Modelling cell separation during plant organ abscission

A simple mathematical model is presented to describe the cell separation process that plants undertake in order to deliberately shed organs. The focus here is on modelling the production of the enzyme polygalacturonase, which breaks down pectin that provides natural cell-to-cell adhesion in the localised abscission zone. A coupled system of three ordinary differential equations is given for a single cell, and then extended to hold for a layer of cells in the abscission zone. Simple observations are made based on the results of this preliminary model and, furthermore, a number of opportunities for applied mathematicians to make contributions in this subject area are discussed.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Micro-business community responsibility – approaches, motivations and barriers

Micro-businesses, those with fewer than five employees, have a significant impact on the economy. These very small players represent 89% of all Australian businesses and, collectively, they provide 17% of the nation’s private sector employment. They are ubiquitous in Australia as in many other nations, embedded in local communities and therefore well placed to influence community wellbeing. Surprisingly, very little is known about micro-Business Community Responsibility (mBCR), the micro-business equivalent of Small Business Social Responsibility (SBSR) and Corporate Social Responsibility (CSR). Most national data available on business support for community wellbeing does not separately identify micro-business contributions. In this study an exploratory approach informed by business ethics theory was taken. Data from 36 semi-structured interviews was analysed to examine perceived mBCR approaches, motivations and barriers. The sample for this study was a mix of micro-business owner-operators situated in suburban shopping areas in Brisbane. Three types of mBCR emerged. All types are at least partly driven by enlightened selfinterest (ESI). However of the three mBCR types, two combine ESI with other approaches. One type combines ESI and philanthropic approaches to mBCR, and the other combines ESI with social entrepreneurial approaches to mBCR. The combination of doing business and doing good for many micro-business owneroperators, suggests mBCR may be a significant, yet unrecognised component of the third sector social economy.

Towards proximity-based passenger sensing on public transport buses

While substantial research on intelligent transportation systems has focused on the development of novel wireless communication technologies and protocols, relatively little work has sought to fully exploit proximity-based wireless technologies that passengers actually carry with them today. This paper presents the real-world deployment of a system that exploits public transit bus passengers’ Bluetooth-capable devices to capture and reconstruct micro- and macro-passenger behavior. We present supporting evidence that approximately 12% of passengers already carry Bluetooth-enabled devices and that the data collected on these passengers captures with almost 80 % accuracy the daily fluctuation of actual passengers flows. The paper makes three contributions in terms of understanding passenger behavior: We verify that the length of passenger trips is exponentially bounded, the frequency of passenger trips follows a power law distribution, and the microstructure of the network of passenger movements is polycentric.

Modelling client puzzles and denial-of-service resistant protocols

Denial-of-service (DoS) attacks are a growing concern to networked services like the Internet. In recent years, major Internet e-commerce and government sites have been disabled due to various DoS attacks. A common form of DoS attack is a resource depletion attack, in which an attacker tries to overload the server's resources, such as memory or computational power, rendering the server unable to service honest clients. A promising way to deal with this problem is for a defending server to identify and segregate malicious traffic as earlier as possible. Client puzzles, also known as proofs of work, have been shown to be a promising tool to thwart DoS attacks in network protocols, particularly in authentication protocols. In this thesis, we design efficient client puzzles and propose a stronger security model to analyse client puzzles. We revisit a few key establishment protocols to analyse their DoS resilient properties and strengthen them using existing and novel techniques. Our contributions in the thesis are manifold. We propose an efficient client puzzle that enjoys its security in the standard model under new computational assumptions. Assuming the presence of powerful DoS attackers, we find a weakness in the most recent security model proposed to analyse client puzzles and this study leads us to introduce a better security model for analysing client puzzles. We demonstrate the utility of our new security definitions by including two hash based stronger client puzzles. We also show that using stronger client puzzles any protocol can be converted into a provably secure DoS resilient key exchange protocol. In other contributions, we analyse DoS resilient properties of network protocols such as Just Fast Keying (JFK) and Transport Layer Security (TLS). In the JFK protocol, we identify a new DoS attack by applying Meadows' cost based framework to analyse DoS resilient properties. We also prove that the original security claim of JFK does not hold. Then we combine an existing technique to reduce the server cost and prove that the new variant of JFK achieves perfect forward secrecy (the property not achieved by original JFK protocol) and secure under the original security assumptions of JFK. Finally, we introduce a novel cost shifting technique which reduces the computation cost of the server significantly and employ the technique in the most important network protocol, TLS, to analyse the security of the resultant protocol. We also observe that the cost shifting technique can be incorporated in any Diffine{Hellman based key exchange protocol to reduce the Diffie{Hellman exponential cost of a party by one multiplication and one addition.

Epilogue : Why Study Twitter?

Each of the thirty-one contributions in this volume implicitly spells out its own answer to this question. Surprisingly perhaps even for such a highly interdisciplinary volume as this one, these answers vary considerably in their approaches, their objectives, and their underlying assumptions about the object of study. This diversity of scholarly perspectives on Twitter, barely half a decade since it first emerged as a popular platform, highlights its versatility. Beginning as a side project to a now-forgotten podcasting platform, rising to popularity as a social network service focussed around mundane communication and therefore widely lambasted as a cesspool of vanity and triviality by incredulous journalists (including technology journalists), it was later embraced by those same journalists, governments, and businesses as a crucial source of real-time information on everything from natural disasters to celebrity gossip, and from debates over sexual violence to Vatican politics.

