996 resultados para Dimensions Reduction
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There is worldwide interest in reducing aircraft emissions. The difficulty of reducing emissions including water vapour, carbon dioxide (CO2) and oxides of nitrogen (NOx) is mainly due from the fact that a commercial aircraft is usually designed for a particular optimal cruise altitude but may be requested or required to operate and deviate at different altitude and speeds to archive a desired or commanded flight plan, resulting in increased emissions. This is a multi- disciplinary problem with multiple trade-offs such as optimising engine efficiency, minimising fuel burnt, minimise emissions while maintaining aircraft separation and air safety. This project presents the coupling of an advanced optimisation technique with mathematical models and algorithms for aircraft emission reduction through flight optimisation. Numerical results show that the method is able to capture a set of useful trade-offs between aircraft range and NOx, and mission fuel consumption and NOx. In addition, alternative cruise operating conditions including Mach and altitude that produce minimum NOx and CO2 (minimum mission fuel weight) are suggested.
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Graphene, functionalized with oleylamine (OA) and soluble in non-polar organic solvents, was produced on a large scale with a high yield by combining the Hummers process for graphite oxidation, an amine-coupling process to make OA-functionalized graphite oxide (OA-GO), and a novel reduction process using trioctylphosphine (TOP). TOP acts as both a reducing agent and an aggregation-prevention surfactant in the reduction of OA-GO in 1,2-dichlorobenzene (DCB). The reduction of OA-GO is confirmed by X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, and Raman spectroscopy. The exfoliation of GO, OA GO, and OA-functionalized graphene (OA-G) is verified by atomic force microscopy. The conductivity of TOP-reduced OA G, which is deduced from the current–voltage characteristics of a vacuum-filtered thin film, shows that the reduction of functionalized GO by TOP is as effective as the reduction of GO by hydrazine.
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We consider time-space fractional reaction diffusion equations in two dimensions. This equation is obtained from the standard reaction diffusion equation by replacing the first order time derivative with the Caputo fractional derivative, and the second order space derivatives with the fractional Laplacian. Using the matrix transfer technique proposed by Ilic, Liu, Turner and Anh [Fract. Calc. Appl. Anal., 9:333--349, 2006] and the numerical solution strategy used by Yang, Turner, Liu, and Ilic [SIAM J. Scientific Computing, 33:1159--1180, 2011], the solution of the time-space fractional reaction diffusion equations in two dimensions can be written in terms of a matrix function vector product $f(A)b$ at each time step, where $A$ is an approximate matrix representation of the standard Laplacian. We use the finite volume method over unstructured triangular meshes to generate the matrix $A$, which is therefore non-symmetric. However, the standard Lanczos method for approximating $f(A)b$ requires that $A$ is symmetric. We propose a simple and novel transformation in which the standard Lanczos method is still applicable to find $f(A)b$, despite the loss of symmetry. Numerical results are presented to verify the accuracy and efficiency of our newly proposed numerical solution strategy.
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Information literacy researchers are beginning to develop a collective consciousness, a consciousness that represents the newly appearing territory of information literacy research. This paper analyses the information literacy research territory as it is represented by the emerging collective consciousness of information literacy researchers. Five dimensions of the collective consciousness are proposed: 1) the sectoral location of the research, 2) ways of seeing information literacy, 3) ‘what’ is being investigated; that is the research object, 4) ‘how’ the object is being investigated; that is the research approaches and paradigms, and 5) disciplinary influences. These dimensions are used to: 1) reveal the character of the information literacy research territory which is in early stages of construction; 2) show how different kinds of research approaches can shed different kinds of light on the object of research; and 3) demonstrate how the five dimensions work together in the development of new studies.
