450 resultados para thermal image segmentation
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This thesis examines and compares imaging methods used during the radiotherapy treatment of prostate cancer. The studies found that radiation therapists were able to localise and target the prostate consistently with planar imaging techniques and that the use of small gold markers in the prostate reduced the variation in prostate localisation when using volumetric imaging. It was concluded that larger safety margins are required when using volumetric imaging without gold markers.
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Through larger-scale molecular dynamics simulations, we investigated the impacts from vacancy-initiated linkages on the thermal conductivity of bilayer graphene sheets (of size L × W = 24.5 nm × 3.7 nm). Three different interlayer linkages, including divacancy bridging, “spiro” interstitial bridging and Frenkel pair defects, are considered. It is found that the presence of interlayer linkages induces a significant degradation in the thermal conductivity of the bilayer graphene sheet. The degradation is strongly dependent on the interlayer linkage type, concentration and location. More importantly, the linkages that contain vacancies lead to more severe suppression of the thermal conductivity, in agreement with theoretical predictions that vacancies induce strong phonon scattering. Our finding provides useful guidelines for the application of multilayer graphene sheets in practical thermal management.
An external field prior for the hidden Potts model with application to cone-beam computed tomography
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In images with low contrast-to-noise ratio (CNR), the information gain from the observed pixel values can be insufficient to distinguish foreground objects. A Bayesian approach to this problem is to incorporate prior information about the objects into a statistical model. A method for representing spatial prior information as an external field in a hidden Potts model is introduced. This prior distribution over the latent pixel labels is a mixture of Gaussian fields, centred on the positions of the objects at a previous point in time. It is particularly applicable in longitudinal imaging studies, where the manual segmentation of one image can be used as a prior for automatic segmentation of subsequent images. The method is demonstrated by application to cone-beam computed tomography (CT), an imaging modality that exhibits distortions in pixel values due to X-ray scatter. The external field prior results in a substantial improvement in segmentation accuracy, reducing the mean pixel misclassification rate for an electron density phantom from 87% to 6%. The method is also applied to radiotherapy patient data, demonstrating how to derive the external field prior in a clinical context.
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Recent changes in the aviation industry and in the expectations of travellers have begun to alter the way we approach our understanding, and thus the segmentation, of airport passengers. The key to successful segmentation of any population lies in the selection of the criteria on which the partitions are based. Increasingly, the basic criteria used to segment passengers (purpose of trip and frequency of travel) no longer provide adequate insights into the passenger experience. In this paper, we propose a new model for passenger segmentation based on the passenger core value, time. The results are based on qualitative research conducted in-situ at Brisbane International Terminal during 2012-2013. Based on our research, a relationship between time sensitivity and degree of passenger engagement was identified. This relationship was used as the basis for a new passenger segmentation model, namely: Airport Enthusiast (engaged, non time sensitive); Time Filler (non engaged, non time sensitive); Efficiency Lover (non engaged, time sensitive) and Efficient Enthusiast (engaged, time sensitive). The outcomes of this research extend the theoretical knowledge about passenger experience in the terminal environment. These new insights can ultimately be used to optimise the allocation of space for future terminal planning and design.
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Non-thermal plasma (NTP) has been introduced over the past several years as a promising method for nitrogen oxide (NOx) removal. The intent, when using NTP, is to selectively transfer input electrical energy to the electrons, and to not expend this in heating the entire gas stream, which generates free radicals through collisions, and promotes the desired chemical changes in the exhaust gases. The generated active species react with the pollutant molecules and decompose them. This paper reviews and summarizes relevant literature regarding various aspects of the application of {NTP} technology on {NOx} removal from exhaust gases. A comprehensive description of available scientific literature on {NOx} removal using {NTP} technology is presented, including various types of NTP, e.g. dielectric barrier discharge, corona discharge and electron beam. Furthermore, the combination of {NTP} with catalyst and adsorbent for better {NOx} removal efficiency is presented in detail. The removal of {NOx} from both simulated gases and real diesel engines is also considered in this review paper. As {NTP} is a new technique and is not yet commercialized, there is a need for more studies to be performed in this field.
