An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

Comparing the diffusion of online service recovery in small and large organisations

A key concern organisations face is how to incorporate Internet tools into their marketing communications mix. Where and how should companies invest their human, technological and financial resources? This paper explores a subset of this problem, online complaining and electronic customer service. It applies diffusion of innovation as a theoretical framework to investigate organisational implementation of email technology and explain the outcome of annual customer service surveys in 2001, 2002 and 2003. The results add to the small body of research on electronic service recovery by extending diffusion of innovations to email service recovery and underscoring the importance of adoption phases, particularly for SMEs. Larger companies provide more channels for submitting complaints, which represents an early phase of adoption. There was little difference in how large and small companies respond to online complaints, a later phase of adoption.

Exploring non-cancer pain conditions in a community sample : critiquing a current conceptual model of the acute to chronic pain transition and examining predictors of chronicity

This program of research examines the experience of chronic pain in a community sample. While, it is clear that like patient samples, chronic pain in non-patient samples is also associated with psychological distress and physical disability, the experience of pain across the total spectrum of pain conditions (including acute and episodic pain conditions) and during the early course of chronic pain is less clear. Information about these aspects of the pain experience is important because effective early intervention for chronic pain relies on identification of people who are likely to progress to chronicity post-injury. A conceptual model of the transition from acute to chronic pain was proposed by Gatchel (1991a). In brief, Gatchel’s model describes three stages that individuals who have a serious pain experience move through, each with worsening psychological dysfunction and physical disability. The aims of this program of research were to describe the experience of pain in a community sample in order to obtain pain-specific data on the problem of pain in Queensland, and to explore the usefulness of Gatchel’s Model in a non-clinical sample. Additionally, five risk factors and six protective factors were proposed as possible extensions to Gatchel’s Model. To address these aims, a prospective longitudinal mixed-method research design was used. Quantitative data was collected in Phase 1 via a comprehensive postal questionnaire. Phase 2 consisted of a follow-up questionnaire 3 months post-baseline. Phase 3 consisted of semi-structured interviews with a subset of the original sample 12 months post follow-up, which used qualitative data to provide a further in-depth examination of the experience and process of chronic pain from respondents’ point of view. The results indicate chronic pain is associated with high levels of anxiety and depressive symptoms. However, the levels of disability reported by this Queensland sample were generally lower than those reported by clinical samples and consistent with disability data reported in a New South Wales population-based study. With regard to the second aim of this program of research, while some elements of the pain experience of this sample were consistent with that described by Gatchel’s Model, overall the model was not a good fit with the experience of this non-clinical sample. The findings indicate that passive coping strategies (minimising activity), catastrophising, self efficacy, optimism, social support, active strategies (use of distraction) and the belief that emotions affect pain may be important to consider in understanding the processes that underlie the transition to and continuation of chronic pain.

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

The relationship between personality characteristics and postconcussion symptoms in a non-clinical sample

Postconcussion symptoms are relatively common in the acute recovery period following mild traumatic brain injury (MTBI). However, for a small subset of patients, self reported postconcussion symptoms continue long after injury. Many factors have been proposed to account for the presence of persistent postconcussion symptoms. The influence of personality traits has been proposed as one explanation. The purpose of this study was to examine the relation between postconcussion-like symptom reporting and personality traits in a sample of 96 healthy participants. Participants completed the British Columbia Postconcussion Symptom Inventory (BC-PSI) and the Millon Clinical Multiaxial Inventory III (MCMI-III). There was a strong positive relation between the majority of MCMI-III scales and postconcussion-like symptom reporting. Approximately half of the sample met the International Classification of Diseases-10 Criterion C symptoms for Postconcussional Syndrome (PCS). Compared with those participants who did not meet this criterion, the PCS group had significant elevations on the negativistic, depression, major depression, dysthymia, anxiety, dependent, sadistic, somatic, and borderline scales of the MCMI-III. These findings support the hypothesis that personality traits can play a contributing role in self reported postconcussion-like symptoms.

