The rules of autogeddon : sex death and law in J G Ballard’s Crash

It was reported that the manuscript of Crash was returned to the publisher with a note reading ‘The author is beyond psychiatric help’. Ballard took the lay diagnosis as proof of complete artistic success. Crash conflates the Freudian tropes of libido and thanatos, overlaying these onto the twentieth century erotic icon, the car. Beyond mere incompetent adolescent copulatory fumblings in the back seat of the parental sedan or the clichéd phallic locomotor of the mid-life Ferrari, Ballard engages the full potentialities of the automobile as the locus and sine qua non of a perverse, though functional erotic. ‘Autoeroticism’ is transformed into automotive, traumatic or surgical paraphilia, driving Helmut Newton’s insipid photo-essays of BDSM and orthopædics into an entirely new dimension, dancing precisely where (but more crucially, because) the ‘body is bruised to pleasure soul’. The serendipity of quotidian accidental collisions is supplanted, in pursuit of the fetishised object, by contrived (though not simulated) recreations of iconographic celebrity deaths. Penetration remains as a guiding trope of sexuality, but it is confounded by a perversity of focus. Such an obsessive pursuit of this autoerotic-as-reality necessitates the rejection of the law of human sexual regulation, requiring the re-interpretation of what constitutes sex itself by looking beyond or through conventional sexuality into Ballard’s paraphiliac and nightmarish consensual Other. This Other allows for (if not demands) the tangled wreckage of a sportscar to function as a transformative sexual agent, creating, of woman, a being of ‘free and perverse sexuality, releasing within its dying chromium and leaking engine-parts, all the deviant possibilities of her sex’.

Entrepreneurial becoming : an educational pathway out of poverty

This paper reports a longitudinal analysis of 20 necessity driven micro-entrepreneurs operating in Beira, Central Mozambique, who received funding and training from the same NGO to establish or grow their business activities and reports the development of these entrepreneurs in terms of their acquired entrepreneurial potential for long-term success. The results indicate there is a process of entrepreneurial becoming that is not just about access to finance but especially learning and, when successful, this process supports the transformation of survival micro-enterprises into entrepreneurial micro-businesses. The concept of ‘becoming’ contains an implicit temporal dimension. Becoming suggests a transformation over time: a change from what one is already. In this study, we witness a significant change in understanding how a business needs to operate, in recognizing opportunities, thinking more creatively, and building self-confidence.

An efficient public key management regime for vehicular ad hoc networks (VANETS)

The primary goal of the Vehicular Ad Hoc Network (VANET) is to provide real-time safety-related messages to motorists to enhance road safety. Accessing and disseminating safety-related information through the use of wireless communications technology in VANETs should be secured, as motorists may make critical decisions in dealing with an emergency situation based on the received information. If security concerns are not addressed in developing VANET systems, an adversary can tamper with, or suppress, the unprotected message to mislead motorists to cause traffic accidents and hazards. Current research on secure messaging in VANETs focuses on employing the certificate-based Public Key Infrastructure (PKI) scheme to support message encryption and digital signing. The security overhead of such a scheme, however, creates a transmission delay and introduces a time-consuming verification process to VANET communications. This thesis has proposed a novel public key verification and management approach for VANETs; namely, the Public Key Registry (PKR) regime. Compared to the VANET PKI scheme, this new approach can satisfy necessary security requirements with improved performance and scalability, and at a lower cost by reducing the security overheads of message transmission and eliminating digital certificate deployment and maintenance issues. The proposed PKR regime consists of the required infrastructure components, rules for public key management and verification, and a set of interactions and associated behaviours to meet these rule requirements. This is achieved through a system design as a logic process model with functional specifications. The PKR regime can be used as development guidelines for conforming implementations. An analysis and evaluation of the proposed PKR regime includes security features assessment, analysis of the security overhead of message transmission, transmission latency, processing latency, and scalability of the proposed PKR regime. Compared to certificate-based PKI approaches, the proposed PKR regime can maintain the necessary security requirements, significantly reduce the security overhead by approximately 70%, and improve the performance by 98%. Meanwhile, the result of the scalability evaluation shows that the latency of employing the proposed PKR regime stays much lower at approximately 15 milliseconds, whether operating in a huge or small environment. It is therefore believed that this research will create a new dimension to the provision of secure messaging services in VANETs.

