Postcode segmentation and recognition using projections and bispectral features

A system to segment and recognize Australian 4-digit postcodes from address labels on parcels is described. Images of address labels are preprocessed and adaptively thresholded to reduce noise. Projections are used to segment the line and then the characters comprising the postcode. Individual digits are recognized using bispectral features extracted from their parallel beam projections. These features are insensitive to translation, scaling and rotation, and robust to noise. Results on scanned images are presented. The system is currently being improved and implemented to work on-line.

Geometric Distortion Insensitive Image Watermarking in Affine Covariant Regions

Feature-based image watermarking schemes, which aim to survive various geometric distortions, have attracted great attention in recent years. Existing schemes have shown robustness against rotation, scaling, and translation, but few are resistant to cropping, nonisotropic scaling, random bending attacks (RBAs), and affine transformations. Seo and Yoo present a geometrically invariant image watermarking based on affine covariant regions (ACRs) that provide a certain degree of robustness. To further enhance the robustness, we propose a new image watermarking scheme on the basis of Seo's work, which is insensitive to geometric distortions as well as common image processing operations. Our scheme is mainly composed of three components: 1) feature selection procedure based on graph theoretical clustering algorithm is applied to obtain a set of stable and nonoverlapped ACRs; 2) for each chosen ACR, local normalization, and orientation alignment are performed to generate a geometrically invariant region, which can obviously improve the robustness of the proposed watermarking scheme; and 3) in order to prevent the degradation in image quality caused by the normalization and inverse normalization, indirect inverse normalization is adopted to achieve a good compromise between the imperceptibility and robustness. Experiments are carried out on an image set of 100 images collected from Internet, and the preliminary results demonstrate that the developed method improves the performance over some representative image watermarking approaches in terms of robustness.

Can the scaling behavior of electric conductivity be used to probe the self-organizational changes in solution with respect to the ionic liquid structure? The case of [C8MIM][NTf2]

Electrical conductivity of the supercooled ionic liquid [C8MIM][NTf2], determined as a function of temperature and pressure, highlights strong differences in its ionic transport behavior between low and high temperature regions. To date, the crossover effect which is very well known for low molecular van der Waals liquids has been rarely described for classical ionic liquids. This finding highlights that the thermal fluctuations could be dominant mechanisms driving the dramatic slowing down of ion motions near Tg. An alternative way to analyze separately low and high temperature dc-conductivity data using a density scaling approach was then proposed. Based on which a common value of the scaling exponent [gamma] = 2.4 was obtained, indicating that the applied density scaling is insensitive to the crossover effect. By comparing the scaling exponent [gamma] reported herein along with literature data for other ionic liquids, it appears that [gamma] decreases by increasing the alkyl chain length on the 1-alkyl-3-methylimidazolium-based ionic liquids. This observation may be related to changes in the interaction between ions in solution driven by an increase in the van der Waals type interaction by increasing the alkyl chain length on the cation. This effect may be related to changes in the ionic liquid nanostructural organization with the alkyl chain length on the cation as previously reported in the literature based on molecular dynamic simulations. In other words, the calculated scaling exponent [gamma] may be then used as a key parameter to probe the interaction and/or self-organizational changes in solution with respect to the ionic liquid structure.

Seasonal metabolic depression, substrate utilisation and changes in scaling patterns during the first year cycle of tegu lizards (Tupinambis merianae)