Resumo:
Magnesium alloys have been of growing interest to various engineering applications, such as the automobile, aerospace, communication and computer industries due to their low density, high specific strength, good machineability and availability as compared with other structural materials. However, most Mg alloys suffer from poor plasticity due to their Hexagonal Close Packed structure. Grain refinement has been proved to be an effective method to enhance the strength and alter the ductility of the materials. Several methods have been proposed to produce materials with nanocrystalline grain structures. So far, most of the research work on nanocrystalline materials has been carried out on Face-Centered Cubic and Body-Centered Cubic metals. However, there has been little investigation of nanocrystalline Mg alloys. In this study, bulk coarse-grained and nanocrystalline Mg alloys were fabricated by a mechanical alloying method. The mixed powder of Mg chips and Al powder was mechanically milled under argon atmosphere for different durations of 0 hours (MA0), 10 hours (MA10), 20 hours (MA20), 30 hours (MA30) and 40 hours (MA40), followed by compaction and sintering. Then the sintered billets were hot-extruded into metallic rods with a 7 mm diameter. The obtained Mg alloys have a nominal composition of Mg–5wt% Al, with grain sizes ranging from 13 μm down to 50 nm, depending on the milling durations. The microstructure characterization and evolution after deformation were carried out by means of Optical microscopy, X-Ray Diffraction, Scanning Electron Microscopy, Transmission Electron Microscopy, Scanning Probe Microscopy and Neutron Diffraction techniques. Nanoindentaion, compression and micro-compression tests on micro-pillars were used to study the size effects on the mechanical behaviour of the Mg alloys. Two kinds of size effects on the mechanical behaviours and deformation mechanisms were investigated: grain size effect and sample size effect. The nanoindentation tests were composed of constant strain rate, constant loading rate and indentation creep tests. The normally reported indentation size effect in single crystal and coarse-grained crystals was observed in both the coarse-grained and nanocrystalline Mg alloys. Since the indentation size effect is correlated to the Geometrically Necessary Dislocations under the indenter to accommodate the plastic deformation, the good agreement between the experimental results and the Indentation Size Effect model indicated that, in the current nanocrystalline MA20 and MA30, the dislocation plasticity was still the dominant deformation mechanism. Significant hardness enhancement with decreasing grain size, down to 58 nm, was found in the nanocrystalline Mg alloys. Further reduction of grain size would lead to a drop in the hardness values. The failure of grain refinement strengthening with the relatively high strain rate sensitivity of nanocrystalline Mg alloys suggested a change in the deformation mechanism. Indentation creep tests showed that the stress exponent was dependent on the loading rate during the loading section of the indentation, which was related to the dislocation structures before the creep starts. The influence of grain size on the mechanical behaviour and strength of extruded coarse-grained and nanocrystalline Mg alloys were investigated using uniaxial compression tests. The macroscopic response of the Mg alloys transited from strain hardening to strain softening behaviour, with grain size reduced from 13 ìm to 50 nm. The strain hardening was related to the twinning induced hardening and dislocation hardening effect, while the strain softening was attributed to the localized deformation in the nanocrystalline grains. The tension–compression yield asymmetry was noticed in the nanocrystalline region, demonstrating the twinning effect in the ultra-fine-grained and nanocrystalline region. The relationship k tensions < k compression failed in the nanocrystalline Mg alloys; this was attributed to the twofold effect of grain size on twinning. The nanocrystalline Mg alloys were found to exhibit increased strain rate sensitivity with decreasing grain size, with strain rate ranging from 0.0001/s to 0.01/s. Strain rate sensitivity of coarse-grained MA0 was increased by more than 10 times in MA40. The Hall-Petch relationship broke down at a critical grain size in the nanocrystalline region. The breakdown of the Hall-Petch relationship and the increased strain rate sensitivity were due to the localized dislocation activities (generalization and annihilation at grain boundaries) and the more significant contribution from grain boundary mediated mechanisms. In the micro-compression tests, the sample size effects on the mechanical behaviours were studied on MA0, MA20 and MA40 micro-pillars. In contrast to the bulk samples under compression, the stress-strain curves of MA0 and MA20 micro-pillars were characterized with a number of discrete strain burst events separated by nearly elastic strain segments. Unlike MA0 and MA20, the stress-strain curves of MA40 micro-pillars were smooth, without obvious strain bursts. The deformation mechanisms of the MA0 and MA20 micro-pillars under micro-compression tests were considered to be initially dominated by deformation twinning, followed by dislocation mechanisms. For MA40 pillars, the deformation mechanisms were believed to be localized dislocation activities and grain boundary related mechanisms. The strain hardening behaviours of the micro-pillars suggested that the grain boundaries in the nanocrystalline micro-pillars would reduce the source (nucleation sources for twins/dislocations) starvation hardening effect. The power law relationship of the yield strength on pillar dimensions in MA0, MA20 supported the fact that the twinning mechanism was correlated to the pre-existing defects, which can promote the nucleation of the twins. Then, we provided a latitudinal comparison of the results and conclusions derived from the different techniques used for testing the coarse-grained and nanocrystalline Mg alloy; this helps to better understand the deformation mechanisms of the Mg alloys as a whole. At the end, we summarized the thesis and highlighted the conclusions, contributions, innovations and outcomes of the research. Finally, it outlined recommendations for future work.
