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.

Crowd Counting Using Multiple Local Features

In public venues, crowd size is a key indicator of crowd safety and stability. Crowding levels can be detected using holistic image features, however this requires a large amount of training data to capture the wide variations in crowd distribution. If a crowd counting algorithm is to be deployed across a large number of cameras, such a large and burdensome training requirement is far from ideal. In this paper we propose an approach that uses local features to count the number of people in each foreground blob segment, so that the total crowd estimate is the sum of the group sizes. This results in an approach that is scalable to crowd volumes not seen in the training data, and can be trained on a very small data set. As a local approach is used, the proposed algorithm can easily be used to estimate crowd density throughout different regions of the scene and be used in a multi-camera environment. A unique localised approach to ground truth annotation reduces the required training data is also presented, as a localised approach to crowd counting has different training requirements to a holistic one. Testing on a large pedestrian database compares the proposed technique to existing holistic techniques and demonstrates improved accuracy, and superior performance when test conditions are unseen in the training set, or a minimal training set is used.

QoS-Based Web Service Scheduling Accommodating Inter-Service Dependencies Using Minimal-Conflict Hill-Climbing Repair Genetic Algorithm

In the filed of semantic grid, QoS-based Web service scheduling for workflow optimization is an important problem.However, in semantic and service rich environment like semantic grid, the emergence of context constraints on Web services is very common making the scheduling consider not only quality properties of Web services, but also inter service dependencies which are formed due to the context constraints imposed on Web services. In this paper, we present a repair genetic algorithm, namely minimal-conflict hill-climbing repair genetic algorithm, to address scheduling optimization problems in workflow applications in the presence of domain constraints and inter service dependencies. Experimental results demonstrate the scalability and effectiveness of the genetic algorithm.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Fast searching algorithm for candidate satellite-node set in NLMG

The Node-based Local Mesh Generation (NLMG) algorithm, which is free of mesh inconsistency, is one of core algorithms in the Node-based Local Finite Element Method (NLFEM) to achieve the seamless link between mesh generation and stiffness matrix calculation, and the seamless link helps to improve the parallel efficiency of FEM. Furthermore, the key to ensure the efficiency and reliability of NLMG is to determine the candidate satellite-node set of a central node quickly and accurately. This paper develops a Fast Local Search Method based on Uniform Bucket (FLSMUB) and a Fast Local Search Method based on Multilayer Bucket (FLSMMB), and applies them successfully to the decisive problems, i.e. presenting the candidate satellite-node set of any central node in NLMG algorithm. Using FLSMUB or FLSMMB, the NLMG algorithm becomes a practical tool to reduce the parallel computation cost of FEM. Parallel numerical experiments validate that either FLSMUB or FLSMMB is fast, reliable and efficient for their suitable problems and that they are especially effective for computing the large-scale parallel problems.

The nature and extent of policing alcohol related crime and reducing violence in and around late night entertainment areas

