337 resultados para spatial pattern
Resumo:
A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants
Resumo:
Condition monitoring of diesel engines can prevent unpredicted engine failures and the associated consequence. This paper presents an experimental study of the signal characteristics of a 4-cylinder diesel engine under various loading conditions. Acoustic emission, vibration and in-cylinder pressure signals were employed to study the effectiveness of these techniques for condition monitoring and identifying symptoms of incipient failures. An event driven synchronous averaging technique was employed to average the quasi-periodic diesel engine signal in the time domain to eliminate or minimize the effect of engine speed and amplitude variations on the analysis of condition monitoring signal. It was shown that acoustic emission (AE) is a better technique than vibration method for condition monitor of diesel engines due to its ability to produce high quality signals (i.e., excellent signal to noise ratio) in a noisy diesel engine environment. It was found that the peak amplitude of AE RMS signals correlating to the impact-like combustion related events decreases in general due to a more stable mechanical process of the engine as the loading increases. A small shift in the exhaust valve closing time was observed as the engine load increases which indicates a prolong combustion process in the cylinder (to produce more power). On the contrary, peak amplitudes of the AE RMS attributing to fuel injection increase as the loading increases. This can be explained by the increase fuel friction caused by the increase volume flow rate during the injection. Multiple AE pulses during the combustion process were identified in the study, which were generated by the piston rocking motion and the interaction between the piston and the cylinder wall. The piston rocking motion is caused by the non-uniform pressure distribution acting on the piston head as a result of the non-linear combustion process of the engine. The rocking motion ceased when the pressure in the cylinder chamber stabilized.
Resumo:
Background: Biomineralization is a process encompassing all mineral containing tissues produced within an organism. One of the most dynamic examples of this process is the formation of the mollusk shell, comprising a variety of crystal phases and microstructures. The organic component incorporated within the shell is said to dictate this architecture. However general understanding of how this process is achieved remains ambiguous. The mantle is a conserved organ involved in shell formation throughout molluscs. Specifically the mantle is thought to be responsible for secreting the protein component of the shell. This study employs molecular approaches to determine the spatial expression of genes within the mantle tissue to further the elucidation of the shell biomineralization. Results: A microarray platform was custom generated (PmaxArray 1.0) from the pearl oyster Pinctada maxima. PmaxArray 1.0 consists of 4992 expressed sequence tags (ESTs) originating from mantle tissue. This microarray was used to analyze the spatial expression of ESTs throughout the mantle organ. The mantle was dissected into five discrete regions and analyzed for differential gene expression with PmaxArray 1.0. Over 2000 ESTs were determined to be differentially expressed among the tissue sections, identifying five major expression regions. In situ hybridization validated and further localized the expression for a subset of these ESTs. Comparative sequence similarity analysis of these ESTs revealed a number of the transcripts were novel while others showed significant sequence similarities to previously characterized shell related genes.
Resumo:
One of the fundamental motivations underlying computational cell biology is to gain insight into the complicated dynamical processes taking place, for example, on the plasma membrane or in the cytosol of a cell. These processes are often so complicated that purely temporal mathematical models cannot adequately capture the complex chemical kinetics and transport processes of, for example, proteins or vesicles. On the other hand, spatial models such as Monte Carlo approaches can have very large computational overheads. This chapter gives an overview of the state of the art in the development of stochastic simulation techniques for the spatial modelling of dynamic processes in a living cell.
Resumo:
Highlights ► Provides a review of the history and development of locative media. ► Outlines different human-computer interaction techniques applied in locative media. ► Discusses how locative media applications have changed interaction affordances in and of physical spaces. ► Discusses practices of people in urban settings that evolved through these new affordances. ► Provides an overview on methods to investigate and elaborate design principles for future locative media.
Resumo:
This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.