The Queensland study of melanoma : Environmental and genetic associations (Q-MEGA); Study design, baseline characteristics, and repeatability of phenotype and sun exposure measures

Cutaneous malignant melanoma (CMM) is a major health issue in Queensland, Australia, which has the world’s highest incidence. Recent molecular and epidemiologic studies suggest that CMM arises through multiple etiological pathways involving gene-environment interactions. Understanding the potential mechanisms leading to CMM requires larger studies than those previously conducted. This article describes the design and baseline characteristics of Q-MEGA, the Queensland Study of Melanoma: Environmental and Genetic Associations, which followed up 4 population-based samples of CMM patients in Queensland, including children, adolescents, men aged over 50, and a large sample of adult cases and their families, including twins. Q-MEGA aims to investigate the roles of genetic and environmental factors, and their interaction, in the etiology of melanoma. Three thousand, four hundred and seventy-one participants took part in the follow-up study and were administered a computer-assisted telephone interview in 2002-2005. Updated data on environmental and phenotypic risk factors, and 2777 blood samples were collected from interviewed participants as well as a subset of relatives. This study provides a large and well-described population-based sample of CMM cases with follow-up data. Characteristics of the cases and repeatability of sun exposure and phenotype measures between the baseline and the follow-up surveys, from 6 to 17 years later, are also described.

Learning to drive with cognitive impairment : the experience of young ADHD diagnosed drivers and their parent supervisors

A subset of novice drivers exhibit executive function impairments which may adversely impact on the learn-to-drive period and subsequent driving experience, potentially explaining their overrepresentation in traffic offences and crashes. This paper presents the results of a qualitative analysis of a small series of in-depth semi-structured interviews undertaken individually with affected young drivers (n = 7) and each of their parent supervisors (n = 6). Young drivers were selected on the basis of their ADHD diagnosis, as a sample particularly affected by executive function impairments. Standardised rating scale measures confirmed the currency of the young drivers’ ADHD symptoms and executive function impairment. Results are discussed in terms of common experiences of the young affected drivers and those of their parents as supervising drivers of the learn-to-drive process and subsequent driving behaviour. Key themes included difficulties that were related to core executive function impairments symptomatic of ADHD. Themes also included common emotions that the young drivers associated with driving, with particular types of impact on their driving behaviour. Common strategies that were used by both the young driver and their parent during this learning process and their perceived effectiveness are also discussed. Those that were perceived to be most effective tended to focus on reducing the cognitive load for the young driver when introducing new information and skills.

Fingerprint analysis of eucommia bark by LC-DAD and LC-MS with the aid of chemometrics

Chromatographic fingerprints of 46 Eucommia Bark samples were obtained by liquid chromatography-diode array detector (LC-DAD). These samples were collected from eight provinces in China, with different geographical locations, and climates. Seven common LC peaks that could be used for fingerprinting this common popular traditional Chinese medicine were found, and six were identified as substituted resinols (4 compounds), geniposidic acid and chlorogenic acid by LC-MS. Principal components analysis (PCA) indicated that samples from the Sichuan, Hubei, Shanxi and Anhui—the SHSA provinces, clustered together. The other objects from the four provinces, Guizhou, Jiangxi, Gansu and Henan, were discriminated and widely scattered on the biplot in four province clusters. The SHSA provinces are geographically close together while the others are spread out. Thus, such results suggested that the composition of the Eucommia Bark samples was dependent on their geographic location and environment. In general, the basis for discrimination on the PCA biplot from the original 46 objects× 7 variables data matrix was the same as that for the SHSA subset (36 × 7 matrix). The seven marker compound loading vectors grouped into three sets: (1) three closely correlating substituted resinol compounds and chlorogenic acid; (2) the fourth resinol compound identified by the OCH3 substituent in the R4 position, and an unknown compound; and (3) the geniposidic acid, which was independent of the set 1 variables, and which negatively correlated with the set 2 ones above. These observations from the PCA biplot were supported by hierarchical cluster analysis, and indicated that Eucommia Bark preparations may be successfully compared with the use of the HPLC responses from the seven marker compounds and chemometric methods such as PCA and the complementary hierarchical cluster analysis (HCA).

