140 resultados para methods and measurement


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Identifying an individual from surveillance video is a difficult, time consuming and labour intensive process. The proposed system aims to streamline this process by filtering out unwanted scenes and enhancing an individual's face through super-resolution. An automatic face recognition system is then used to identify the subject or present the human operator with likely matches from a database. A person tracker is used to speed up the subject detection and super-resolution process by tracking moving subjects and cropping a region of interest around the subject's face to reduce the number and size of the image frames to be super-resolved respectively. In this paper, experiments have been conducted to demonstrate how the optical flow super-resolution method used improves surveillance imagery for visual inspection as well as automatic face recognition on an Eigenface and Elastic Bunch Graph Matching system. The optical flow based method has also been benchmarked against the ``hallucination'' algorithm, interpolation methods and the original low-resolution images. Results show that both super-resolution algorithms improved recognition rates significantly. Although the hallucination method resulted in slightly higher recognition rates, the optical flow method produced less artifacts and more visually correct images suitable for human consumption.

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Road and highway infrastructure provides the backbone for a nation’s economic growth. The versatile dispersion of population in Australia and its resource boom, coupled with improved living standards and growing societal expectations, calls for continuing development and improvement of road infrastructure under the current local, state and federal governments’ policies and strategic plans. As road infrastructure projects involve huge resources and mechanisms, achieving sustainability not only on economic scales but also through environmental and social responsibility becomes a crucial issue. While sustainability is a logical link to infrastructure development, literature study and consultation with the industry found that there is a lack of common understanding on what constitutes sustainability in the infrastructure context. Its priorities are often interpreted differently among multiple stakeholders. For road infrastructure projects which typically span over long periods of time, achieving tangible sustainability outcomes during the lifecycle of development remains a formidable task. Sustainable development initiatives often remain ideological as in macro-level policies and broad-based concepts. There were little elaboration and exemplar cases on how these policies and concepts can be translated into practical decision-making during project implementation. In contrast, there seemed to be over commitment on research and development of sustainability assessment methods and tools. Between the two positions, there is a perception-reality gap and mismatch, specifically on how to enhance sustainability deliverables during infrastructure project delivery. Review on past research in this industry sector also found that little has been done to promote sustainable road infrastructure development; this has wide and varied potential impacts. This research identified the common perceptions and expectations by different stakeholders towards achieving sustainability in road and highway infrastructure projects. Face to face interviews on selected representatives of these stakeholders were carried out in order to select and categorize, confirm and prioritize a list of sustainability performance targets identified through literature and past research. A Delphi study was conducted with the assistance of a panel of senior industry professionals and academic experts, which further considered the interrelationship and influence of the sustainability indicators, and identified critical sustainability indicators under ten critical sustainability criteria (e.g. Environmental, Health & Safety, Resource Utilization & Management, Social & Cultural, Economic, Public Governance & Community Engagement, Relations Management, Engineering, Institutional and Project Management). This presented critical sustainability issues that needed to be addressed at the project level. Accordingly, exemplar highway development projects were used as case studies to elicit solutions for the critical issues. Through the identification and integration of different perceptions and priority needs of the stakeholders, as well as key sustainability indicators and solutions for critical issues, a set of decision-making guidelines was developed to promote and drive consistent sustainability deliverables in road infrastructure projects.

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Difference and Dispersion is the fourth in a series of annual research papers produced by doctoral students from The Graduate School of Education, The University of Queensland, following their presentation at the School’s annual Postgraduate Research Conference in Education. The work featured herein celebrates the diversity of cultural and disciplinary backgrounds of education researchers who come from as far afield as Germany, Hong Kong, China, Nigeria, Russia, Singapore, Thailand and of course different parts of Australia. In keeping with a postmodern epistemology, ‘difference’ and ‘dispersion’ are key themes in apprehending the multiplicity of their research topics, methodologies, methods and speaking/writing positions. From widely differing contexts and situations, these writers address the consequences, implications and possibilities for education at the beginning of the third millennium. Their interest ranges from location-specific issues in schools and classrooms, change in learning contexts and processes, educational discourses and relations of power in diverse geographical settings, and the differing articulations of the local and the global in situated policy contexts. Conceived and developed in a spirit of ongoing dialogue with and insight to alternative views and visions of education and society, this edited collection exemplifies the quality in diversity and the high levels of scholarship and supervision at one of Australia’s finest Graduate Schools of Education.

