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.

Is globalisation an enabler of radical innovation in Toyota?

Prior evidence from the fields of innovation management and supplier relations predicts that Japanese firms should be naturally disadvantaged in developing and deploying radical innovations. But this conclusion is inconsistent with recent developments in the automotive industry. This paper presents secondary case study data focusing on fuel cell powered vehicles and hybrid cars to show that Toyota, one of Japan's largest and most influential corporations, is capable of developing radically new technologies, and is in several respects better at this sort of innovation than the rest of the global automotive industry.

Efficient hybrid-game strategies coupled to evolutionary algorithms for robust multidisciplinary design optimization in aerospace engineering

A number of game strategies have been developed in past decades and used in the fields of economics, engineering, computer science, and biology due to their efficiency in solving design optimization problems. In addition, research in multiobjective and multidisciplinary design optimization has focused on developing a robust and efficient optimization method so it can produce a set of high quality solutions with less computational time. In this paper, two optimization techniques are considered; the first optimization method uses multifidelity hierarchical Pareto-optimality. The second optimization method uses the combination of game strategies Nash-equilibrium and Pareto-optimality. This paper shows how game strategies can be coupled to multiobjective evolutionary algorithms and robust design techniques to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid and non-Hybrid-Game strategies are demonstrated.

Fixing the city one photo at a time : mobile logging of maintenance requests

We have designed a mobile application that takes advantage of the built-in features of smart phones such as camera and GPS that allow users to take geo-tagged photos while on the move. Urban residents can take pictures of broken street furniture and public property requiring repair, attach a brief description, and submit the information as a maintenance request to the local government organisation of their city. This paper discusses the design approach that led to the application, highlights a built-in mechanism to elicit user feedback, and evaluates the progress to date with user feedback and log statistics. It concludes with an outlook highlighting user requested features and our own design aspirations for moving from a reporting tool to a civic engagement tool.

One approach to finding evidence for the effectiveness of scientific visualisations in high school physics and chemistry education

Enormous amounts of money and energy are being devoted to the development, use and organisation of computer-based scientific visualisations (e.g. animations and simulations) in science education. It seems plausible that visualisations that enable students to gain visual access to scientific phenomena that are too large, too small or occur too quickly or too slowly to be seen by the naked eye, or to scientific concepts and models, would yield enhanced conceptual learning. When the literature is searched, however, it quickly becomes apparent that there is a dearth of quantitative evidence for the effectiveness of scientific visualisations in enhancing students’ learning of science concepts. This paper outlines an Australian project that is using innovative research methodology to gather evidence on this question in physics and chemistry classrooms.

Improving patient privacy and confidentiality in one regional Emergency Department – a quality project

Background: Patient privacy and confidentiality (PPaC) is an important consideration for nurses and other members of the health care team. Can a patient expect to have confidentiality and in particular privacy in the current climate of emergency health care? Do staff who work in the Emergency Department (ED) see confidentiality as an important factor when providing emergency care? These questions are important to consider. Methods: This is a two phased quality improvement project, developed and implemented over a six month period in a busy regional, tertiary referral ED. Results: Issues identified for this department included department design and layout, overcrowding due to patient flow and access block, staff practices and department policies which were also impacted upon by culture of the team, and use of space. Conclusions: Changes successful in improving this issue include increased staff awareness about PPaC, intercom paging prior to nursing handover to remove visitors during handover, one visitor per patient policy, designated places for handover, allocated bed space for patient reviews/assessment and a strategy to temporarily move the patient if procedures would have been undertaken in shared bed space. These are important issues when considering policy, practice and department design in the ED.

That one piece of advice - microlecture

Programme: In these microlectures, developers, educators, critics, and artists give you the one piece of advice that they hold above all others. That one piece of advice: It's about the passion: Excerpt: Shades of madness - Creativity - Passion: There is something very important to observe about an industry that engages in these intense weekends. The monolithic Hollywood model is not viable, we need to scaffold the next gen of game designers, foster the passion, provide opportunity, CHANGE the model – not just dress it in new clothes

On forward secrecy in one-round key exchange

Most one-round key exchange protocols provide only weak forward secrecy at best. Furthermore, one-round protocols with strong forward secrecy often break badly when faced with an adversary who can obtain ephemeral keys. We provide a characterisation of how strong forward secrecy can be achieved in one-round key exchange. Moreover, we show that protocols exist which provide strong forward secrecy and remain secure with weak forward secrecy even when the adversary is allowed to obtain ephemeral keys. We provide a compiler to achieve this for any existing secure protocol with weak forward secrecy.