Caseload management, work-related stress and case manager self-efficacy among Victorian mental health case managers

Objective: In Australia and comparable countries, case management has become the dominant process by which public mental health services provide outpatient clinical services to people with severe mental illness. There is recognition that caseload size impacts on service provision and that management of caseloads is an important dimension of overall service management. There has been little empirical investigation, however, of caseload and its management. The present study was undertaken in the context of an industrial agreement in Victoria, Australia that required services to introduce standardized approaches to caseload management. The aims of the present study were therefore to (i) investigate caseload size and approaches to caseload management in Victoria's mental health services; and (ii) determine whether caseload size and/or approach to caseload management is associated with work-related stress or case manager self-efficacy among community mental health professionals employed in Victoria's mental health services. Method: A total of 188 case managers responded to an online cross-sectional survey with both purpose-developed items investigating methods of case allocation and caseload monitoring, and standard measures of work-related stress and case manager personal efficacy. Results: The mean caseload size was 20 per full-time case manager. Both work-related stress scores and case manager personal efficacy scores were broadly comparable with those reported in previous studies. Higher caseloads were associated with higher levels of work-related stress and lower levels of case manager personal efficacy. Active monitoring of caseload was associated with lower scores for work-related stress and higher scores for case manager personal efficacy, regardless of size of caseload. Although caseloads were most frequently monitored by the case manager, there was evidence that monitoring by a supervisor was more beneficial than self-monitoring. Conclusion: Routine monitoring of caseload, especially by a workplace supervisor, may be effective in reducing work-related stress and enhancing case manager personal efficacy. Keywords: case management, caseload, stress

Journeys to health services in Great Britain : an analysis of changing travel patterns 1985-2006

This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2006). The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Regression analyses were conducted to investigate the differences between different socio-spatial groups in these indicators over the period 1985-2006. This study found that journey distances to health facilities were significantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. However, most of their rates of utilisation of health services were found to be significantly lower because their journey times were significantly longer and also gradually increased over the periods. These findings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension.

The HarmonyGrid : music, space and performance in grid music systems

This research explores music in space, as experienced through performing and music-making with interactive systems. It explores how musical parameters may be presented spatially and displayed visually with a view to their exploration by a musician during performance. Spatial arrangements of musical components, especially pitches and harmonies, have been widely studied in the literature, but the current capabilities of interactive systems allow the improvisational exploration of these musical spaces as part of a performance practice. This research focuses on quantised spatial organisation of musical parameters that can be categorised as grid music systems (GMSs), and interactive music systems based on them. The research explores and surveys existing and historical uses of GMSs, and develops and demonstrates the use of a novel grid music system designed for whole body interaction. Grid music systems provide plotting of spatialised input to construct patterned music on a two-dimensional grid layout. GMSs are navigated to construct a sequence of parametric steps, for example a series of pitches, rhythmic values, a chord sequence, or terraced dynamic steps. While they are conceptually simple when only controlling one musical dimension, grid systems may be layered to enable complex and satisfying musical results. These systems have proved a viable, effective, accessible and engaging means of music-making for the general user as well as the musician. GMSs have been widely used in electronic and digital music technologies, where they have generally been applied to small portable devices and software systems such as step sequencers and drum machines. This research shows that by scaling up a grid music system, music-making and musical improvisation are enhanced, gaining several advantages: (1) Full body location becomes the spatial input to the grid. The system becomes a partially immersive one in four related ways: spatially, graphically, sonically and musically. (2) Detection of body location by tracking enables hands-free operation, thereby allowing the playing of a musical instrument in addition to “playing” the grid system. (3) Visual information regarding musical parameters may be enhanced so that the performer may fully engage with existing spatial knowledge of musical materials. The result is that existing spatial knowledge is overlaid on, and combined with, music-space. Music-space is a new concept produced by the research, and is similar to notions of other musical spaces including soundscape, acoustic space, Smalley's “circumspace” and “immersive space” (2007, 48-52), and Lotis's “ambiophony” (2003), but is rather more textural and “alive”—and therefore very conducive to interaction. Music-space is that space occupied by music, set within normal space, which may be perceived by a person located within, or moving around in that space. Music-space has a perceivable “texture” made of tensions and relaxations, and contains spatial patterns of these formed by musical elements such as notes, harmonies, and sounds, changing over time. The music may be performed by live musicians, created electronically, or be prerecorded. Large-scale GMSs have the capability not only to interactively display musical information as music representative space, but to allow music-space to co-exist with it. Moving around the grid, the performer may interact in real time with musical materials in music-space, as they form over squares or move in paths. Additionally he/she may sense the textural matrix of the music-space while being immersed in surround sound covering the grid. The HarmonyGrid is a new computer-based interactive performance system developed during this research that provides a generative music-making system intended to accompany, or play along with, an improvising musician. This large-scale GMS employs full-body motion tracking over a projected grid. Playing with the system creates an enhanced performance employing live interactive music, along with graphical and spatial activity. Although one other experimental system provides certain aspects of immersive music-making, currently only the HarmonyGrid provides an environment to explore and experience music-space in a GMS.