A novel nonrepudiable threshold multi-proxy multi-signature scheme with shared verification

Tzeng et al. proposed a new threshold multi-proxy multi-signature scheme with threshold verification. In their scheme, a subset of original signers authenticates a designated proxy group to sign on behalf of the original group. A message m has to be signed by a subset of proxy signers who can represent the proxy group. Then, the proxy signature is sent to the verifier group. A subset of verifiers in the verifier group can also represent the group to authenticate the proxy signature. Subsequently, there are two improved schemes to eliminate the security leak of Tzeng et al.’s scheme. In this paper, we have pointed out the security leakage of the three schemes and further proposed a novel threshold multi-proxy multi-signature scheme with threshold verification.

Investigation of molecular mechanisms regulating biomineralization of pearl oyster Pinctada maxima

Biomineralization is a process encompassing all mineral containing tissues produced within an organism. The most dynamic example of this process is the formation of the mollusk shell, comprising a variety of crystal phases and microstructures. The organic component incorporated within the shell is said to dictate this remarkable architecture. Subsequently, for the past decade considerable research have been undertaken to identify and characterize the protein components involved in biomineralization. Despite these efforts the general understanding of the process remains ambiguous. This study employs a novel molecular approach to further the elucidation of the shell biomineralization. A microarray platform has been custom generated (PmaxArray 1.0) from the pearl oyster Pinctada maxima. PmaxArray 1.0 consists of 4992 expressed sequence tags (ESTs) originating from the mantle, an organ involved in shell formation. This microarray has been used as the primary tool for three separate investigations in an effort to associate transcriptional gene expression from P. maxima to the process of shell biomineralization. The first investigation analyzes the spatial expression of ESTs throughout the mantle organ. The mantle was dissected into five discrete regions and each analyzed for gene expression with PmaxArray 1.0. Over 2000 ESTs were differentially expressed among the tissue sections, identifying five major expression regions. Three of these regions have been proposed to have shell formation functions belonging to nacre, prismatic calcite and periostracum. The spatial gene expression map was confirmed by in situ hybridization, localizing a subset of ESTs from each expression region to the same mantle area. Comparative sequence analysis of ESTs expressed in the proposed shell formation regions with the BLAST tool, revealed a number of the transcripts were novel while others showed significant sequence similarities to previously characterized shell formation genes. The second investigation correlates temporal EST expression during P. maxima larval ontogeny with transitions in shell mineralization during the same period. A timeline documenting the morphologicat microstructural and mineralogical shell characteristics of P. maxima throughout larval ontogeny has been established. Three different shell types were noted based on the physical characters and termed, prodissoconch I, prodissoconch 11 and dissoconch. PmaxArray 1.0 analyzed ESTs expression of animals throughout the larval development of P. maxima, noting up-regulation of 359 ESTs in association with the shell transitions from prodissoconch 1 to prodissoconch 11 to dissoconch. Comparative sequence analysis of these ESTs indicates a number of the transcripts are novel as well as showing significant sequence similarities between ESTs and known shell matrix associated genes and proteins. These ESTs are discussed in relation to the shell characters associated with their temporal expression. The third investigation uses PmaxArray 1.0 to analyze gene expression in the mantle tissue of P. maxima specimens exposed to sub-lethal concentrations of a shell-deforming toxin, tributyltin (TBT). The shell specific effects of TBT are used in this investigation to interpret differential expression of ESTs with respect to shell formation functions. A lethal and sublethal TBT concentration range was established for P. maxima, noting a concentration of 50 ng L- 1 TBT as sub-lethal over a 21 day period. Mantle tissue from P. maxima animals treated with 50 ng L- 1 TBT was assessed for differential EST expression with untreated control animals. A total of 102 ESTs were identified as differentially expressed in association with TBT exposure, comparative sequence identities included an up-regulation of immunity and detoxification related genes and down-regulation of several shell matrix genes. A number of transcripts encoding novel peptides were additionally identified. The potential actions of these genes are discussed with reference to TBT toxicity and shell biomineralization. This thesis has used a microarray platform to analyze gene expression in spatial, temporal and toxicity investigations, revealing the involvement of numerous gene transcripts in specific shell formation functions. Investigation of thousands of transcripts simultaneously has provided a holistic interpretation of the organic components regulating shell biomineralization.