Selection and monitoring of navigation modes for an autonomous rover

Considering the wide spectrum of situations that it may encounter, a robot navigating autonomously in outdoor environments needs to be endowed with several operating modes, for robustness and efficiency reasons. Indeed, the terrain it has to traverse may be composed of flat or rough areas, low cohesive soils such as sand dunes, concrete road etc. . .Traversing these various kinds of environment calls for different navigation and/or locomotion functionalities, especially if the robot is endowed with different locomotion abilities, such as the robots WorkPartner, Hylos [4], Nomad or the Marsokhod rovers. Numerous rover navigation techniques have been proposed, each of them being suited to a particular environment context (e.g. path following, obstacle avoidance in more or less cluttered environments, rough terrain traverses...). However, seldom contributions in the literature tackle the problem of selecting autonomously the most suited mode [3]. Most of the existing work is indeed devoted to the passive analysis of a single navigation mode, as in [2]. Fault detection is of course essential: one can imagine that a proper monitoring of the Mars Exploration Rover Opportunity could have avoided the rover to be stuck during several weeks in a dune, by detecting non-nominal behavior of some parameters. But the ability to recover the anticipated problem by switching to a better suited navigation mode would bring higher autonomy abilities, and therefore a better overall efficiency. We propose here a probabilistic framework to achieve this, which fuses environment related and robot related information in order to actively control the rover operations.

Telecommunications Impacts on the Structure and Organisation of Male Sex Work

(Sub)Urban Sexscapes brings together a collection of theoretically-informed and empirically rich case studies highlighting the contemporary and historical geographies and regulation of the commercial sex industry. Contributions in this edited volume examine the spatial and regulatory contours of the sex industry from a range of disciplinary perspectives—urban planning, urban geography, urban sociology, and, cultural and media studies—and geographical contexts—Australia, the UK, US and North Africa. In overall terms, (Sub)urban Sexscapes highlights the mainstreaming of commercial sex premises—sex shops, brothels, strip clubs and queer spaces—and products—sex toys, erotic literature and pornography—now being commonplace in night time economy spaces, the high street, suburban shopping centres and the home. In addition, the aesthetics of commercial and alternative sexual practices—BDSM and pornography—permeate the (sub)urban landscape via billboards, newspapers and magazines, television, music videos and the Internet. The role of sex, sexuality and commercialized sex, in contributing to the general character of our cities cannot be ignored. In short, there is a need for policy-makers to be realistic about the historical, contemporary and future presence of the sex industry. Ultimately, the regulation of the sex industry should be informed by evidence as opposed to moral panics.

Collaborative learning from distributed places and spaces: Exploring the use of virtual collaborative tools for local and global student teamwork projects

Educating responsive graduates. Graduate competencies include reliability, communication skills and ability to work in teams. Students using Collaborative technologies adapt to a new working environment, working in teams and using collaborative technologies for learning. Collaborative Technologies were used not simply for delivery of learning but innovatively to supplement and enrich research-based learning, providing a space for active engagement and interaction with resources and team. This promotes the development of responsive ‘intellectual producers’, able to effectively communicate, collaborate and negotiate in complex work environments. Exploiting technologies. Students use ‘new’ technologies to work collaboratively, allowing them to experience the reality of distributed workplaces incorporating both flexibility and ‘real’ time responsiveness. Students are responsible and accountable for individual and group work contributions in a highly transparent and readily accessible workspace. This experience provides a model of an effective learning tool. Navigating uncertainty and complexity. Collaborative technologies allows students to develop critical thinking and reflective skills as they develop a group product. In this forum students build resilience by taking ownership and managing group work, and navigating the uncertainties and complexities of group dynamics as they constructively and professionally engage in team dialogue and learn to focus on the goal of the team task.

Taken for granted: Material relations between disability and codes/guidelines

This paper provides a critical examination of the taken for granted nature of the codes/guidelines used towards the creation of designed spaces, their social relations with designers, and their agency in designing for people with disabilities. We conducted case studies at three national museums in Canada where we began by questioning societal representations of disability within and through material culture through the potential of actor-network theory where non-human actors have considerable agency. Specifically, our exploration looks into how representations of disability for designing, are interpreted through mediums such as codes, standards and guidelines. We accomplish this through: deep analyses of the museums’ built environments (outdoors and indoors); interviewed curators, architects and designers involved in the creation of the spaces/displays; completed dialoguing while in motion interviews with people who have disabilities within the spaces; and analyzed available documents relating to the creation of the museums. Through analyses of our rich data set involving the mapping of codes/guidelines in their ‘representation’ of disability and their contributions in ‘fixing’ disability, this paper takes an alternative approach to designing for/with disability by aiming to question societal representations of disability within and through material culture.

Personalised ontology learning and mining for web information gathering

Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.

Encyclopedia contributions: entries C-G in Oxford Companion to Australian Gardens

Caulfield, Harold William; p.131 Cowan, Alexander; p.164 Cowley, Ebenezer; p.164 East Talgai Station; p.193 Eaves, S.H.; p.193-194 Edgar, J.S.; p.196 Everist, Selwyn; p.206 Experimental Farms and Gardens; pp.207-208 Government Houses - Queensland; pp.267-268

Encyclopedia contributions: Entries H-M in Oxford Companion to Australian Gardens

The Oxford Companion to Australian Gardens is the first comprehensive reference book to cover all aspects of Australian gardens, and the history of gardening and garden design in Australia. The book is comprised of over 400 thematic, bibliographic and place based entries, and is extensively illustrated and cross referenced to ensure ease of use and thorough coverage of the field. The Companion contributes to the understanding of gardens and gardening by including entries on designed landscapes, agriculture, architecture, art, botany, ecology, forestry, horticulture, landscape architecture, town planning and viticulture and will become the standard reference on the subject. Herbert,