The misuse of alcohol is well documented in Australia and has been associated with disorders and harms that often require police attention. The extent of alcohol-related incidents requiring police attention has been recorded as substantial in some Australian cities (Arro, Crook, & Fenton, 1992; Davey & French, 1995; Ireland & Thommeny, 1993). A significant proportion of harmful drinking occurs in and around licensed premises (Jochelson, 1997; Stockwell, Masters, Phillips, Daly, Gahegan, Midford, & Philp, 1998; Borges, Cherpitel, & Rosovsky, 1998) and most of these incidents are not reported to police (Bryant & Williams, 2000; Lister, Hobbs, Hall, & Winlow, 2000). Alcohol-related incidents have also been found to be concentrated in certain places at certain times (Jochelson, 1997) and therefore manipulating the context in which these incidents occur may provide a means to prevent and reduce the harm associated with alcohol misuse. One of the major objectives of the present program of research was to investigate the occurrence and resource impact of alcohol-related incidents on operational (general duties) policing across a large geographical area. A second objective of the thesis was to examine the characteristics and temporal/spatial dynamics of police attended alcohol incidents in the context of Place Based theories of crime. It was envisaged that this approach would reveal the patterns of the most prevalent offences and demonstrate the relevance of Place Based theories of crime to understanding these patterns. In addition, the role of alcohol, time and place were also explored in order to examine the association between non criminal traffic offences and other types of criminal offences. A final objective of the thesis was to examine the impact of a situational crime prevention strategy that had been initiated to reduce the violence and disorder associated with late-night liquor trading premises. The program of research in this doctorate thesis has been undertaken through the presentation of published papers. The research was conducted in three stages which produced six manuscripts, five of which were submitted to peer reviewed journals and one that was published in a peer reviewed conference proceedings. Stage One included two studies (Studies 1 & 2) both of which involved a cross sectional approach to examine the prevalence and characteristics of alcohol-related incidents requiring police attendance across three large geographical areas that included metropolitan cities, provincial regions and rural areas. Stage Two of the program of research also comprised two cross sectional quantitative studies (Studies 3 & 4) that investigated the temporal and spatial dynamics of the major offence categories attended by operational police in a specific Police District (Gold Coast). Stage Three of the program of research involved two studies (Studies 5 & 6) that assessed the effectiveness of a situational crime prevention strategy. The studies employed a pre-post design to assess the impact on crime, disorder and violence by preventing patrons from entering late-night liquor trading premises between 3 a.m. and 5 a.m. (lockout policy). Although Study Five was solely quantitative in nature, Study Six included both quantitative and qualitative aspects. The approach adopted in Study Six, therefore facilitated not only a quantative comparison of the impact of the lockout policy on different policing areas, but also enabled the processes related to the implementation of the lockout policy to be examined. The thesis reports a program of research involving a common data collection method which then involved a series of studies being conducted to explore different aspects of the data. The data was collected from three sources. Firstly a pilot phase was undertaken to provide participants with training. Secondly a main study period was undertaken immediately following the pilot phase. The first and second sources of data were collected between 29th March 2004 and 2nd May 2004. Thirdly, additional data was collected between the 1st April 2005 and 31st May 2005. Participants in the current program of research were first response operational police officers who completed a modified activity log over a 9 week period (4 week pilot phase & 5 week survey study phase), identifying the type, prevalence and characteristics of alcohol-related incidents that were attended. During the study period police officers attended 31,090 alcohol-related incidents. Studies One and Two revealed that a substantial proportion of current police work involves attendance at alcohol-related incidents (i.e., 25% largely involving young males aged between 17 and 24 years). The most common incidents police attended were vehicle and/or traffic matters, disturbances and offences against property. The major category of offences most likely to involve alcohol included vehicle/traffic matters, disturbances and offences against the person (e.g., common & serious assaults). These events were most likely to occur in the late evenings and early hours of the morning on the weekends, and importantly, usually took longer for police to complete than non alcohol-related incidents. The findings in Studies Three and Four suggest that serious traffic offences, disturbances and offences against the person share similar characteristics and occur in concentrated places at similar times. In addition, it was found that time, place and incident type all have an influence on whether an incident attended by a police officer is alcohol-related. Alcohol-related incidents are more likely to occur in particular locations in the late evenings and early mornings on the weekends. In particular, there was a strong association between the occurrence of alcohol-related disturbances and alcohol-related serious traffic offences in regards to place and time. In general, stealing and property offences were not alcohol-related and occurred in daylight hours during weekdays. The results of Studies Five and Six were mixed. A number of alcohol-related offences requiring police attention were significantly reduced for some policing areas and for some types of offences following the implementation of the lockout policy. However, in some locations the lockout policy appeared to have a negative or minimal impact. Interviews with licensees revealed that although all were initially opposed to the lockout policy as they believed it would have a negative impact on business, most perceived some benefits from its introduction. Some of the benefits included, improved patron safety and the development of better business strategies to increase patron numbers. In conclusion, the overall findings of the six studies highlight the pervasive nature of alcohol across a range of criminal incidents, demonstrating the tremendous impact alcohol-related incidents have on police. The findings also demonstrate the importance of time and place in predicting the occurrence of alcohol-related offences. Although this program of research did not set out to test Place Based theories of crime, these theories were used to inform the interpretation of findings. The findings in the current research program provide evidence for the relevance of Place Based theories of crime to understanding the factors contributing to violence and disorder, and designing relevant crime prevention strategies. For instance, the results in Studies Five and Six provide supportive evidence that this novel lockout initiative can be beneficial for public safety by reducing some types of offences in particular areas in and around late-night liquor trading premises. Finally, intelligent-led policing initiatives based on problem oriented policing, such as the lockout policy examined in this thesis, have potential as a major crime prevention technique to reduce specific types of alcohol-related offences.