Resumo:
The Giant Long-Armed Prawn, Macrobrachium lar is a freshwater species native to the Indo-Pacific. M. lar has a long-lived, passive, pelagic marine larval stage where larvae need to colonise freshwater within three months to complete their development. Dispersal is likely to be influenced by the extensive distances larvae must transit between small oceanic islands to find suitable freshwater habitat, and by prevailing east to west wind and ocean currents in the southern Pacific Ocean. Thus, both intrinsic and extrinsic factors are likely to influence wild population structure in this species. The present study sought to define the contemporary broad and fine-scale population genetic structure of Macrobrachium lar in the south-western Pacific Ocean. Three polymorphic microsatellite loci were used to assess patterns of genetic variation within and among 19 wild adult sample sites. Statistical procedures that partition variation implied that at both spatial scales, essentially all variation was present within sample sites and differentiation among sites was low. Any differentiation observed also was not correlated with geographical distance. Statistical approaches that measure genetic distance, at the broad-scale, showed that all south-western Pacific Islands were essentially homogeneous, with the exception of a well supported divergent Cook Islands group. These findings are likely the result of some combination of factors that may include the potential for allelic homoplasy, through to the effects of sampling regime. Based on the findings, there is most likely a divergent M. lar Cook Islands clade in the south-western Pacific Ocean, resulting from prevailing ocean currents. Confirmation of this pattern will require a more detailed analysis of nDNA variation using a larger number of loci and, where possible, use of larger population sizes.
Resumo:
Self-segregation and compartimentalisation are observed experimentally to occur spontaneously on live membranes as well as reconstructed model membranes. It is believed that many of these processes are caused or supported by anomalous diffusive behaviours of biomolecules on membranes due to the complex and heterogeneous nature of these environments. These phenomena are on the one hand of great interest in biology, since they may be an important way for biological systems to selectively localize receptors, regulate signaling or modulate kinetics; and on the other, they provide an inspiration for engineering designs that mimick natural systems. We present an interactive software package we are developing for the purpose of simulating such processes numerically using a fundamental Monte Carlo approach. This program includes the ability to simulate kinetics and mass transport in the presence of either mobile or immobile obstacles and other relevant structures such as liquid-ordered lipid microdomains. We also present preliminary simulation results regarding the selective spatial localization and chemical kinetics modulating power of immobile obstacles on the membrane, obtained using the program.
Resumo:
A new approach to pattern recognition using invariant parameters based on higher order spectra is presented. In particular, invariant parameters derived from the bispectrum are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale and amplification invariant, as well. A minimal set of these invariants is selected as the feature vector for pattern classification, and a minimum distance classifier using a statistical distance measure is used to classify test patterns. The classification technique is shown to distinguish two similar, but different bolts given their one-dimensional profiles. Pattern recognition using higher order spectral invariants is fast, suited for parallel implementation, and has high immunity to additive Gaussian noise. Simulation results show very high classification accuracy, even for low signal-to-noise ratios.
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Project as a Capstone Learning Unit: Courses of the QUT Faculty of BEE seek to enable students to practice as professionals in their respective disciplines. A major part of such practice is the instigation, management,monitoring, and reporting on an urban development project. This unit offers the student a capstone learning experience near the end of their fourth year of undergraduate study. Expose the student to a set of integrated activities, each building upon the preceding, and culminating in a 'completed' project. Students apply skills and knowledge attained earlier in the course and develop new abilities for application to a real-world problem, industry or research based, to simulate the design, development and management of a project solution. These 10-12minute seminar presentations comprise the mini-conference event that are of benefit to the wider surveying and spatial science industry.
Resumo:
Abstract: Goals and potential impacts of QUT corporate Blueprint3 framework, university has made significant investments in physical infrastructure, and investments to improve staff profiles, particularly in relation to science, technology, engineering, and mathematics (STEM) disciplines. The most significant physical change to the Faculty’s infrastructure has seen new workshop and teaching and research spaces located in Science and Technology precinct under construction. Also includes Alumni news, input and output numbers Spatial Science discussion, Work Integrated Learning (WIL) in 2011, some key teaching administrative dates in 2011.
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Multiple awards for Spatial/Surveying lecturer, raising entry quality and commencing numbers at QUT, Gardens Point rapt in promise of things to come, STEM building progress.