Evolutionary morphing for music composition

From one view of composition—let us call it the inspired or “Mozartian” view—musical compositions arrive fully formed in the mind of the composer and simply require transcription. In reality, however, it seems that very few people are so inspired, and composition is often more akin to a gradual clarification and refinement of partially formed ideas on the musical landscape. Particular landmarks in the compositional landscape tend to become clear before others, such that the incomplete piece is a patchwork of disconnected musical islands. An interactive evolutionary morphing system may provide some assistance for composers, to help build bridges between musical islands by generating hybrid musical transitions.

Service delivery in one-stop government portals : observations based on a market research study in Queensland

New government service delivery models based on a “franchise” metaphor are being proposed recently to allow more citizen-centric service delivery by decoupling the government’s internal departmental structure from the way services are presented and delivered to citizens. In order to evaluate the approach from an online channel perspective, the Queensland Government commissioned a market research study to compare their websites with the online presences of the UK Government and the South Australian Government, who both have adopted the “franchise” approach. The study aimed to inform an understanding of citizens’ preferred model for interacting in the online channel and to identify the relative strengths and weaknesses of the existing websites. In this paper, we will a) report on the findings of this third party usability study and b) position the study, in the form of a critical reflection, against the background of a more comprehensive “Transformational Government” approach using a “franchise marketplace”. The critical reflection points towards limitations of the study with regard to this bigger picture and discusses the potential benefits of service bundling that remained unconsidered in the study.

Effective hybrid recommendation combining users-searches correlations using tensors

Most recommendation methods employ item-item similarity measures or use ratings data to generate recommendations. These methods use traditional two dimensional models to find inter relationships between alike users and products. This paper proposes a novel recommendation method using the multi-dimensional model, tensor, to group similar users based on common search behaviour, and then finding associations within such groups for making effective inter group recommendations. Web log data is multi-dimensional data. Unlike vector based methods, tensors have the ability to highly correlate and find latent relationships between such similar instances, consisting of users and searches. Non redundant rules from such associations of user-searches are then used for making recommendations to the users.

Application of operations research techniques to improve efficiency in the emergency department

The main aim of this thesis is to analyse and optimise a public hospital Emergency Department. The Emergency Department (ED) is a complex system with limited resources and a high demand for these resources. Adding to the complexity is the stochastic nature of almost every element and characteristic in the ED. The interaction with other functional areas also complicates the system as these areas have a huge impact on the ED and the ED is powerless to change them. Therefore it is imperative that OR be applied to the ED to improve the performance within the constraints of the system. The main characteristics of the system to optimise included tardiness, adherence to waiting time targets, access block and length of stay. A validated and verified simulation model was built to model the real life system. This enabled detailed analysis of resources and flow without disruption to the actual ED. A wide range of different policies for the ED and a variety of resources were able to be investigated. Of particular interest was the number and type of beds in the ED and also the shift times of physicians. One point worth noting was that neither of these resources work in isolation and for optimisation of the system both resources need to be investigated in tandem. The ED was likened to a flow shop scheduling problem with the patients and beds being synonymous with the jobs and machines typically found in manufacturing problems. This enabled an analytic scheduling approach. Constructive heuristics were developed to reactively schedule the system in real time and these were able to improve the performance of the system. Metaheuristics that optimised the system were also developed and analysed. An innovative hybrid Simulated Annealing and Tabu Search algorithm was developed that out-performed both simulated annealing and tabu search algorithms by combining some of their features. The new algorithm achieves a more optimal solution and does so in a shorter time.

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.

Anonymity and one-way authentication in key exchange protocols

Key establishment is a crucial cryptographic primitive for building secure communication channels between two parties in a network. It has been studied extensively in theory and widely deployed in practice. In the research literature a typical protocol in the public-key setting aims for key secrecy and mutual authentication. However, there are many important practical scenarios where mutual authentication is undesirable, such as in anonymity networks like Tor, or is difficult to achieve due to insufficient public-key infrastructure at the user level, as is the case on the Internet today. In this work we are concerned with the scenario where two parties establish a private shared session key, but only one party authenticates to the other; in fact, the unauthenticated party may wish to have strong anonymity guarantees. We present a desirable set of security, authentication, and anonymity goals for this setting and develop a model which captures these properties. Our approach allows for clients to choose among different levels of authentication. We also describe an attack on a previous protocol of Øverlier and Syverson, and present a new, efficient key exchange protocol that provides one-way authentication and anonymity.