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The thermal behavior of kaolinite–urea intercalation complex was investigated by thermogravimetry–differential scanning calorimetry (TG–DSC), X-ray diffraction (XRD), and fourier transform infrared spectroscopy (FTIR). In addition, the interaction mode of urea molecules intercalated into the kaolinite gallery was studied by means of molecular dynamics simulation. Three main mass losses were observed at 136 °C, in the range of 210–270 °C, and at 500 °C in the TG–DSC curves, which were, respectively, attributed to (1) melting of the surface-adsorbed urea, (2) removal of the intercalated urea, and (3) dehydroxylation of the deintercalated kaolinite. The three DSC endothermic peaks at 218, 250, and 261 °C were related to the successive removals of intercalated urea with three different distribution structures. Based on the angle between the dipole moment vector of urea and the basal surface of kaolinite, the three urea models could be described as follows: (1) Type A, the dipole moment vector is nearly parallel to the basal surface of kaolinite; (2) Type B, the dipole moment vector points to the silica tetrahedron with the angle between it and the basal surface of kaolinite ranging from 20°to 40°; and (3) Type C, the dipole moment vector is nearly perpendicular to the basal surface of kaolinite. The three distribution structures of urea molecules were validated by the results of the molecular dynamics simulation. Furthermore, the thermal behavior of the kaolinite–urea intercalation complex investigated by TG–DSC was also supported by FTIR and XRD analyses.
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A series of rubber composites were prepared by blending styrene-butadiene rubber (SBR) latex and the different particle sized kaolinites. The thermal stabilities of the rubber composites were characterized using thermogravimetry, digital photography, scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and Raman spectroscopy. Kaolinite SBR composites showed much greater thermal stability when compared with that of the pure SBR. With the increase of kaolinite particle size, the pyrolysis products became much looser; the char layer and crystalline carbon content gradually decreased in the pyrolysis residues. The pyrolysis residues of the SBR composites filled with the different particle sized kaolinites showed some remarkable changes in structural characteristics. The increase of kaolinite particle size was not beneficial to form the compact and stable crystalline carbon in the pyrolysis process, and resulted in a negative influence in improving the thermal stability of kaolinite/SBR composites.
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The output of a differential scanning fluorimetry (DSF) assay is a series of melt curves, which need to be interpreted to get value from the assay. An application that translates raw thermal melt curve data into more easily assimilated knowledge is described. This program, called “Meltdown,” conducts four main activities—control checks, curve normalization, outlier rejection, and melt temperature (Tm) estimation—and performs optimally in the presence of triplicate (or higher) sample data. The final output is a report that summarizes the results of a DSF experiment. The goal of Meltdown is not to replace human analysis of the raw fluorescence data but to provide a meaningful and comprehensive interpretation of the data to make this useful experimental technique accessible to inexperienced users, as well as providing a starting point for detailed analyses by more experienced users.
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This study is seeking to investigate the effect of non-thermal plasma technology in the abatement of particulate matter (PM) from the actual diesel exhaust. Ozone (O3) strongly promotes PM oxidation, the main product of which is carbon dioxide (CO2). PM oxidation into the less harmful product (CO2) is the main objective whiles the correlation between PM, O3 and CO2 is considered. A dielectric barrier discharge reactor has been designed with pulsed power technology to produce plasma inside the diesel exhaust. To characterise the system under varied conditions, a range of applied voltages from 11 kVPP to 21kVPP at repetition rates of 2.5, 5, 7.5 and 10 kHz, have been experimentally investigated. The results show that by increasing the applied voltage and repetition rate, higher discharge power and CO2 dissociation can be achieved. The PM removal efficiency of more than 50% has been achieved during the experiments and high concentrations of ozone on the order of a few hundreds of ppm have been observed at high discharge powers. Furthermore, O3, CO2 and PM concentrations at different plasma states have been analysed for time dependence. Based on this analysis, an inverse relationship between ozone concentration and PM removal has been found and the role of ozone in PM removal in plasma treatment of diesel exhaust has been highlighted.