The tegus increase in body mass after hatching until early autumn, when the energy intake becomes gradually reduced. Resting rates of oxygen consumption in winter drop to 20% of the values in the active season (Vo(2)=0.0636 ml g(-1) h(-1)) and are nearly temperature insensitive over the range of 17-25degreesC (Q(10)=1.55). During dormancy, plasma glucose levels are 60% lower than those in active animals, while total protein, total lipids and beta-hydroxybutyrate are elevated by 24%, 43% and 113%, respectively. In addition, a significant depletion of liver carbohydrate (50%) and of fat deposited in the visceral fat bodies (24%) and in the tail (25%) and a slight loss of skeletal muscle protein (14%) were measured halfway through the inactive period. Otherwise, glycogen content is increased 4-fold in the brain and 2.3-fold in the heart of dormant lizards, declining by the onset of arousal. During early arousal, the young tegus are still anorexic, although Vo(2) is significantly greater than winter rates. The fat deposits analysed are further reduced (62% and 45%, respectively) and there is a large decrease in tail muscle protein (50%) together with a significant increase in glycogen (2-3-fold) and an increase in plasma glucose (40%), which suggests a role for gluconeogenesis as a supplementary energy source in arousing animals. No change is detectable in citrate synthase activity, but beta-hydroxyacyl CoA dehydrogenase activities are strongly affected by season, reaching a Mold and 5-fold increase in the liver tissue of winter and arousing animals, respectively, and becoming reduced by half in skeletal muscle and heart of winter animals compared with late fall or spring active individuals. From hatching to late autumn, the increase of the fat body mass relatively to body mass is disproportionate (b=1.44), and the mass exponent changes significantly to close to 1.0 during the fasting period. The concomitant shift in the Vo(2) mass exponent in early autumn (b=0.75) to values significantly greater than 1.0 in late autumn and during winter dormancy indicates an allometric effect on the degree of metabolic depression related to the size of the fat stores and suggests greater energy conservation in the smaller young.

Invariant scaling relationships for interspecific plant biomass production rates and body size

The allometric relationships for plant annualized biomass production (“growth”) rates, different measures of body size (dry weight and length), and photosynthetic biomass (or pigment concentration) per plant (or cell) are reported for multicellular and unicellular plants representing three algal phyla; aquatic ferns; aquatic and terrestrial herbaceous dicots; and arborescent monocots, dicots, and conifers. Annualized rates of growth G scale as the 3/4-power of body mass M over 20 orders of magnitude of M (i.e., G ∝ M3/4); plant body length L (i.e., cell length or plant height) scales, on average, as the 1/4-power of M over 22 orders of magnitude of M (i.e., L ∝ M1/4); and photosynthetic biomass Mp scales as the 3/4-power of nonphotosynthetic biomass Mn (i.e., Mp ∝ Mn3/4). Because these scaling relationships are indifferent to phylogenetic affiliation and habitat, they have far-reaching ecological and evolutionary implications (e.g., net primary productivity is predicted to be largely insensitive to community species composition or geological age).

The influence of instructions and body-scaling as constraints on decision-making processes in team sports

Team games conceptualized as dynamical systems engender a view of emergent decision-making behaviour under constraints, although specific effects of instructional and body-scaling constraints have yet to be verified empirically. For this purpose, we studied the effects of task and individual constraints on decision-making processes in basketball. Eleven experienced female players performed 350 trials in 1 vs. 1 sub-phases of basketball in which an attacker tried to perturb the stable state of a dyad formed with a defender (i.e. break the symmetry). In Experiment 1, specific instructions (neutral, risk taking or conservative) were manipulated to observe effects on emergent behaviour of the dyadic system. When attacking players were given conservative instructions, time to cross court mid-line and variability of the attacker's trajectory were significantly greater. In Experiment 2, body-scaling of participants was manipulated by creating dyads with different height relations. When attackers were considerably taller than defenders, there were fewer occurrences of symmetry-breaking. When attackers were considerably shorter than defenders, time to cross court mid-line was significantly shorter than when dyads were composed of athletes of similar height or when attackers were considerably taller than defenders. The data exemplify how interacting task and individual constraints can influence emergent decision-making processes in team ball games.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

Scaling acoustic data analysis through collaboration and automation

Monitoring and assessing environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods of time. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data effectively and efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; collaboration, manual, automatic and human-in-the loop analysis.