Synthesis of one-dimensional nanocomposites based on alumina nanofibres and their catalytic applications

Materials with one-dimensional (1D) nanostructure are important for catalysis. They are the preferred building blocks for catalytic nanoarchitecture, and can be used to fabricate designer catalysts. In this thesis, one such material, alumina nanofibre, was used as a precursor to prepare a range of nanocomposite catalysts. Utilising the specific properties of alumina nanofibres, a novel approach was developed to prepare macro-mesoporous nanocomposites, which consist of a stacked, fibrous nanocomposite with a core-shell structure. Two kinds of fibrous ZrO2/Al2O3 and TiO2/Al2O3 nanocomposites were successfully synthesised using boehmite nanofibers as a hard temperate and followed by a simple calcination. The alumina nanofibres provide the resultant nanocomposites with good thermal stability and mechanical stability. A series of one-dimensional (1D) zirconia/alumina nanocomposites were prepared by the deposition of zirconium species onto the 3D framework of boehmite nanofibres formed by dispersing boehmite nanofibres into a butanol solution, followed by calcination at 773 K. The materials were characterised by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM), N2 adsorption/desorption, Infrared Emission Spectroscopy (IES), and Fourier Transform Infrared spectroscopy (FT-IR). The results demonstrated that when the molar percentage, X, X=100*Zr/(Al+Zr), was > 30%, extremely long ZrO2/Al2O3 composite nanorods with evenly distributed ZrO2 nanocrystals formed on their surface. The stacking of such nanorods gave rise to a new kind of macroporous material without the use of any organic space filler\template or other specific drying techniques. The mechanism for the formation of these long ZrO2/Al2O3 composite nanorods is proposed in this work. A series of solid-superacid catalysts were synthesised from fibrous ZrO2/Al2O3 core and shell nanocomposites. In this series, the zirconium molar percentage was varied from 2 % to 50 %. The ZrO2/Al2O3 nanocomposites and their solid superacid counterparts were characterised by a variety of techniques including 27Al MAS-NMR, SEM, TEM, XPS, Nitrogen adsorption and Infrared Emission Spectroscopy. NMR results show that the interaction between zirconia species and alumina strongly correlates with pentacoordinated aluminium sites. This can also be detected by the change in binding energy of the 3d electrons of the zirconium. The acidity of the obtained superacids was tested by using them as catalysts for the benzolyation of toluene. It was found that a sample with a 50 % zirconium molar percentage possessed the highest surface acidity equalling that of pristine sulfated zirconia despite the reduced mass of zirconia. Preparation of hierarchically macro-mesoporous catalyst by loading nanocrystallites on the framework of alumina bundles can provide an alternative system to design advanced nanocomposite catalyst with enhanced performance. A series of macro-mesoporous TiO2/Al2O3 nanocomposites with different morphologies were synthesised. The materials were calcined at 723 K and were characterised by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM), N2 adsorption/desorption, Infrared Emission Spectroscopy (IES), and UV-visible spectroscopy (UV-visible). A modified approach was proposed for the synthesis of 1D (fibrous) nanocomposite with higher Ti/Al molar ratio (2:1) at lower temperature (<100oC), which makes it possible to synthesize such materials on industrial scale. The performances of a series of resultant TiO2/Al2O3 nanocomposites with different morphologies were evaluated as a photocatalyst for the phenol degradation under UV irradiation. The photocatalyst (Ti/Al =2) with fibrous morphology exhibits higher activity than that of the photocatalyst with microspherical morphology which indeed has the highest Ti to Al molar ratio (Ti/Al =3) in the series of as-synthesised hierarchical TiO2/Al2O3 nanocomposites. Furthermore, the photocatalytic performances, for the fibrous nanocomposites with Ti/Al=2, were optimized by calcination at elevated temperatures. The nanocomposite prepared by calcination at 750oC exhibits the highest catalytic activity, and its performance per TiO2 unit is very close to that of the gold standard, Degussa P 25. This work also emphasizes two advantages of the nanocomposites with fibrous morphology: (1) the resistance to sintering, and (2) good catalyst recovery.