Andrzej Zielinski : pulp digital fictions

This is a review of painter Andrzej Zielinski's exhibition at gallery 9 in Sydney. It highlights the artist's expressionistic style and strong colour sense as well as his association with American painterly traditions. The artist application of acrylic modelling paste and his paintings also gives them a sculptural and architectural dimension, and on a conceptual level play with notions of mimesis and material form.

The analysis of social capital in online social communities

Social networks have proven to be an attractive avenue of investigation for researchers since humans are social creatures. Numerous literature have explored the term “social networks” from different perspectives and in diverse research fields. With the popularity of the Internet, social networking has taken on a new dimension. Online social communities therefore have become an emerging social avenue for people to communicate in today’s information age. People use online social communities to share their interests, maintain friendships, and extend their so-called circle of “friends”. Likewise, social capital, also known as human capital, is an important theory in sociology. Researchers usually utilise social capital theory when they investigate the topic relating to social networks. However, there is little literature that can provide an explicit and strong assertion in that research area due to the complexity of social capital. This thesis therefore focuses on the issue related to providing a better understanding about the relationship between social capital and online social communities. To enhance the value within the scope of this analysis, an online survey was conducted to examine the effects of the dimensions of social capital: relational capital, structural capital, and cognitive capital, determining the intensity of using online social communities. The data were derived from a total of 350 self-selected respondents completing an online survey during the research period. The main results indicate that social capital exists in online social communities under normal circumstances. Finally, this thesis also presents three contributions for both theory and practice in Chapter 5. The main results contribute to the understanding of connectivity in the interrelationships between individual social capital exchange within online social networks. Secondly, social trust was found to have a weak effect in influencing the intensity of individuals using online social communities. Third, the perpetual role of information sharing has an indirect influence on individual users participating in online social communities. This study also benefits online marketing consultants as marketers can not only gain consumer information easier from online social communities but also this understanding assists in designing effective communication within online social communities. The cross-sectional study, the reliability of Internet survey data, and sampling issues are the major three limitations in this research. The thesis provides a new research model and recommends that the mediating effects, privacy paradox, and social trust on online social communities should be further explored in future research.

Trading spaces : on the lore and limitations of latent semantic analysis

Two decades after its inception, Latent Semantic Analysis(LSA) has become part and parcel of every modern introduction to Information Retrieval. For any tool that matures so quickly, it is important to check its lore and limitations, or else stagnation will set in. We focus here on the three main aspects of LSA that are well accepted, and the gist of which can be summarized as follows: (1) that LSA recovers latent semantic factors underlying the document space, (2) that such can be accomplished through lossy compression of the document space by eliminating lexical noise, and (3) that the latter can best be achieved by Singular Value Decomposition. For each aspect we performed experiments analogous to those reported in the LSA literature and compared the evidence brought to bear in each case. On the negative side, we show that the above claims about LSA are much more limited than commonly believed. Even a simple example may show that LSA does not recover the optimal semantic factors as intended in the pedagogical example used in many LSA publications. Additionally, and remarkably deviating from LSA lore, LSA does not scale up well: the larger the document space, the more unlikely that LSA recovers an optimal set of semantic factors. On the positive side, we describe new algorithms to replace LSA (and more recent alternatives as pLSA, LDA, and kernel methods) by trading its l2 space for an l1 space, thereby guaranteeing an optimal set of semantic factors. These algorithms seem to salvage the spirit of LSA as we think it was initially conceived.

Monitoring identity of past, current and future : a performance management system perspective

This paper seeks to explore how organisations can effectively use performance management systems (PMS) to monitor collective identities. The monitoring of relationships between identity and an influential PMS—the balanced scorecard (BSC)—are explored. Drawing from identity and management accounting literature, this paper argues that identity products, patternings and processes are commonly positioned, monitored and interpreted through the multiple perspectives and levels of the BSC. Specifically, human, technical and organisational capital under the Learning and Growth perspective of the BSC can incorporate various identity measures that sustain the relative, distinctive and fluid nature of identities. The value of this research is to strengthen the theoretical grounds which position identity as an important dimension of organisational capital in PMS.