Determining a set of surrogate parameters to evaluate urban stormwater quality

This thesis details methodology to estimate urban stormwater quality based on a set of easy to measure physico-chemical parameters. These parameters can be used as surrogate parameters to estimate other key water quality parameters. The key pollutants considered in this study are nitrogen compounds, phosphorus compounds and solids. The use of surrogate parameter relationships to evaluate urban stormwater quality will reduce the cost of monitoring and so that scientists will have added capability to generate a large amount of data for more rigorous analysis of key urban stormwater quality processes, namely, pollutant build-up and wash-off. This in turn will assist in the development of more stringent stormwater quality mitigation strategies. The research methodology was based on a series of field investigations, laboratory testing and data analysis. Field investigations were conducted to collect pollutant build-up and wash-off samples from residential roads and roof surfaces. Past research has identified that these impervious surfaces are the primary pollutant sources to urban stormwater runoff. A specially designed vacuum system and rainfall simulator were used in the collection of pollutant build-up and wash-off samples. The collected samples were tested for a range of physico-chemical parameters. Data analysis was conducted using both univariate and multivariate data analysis techniques. Analysis of build-up samples showed that pollutant loads accumulated on road surfaces are higher compared to the pollutant loads on roof surfaces. Furthermore, it was found that the fraction of solids smaller than 150 ìm is the most polluted particle size fraction in solids build-up on both roads and roof surfaces. The analysis of wash-off data confirmed that the simulated wash-off process adopted for this research agrees well with the general understanding of the wash-off process on urban impervious surfaces. The observed pollutant concentrations in wash-off from road surfaces were different to pollutant concentrations in wash-off from roof surfaces. Therefore, firstly, the identification of surrogate parameters was undertaken separately for roads and roof surfaces. Secondly, a common set of surrogate parameter relationships were identified for both surfaces together to evaluate urban stormwater quality. Surrogate parameters were identified for nitrogen, phosphorus and solids separately. Electrical conductivity (EC), total organic carbon (TOC), dissolved organic carbon (DOC), total suspended solids (TSS), total dissolved solids (TDS), total solids (TS) and turbidity (TTU) were selected as the relatively easy to measure parameters. Consequently, surrogate parameters for nitrogen and phosphorus were identified from the set of easy to measure parameters for both road surfaces and roof surfaces. Additionally, surrogate parameters for TSS, TDS and TS which are key indicators of solids were obtained from EC and TTU which can be direct field measurements. The regression relationships which were developed for surrogate parameters and key parameter of interest were of a similar format for road and roof surfaces, namely it was in the form of simple linear regression equations. The identified relationships for road surfaces were DTN-TDS:DOC, TP-TS:TOC, TSS-TTU, TDS-EC and TSTTU: EC. The identified relationships for roof surfaces were DTN-TDS and TSTTU: EC. Some of the relationships developed had a higher confidence interval whilst others had a relatively low confidence interval. The relationships obtained for DTN-TDS, DTN-DOC, TP-TS and TS-EC for road surfaces demonstrated good near site portability potential. Currently, best management practices are focussed on providing treatment measures for stormwater runoff at catchment outlets where separation of road and roof runoff is not found. In this context, it is important to find a common set of surrogate parameter relationships for road surfaces and roof surfaces to evaluate urban stormwater quality. Consequently DTN-TDS, TS-EC and TS-TTU relationships were identified as the common relationships which are capable of providing measurements of DTN and TS irrespective of the surface type.

QoS-based web service composition accommodating inter-service dependencies using minimal-conflict , hill-climbing repair genetic algorithm

In the field of semantic grid, QoS-based Web service composition is an important problem. In semantic and service rich environment like semantic grid, the emergence of context constraints on Web services is very common making the composition consider not only QoS properties of Web services, but also inter service dependencies and conflicts which are formed due to the context constraints imposed on Web services. In this paper, we present a repair genetic algorithm, namely minimal-conflict hill-climbing repair genetic algorithm, to address the Web service composition optimization problem in the presence of domain constraints and inter service dependencies and conflicts. Experimental results demonstrate the scalability and effectiveness of the genetic algorithm.

Destination branding : tracking brand equity for a competitive set of near-home destinations

In the emerging literature related to destination branding, little has been reported about performance metrics. The focus of most research reported to date has been concerned with the development of destination brand identities and the implementation of campaigns (see for example, Crockett & Wood 1999, Hall 1999, May 2001, Morgan et al 2002). One area requiring increased attention is that of tracking the performance of destination brands over time. This is an important gap in the tourism literature, given: i) the increasing level of investment by destination marketing organisations (DMO) in branding since the 1990s, ii) the complex political nature of DMO brand decision-making and increasing accountability to stakeholders (see Pike, 2005), and iii) the long-term nature of repositioning a destination’s image in the market place (see Gartner & Hunt, 1987). Indeed, a number of researchers in various parts of the world have pointed to a lack of market research monitoring destination marketing objectives, such as in Australia (see Prosser et. al 2000, Carson, Beattie and Gove 2003), North America (Sheehan & Ritchie 1997, Masberg 1999), and Europe (Dolnicar & Schoesser 2003)...