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Our working hypotheses is that cross-cultural differences in tax compliance behaviour have foundations in the institutions of tax administration and citizen assessment of the quality of governance. Tax compliance being a complex behavioural issue. Its investigation requires use of a variety of methods and data sources. Results from artefactual field experiments conducted in countries with substantially different political histories and records of governance quality demondtrate that observed differences in tax compliance levels persist over alternative levels of enforcement. The experimental results are shown to be robust by replicating them for the same countries using survey response measures of tax compliance.

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Position estimation for planetary rovers has been typically limited to odometry based on proprioceptive measurements such as the integration of distance traveled and measurement of heading change. Here we present and compare two methods of online visual odometry suited for planetary rovers. Both methods use omnidirectional imagery to estimate motion of the rover. One method is based on robust estimation of optical flow and subsequent integration of the flow. The second method is a full structure-from-motion solution. To make the comparison meaningful we use the same set of raw corresponding visual features for each method. The dataset is an sequence of 2000 images taken during a field experiment in the Atacama desert, for which high resolution GPS ground truth is available.

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Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

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Structural health is a vital aspect of infrastructure sustainability. As a part of a vital infrastructure and transportation network, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs are a difficult burden for infrastructure owners. The structural health monitoring (SHM) systems proposed recently are incorporated with vibration-based damage detection techniques, statistical methods and signal processing techniques and have been regarded as efficient and economical ways to assess bridge condition and foresee probable costly failures. In this chapter, the recent developments in damage detection and condition assessment techniques based on vibration-based damage detection and statistical methods are reviewed. The vibration-based damage detection methods based on changes in natural frequencies, curvature or strain modes, modal strain energy, dynamic flexibility, artificial neural networks, before and after damage, and other signal processing methods such as Wavelet techniques, empirical mode decomposition and Hilbert spectrum methods are discussed in this chapter.

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Defining the precise promoter DNA sequence motifs where nuclear receptors and other transcription factors bind is an essential prerequisite for understanding how these proteins modulate the expression of their specific target genes. The purpose of this chapter is to provide the reader with a detailed guide with respect to the materials and the key methods required to perform this type of DNA-binding analysis. Irrespective of whether starting with purified DNA-binding proteins or somewhat crude cellular extracts, the tried-and-true procedures described here will enable one to accurately access the capacity of specific proteins to bind to DNA as well as to determine the exact sequences and DNA contact nucleotides involved. For illustrative purposes, we primarily have used the interaction of the androgen receptor with the rat probasin proximal promoter as our model system.

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We consider a time and space-symmetric fractional diffusion equation (TSS-FDE) under homogeneous Dirichlet conditions and homogeneous Neumann conditions. The TSS-FDE is obtained from the standard diffusion equation by replacing the first-order time derivative by a Caputo fractional derivative, and the second order space derivative by a symmetric fractional derivative. First, a method of separating variables expresses the analytical solution of the TSS-FDE in terms of the Mittag--Leffler function. Second, we propose two numerical methods to approximate the Caputo time fractional derivative: the finite difference method; and the Laplace transform method. The symmetric space fractional derivative is approximated using the matrix transform method. Finally, numerical results demonstrate the effectiveness of the numerical methods and to confirm the theoretical claims.

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Fractional Fokker-Planck equations (FFPEs) have gained much interest recently for describing transport dynamics in complex systems that are governed by anomalous diffusion and nonexponential relaxation patterns. However, effective numerical methods and analytic techniques for the FFPE are still in their embryonic state. In this paper, we consider a class of time-space fractional Fokker-Planck equations with a nonlinear source term (TSFFPE-NST), which involve the Caputo time fractional derivative (CTFD) of order α ∈ (0, 1) and the symmetric Riesz space fractional derivative (RSFD) of order μ ∈ (1, 2). Approximating the CTFD and RSFD using the L1-algorithm and shifted Grunwald method, respectively, a computationally effective numerical method is presented to solve the TSFFPE-NST. The stability and convergence of the proposed numerical method are investigated. Finally, numerical experiments are carried out to support the theoretical claims.

