143 resultados para Gaussian extended cubature formula


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Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

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Speeding in school zones is a problem in both Malaysia and Australia. While there are differences between the countries in terms of school zone treatments and more generally, these differences do not explain why people choose to speed in school zones. Because speeding is usually an intentional behaviour, the Theory of Planned Behaviour (TPB) has been used to understand speeding and develop interventions, however it has limitations which can be addressed by extending the model to incorporate other constructs. One promising construct is mindfulness, which can improve the explanatory value of the TPB by taking into account unintentional speeding attributable to a lack of focus on important elements of the driving environment. We explain what mindfulness is (and is not), how it can assist in providing a better understanding of speeding in school zones, and how it can contribute to the development of interventions. We then outline a program of research which has been commenced, investigating the contribution of mindfulness to an understanding of speed choice in school zones in two different settings (Australia and Malaysia) using the TPB.

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Injury is the leading cause of death among adolescents, and in many countries, accounts for more deaths than all other causes combined. Rates of death due to injury also increase dramatically across adolescence. The Australian Institute of Health and Welfare reported that, in 2005, there were 954 deaths of young Australians due to injury, which is a rate of 26 deaths per 100,000 young people. Of these deaths, 4% were adolescents aged 12-14, 17% were aged 15-17, and 80% were aged 18-24 years. Issues addressed: Injuries are the leading cause of death among adolescents. The current research examined a measure of adolescent injury in terms of whether it encompasses the diverse injury experiences of Australian adolescents, including high-risk and normative adolescents, and thus determine its utility as a tool for health promotion research. Grade 9 students from two Brisbane high schools (n=202, aged 13-14 years) and adolescents recruited from the Emergency Department waiting rooms of four Brisbane hospitals (n=98, aged 16-18 years) completed the Extended Adolescent Injury Checklist (E-AIC). The most common cause of injury among adolescents was a sports activity, followed by fights for all participants except schoolbased males, who experienced more bicycle injuries. Alcohol use was most frequently reported in association with interpersonal violence injuries. A broad variety of injuries, occurring in context of multiple risk as well as normative behaviours, were reported by adolescents in both school and ED settings, and were captured by the E-AIC. Findings suggest that the E-AIC is a useful measure that captures the injury experiences of adolescents in different contexts. The high occurrence of injuries that do not result in formal medical treatment also indicates scope for interventions to be based around lessons in first aid, while also incorporating injury prevention components.

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We have successfully synthesized hydrotalcites (HTs) contg. calcium, which are naturally occurring minerals. Insight into the unique structure of HTs has been obtained using a combination of X-ray diffraction (XRD) as well as IR and Raman spectroscopies. Calcium-contg. hydrotalcites (Ca-HTs) of the formula Ca4Al2(CO3)(OH)12·4H2O (2:1 Ca-HT) to Ca8Al2(CO3)(OH)20· 4H2O (4:1 Ca-HT) have been successfully synthesized and characterised by XRD and Raman spectroscopy. XRD has shown that 3:1 calcium HTs have the largest interlayer distance. Raman spectroscopy complemented with selected IR data has been used to characterize the synthesized Ca-HTs. The Raman bands obsd. at around 1086 and 1077 cm-1 were attributed to the ν1 sym. stretching modes of the (CO32-) units of calcite and carbonate intercalated into the HT interlayer. The corresponding ν3 CO32- antisym. stretching modes are found at around 1410 and 1475 cm-1.

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This paper proposes a novel approach for identifying risks in executable business processes and detecting them at run time. The approach considers risks in all phases of the business process management lifecycle, and is realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of faults to occur. Both historical and current execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a process automation suite to prompt the results to the user who may take remedial actions. The proposed architecture has been implemented in the YAWL system and its performance has been evaluated in practice.

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Background Chlamydia pneumoniae is a widespread pathogen causing upper and lower respiratory tract infections in addition to a range of other diseases in humans and animals. Previous whole genome analyses have focused on four essentially clonal (> 99% identity) C. pneumoniae human genomes (AR39, CWL029, J138 and TW183), providing relatively little insight into strain diversity and evolution of this species. Results We performed individual gene-by-gene comparisons of the recently sequenced C. pneumoniae koala genome and four C. pneumoniae human genomes to identify species-specific genes, and more importantly, to gain an insight into the genetic diversity and evolution of the species. We selected genes dispersed throughout the chromosome, representing genes that were specific to C. pneumoniae, genes with a demonstrated role in chlamydial biology and/or pathogenicity (n = 49), genes encoding nucleotide salvage or amino acid biosynthesis proteins (n = 6), and extrachromosomal elements (9 plasmid and 2 bacteriophage genes). Conclusions We have identified strain-specific differences and targets for detection of C. pneumoniae isolates from both human and animal origin. Such characterisation is necessary for an improved understanding of disease transmission and intervention.