Soft-biometrics : unconstrained authentication in a surveillance environment

Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. These include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics (i.e. face, voice) which require cooperation from the subject, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. Whilst these traits cannot provide robust authentication, they can be used to provide coarse authentication or identification at long range, locate a subject who has been previously seen or who matches a description, as well as aid in object tracking. In this paper we propose three part (head, torso, legs) height and colour soft biometric models, and demonstrate their verification performance on a subset of the PETS 2006 database. We show that these models, whilst not as accurate as traditional biometrics, can still achieve acceptable rates of accuracy in situations where traditional biometrics cannot be applied.

Clustering of ad-hoc microphone arrays for robust blind beamforming

This paper proposes a clustered approach for blind beamfoming from ad-hoc microphone arrays. In such arrangements, microphone placement is arbitrary and the speaker may be close to one, all or a subset of microphones at a given time. Practical issues with such a configuration mean that some microphones might be better discarded due to poor input signal to noise ratio (SNR) or undesirable spatial aliasing effects from large inter-element spacings when beamforming. Large inter-microphone spacings may also lead to inaccuracies in delay estimation during blind beamforming. In such situations, using a cluster of microphones (ie, a sub-array), closely located both to each other and to the desired speech source, may provide more robust enhancement than the full array. This paper proposes a method for blind clustering of microphones based on the magnitude square coherence function, and evaluates the method on a database recorded using various ad-hoc microphone arrangements.

Latent variable models in statistical genetics

Understanding the complexities that are involved in the genetics of multifactorial diseases is still a monumental task. In addition to environmental factors that can influence the risk of disease, there is also a number of other complicating factors. Genetic variants associated with age of disease onset may be different from those variants associated with overall risk of disease, and variants may be located in positions that are not consistent with the traditional protein coding genetic paradigm. Latent Variable Models are well suited for the analysis of genetic data. A latent variable is one that we do not directly observe, but which is believed to exist or is included for computational or analytic convenience in a model. This thesis presents a mixture of methodological developments utilising latent variables, and results from case studies in genetic epidemiology and comparative genomics. Epidemiological studies have identified a number of environmental risk factors for appendicitis, but the disease aetiology of this oft thought useless vestige remains largely a mystery. The effects of smoking on other gastrointestinal disorders are well documented, and in light of this, the thesis investigates the association between smoking and appendicitis through the use of latent variables. By utilising data from a large Australian twin study questionnaire as both cohort and case-control, evidence is found for the association between tobacco smoking and appendicitis. Twin and family studies have also found evidence for the role of heredity in the risk of appendicitis. Results from previous studies are extended here to estimate the heritability of age-at-onset and account for the eect of smoking. This thesis presents a novel approach for performing a genome-wide variance components linkage analysis on transformed residuals from a Cox regression. This method finds evidence for a dierent subset of genes responsible for variation in age at onset than those associated with overall risk of appendicitis. Motivated by increasing evidence of functional activity in regions of the genome once thought of as evolutionary graveyards, this thesis develops a generalisation to the Bayesian multiple changepoint model on aligned DNA sequences for more than two species. This sensitive technique is applied to evaluating the distributions of evolutionary rates, with the finding that they are much more complex than previously apparent. We show strong evidence for at least 9 well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least 7 classes in an alignment of four mammals, including human. A pattern of enrichment and depletion of genic regions in the profiled segments suggests they are functionally significant, and most likely consist of various functional classes. Furthermore, a method of incorporating alignment characteristics representative of function such as GC content and type of mutation into the segmentation model is developed within this thesis. Evidence of fine-structured segmental variation is presented.

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

Characteristics of sustainable entrepreneurship : some early explorations from the CAUSEE study