Scaling of natural convection of an inclined flat plate : ramp cooling condition

A scaling analysis is performed for the transient boundary layer established adjacent to an inclined flat plate following a ramp cooling boundary condition. The imposed wall temperature decreases linearly up to a specific value over a specific time. It is revealed that if the ramp time is sufficiently large then the boundary layer reaches quasi-steady mode before the growth of the temperature is finished. However, if the ramp time is shorter then the steady state of the boundary layer may be reached after the growth of the temperature is completed. In this case, the ultimate steady state is the same as if the start up had been instantaneous. Note that the cold boundary layer adjacent to the plate is potentially unstable to Rayleigh-Bénard instability if the Rayleigh number exceeds a certain critical value for this cooling case. The onset of instability may set in at different stages of the boundary layer development. A proper identification of the time when the instability may set in is discussed. A numerical verification of the time for the onset of instability is presented in this study. Different flow regimes based on the stability of the boundary layer have also been discussed with numerical results.

Scaling of natural convection of an inclined flat plate : sudden cooling condition

The natural convection boundary layer adjacent to an inclined plate subject to sudden cooling boundary condition has been studied. It is found that the cold boundary layer adjacent to the plate is potentially unstable to Rayleigh-Bénard instability if the Rayleigh number exceeds a certain critical value. A scaling relation for the onset of instability of the boundary layer is achieved. The scaling relations have been developed by equating important terms of the governing equations based on the development of the boundary layer with time. The flow adjacent to the plate can be classified broadly into a conductive, a stable convective or an unstable convective regime determined by the Rayleigh number. Proper scales have been established to quantify the flow properties in each of these flow regimes. An appropriate identification of the time when the instability may set in is discussed. A numerical verification of the time for the onset of instability is also presented in this study. Different flow regimes based on the stability of the boundary layer have been discussed with numerical results.

Scaling of free convection heat transfer in a triangular cavity for Pr>1

Unsteady natural convection inside a triangular cavity subject to a non-instantaneous heating on the inclined walls in the form of an imposed temperature which increases linearly up to a prescribed steady value over a prescribed time is reported. The development of the flow from start-up to a steady-state has been described based on scaling analyses and direct numerical simulations. The ramp temperature has been chosen in such a way that the boundary layer is reached a quasi-steady mode before the growth of the temperature is completed. In this mode the thermal boundary layer at first grows in thickness, then contracts with increasing time. However, if the imposed wall temperature growth period is sufficiently short, the boundary layer develops differently. It is seen that the shape of many houses are isosceles triangular cross-section. The heat transfer process through the roof of the attic-shaped space should be well understood. Because, in the building energy, one of the most important objectives for design and construction of houses is to provide thermal comfort for occupants. Moreover, in the present energy-conscious society it is also a requirement for houses to be energy efficient, i.e. the energy consumption for heating or air-conditioning houses must be minimized.

Scaling analysis of the thermal boundary layer adjacent to an abruptly heated inclined flat plate

The natural convection thermal boundary layer adjacent to an abruptly heated inclined flat plate is investigated through a scaling analysis and verified by numerical simulations. In general, the development of the thermal flow can be characterized by three distinct stages, i.e. a start-up stage, a transitional stage and a steady state stage. Major scales including the flow velocity, flow development time, and the thermal and viscous boundary layer thicknesses are established to quantify the flow development at different stages and over a wide range of flow parameters. Details of the scaling analysis and the numerical procedures are described in this paper.

Scaling analysis of unsteady natural convection boundary layer for ramp heating

A scaling analysis for the natural convection boundary layer adjacent to an inclined semi-infinite plate subject to a non-instantaneous heating in the form of an imposed wall temperature which increases linearly up to a prescribed steady value over a prescribed time is reported. The development of the flow from start-up to a steady-state has been described based on scaling analyses and verified by numerical simulations. The analysis reveals that, if the period of temperature growth on the wall is sufficiently long, the boundary layer reaches a quasisteady mode before the growth of the temperature is completed. In this mode the thermal boundary layer at first grows in thickness and then contracts with increasing time. However, if the imposed wall temperature growth period is sufficiently short, the boundary layer develops differently, but after the wall temperature growth is completed, the boundary layer develops as though the start up had been instantaneous. The steady state values of the boundary layer for both cases are ultimately the same.