Face recognition using fractal codes

In this paper we propose a new method for face recognition using fractal codes. Fractal codes represent local contractive, affine transformations which when iteratively applied to range-domain pairs in an arbitrary initial image result in a fixed point close to a given image. The transformation parameters such as brightness offset, contrast factor, orientation and the address of the corresponding domain for each range are used directly as features in our method. Features of an unknown face image are compared with those pre-computed for images in a database. There is no need to iterate, use fractal neighbor distances or fractal dimensions for comparison in the proposed method. This method is robust to scale change, frame size change and rotations as well as to some noise, facial expressions and blur distortion in the image

Characteristics of airborne ultrafine and coarse particles during the Australian dust storm of 23 September 2009

Particle number concentrations and size distributions, visibility and particulate mass concentrations and weather parameters were monitored in Brisbane, Australia, on 23 September 2009, during the passage of a dust storm that originated 1400 km away in the dry continental interior. The dust concentration peaked at about mid-day when the hourly average PM2.5 and PM10 values reached 814 and 6460 µg m-3, respectively, with a sharp drop in atmospheric visibility. A linear regression analysis showed a good correlation between the coefficient of light scattering by particles (Bsp) and both PM10 and PM2.5. The particle number in the size range 0.5-20 µm exhibited a lognormal size distribution with modal and geometrical mean diameters of 1.6 and 1.9 µm, respectively. The modal mass was around 10 µm with less than 10% of the mass carried by particles smaller than 2.5 µm. The PM10 fraction accounted for about 68% of the total mass. By mid-day, as the dust began to increase sharply, the ultrafine particle number concentration fell from about 6x103 cm-3 to 3x103 cm-3 and then continued to decrease to less than 1x103 cm-3 by 14h, showing a power-law decrease with Bsp with an R2 value of 0.77 (p<0.01). Ultrafine particle size distributions also showed a significant decrease in number during the dust storm. This is the first scientific study of particle size distributions in an Australian dust storm.

Pattern recognition using invariants defined from higher order spectra - one-dimensional inputs

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.

Instantaneous phase of the autocorrelation and robustness to signal-dependent noise

The phase of an analytic signal constructed from the autocorrelation function of a signal contains significant information about the shape of the signal. Using Bedrosian's (1963) theorem for the Hilbert transform it is proved that this phase is robust to multiplicative noise if the signal is baseband and the spectra of the signal and the noise do not overlap. Higher-order spectral features are interpreted in this context and shown to extract nonlinear phase information while retaining robustness. The significance of the result is that prior knowledge of the spectra is not required.

On the behaviour of higher-order spectral features for object recognition in the presence of various types of noise

This paper presents results on the robustness of higher-order spectral features to Gaussian, Rayleigh, and uniform distributed noise. Based on cluster plots and accuracy results for various signal to noise conditions, the higher-order spectral features are shown to be better than moment invariant features.

Young children's understandings about "square" in 3D virtual reality microworlds

This paper reports an investigation of primary school children’s understandings about "square". 12 students participated in a small group teaching experiment session, where they were interviewed and guided to construct a square in a 3D virtual reality learning environment (VRLE). Main findings include mixed levels of "quasi" geometrical understandings, misconceptions about length and angles, and ambiguous uses of geometrical language for location, direction, and movement. These have implications for future teaching and learning about 2D shapes with particular reference to VRLE.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Improved design rules for hollow flange sections subject to lateral distortional buckling

The LiteSteel Beam (LSB) is a new hollow flange section with a unique geometry consisting of torsionally rigid rectangular hollow flanges and a relatively slender web. It is subjected to lateral distortional buckling when used as flexural members, which reduces its member moment capacity. An investigation into the flexural behaviour of LSBs using experiments and numerical analyses led to the development of new design rules for LSBs subject to lateral distortional buckling. However, the comparison of moment capacity results with the new design rules showed that they were conservative for some LSB sections while slightly unconservative for others due to the effects of section geometry. It is also unknown whether these design rules are applicable to other hollow flange sections such as hollow flange beams (HFB). This paper presents the details of a study into the lateral distortional buckling behaviour of hollow flange sections such as LSBs, HFBs and their variations. A geometrical parameter defined as the ratio of flange torsional rigidity to the major axis flexural rigidity of the web (GJf/EIxweb) was found to be a critical parameter in evaluating the lateral distortional buckling behaviour and moment capacities of hollow flange sections. New design rules were therefore developed by using a member slenderness parameter modified by K, where K is a function of GJf/EIxweb. The new design rules based on the modified slenderness parameter were found to be accurate in calculating the moment capacities of not only LSBs and HFBs, but also other types of hollow flange sections.

