998 resultados para Texture synthesis


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In this work, a range of nanomaterials have been synthesised based on metal oxyhydroxides MO(OH), where M=Al, Co, Cr, etc. Through a self-assembly hydrothermal route, metal oxyhydroxide nanomaterials with various morphologies were successfully synthesised: one dimensional boehmite (AlO(OH)) nanofibres, zero dimensional indium hydroxide (In(OH)3) nanocubes and chromium oxyhydroxide (CrO(OH)) nanoparticles, as well as two dimensional cobalt hydroxide and oxyhydroxide (Co(OH)2 & CoO(OH)) nanodiscs. In order to control the synthetic nanomaterial morphology and growth, several factors were investigated including cation concentration, temperature, hydrothermal treatment time, and pH. Metal ion doping is a promising technique to modify and control the properties of materials by intentionally introducing impurities or defects into the material. Chromium was successfully applied as a dopant for fabricating doped boehmite nanofibres. The thermal stability of the boehmite nanofibres was enhanced by chromium doping, and the photoluminescence property was introduced to the chromium doped alumina nanofibres. Doping proved to be an efficient method to modify and functionalize nanomaterials. The synthesised nanomaterials were fully characterised by X-ray diffraction (XRD), transmission electron microscopy (TEM) combined with selected area electron diffraction (SAED), scanning electron microscopy (SEM), BET specific surface area analysis, X-ray photoelectron spectroscopy (XPS) and thermo gravimetric analysis (TGA). Hot-stage Raman and infrared emission spectroscopy were applied to study the chemical reactions during dehydration and dehydroxylation. The advantage of these techniques is that the changes in molecular structure can be followed in situ and at the elevated temperatures.

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Texture analysis and textural cues have been applied for image classification, segmentation and pattern recognition. Dominant texture descriptors include directionality, coarseness, line-likeness etc. In this dissertation a class of textures known as particulate textures are defined, which are predominantly coarse or blob-like. The set of features that characterise particulate textures are different from those that characterise classical textures. These features are micro-texture, macro-texture, size, shape and compaction. Classical texture analysis techniques do not adequately capture particulate texture features. This gap is identified and new methods for analysing particulate textures are proposed. The levels of complexity in particulate textures are also presented ranging from the simplest images where blob-like particles are easily isolated from their back- ground to the more complex images where the particles and the background are not easily separable or the particles are occluded. Simple particulate images can be analysed for particle shapes and sizes. Complex particulate texture images, on the other hand, often permit only the estimation of particle dimensions. Real life applications of particulate textures are reviewed, including applications to sedimentology, granulometry and road surface texture analysis. A new framework for computation of particulate shape is proposed. A granulometric approach for particle size estimation based on edge detection is developed which can be adapted to the gray level of the images by varying its parameters. This study binds visual texture analysis and road surface macrotexture in a theoretical framework, thus making it possible to apply monocular imaging techniques to road surface texture analysis. Results from the application of the developed algorithm to road surface macro-texture, are compared with results based on Fourier spectra, the auto- correlation function and wavelet decomposition, indicating the superior performance of the proposed technique. The influence of image acquisition conditions such as illumination and camera angle on the results was systematically analysed. Experimental data was collected from over 5km of road in Brisbane and the estimated coarseness along the road was compared with laser profilometer measurements. Coefficient of determination R2 exceeding 0.9 was obtained when correlating the proposed imaging technique with the state of the art Sensor Measured Texture Depth (SMTD) obtained using laser profilometers.

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Unusual event detection in crowded scenes remains challenging because of the diversity of events and noise. In this paper, we present a novel approach for unusual event detection via sparse reconstruction of dynamic textures over an overcomplete basis set, with the dynamic texture described by local binary patterns from three orthogonal planes (LBPTOP). The overcomplete basis set is learnt from the training data where only the normal items observed. In the detection process, given a new observation, we compute the sparse coefficients using the Dantzig Selector algorithm which was proposed in the literature of compressed sensing. Then the reconstruction errors are computed, based on which we detect the abnormal items. Our application can be used to detect both local and global abnormal events. We evaluate our algorithm on UCSD Abnormality Datasets for local anomaly detection, which is shown to outperform current state-of-the-art approaches, and we also get promising results for rapid escape detection using the PETS2009 dataset.

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Variants of the same process can be encountered within one organization or across different organizations. For example, different municipalities, courts, and rental agencies all need to support highly similar processes. In fact, procurement and sales processes can be found in almost any organization. However, despite these similarities, there is also the need to allow for local variations in a controlled manner. Therefore, many academics and practitioners have advocated the use of configurable process models (sometimes referred to as reference models). A configurable process model describes a family of similar process models in a given domain. Such a model can be configured to obtain a specific process model that is subsequently used to handle individual cases, for instance, to process customer orders. Process configuration is notoriously difficult as there may be all kinds of interdependencies between configuration decisions. In fact, an incorrect configuration may lead to behavioral issues such as deadlocks and livelocks. To address this problem, we present a novel verification approach inspired by the “operating guidelines” used for partner synthesis. We view the configuration process as an external service, and compute a characterization of all such services which meet particular requirements via the notion of configuration guideline. As a result, we can characterize all feasible configurations (i. e., configurations without behavioral problems) at design time, instead of repeatedly checking each individual configuration while configuring a process model.

