiO2 or ZnO. These observations are attributed primarily to weak electronic coupling with the surfaces, since the DFT-derived LUMOs include no electron density near the carboxylic acid anchors.

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The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been demonstrated to be limited in their capacity to distinguish intact (visually normal) from degraded cartilage samples. In this paper, we explore the correlation between a new mechanical parameter, namely the reswelling of articular cartilage following unloading from a given compressive load, and the near infrared (NIR) spectrum. The capacity to distinguish mechanically intact from proteoglycan-depleted tissue relative to the "reswelling" characteristic was first established, and the result was subsequently correlated with the NIR spectral data of the respective tissue samples. To achieve this, normal intact and enzymatically degraded samples were subjected to both NIR probing and mechanical compression based on a load-unload-reswelling protocol. The parameter δ(r), characteristic of the osmotic "reswelling" of the matrix after unloading to a constant small load in the order of the osmotic pressure of cartilage, was obtained for the different sample types. Multivariate statistics was employed to determine the degree of correlation between δ(r) and the NIR absorption spectrum of relevant specimens using Partial Least Squared (PLS) regression. The results show a strong relationship (R(2)=95.89%, p<0.0001) between the spectral data and δ(r). This correlation of δ(r) with NIR spectral data suggests the potential for determining the reswelling characteristics non-destructively. It was also observed that δ(r) values bear a significant relationship with the cartilage matrix integrity, indicated by its proteoglycan content, and can therefore differentiate between normal and artificially degraded proteoglycan-depleted cartilage samples. It is therefore argued that the reswelling of cartilage, which is both biochemical (osmotic) and mechanical (hydrostatic pressure) in origin, could be a strong candidate for characterizing the tissue, especially in regions surrounding focal cartilage defects in joints.

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Opening up a band gap and finding a suitable substrate material are two big challenges for building graphene-based nanodevices. Using state-of-the-art hybrid density functional theory incorporating long range dispersion corrections, we investigate the interface between optically active graphitic carbon nitride (g-C3N4) and electronically active graphene. We find an inhomogeneous planar substrate (g-C3N4) promotes electronrich and hole-rich regions, i.e., forming a well-defined electron−hole puddle, on the supported graphene layer. The composite displays significant charge transfer from graphene to the g-C3N4 substrate, which alters the electronic properties of both components. In particular, the strong electronic coupling at the graphene/g-C3N4 interface opens a 70 meV gap in g-C3N4-supported graphene, a feature that can potentially allow overcoming the graphene’s band gap hurdle in constructing field effect transistors. Additionally, the 2-D planar structure of g-C3N4 is free of dangling bonds, providing an ideal substrate for graphene to sit on. Furthermore, when compared to a pure g-C3N4 monolayer, the hybrid graphene/g-C3N4 complex displays an enhanced optical absorption in the visible region, a promising feature for novel photovoltaic and photocatalytic applications.

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We demonstrated for the first time by large-scale ab initio calculations that a graphene/titania interface in the ground electronic state forms a charge-transfer complex due to the large difference of work functions between graphene and titania, leading to substantial hole doping in graphene. Interestingly, electrons in the upper valence band can be directly excited from graphene to the conduction band, that is, the 3d orbitals of titania, under visible light irradiation. This should yield well-separated electron−hole pairs, with potentially high photocatalytic or photovoltaic performance in hybrid graphene and titania nanocomposites. Experimental wavelength-dependent photocurrent generation of the graphene/titania photoanode demonstrated noticeable visible light response and evidently verified our ab initio prediction.

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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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A synthetic reevesite-like material has been shown to decolorize selected dyes and degrade phenolic contaminants photocatalytically in water when irradiated with visible light. This material can photoactively decolorize dyes such as bromophenol blue, bromocresol green, bromothymol blue, thymol blue and methyl orange in less than 15 min under visible light radiation in the absence of additional oxidizing agents. Conversely, phenolic compounds suc has phenol, p-chlorophenol and p-nitrophenol are photocat- alytically degraded in approximately 3hwith additional H2O2 when irradiated with visible light. These reactions offer potentially energy effective pathways for the removal of recalcitrant organic waste contaminants.

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The work described in this technical report is part of an ongoing project at QUT to build practical tools for the manipulation, analysis and visualisation of recordings of the natural environment. This report describes the algorithm we use to cluster the spectra in a spectrogram. The report begins with a brief description of the signal processing that prepares the spectrograms.

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This practice-led project has two outcomes: a collection of short stories titled 'Corkscrew Section', and an exegesis. The short stories combine written narrative with visual elements such as images and typographic devices, while the exegesis analyses the function of these graphic devices within adult literary fiction. My creative writing explores a variety of genres and literary styles, but almost all of the stories are concerned with fusing verbal and visual modes of communication. The exegesis adopts the interpretive paradigm of multimodal stylistics, which aims to analyse graphic devices with the same level of detail as linguistic analysis. Within this framework, the exegesis compares and extends previous studies to develop a systematic method for analysing how the interactions between language, images and typography create meaning within multimodal literature.

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This study investigated the practices of two teachers in a school that was successful in enabling the mathematical learning of students in Years 1 and 2, including those from backgrounds associated with low mathematical achievement. The study explained how the practices of the teachers constituted a radical visible pedagogy that enabled equitable outcomes. The study also showed that teachers’ practices have collective power to shape students’ mathematical identities. The role of the principal in the school was pivotal because she structured curriculum delivery so that students experienced the distinct practices of both teachers.