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Objective This study seeks establish whether meaningful subgroups exist within a 14-16 year old adolescent population and if these segments respond differently to the Game On: Know Alcohol (GOKA) intervention, a school-based alcohol social marketing program. Methodology This study is part of a larger cluster randomized controlled evaluation of the Game On: Know Alcohol (GOKA) program implemented in 14 schools in 2013/2014. TwoStep cluster analysis was conducted to segment 2114 high school adolescents (14-16 years old) on the basis of 22 demographic, behavioral and psychographic variables. Program effects on knowledge, attitudes, behavioral intentions, social norms, expectancies and refusal self-efficacy of identified segments was subsequently examined. Results Three segments were identified: (1) Abstainers (2) Bingers (3) Moderate Drinkers. Program effects varied significantly across segments. The strongest positive change effects post participation were observed for the Bingers, while mixed effects were evident for Moderate Drinkers and Abstainers. Conclusions These findings provide preliminary empirical evidence supporting application of social marketing segmentation in alcohol education programs. Development of targeted programs that meet the unique needs of each of the three identified segments is indicated to extend the social marketing footprint in alcohol education.
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Robustness to variations in environmental conditions and camera viewpoint is essential for long-term place recognition, navigation and SLAM. Existing systems typically solve either of these problems, but invariance to both remains a challenge. This paper presents a training-free approach to lateral viewpoint- and condition-invariant, vision-based place recognition. Our successive frame patch-tracking technique infers average scene depth along traverses and automatically rescales views of the same place at different depths to increase their similarity. We combine our system with the condition-invariant SMART algorithm and demonstrate place recognition between day and night, across entire 4-lane-plus-median-strip roads, where current algorithms fail.
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Advances in nanomaterials/nanostructures offer the possibility of fabricating multifunctional materials for use in engineering applications. Carbon nanotube (CNT)-based nanostructures are a representative building block for these multifunctional materials. Based on a series of in silico studies, we investigated the possibility of tuning the thermal conductivity of a three-dimensional CNT-based nanostructure: a single-walled CNT-based super-nanotube. The thermal conductivity of the super-nanotubes was shown to vary with different connecting carbon rings and super-nanotubes with longer constituent single-walled CNTs and larger diameters had a smaller thermal conductivity. The inverse of the thermal conductivity of the super-nanotubes showed a good linear relationship with the inverse of the length. The thermal conductivity was approximately proportional to the inverse of the temperature, but was insensitive to the axial strain as a result of the Poisson ratio. These results provide a fundamental understanding of the thermal conductivity of the super-nanotubes and will guide their future design/fabrication and engineering applications.
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Volcanic eruption centres of the mostly 4.5 Ma-5000 BP Newer Volcanics Province in the Hamilton area of southeastern Australia were examined in detail using a multifaceted approach, including ground truthing and analysis of ArcGIS Total Magnetic Intensity and seamless geology data, NASA Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation models and Google Earth satellite image interpretation. Sixteen eruption centres were recognised in the Hamilton area, including three previously unrecorded volcanoes-one of which, the Cas Maar, constitutes the northernmost maar-cone volcanic complex in the Western Plains subprovince. Seven previously allocated eruption centres were placed into question based on field and laboratory observations. Three phases of volcanic activity have been suggested by other authors and are interpreted to correlate with ages of >4 Ma, ca 2 Ma and <0.5 Ma, which may be further subdivided based on preservation of outcrop. Geochemical compositions of the dominantly basaltic products become increasingly alkaline and enriched in incompatible elements from Phases 1 to 2, with Phase 3 eruptions both covering the entire geochemical range and extending into increasingly enriched compositions. This research highlights the importance of a multifaceted approach to landform mapping and demonstrates that additional volcanic centres may yet be discovered in the Newer Volcanics Province
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This paper is concerned with the interfacial thermal resistance for polymer composites reinforced by various covalently functionalised graphene. By using molecular dynamics simulations, the obtained results show that the covalent functionalisation in graphene plays a significant role in reducing the graphene-paraffin interfacial thermal resistance. This reduction is dependent on the coverage and type of functional groups. Among the various functional groups, butyl is found to be the most effective in reducing the interfacial thermal resistance, followed by methyl, phenyl and formyl. The other functional groups under consideration such as carboxyl, hydroxyl and amines are found to produce negligible reduction in the interfacial thermal resistance. For multilayer graphene with a layer number up to four, the interfacial thermal resistance is insensitive to the layer number. The effects of the different functional groups and the layer number on the interfacial thermal resistance are also elaborated using the vibrational density of states of the graphene and the paraffin matrix. The present findings provide useful guidelines in the application of functionalised graphene for practical thermal management.
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Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.