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Signal-degrading speckle is one factor that can reduce the quality of optical coherence tomography images. We demonstrate the use of a hierarchical model-based motion estimation processing scheme based on an affine-motion model to reduce speckle in optical coherence tomography imaging, by image registration and the averaging of multiple B-scans. The proposed technique is evaluated against other methods available in the literature. The results from a set of retinal images show the benefit of the proposed technique, which provides an improvement in signal-to-noise ratio of the square root of the number of averaged images, leading to clearer visual information in the averaged image. The benefits of the proposed technique are also explored in the case of ocular anterior segment imaging.
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Several authors stress the importance of data’s crucial foundation for operational, tactical and strategic decisions (e.g., Redman 1998, Tee et al. 2007). Data provides the basis for decision making as data collection and processing is typically associated with reducing uncertainty in order to make more effective decisions (Daft and Lengel 1986). While the first series of investments of Information Systems/Information Technology (IS/IT) into organizations improved data collection, restricted computational capacity and limited processing power created challenges (Simon 1960). Fifty years on, capacity and processing problems are increasingly less relevant; in fact, the opposite exists. Determining data relevance and usefulness is complicated by increased data capture and storage capacity, as well as continual improvements in information processing capability. As the IT landscape changes, businesses are inundated with ever-increasing volumes of data from both internal and external sources available on both an ad-hoc and real-time basis. More data, however, does not necessarily translate into more effective and efficient organizations, nor does it increase the likelihood of better or timelier decisions. This raises questions about what data managers require to assist their decision making processes.
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Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.
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Within Australia, motor vehicle injury is the leading cause of hospital admissions and fatalities. Road crash data reveals that among the factors contributing to crashes in Queensland, speed and alcohol continue to be overrepresented. While alcohol is the number one contributing factor to fatal crashes, speeding also contributes to a high proportion of crashes. Research indicates that risky driving is an important contributor to road crashes. However, it has been debated whether all risky driving behaviours are similar enough to be explained by the same combination of factors. Further, road safety authorities have traditionally relied upon deterrence based countermeasures to reduce the incidence of illegal driving behaviours such as speeding and drink driving. However, more recent research has focussed on social factors to explain illegal driving behaviours. The purpose of this research was to examine and compare the psychological, legal, and social factors contributing to two illegal driving behaviours: exceeding the posted speed limit and driving when over the legal blood alcohol concentration (BAC) for the drivers licence type. Complementary theoretical perspectives were chosen to comprehensively examine these two behaviours including Akers’ social learning theory, Stafford and Warr’s expanded deterrence theory, and personality perspectives encompassing alcohol misuse, sensation seeking, and Type-A behaviour pattern. The program of research consisted of two phases: a preliminary pilot study, and the main quantitative phase. The preliminary pilot study was undertaken to inform the development of the quantitative study and to ensure the clarity of the theoretical constructs operationalised in this research. Semi-structured interviews were conducted with 11 Queensland drivers recruited from Queensland Transport Licensing Centres and Queensland University of Technology (QUT). These interviews demonstrated that the majority of participants had engaged in at least one of the behaviours, or knew of someone who had. It was also found among these drivers that the social environment in which both behaviours operated, including family and friends, and the social rewards and punishments associated with the behaviours, are important in their decision making. The main quantitative phase of the research involved a cross-sectional survey of 547 Queensland licensed drivers. The aim of this study was to determine the relationship between speeding and drink driving and whether there were any similarities or differences in the factors that contribute to a driver’s decision to engage in one or the other. A comparison of the participants self-reported speeding and self-reported drink driving behaviour demonstrated that there was a weak positive association between these two