Employee work motivation and discretionary work effort

The focus of this thesis is discretionary work effort, that is, work effort that is voluntary, is above and beyond what is minimally required or normally expected to avoid reprimand or dismissal, and is organisationally functional. Discretionary work effort is an important construct because it is known to affect individual performance as well as organisational efficiency and effectiveness. To optimise organisational performance and ensure their long term competitiveness and sustainability, firms need to be able to induce their employees to work at or near their peak level. To work at or near their peak level, individuals must be willing to supply discretionary work effort. Thus, managers need to understand the determinants of discretionary work effort. Nonetheless, despite many years of scholarly investigation across multiple disciplines, considerable debate still exists concerning why some individuals supply only minimal work effort whilst others expend effort well above and beyond what is minimally required of them (Le. they supply discretionary work effort). Even though it is well recognised that discretionary work effort is important for promoting organisational performance and effectiveness, many authors claim that too little is being done by managers to increase the discretionary work effort of their employees. In this research, I have adopted a multi-disciplinary approach towards investigating the role of monetary and non-monetary work environment characteristics in determining discretionary work effort. My central research questions were "What non-monetary work environment characteristics do employees perceive as perks (perquisites) and irks (irksome work environment characteristics)?" and "How do perks, irks and monetary rewards relate to an employee's level of discretionary work effort?" My research took a unique approach in addressing these research questions. By bringing together the economics and organisational behaviour (OB) literatures, I identified problems with the current definition and conceptualisations of the discretionary work effort construct. I then developed and empirically tested a more concise and theoretically-based definition and conceptualisation of this construct. In doing so, I disaggregated discretionary work effort to include three facets - time, intensity and direction - and empirically assessed if different classes of work environment characteristics have a differential pattern of relationships with these facets. This analysis involved a new application of a multi-disciplinary framework of human behaviour as a tool for classifying work environment characteristics and the facets of discretionary work effort. To test my model of discretionary work effort, I used a public sector context in which there has been limited systematic empirical research into work motivation. The program of research undertaken involved three separate but interrelated studies using mixed methods. Data on perks, irks, monetary rewards and discretionary work effort were gathered from employees in 12 organisations in the local government sector in Western Australia. Non-monetary work environment characteristics that should be associated with discretionary work effort were initially identified through a review of the literature. Then, a qualitative study explored what work behaviours public sector employees perceive as discretionary and what perks and irks were associated with high and low levels of discretionary work effort. Next, a quantitative study developed measures of these perks and irks. A Q-sorttype procedure and exploratory factor analysis were used to develop the perks and irks measures. Finally, a second quantitative study tested the relationships amongst perks, irks, monetary rewards and discretionary work effort. Confirmatory factor analysis was firstly used to confirm the factor structure of the measurement models. Correlation analysis, regression analysis and effect-size correlation analysis were used to test the hypothesised relationships in the proposed model of discretionary work effort. The findings confirmed five hypothesised non-monetary work environment characteristics as common perks and two of three hypothesised non-monetary work environment characteristics as common irks. Importantly, they showed that perks, irks and monetary rewards are differentially related to the different facets of discretionary work effort. The convergent and discriminant validities of the perks and irks constructs as well as the time, intensity and direction facets of discretionary work effort were generally confirmed by the research findings. This research advances the literature in several ways: (i) it draws on the Economics and OB literatures to redefine and reconceptualise the discretionary work effort construct to provide greater definitional clarity and a more complete conceptualisation of this important construct; (ii) it builds on prior research to create a more comprehensive set of perks and irks for which measures are developed; (iii) it develops and empirically tests a new motivational model of discretionary work effort that enhances our understanding of the nature and functioning of perks and irks and advances our ability to predict discretionary work effort; and (iv) it fills a substantial gap in the literature on public sector work motivation by revealing what work behaviours public sector employees perceive as discretionary and what work environment characteristics are associated with their supply of discretionary work effort. Importantly, by disaggregating discretionary work effort this research provides greater detail on how perks, irks and monetary rewards are related to the different facets of discretionary work effort. Thus, from a theoretical perspective this research also demonstrates the conceptual meaningfulness and empirical utility of investigating the different facets of discretionary work effort separately. From a practical perspective, identifying work environment factors that are associated with discretionary work effort enhances managers' capacity to tap this valuable resource. This research indicates that to maximise the potential of their human resources, managers need to address perks, irks and monetary rewards. It suggests three different mechanisms through which managers might influence discretionary work effort and points to the importance of training for both managers and non-managers in cultivating positive interpersonal relationships.

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.