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Hydrotalcites based upon gallium as a replacement for aluminium in hydrotalcite over a Mg/Al ratio of 2:1 to 4:1 were synthesised. The d(003) spacing varied from 7.83 A ° for the 2:1 hydrotalcite to 8.15 A ° for the 3:1 gallium containing hydrotalcite. A comparison is made with the Mg Al hydrotalcite in which the d(003) spacing for the Mg/Al hydrotalcite varied from 7.62 A ° for the 2:1Mg hydrotalcite to 7.98 A ° for the 4:1 hydrotalcite. The thermal stability of the gallium containing hydrotalcite was determined using thermogravimetric analysis. Four mass loss steps at 77, 263–280,485 and 828 degrees C with mass losses of 10.23, 21.55, 5.20 and 7.58% are attributed to dehydration, dehydroxylation and decarbonation. The thermal stability of the galliumcontaining hydrotalcite is slightly less than the aluminium hydrotalcite.

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Materials with one-dimensional (1D) nanostructure are important for catalysis. They are the preferred building blocks for catalytic nanoarchitecture, and can be used to fabricate designer catalysts. In this thesis, one such material, alumina nanofibre, was used as a precursor to prepare a range of nanocomposite catalysts. Utilising the specific properties of alumina nanofibres, a novel approach was developed to prepare macro-mesoporous nanocomposites, which consist of a stacked, fibrous nanocomposite with a core-shell structure. Two kinds of fibrous ZrO2/Al2O3 and TiO2/Al2O3 nanocomposites were successfully synthesised using boehmite nanofibers as a hard temperate and followed by a simple calcination. The alumina nanofibres provide the resultant nanocomposites with good thermal stability and mechanical stability. A series of one-dimensional (1D) zirconia/alumina nanocomposites were prepared by the deposition of zirconium species onto the 3D framework of boehmite nanofibres formed by dispersing boehmite nanofibres into a butanol solution, followed by calcination at 773 K. The materials were characterised by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM), N2 adsorption/desorption, Infrared Emission Spectroscopy (IES), and Fourier Transform Infrared spectroscopy (FT-IR). The results demonstrated that when the molar percentage, X, X=100*Zr/(Al+Zr), was > 30%, extremely long ZrO2/Al2O3 composite nanorods with evenly distributed ZrO2 nanocrystals formed on their surface. The stacking of such nanorods gave rise to a new kind of macroporous material without the use of any organic space filler\template or other specific drying techniques. The mechanism for the formation of these long ZrO2/Al2O3 composite nanorods is proposed in this work. A series of solid-superacid catalysts were synthesised from fibrous ZrO2/Al2O3 core and shell nanocomposites. In this series, the zirconium molar percentage was varied from 2 % to 50 %. The ZrO2/Al2O3 nanocomposites and their solid superacid counterparts were characterised by a variety of techniques including 27Al MAS-NMR, SEM, TEM, XPS, Nitrogen adsorption and Infrared Emission Spectroscopy. NMR results show that the interaction between zirconia species and alumina strongly correlates with pentacoordinated aluminium sites. This can also be detected by the change in binding energy of the 3d electrons of the zirconium. The acidity of the obtained superacids was tested by using them as catalysts for the benzolyation of toluene. It was found that a sample with a 50 % zirconium molar percentage possessed the highest surface acidity equalling that of pristine sulfated zirconia despite the reduced mass of zirconia. Preparation of hierarchically macro-mesoporous catalyst by loading nanocrystallites on the framework of alumina bundles can provide an alternative system to design advanced nanocomposite catalyst with enhanced performance. A series of macro-mesoporous TiO2/Al2O3 nanocomposites with different morphologies were synthesised. The materials were calcined at 723 K and were characterised by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM), N2 adsorption/desorption, Infrared Emission Spectroscopy (IES), and UV-visible spectroscopy (UV-visible). A modified approach was proposed for the synthesis of 1D (fibrous) nanocomposite with higher Ti/Al molar ratio (2:1) at lower temperature (<100oC), which makes it possible to synthesize such materials on industrial scale. The performances of a series of resultant TiO2/Al2O3 nanocomposites with different morphologies were evaluated as a photocatalyst for the phenol degradation under UV irradiation. The photocatalyst (Ti/Al =2) with fibrous morphology exhibits higher activity than that of the photocatalyst with microspherical morphology which indeed has the highest Ti to Al molar ratio (Ti/Al =3) in the series of as-synthesised hierarchical TiO2/Al2O3 nanocomposites. Furthermore, the photocatalytic performances, for the fibrous nanocomposites with Ti/Al=2, were optimized by calcination at elevated temperatures. The nanocomposite prepared by calcination at 750oC exhibits the highest catalytic activity, and its performance per TiO2 unit is very close to that of the gold standard, Degussa P 25. This work also emphasizes two advantages of the nanocomposites with fibrous morphology: (1) the resistance to sintering, and (2) good catalyst recovery.