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We consider a time and space-symmetric fractional diffusion equation (TSS-FDE) under homogeneous Dirichlet conditions and homogeneous Neumann conditions. The TSS-FDE is obtained from the standard diffusion equation by replacing the first-order time derivative by the Caputo fractional derivative and the second order space derivative by the symmetric fractional derivative. Firstly, a method of separating variables is used to express the analytical solution of the tss-fde in terms of the Mittag–Leffler function. Secondly, we propose two numerical methods to approximate the Caputo time fractional derivative, namely, the finite difference method and the Laplace transform method. The symmetric space fractional derivative is approximated using the matrix transform method. Finally, numerical results are presented to demonstrate the effectiveness of the numerical methods and to confirm the theoretical claims.

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Identification of hot spots, also known as the sites with promise, black spots, accident-prone locations, or priority investigation locations, is an important and routine activity for improving the overall safety of roadway networks. Extensive literature focuses on methods for hot spot identification (HSID). A subset of this considerable literature is dedicated to conducting performance assessments of various HSID methods. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. The authors contend that currently employed HSID assessment criteria—namely false positives and false negatives—are necessary but not sufficient, and additional criteria are needed to exploit the ordinal nature of site ranking data. With the intent to equip road safety professionals and researchers with more useful tools to compare the performances of various HSID methods and to improve the level of HSID assessments, this paper proposes four quantitative HSID evaluation tests that are, to the authors’ knowledge, new and unique. These tests evaluate different aspects of HSID method performance, including reliability of results, ranking consistency, and false identification consistency and reliability. It is intended that road safety professionals apply these different evaluation tests in addition to existing tests to compare the performances of various HSID methods, and then select the most appropriate HSID method to screen road networks to identify sites that require further analysis. This work demonstrates four new criteria using 3 years of Arizona road section accident data and four commonly applied HSID methods [accident frequency ranking, accident rate ranking, accident reduction potential, and empirical Bayes (EB)]. The EB HSID method reveals itself as the superior method in most of the evaluation tests. In contrast, identifying hot spots using accident rate rankings performs the least well among the tests. The accident frequency and accident reduction potential methods perform similarly, with slight differences explained. The authors believe that the four new evaluation tests offer insight into HSID performance heretofore unavailable to analysts and researchers.

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The track allocation problem (TAP) at a multi-track, multi-platform mainline railway station is defined by the station track layout and service timetable, which implies combinations of spatial and temporal conflicts. Feasible solutions are available from either traditional planning or advanced intelligent searching methods and their evaluations with respect to operational requirements are essential for the operators. To facilitate thorough analysis, a timed Coloured Petri Nets (CPN) model is presented here to encapsulate the inter-relationships of the spatial and temporal constraints in the TAP.

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Web applications such as blogs, wikis, video and photo sharing sites, and social networking systems have been termed ‘Web 2.0’ to highlight an arguably more open, collaborative, personalisable, and therefore more participatory internet experience than what had previously been possible. Giving rise to a culture of participation, an increasing number of these social applications are now available on mobile phones where they take advantage of device-specific features such as sensors, location and context awareness. This international volume of book chapters will make a contribution towards exploring and better understanding the opportunities and challenges provided by tools, interfaces, methods and practices of social and mobile technology that enable participation and engagement. It brings together an international group of academics and practitioners from a diverse range of disciplines such as computing and engineering, social sciences, digital media and human-computer interaction to critically examine a range of applications of social and mobile technology, such as social networking, mobile interaction, wikis, twitter, blogging, virtual worlds, shared displays and urban sceens, and their impact to foster community activism, civic engagement and cultural citizenship.

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Purpose: The aims of this paper are: to investigate the perceptions held by police (insiders) and community member (outsiders) of the recruitment and retention of culturally and linguistically diverse employees of Victoria Police; and, to develop a model that can assist in future recruitment and retention policy development.---------- Design/methodology/approach: Structured focus group interviews were conducted based on an instrument deduced from existing literature. Police and community members were interviewed separate cohorts. The discussions were thematically coded to themes and sub-themes.---------- Findings: Specific differences were identified in perceptions of the importance of recruiting culturally and linguistically diverse groups, barriers to recruitment, recruitment methods, and retention methods.---------- Research limitations/implications: Based on these perceptions, a propose a model addresses the importance of cultural diversity in policing and barriers to recruitment and retention of culturally and linguistically diverse employees. Further research is necessary to assess the broader applicability of this model.---------- Practical implications: The proposed model is may be used as the basis for future recruitment and retention activities, and human resource management policy development.---------- Originality/value: This is the first study in the Australian context of recruitment and retention of culturally and linguistically diverse police that addresses both community and police perspectives. Aligning the demographic profile of the police service with that of the community is beneficial to effective policing.