Characterisation and source identification of selected pollutants in house dust

House dust is a heterogeneous matrix, which contains a number of biological materials and particulate matter gathered from several sources. It is the accumulation of a number of semi-volatile and non-volatile contaminants. The contaminants are trapped and preserved. Therefore, house dust can be viewed as an archive of both the indoor and outdoor air pollution. There is evidence to show that on average, people tend to stay indoors most of the time and this increases exposure to house dust. The aims of this investigation were to: " assess the levels of Polycyclic Aromatic Hydrocarbons (PAHs), elements and pesticides in the indoor environment of the Brisbane area; " identify and characterise the possible sources of elemental constituents (inorganic elements), PAHs and pesticides by means of Positive Matrix Factorisation (PMF); and " establish the correlations between the levels of indoor air pollutants (PAHs, elements and pesticides) with the external and internal characteristics or attributes of the buildings and indoor activities by means of multivariate data analysis techniques. The dust samples were collected during the period of 2005-2007 from homes located in different suburbs of Brisbane, Ipswich and Toowoomba, in South East Queensland, Australia. A vacuum cleaner fitted with a paper bag was used as a sampler for collecting the house dust. A survey questionnaire was filled by the house residents which contained information about the indoor and outdoor characteristics of their residences. House dust samples were analysed for three different pollutants: Pesticides, Elements and PAHs. The analyses were carried-out for samples of particle size less than 250 µm. The chemical analyses for both pesticides and PAHs were performed using a Gas Chromatography Mass Spectrometry (GC-MS), while elemental analysis was carried-out by using Inductively-Coupled Plasma-Mass Spectroscopy (ICP-MS). The data was subjected to multivariate data analysis techniques such as multi-criteria decision-making procedures, Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE), coupled with Geometrical Analysis for Interactive Aid (GAIA) in order to rank the samples and to examine data display. This study showed that compared to the results from previous works, which were carried-out in Australia and overseas, the concentrations of pollutants in house dusts in Brisbane and the surrounding areas were relatively very high. The results of this work also showed significant correlations between some of the physical parameters (types of building material, floor level, distance from industrial areas and major road, and smoking) and the concentrations of pollutants. Types of building materials and the age of houses were found to be two of the primary factors that affect the concentrations of pesticides and elements in house dust. The concentrations of these two types of pollutant appear to be higher in old houses (timber houses) than in the brick ones. In contrast, the concentrations of PAHs were noticed to be higher in brick houses than in the timber ones. Other factors such as floor level, and distance from the main street and industrial area, also affected the concentrations of pollutants in the house dust samples. To apportion the sources and to understand mechanisms of pollutants, Positive Matrix Factorisation (PMF) receptor model was applied. The results showed that there were significant correlations between the degree of concentration of contaminants in house dust and the physical characteristics of houses, such as the age and the type of the house, the distance from the main road and industrial areas, and smoking. Sources of pollutants were identified. For PAHs, the sources were cooking activities, vehicle emissions, smoking, oil fumes, natural gas combustion and traces of diesel exhaust emissions; for pesticides the sources were application of pesticides for controlling termites in buildings and fences, treating indoor furniture and in gardens for controlling pests attacking horticultural and ornamental plants; for elements the sources were soil, cooking, smoking, paints, pesticides, combustion of motor fuels, residual fuel oil, motor vehicle emissions, wearing down of brake linings and industrial activities.

On selecting an optimal wavelet for detecting singularities in traffic and vehicular data

Serving as a powerful tool for extracting localized variations in non-stationary signals, applications of wavelet transforms (WTs) in traffic engineering have been introduced; however, lacking in some important theoretical fundamentals. In particular, there is little guidance provided on selecting an appropriate WT across potential transport applications. This research described in this paper contributes uniquely to the literature by first describing a numerical experiment to demonstrate the shortcomings of commonly-used data processing techniques in traffic engineering (i.e., averaging, moving averaging, second-order difference, oblique cumulative curve, and short-time Fourier transform). It then mathematically describes WT’s ability to detect singularities in traffic data. Next, selecting a suitable WT for a particular research topic in traffic engineering is discussed in detail by objectively and quantitatively comparing candidate wavelets’ performances using a numerical experiment. Finally, based on several case studies using both loop detector data and vehicle trajectories, it is shown that selecting a suitable wavelet largely depends on the specific research topic, and that the Mexican hat wavelet generally gives a satisfactory performance in detecting singularities in traffic and vehicular data.

Same old 'other' mother: Neil Gaiman's Coraline

Central to Coraline’s experiences in the fantasy world beyond the walls of her flat is the ‘other’ mother, who is initially constructed as an idealised image of maternal care whose only concern is for the welfare and comfort of her child. But as the story unfolds, this belle dame rapidly transforms into the ‘beldam sans merci’, an old crone, a she-devil whose real interest lies in the power she can draw from possessing the souls of children such as Coraline. This paper explores the Gaiman’s use of archetypes and cultural stereotypes of the mother figure that feminisms have been intent on expunging, interrogating, or appropriating in positive ways.