Print media portrayals of giving : exploring national ‘cultures of philanthropy’

In their 2010 study drawing on 500 empirical philanthropy studies, Bekkers and Wiepking identified eight consistently significant giving mechanisms. The pilot study reported here extends what is known about one mechanism, values, as a giving driver, in particular considering how national cultural values apply to giving. Personal values are not formed in a vacuum. They are influenced by the wider culture and society: thus values have a socio-cultural dimension. Accordingly, this pilot research draws on media theory and cultural studies work on national ethos to explore how these national cultural values interact with giving. A directed qualitative content analysis has been undertaken to compare US and Australian print media coverage about philanthropy. The two nations share an Anglo–Saxon orientation but differ significantly in national character and philanthropic activity. This study posits that a nation's media coverage about giving will reflect its national cultural ethos. This coverage can also shape personal values, thus implications exist for theory about the antecedents of personal giving values. Wider national values may drive or stifle giving, so this wider view of values as a driver has implications also for philanthropy promotion and fundraising.

Validating the is-impact model in the Malaysian public sector

This research is one of several ongoing studies conducted within the IT Professional Services (ITPS) research programme at Queensland University of Technology (QUT). In 2003, ITPS introduced the IS-Impact model, a measurement model for measuring information systems success from the viewpoint of multiple stakeholders. The model, along with its instrument, is robust, simple, yet generalisable, and yields results that are comparable across time, stakeholders, different systems and system contexts. The IS-Impact model is defined as “a measure at a point in time, of the stream of net benefits from the Information System (IS), to date and anticipated, as perceived by all key-user-groups”. The model represents four dimensions, which are ‘Individual Impact’, ‘Organizational Impact’, ‘Information Quality’ and ‘System Quality’. The two Impact dimensions measure the up-to-date impact of the evaluated system, while the remaining two Quality dimensions act as proxies for probable future impacts (Gable, Sedera & Chan, 2008). To fulfil the goal of ITPS, “to develop the most widely employed model” this research re-validates and extends the IS-Impact model in a new context. This method/context-extension research aims to test the generalisability of the model by addressing known limitations of the model. One of the limitations of the model relates to the extent of external validity of the model. In order to gain wide acceptance, a model should be consistent and work well in different contexts. The IS-Impact model, however, was only validated in the Australian context, and packaged software was chosen as the IS understudy. Thus, this study is concerned with whether the model can be applied in another different context. Aiming for a robust and standardised measurement model that can be used across different contexts, this research re-validates and extends the IS-Impact model and its instrument to public sector organisations in Malaysia. The overarching research question (managerial question) of this research is “How can public sector organisations in Malaysia measure the impact of information systems systematically and effectively?” With two main objectives, the managerial question is broken down into two specific research questions. The first research question addresses the applicability (relevance) of the dimensions and measures of the IS-Impact model in the Malaysian context. Moreover, this research question addresses the completeness of the model in the new context. Initially, this research assumes that the dimensions and measures of the IS-Impact model are sufficient for the new context. However, some IS researchers suggest that the selection of measures needs to be done purposely for different contextual settings (DeLone & McLean, 1992, Rai, Lang & Welker, 2002). Thus, the first research question is as follows, “Is the IS-Impact model complete for measuring the impact of IS in Malaysian public sector organisations?” [RQ1]. The IS-Impact model is a multidimensional model that consists of four dimensions or constructs. Each dimension is represented by formative measures or indicators. Formative measures are known as composite variables because these measures make up or form the construct, or, in this case, the dimension in the IS-Impact model. These formative measures define different aspects of the dimension, thus, a measurement model of this kind needs to be tested not just on the structural relationship between the constructs but also the validity of each measure. In a previous study, the IS-Impact model was validated using formative validation techniques, as proposed in the literature (i.e., Diamantopoulos and Winklhofer, 2001, Diamantopoulos and Siguaw, 2006, Petter, Straub and Rai, 2007). However, there is potential for improving the validation testing of the model by adding more criterion or dependent variables. This includes identifying a consequence of the IS-Impact construct for the purpose of validation. Moreover, a different approach is employed in this research, whereby the validity of the model is tested using the Partial Least Squares (PLS) method, a component-based structural equation modelling (SEM) technique. Thus, the second research question addresses the construct validation of the IS-Impact model; “Is the IS-Impact model valid as a multidimensional formative construct?” [RQ2]. This study employs two rounds of surveys, each having a different and specific aim. The first is qualitative and exploratory, aiming to investigate the applicability and sufficiency of the IS-Impact dimensions and measures in the new context. This survey was conducted in a state government in Malaysia. A total of 77 valid responses were received, yielding 278 impact statements. The results from the qualitative analysis demonstrate the applicability of most of the IS-Impact measures. The analysis also shows a significant new measure having emerged from the context. This new measure was added as one of the System Quality measures. The second survey is a quantitative survey that aims to operationalise the measures identified from the qualitative analysis and rigorously validate the model. This survey was conducted in four state governments (including the state government that was involved in the first survey). A total of 254 valid responses were used in the data analysis. Data was analysed using structural equation modelling techniques, following the guidelines for formative construct validation, to test the validity and reliability of the constructs in the model. This study is the first research that extends the complete IS-Impact model in a new context that is different in terms of nationality, language and the type of information system (IS). The main contribution of this research is to present a comprehensive, up-to-date IS-Impact model, which has been validated in the new context. The study has accomplished its purpose of testing the generalisability of the IS-Impact model and continuing the IS evaluation research by extending it in the Malaysian context. A further contribution is a validated Malaysian language IS-Impact measurement instrument. It is hoped that the validated Malaysian IS-Impact instrument will encourage related IS research in Malaysia, and that the demonstrated model validity and generalisability will encourage a cumulative tradition of research previously not possible. The study entailed several methodological improvements on prior work, including: (1) new criterion measures for the overall IS-Impact construct employed in ‘identification through measurement relations’; (2) a stronger, multi-item ‘Satisfaction’ construct, employed in ‘identification through structural relations’; (3) an alternative version of the main survey instrument in which items are randomized (rather than blocked) for comparison with the main survey data, in attention to possible common method variance (no significant differences between these two survey instruments were observed); (4) demonstrates a validation process of formative indexes of a multidimensional, second-order construct (existing examples mostly involved unidimensional constructs); (5) testing the presence of suppressor effects that influence the significance of some measures and dimensions in the model; and (6) demonstrates the effect of an imbalanced number of measures within a construct to the contribution power of each dimension in a multidimensional model.