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We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we prove general risk bounds in terms of these complexities. We consider function classes that can be expressed as combinations of functions from basis classes and show how the Rademacher and Gaussian complexities of such a function class can be bounded in terms of the complexity of the basis classes. We give examples of the application of these techniques in finding data-dependent risk bounds for decision trees, neural networks and support vector machines.

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Gaussian mixture models (GMMs) have become an established means of modeling feature distributions in speaker recognition systems. It is useful for experimentation and practical implementation purposes to develop and test these models in an efficient manner particularly when computational resources are limited. A method of combining vector quantization (VQ) with single multi-dimensional Gaussians is proposed to rapidly generate a robust model approximation to the Gaussian mixture model. A fast method of testing these systems is also proposed and implemented. Results on the NIST 1996 Speaker Recognition Database suggest comparable and in some cases an improved verification performance to the traditional GMM based analysis scheme. In addition, previous research for the task of speaker identification indicated a similar system perfomance between the VQ Gaussian based technique and GMMs

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Many optical networks are limited in speed and processing capability due to the necessity for the optical signal to be converted to an electrical signal and back again. In addition, electronically manipulated interconnects in an otherwise optical network lead to overly complicated systems. Optical spatial solitons are optical beams that propagate without spatial divergence. They are capable of phase dependent interactions, and have therefore been extensively researched as suitable all optical interconnects for over 20 years. However, they require additional external components, initially high voltage power sources were required, several years later, high power background illumination had replaced the high voltage. However, these additional components have always remained as the greatest hurdle in realising the applications of the interactions of spatial optical solitons as all optical interconnects. Recently however, self-focusing was observed in an otherwise self-defocusing photorefractive crystal. This observation raises the possibility of the formation of soliton-like fields in unbiased self-defocusing media, without the need for an applied electrical field or background illumination. This thesis will present an examination of the possibility of the formation of soliton-like low divergence fields in unbiased self-defocusing photorefractive media. The optimal incident beam and photorefractive media parameters for the formation of these fields will be presented, together with an analytical and numerical study of the effect of these parameters. In addition, preliminary examination of the interactions of two of these fields will be presented. In order to complete an analytical examination of the field propagating through the photorefractive medium, the spatial profile of the beam after propagation through the medium was determined. For a low power solution, it was found that an incident Gaussian field maintains its Gaussian profile as it propagates. This allowed the beam at all times to be described by an individual complex beam parameter, while also allowing simple analytical solutions to the appropriate wave equation. An analytical model was developed to describe the effect of the photorefractive medium on the Gaussian beam. Using this model, expressions for the required intensity dependent change in both the real and imaginary components of the refractive index were found. Numerical investigation showed that under certain conditions, a low powered Gaussian field could propagate in self-defocusing photorefractive media with divergence of approximately 0.1 % per metre. An investigation into the parameters of a Ce:BaTiO3 crystal showed that the intensity dependent absorption is wavelength dependent, and can in fact transition to intensity dependent transparency. Thus, with careful wavelength selection, the required intensity dependent change in both the real and imaginary components of the refractive index for the formation of a low divergence Gaussian field are physically realisable. A theoretical model incorporating the dependence of the change in real and imaginary components of the refractive index on propagation distance was developed. Analytical and numerical results from this model are congruent with the results from the previous model, showing low divergence fields with divergence less than 0.003 % over the propagation length of the photorefractive medium. In addition, this approach also confirmed the previously mentioned self-focusing effect of the self-defocusing media, and provided an analogy to a negative index GRIN lens with an intensity dependent focal length. Experimental results supported the findings of the numerical analysis. Two low divergence fields were found to possess the ability to interact in a Ce:BaTiO3 crystal in a soliton-like fashion. The strength of these interactions was found to be dependent on the degree of divergence of the individual beams. This research found that low-divergence fields are possible in unbiased self-defocusing photorefractive media, and that soliton-like interactions between two of these fields are possible. However, in order for these types of fields to be used in future all optical interconnects, the manipulation of these interactions, together with the ability for these fields to guide a second beam at a different wavelength, must be investigated.