Strolling through the (post)modern city: Modes of being a flaneur in picture books

The city and the urban condition, popular subjects of art, literature, and film, have been commonly represented as fragmented, isolating, violent, with silent crowds moving through the hustle and bustle of a noisy, polluted cityspace. Included in this diverse artistic field is children’s literature—an area of creative and critical inquiry that continues to play a central role in illuminating and shaping perceptions of the city, of city lifestyles, and of the people who traverse the urban landscape. Fiction’s textual representations of cities, its sites and sights, lifestyles and characters have drawn on traditions of realist, satirical, and fantastic writing to produce the protean urban story—utopian, dystopian, visionary, satirical—with the goal of offering an account or critique of the contemporary city and the urban condition. In writing about cities and urban life, children’s literature variously locates the child in relation to the social (urban) space. This dialogic relation between subject and social space has been at the heart of writings about/of the flâneur: a figure who experiences modes of being in the city as it transforms under the influences of modernism and postmodernism. Within this context of a changing urban ontology brought about by (post)modern styles and practices, this article examines five contemporary picture books: The Cows Are Going to Paris by David Kirby and Allen Woodman; Ooh-la-la (Max in love) by Maira Kalman; Mr Chicken Goes to Paris and Old Tom’s Holiday by Leigh Hobbs; and The Empty City by David Megarrity. I investigate the possibility of these texts reviving the act of flânerie, but in a way that enables different modes of being a flâneur, a neo-flâneur. I suggest that the neo-flâneur retains some of the characteristics of the original flâneur, but incorporates others that take account of the changes wrought by postmodernity and globalization, particularly tourism and consumption. The dual issue at the heart of the discussion is that tourism and consumption as agents of cultural globalization offer a different way of thinking about the phenomenon of flânerie. While the flâneur can be regarded as the precursor to the tourist, the discussion considers how different modes of flânerie, such as the tourist-flâneur, are an inevitable outcome of commodification of the activities that accompany strolling through the (post)modern urban space.

Semantic service discovery in the service ecosystem

Electronic services are a leitmotif in ‘hot’ topics like Software as a Service, Service Oriented Architecture (SOA), Service oriented Computing, Cloud Computing, application markets and smart devices. We propose to consider these in what has been termed the Service Ecosystem (SES). The SES encompasses all levels of electronic services and their interaction, with human consumption and initiation on its periphery in much the same way the ‘Web’ describes a plethora of technologies that eventuate to connect information and expose it to humans. Presently, the SES is heterogeneous, fragmented and confined to semi-closed systems. A key issue hampering the emergence of an integrated SES is Service Discovery (SD). A SES will be dynamic with areas of structured and unstructured information within which service providers and ‘lay’ human consumers interact; until now the two are disjointed, e.g., SOA-enabled organisations, industries and domains are choreographed by domain experts or ‘hard-wired’ to smart device application markets and web applications. In a SES, services are accessible, comparable and exchangeable to human consumers closing the gap to the providers. This requires a new SD with which humans can discover services transparently and effectively without special knowledge or training. We propose two modes of discovery, directed search following an agenda and explorative search, which speculatively expands knowledge of an area of interest by means of categories. Inspired by conceptual space theory from cognitive science, we propose to implement the modes of discovery using concepts to map a lay consumer’s service need to terminologically sophisticated descriptions of services. To this end, we reframe SD as an information retrieval task on the information attached to services, such as, descriptions, reviews, documentation and web sites - the Service Information Shadow. The Semantic Space model transforms the shadow's unstructured semantic information into a geometric, concept-like representation. We introduce an improved and extended Semantic Space including categorization calling it the Semantic Service Discovery model. We evaluate our model with a highly relevant, service related corpus simulating a Service Information Shadow including manually constructed complex service agendas, as well as manual groupings of services. We compare our model against state-of-the-art information retrieval systems and clustering algorithms. By means of an extensive series of empirical evaluations, we establish optimal parameter settings for the semantic space model. The evaluations demonstrate the model’s effectiveness for SD in terms of retrieval precision over state-of-the-art information retrieval models (directed search) and the meaningful, automatic categorization of service related information, which shows potential to form the basis of a useful, cognitively motivated map of the SES for exploratory search.