behaviours. Further, participants reported engaging in more frequent speeding at both low (i.e., up to 10 kilometres per hour) and high (i.e., 10 kilometres per hour or more) levels, than engaging in drink driving behaviour. It was noted that those who indicated they drove when they may be over the legal limit for their licence type, more frequently exceeded the posted speed limit by 10 kilometres per hour or more than those who complied with the regulatory limits for drink driving. A series of regression analyses were conducted to investigate the factors that predict self-reported speeding, self-reported drink driving, and the preparedness to engage in both behaviours. In relation to self-reported speeding (n = 465), it was found that among the sociodemographic and person-related factors, younger drivers and those who score high on measures of sensation seeking were more likely to report exceeding the posted speed limit. In addition, among the legal and psychosocial factors it was observed that direct exposure to punishment (i.e., being detected by police), direct punishment avoidance (i.e., engaging in an illegal driving behaviour and not being detected by police), personal definitions (i.e., personal orientation or attitudes toward the behaviour), both the normative and behavioural dimensions of differential association (i.e., refers to both the orientation or attitude of their friends and family, as well as the behaviour of these individuals), and anticipated punishments were significant predictors of self-reported speeding. It was interesting to note that associating with significant others who held unfavourable definitions towards speeding (the normative dimension of differential association) and anticipating punishments from others were both significant predictors of a reduction in self-reported speeding. In relation to self-reported drink driving (n = 462), a logistic regression analysis indicated that there were a number of significant predictors which increased the likelihood of whether participants had driven in the last six months when they thought they may have been over the legal alcohol limit. These included: experiences of direct punishment avoidance; having a family member convicted of drink driving; higher levels of Type-A behaviour pattern; greater alcohol misuse (as measured by the AUDIT); and the normative dimension of differential association (i.e., associating with others who held favourable attitudes to drink driving). A final logistic regression analysis examined the predictors of whether the participants reported engaging in both drink driving and speeding versus those who reported engaging in only speeding (the more common of the two behaviours) (n = 465). It was found that experiences of punishment avoidance for speeding decreased the likelihood of engaging in both speeding and drink driving; whereas in the case of drink driving, direct punishment avoidance increased the likelihood of engaging in both behaviours. It was also noted that holding favourable personal definitions toward speeding and drink driving, as well as higher levels of on Type-A behaviour pattern, and greater alcohol misuse significantly increased the likelihood of engaging in both speeding and drink driving. This research has demonstrated that the compliance with the regulatory limits was much higher for drink driving than it was for speeding. It is acknowledged that while speed limits are a fundamental component of speed management practices in Australia, the countermeasures applied to both speeding and drink driving do not appear to elicit the same level of compliance across the driving population. Further, the findings suggest that while the principles underpinning the current regime of deterrence based countermeasures are sound, current enforcement practices are insufficient to force compliance among the driving population, particularly in the case of speeding. Future research should further examine the degree of overlap between speeding and drink driving behaviour and whether punishment avoidance experiences for a specific illegal driving behaviour serve to undermine the deterrent effect of countermeasures aimed at reducing the incidence of another illegal driving behaviour. Furthermore, future work should seek to understand the factors which predict engaging in speeding and drink driving behaviours at the same time. Speeding has shown itself to be a pervasive and persistent behaviour, hence it would be useful to examine why road safety authorities have been successful in convincing the majority of drivers of the dangers of drink driving, but not those associated with speeding. In conclusion, the challenge for road safety practitioners will be to convince drivers that speeding and drink driving are equally risky behaviours, with the ultimate goal to reduce the prevalence of both behaviours.
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Gold nanoparticles supported on CeO2 were found to be efficient photocatalysts for three selective reductions of organic compounds at ambient temperatures, under irradiation of visible light; their reduction ability can be tuned by manipulating the irradiation wavelength.