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

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.

Enriching XML documents clustering by using concise structure and content

With the growing number of XML documents on theWeb it becomes essential to effectively organise these XML documents in order to retrieve useful information from them. A possible solution is to apply clustering on the XML documents to discover knowledge that promotes effective data management, information retrieval and query processing. However, many issues arise in discovering knowledge from these types of semi-structured documents due to their heterogeneity and structural irregularity. Most of the existing research on clustering techniques focuses only on one feature of the XML documents, this being either their structure or their content due to scalability and complexity problems. The knowledge gained in the form of clusters based on the structure or the content is not suitable for reallife datasets. It therefore becomes essential to include both the structure and content of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both these kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. The overall objective of this thesis is to address these issues by: (1) proposing methods to utilise frequent pattern mining techniques to reduce the dimension; (2) developing models to effectively combine the structure and content of XML documents; and (3) utilising the proposed models in clustering. This research first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. A clustering framework with two types of models, implicit and explicit, is developed. The implicit model uses a Vector Space Model (VSM) to combine the structure and the content information. The explicit model uses a higher order model, namely a 3- order Tensor Space Model (TSM), to explicitly combine the structure and the content information. This thesis also proposes a novel incremental technique to decompose largesized tensor models to utilise the decomposed solution for clustering the XML documents. The proposed framework and its components were extensively evaluated on several real-life datasets exhibiting extreme characteristics to understand the usefulness of the proposed framework in real-life situations. Additionally, this research evaluates the outcome of the clustering process on the collection selection problem in the information retrieval on the Wikipedia dataset. The experimental results demonstrate that the proposed frequent pattern mining and clustering methods outperform the related state-of-the-art approaches. In particular, the proposed framework of utilising frequent structures for constraining the content shows an improvement in accuracy over content-only and structure-only clustering results. The scalability evaluation experiments conducted on large scaled datasets clearly show the strengths of the proposed methods over state-of-the-art methods. In particular, this thesis work contributes to effectively combining the structure and the content of XML documents for clustering, in order to improve the accuracy of the clustering solution. In addition, it also contributes by addressing the research gaps in frequent pattern mining to generate efficient and concise frequent subtrees with various node relationships that could be used in clustering.