Principal Topic: For forward thinking companies, the environment may represent the ''biggest opportunity for enterprise and invention the industrial world has ever seen'' (Cairncross 1990). Increasing awareness of environmental and sustainability issues through media including the promotion of Al Gore's ''An Inconvenient Truth'' has seen increased awareness of environmental and sustainability issues and increased demand for business processes that reduce detrimental environmental impacts of global development (Dean & McMullen 2007). The increased demand for more environmentally sensitive products and services represents an opportunity for the development of ventures that seek to satisfy this demand through entrepreneurial action. As a consequence, increasing recent market developments in renewable energy, carbon emissions, fuel cells, green building, and other sectors suggest an increasing importance of opportunities for environmental entrepreneurship (Dean and McMullen 2007) and increasingly important area of business activity (Schaper 2005). In the last decade in particular, big business has sought to develop a more ''sustainability/ green friendly'' orientation as a response to public pressure and increased government legislation and policy to improve environmental performance (Cohen and Winn 2007). Whilst much of the literature and media is littered with examples of sustainability practices of large firms, nascent and young sustainability firms have only recently begun generating strong research and policy interest (Shepherd, Kuskova and Patzelt 2009): not only for their potential to generate above average financial performance and returns owing to a greater popularity and demand towards sustainability products and services offerings, but also for their intent to lessen environmental impacts, and to provide a more accurate reflection of the ''true cost'' of market offerings taking into account carbon and environmental impacts. More specifically, researchers have suggested that although the previous focus has been on large firms and their impact on the environment, the estimated collective impact of entries and exits of nascent and young firms in development is substantial and could outweigh the combined environmental impact of large companies (Hillary, 2000). Therefore, it may be argued that greater attention should be paid to nascent and young firms and researching sustainability practices, for both their impact in reducing environmental impacts and potential higher financial performance. Whilst acknowledging this research only uses the first wave of a four year longitudinal study of nascent and young firms, it can still begin to provide initial analysis on which to continue further research. The aim of this paper therefore is to provide an overview of the emerging literature in sustainable entrepreneurship and to present some selected preliminary results from the first wave of the data collection, with comparison, where appropriate, of sustainable and firms that do not fulfil this criteria. ''One of the key challenges in evaluating sustainability entrepreneurship is the lack of agreement in how it is defined'' (Schaper, 2005: 10). Some evaluate sustainable entrepreneurs simply as one category of entrepreneurs with little difference between them and traditional entrepreneurs (Dees, 1998). Other research recognises values-based sustainable enterprises requiring a unique perspective (Parrish, 2005). Some see the environmental or sustainable entrepreneurship is a subset of social entrepreneurship (Cohen & Winn, 2007; Dean & McMullen, 2007) whilst others see it as a separate, distinct theory (Archer 2009). Following one of the first definitions of sustainability developed by the Brundtland Commission (1987) we define sustainable entrepreneurship as firms which ''seek to meet the needs and aspirations of the present without compromising the ability to meet those of the future''. ---------- Methodology/Key Propositions: In this exploratory paper we investigate sustainable entrepreneurship using Cohen et al.'s (2008) framework to identify strategies of nascent and young entrepreneurial firms. We use data from The Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE). This study shares the general empirical approach with PSED studies in the US (Reynolds et al 1994; Reynolds & Curtin 2008). The overall study uses samples of 727 nascent (not yet operational) firms and another 674 young firms, the latter being in an operational stage but less than four years old. To generate the sub sample of sustainability firms, we used content analysis techniques on firm titles, descriptions and product descriptions provided by respondents. Two independent coders used a predefined codebook developed from our review of the sustainability entrepreneurship literature (Cohen et al. 2009) to evaluate the content based on terms such as ''sustainable'' ''eco-friendly'' ''renewable energy'' ''environment'' amongst others. The inter-rater reliability was checked and the Kappa's co-efficient was found to be within the acceptable range (0.746). 85 firms fulfilled the criteria given for inclusion in the sustainability cohort. ---------- Results and Implications: The results for this paper are based on Wave one of the CAUSEE survey which has been completed and the data is available for analysis. It is expected that the findings will assist in beginning to develop an understanding of nascent and young firms that are driven to contribute to a society which is sustainable, not just from an economic perspective (Cohen et al 2008), but from an environmental and social perspective as well. The CAUSEE study provides an opportunity to compare the characteristics of sustainability entrepreneurs with entrepreneurial firms without a stated environmental purpose, which constitutes the majority of the new firms created each year, using a large scale novel longitudinal dataset. The results have implications for Government in the design of better conditions for the creation of new business, firms who assist sustainability in developing better advice programs in line with a better understanding of their needs and requirements, individuals who may be considering becoming entrepreneurs in high potential arenas and existing entrepreneurs make better decisions.