A hierarchical evolutionary algorithmic design (HEAD) system for generating and evolving building design models

This thesis develops a detailed conceptual design method and a system software architecture defined with a parametric and generative evolutionary design system to support an integrated interdisciplinary building design approach. The research recognises the need to shift design efforts toward the earliest phases of the design process to support crucial design decisions that have a substantial cost implication on the overall project budget. The overall motivation of the research is to improve the quality of designs produced at the author's employer, the General Directorate of Major Works (GDMW) of the Saudi Arabian Armed Forces. GDMW produces many buildings that have standard requirements, across a wide range of environmental and social circumstances. A rapid means of customising designs for local circumstances would have significant benefits. The research considers the use of evolutionary genetic algorithms in the design process and the ability to generate and assess a wider range of potential design solutions than a human could manage. This wider ranging assessment, during the early stages of the design process, means that the generated solutions will be more appropriate for the defined design problem. The research work proposes a design method and system that promotes a collaborative relationship between human creativity and the computer capability. The tectonic design approach is adopted as a process oriented design that values the process of design as much as the product. The aim is to connect the evolutionary systems to performance assessment applications, which are used as prioritised fitness functions. This will produce design solutions that respond to their environmental and function requirements. This integrated, interdisciplinary approach to design will produce solutions through a design process that considers and balances the requirements of all aspects of the design. Since this thesis covers a wide area of research material, 'methodological pluralism' approach was used, incorporating both prescriptive and descriptive research methods. Multiple models of research were combined and the overall research was undertaken following three main stages, conceptualisation, developmental and evaluation. The first two stages lay the foundations for the specification of the proposed system where key aspects of the system that have not previously been proven in the literature, were implemented to test the feasibility of the system. As a result of combining the existing knowledge in the area with the newlyverified key aspects of the proposed system, this research can form the base for a future software development project. The evaluation stage, which includes building the prototype system to test and evaluate the system performance based on the criteria defined in the earlier stage, is not within the scope this thesis. The research results in a conceptual design method and a proposed system software architecture. The proposed system is called the 'Hierarchical Evolutionary Algorithmic Design (HEAD) System'. The HEAD system has shown to be feasible through the initial illustrative paper-based simulation. The HEAD system consists of the two main components - 'Design Schema' and the 'Synthesis Algorithms'. The HEAD system reflects the major research contribution in the way it is conceptualised, while secondary contributions are achieved within the system components. The design schema provides constraints on the generation of designs, thus enabling the designer to create a wide range of potential designs that can then be analysed for desirable characteristics. The design schema supports the digital representation of the human creativity of designers into a dynamic design framework that can be encoded and then executed through the use of evolutionary genetic algorithms. The design schema incorporates 2D and 3D geometry and graph theory for space layout planning and building formation using the Lowest Common Design Denominator (LCDD) of a parameterised 2D module and a 3D structural module. This provides a bridge between the standard adjacency requirements and the evolutionary system. The use of graphs as an input to the evolutionary algorithm supports the introduction of constraints in a way that is not supported by standard evolutionary techniques. The process of design synthesis is guided as a higher level description of the building that supports geometrical constraints. The Synthesis Algorithms component analyses designs at four levels, 'Room', 'Layout', 'Building' and 'Optimisation'. At each level multiple fitness functions are embedded into the genetic algorithm to target the specific requirements of the relevant decomposed part of the design problem. Decomposing the design problem to allow for the design requirements of each level to be dealt with separately and then reassembling them in a bottom up approach reduces the generation of non-viable solutions through constraining the options available at the next higher level. The iterative approach, in exploring the range of design solutions through modification of the design schema as the understanding of the design problem improves, assists in identifying conflicts in the design requirements. Additionally, the hierarchical set-up allows the embedding of multiple fitness functions into the genetic algorithm, each relevant to a specific level. This supports an integrated multi-level, multi-disciplinary approach. The HEAD system promotes a collaborative relationship between human creativity and the computer capability. The design schema component, as the input to the procedural algorithms, enables the encoding of certain aspects of the designer's subjective creativity. By focusing on finding solutions for the relevant sub-problems at the appropriate levels of detail, the hierarchical nature of the system assist in the design decision-making process.

Coupling of energy from quantum emitters to the plasmonic mode of V groove waveguides: A numerical study

This work is a theoretical investigation into the coupling of a single excited quantum emitter to the plasmon mode of a V groove waveguide. The V groove waveguide consists of a triangular channel milled in gold and the emitter is modeled as a dipole emitter, and could represent a quantum dot, nitrogen vacancy in diamond, or similar. In this work the dependence of coupling efficiency of emitter to plasmon mode is determined for various geometrical parameters of the emitter-waveguide system. Using the finite element method, the effect on coupling efficiency of the emitter position and orientation, groove angle, groove depth, and tip radius, is studied in detail. We demonstrate that all parameters, with the exception of groove depth, have a significant impact on the attainable coupling efficiency. Understanding the effect of various geometrical parameters on the coupling between emitters and the plasmonic mode of the waveguide is essential for the design and optimization of quantum dot–V groove devices.