987 resultados para Multimedia Approach
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This paper proposes that the generational approach to conceptualising first year student learning behaviour, while it has made a very useful contribution to understanding that behaviour, can be expanded upon. The generational approach has an explicit focus on student behaviour and it is suggested that a capability maturity model interpretation may provide a complementary extension of that as it allows an assessment of institutional capability to initiate, plan, manage and evaluate institutional student engagement practices. The development of a Student Engagement, Success and Retention Maturity Model (SESR-MM) is discussed along with Australasian FYE generational data and Australian SESR-MM data.
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Anisotropic damage distribution and evolution have a profound effect on borehole stress concentrations. Damage evolution is an irreversible process that is not adequately described within classical equilibrium thermodynamics. Therefore, we propose a constitutive model, based on non-equilibrium thermodynamics, that accounts for anisotropic damage distribution, anisotropic damage threshold and anisotropic damage evolution. We implemented this constitutive model numerically, using the finite element method, to calculate stress–strain curves and borehole stresses. The resulting stress–strain curves are distinctively different from linear elastic-brittle and linear elastic-ideal plastic constitutive models and realistically model experimental responses of brittle rocks. We show that the onset of damage evolution leads to an inhomogeneous redistribution of material properties and stresses along the borehole wall. The classical linear elastic-brittle approach to borehole stability analysis systematically overestimates the stress concentrations on the borehole wall, because dissipative strain-softening is underestimated. The proposed damage mechanics approach explicitly models dissipative behaviour and leads to non-conservative mud window estimations. Furthermore, anisotropic rocks with preferential planes of failure, like shales, can be addressed with our model.
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Completing a PhD on time is a complex process, influenced by many interacting factors. In this paper we take a Bayesian Network approach to analyzing the factors perceived to be important in achieving this aim. Focusing on a single research group in Mathematical Sciences, we develop a conceptual model to describe the factors considered to be important to students and then quantify the network based on five individual perspectives: the students, a supervisor and a university research students centre manager. The resultant network comprised 37 factors and 40 connections, with an overall probability of timely completion of between 0.6 and 0.8. Across all participants, the four factors that were considered to most directly influence timely completion were personal aspects, the research environment, the research project, and incoming skills.
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Language has been of interest to numerous economists since the late 20th century, with the majority of the studies focusing on its effects on immigrants’ labour market outcomes; earnings in particular. However, language is an endogenous variable, which along with its susceptibility to measurement error causes biases in ordinary-least-squares estimates. The instrumental variables method overcomes the shortcomings of ordinary least squares in modelling endogenous explanatory variables. In this dissertation, age at arrival combined with country of origin form an instrument creating a difference-in-difference scenario, to address the issue of endogeneity and attenuation error in language proficiency. The first half of the study aims to investigate the extent to which English speaking ability of immigrants improves their labour market outcomes and social assimilation in Australia, with the use of the 2006 Census. The findings have provided evidence that support the earlier studies. As expected, immigrants in Australia with better language proficiency are able to earn higher income, attain higher level of education, have higher probability of completing tertiary studies, and have more hours of work per week. Language proficiency also improves social integration, leading to higher probability of marriage to a native and higher probability of obtaining citizenship. The second half of the study further investigates whether language proficiency has similar effects on a migrant’s physical and mental wellbeing, health care access and lifestyle choices, with the use of three National Health Surveys. However, only limited evidence has been found with respect to the hypothesised causal relationship between language and health for Australian immigrants.
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Least developed countries (LDCs) are the primary victims of environmental changes, including present and future impacts of climate change. Environmental degradation poses a serious threat to the conservation and sustainable use of natural resources, thus hindering development in LDCs. Simultaneously, poverty is itself both a major cause and effect of global environmental problems. Against this backdrop, this essay argues that without recognition and protection of a collective right to development, genuine environmental protection will remain unachievable. Further, this essay submits that, particularly in the context of LDCs, the right to environment and the right to development are inseparable. Finally, this essay argues that the relationship between the right to environment and the right to development must fall within the paradigm of sustainable development if the promotion and protection of those rights are to be justified.
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Topic modeling has been widely utilized in the fields of information retrieval, text mining, text classification etc. Most existing statistical topic modeling methods such as LDA and pLSA generate a term based representation to represent a topic by selecting single words from multinomial word distribution over this topic. There are two main shortcomings: firstly, popular or common words occur very often across different topics that bring ambiguity to understand topics; secondly, single words lack coherent semantic meaning to accurately represent topics. In order to overcome these problems, in this paper, we propose a two-stage model that combines text mining and pattern mining with statistical modeling to generate more discriminative and semantic rich topic representations. Experiments show that the optimized topic representations generated by the proposed methods outperform the typical statistical topic modeling method LDA in terms of accuracy and certainty.
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This paper presents an alternative approach to image segmentation by using the spatial distribution of edge pixels as opposed to pixel intensities. The segmentation is achieved by a multi-layered approach and is intended to find suitable landing areas for an aircraft emergency landing. We combine standard techniques (edge detectors) with novel developed algorithms (line expansion and geometry test) to design an original segmentation algorithm. Our approach removes the dependency on environmental factors that traditionally influence lighting conditions, which in turn have negative impact on pixel-based segmentation techniques. We present test outcomes on realistic visual data collected from an aircraft, reporting on preliminary feedback about the performance of the detection. We demonstrate consistent performances over 97% detection rate.
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Understanding network traffic behaviour is crucial for managing and securing computer networks. One important technique is to mine frequent patterns or association rules from analysed traffic data. On the one hand, association rule mining usually generates a huge number of patterns and rules, many of them meaningless or user-unwanted; on the other hand, association rule mining can miss some necessary knowledge if it does not consider the hierarchy relationships in the network traffic data. Aiming to address such issues, this paper proposes a hybrid association rule mining method for characterizing network traffic behaviour. Rather than frequent patterns, the proposed method generates non-similar closed frequent patterns from network traffic data, which can significantly reduce the number of patterns. This method also proposes to derive new attributes from the original data to discover novel knowledge according to hierarchy relationships in network traffic data and user interests. Experiments performed on real network traffic data show that the proposed method is promising and can be used in real applications. Copyright2013 John Wiley & Sons, Ltd.
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This paper explores the sensuous relationship amongst people and the physical elements located in public squares. The research focuses on the study of sensuous geography and its social implications in contemporary city context. Case studies were drawn from various Western countries. A Lefebvrian approach was utilized to analyse the research findings. The study has generated a preliminary sensuous geography checklist for public squares that can predict the degree of popularity and experiential qualities of public squares. However, limits existed in the paper as sensory experiences are conditioned by individual, socio-cultural and climatic influences. The study suggests further integrated approach is needed in this field of study. The research findings indicated that better knowledge of sensuous geography is important in the design and planning disciplines.
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Evaluation practices in the higher education sector have been criticised for having unclear purpose and principles; ignoring the complexity and changing nature of learning and teaching and the environments in which they occur; relying almost exclusively on student ratings of teachers working in classroom settings; lacking reliability and validity; using data for inappropriate purposes; and focusing on accountability and marketing rather than the improvement of learning and teaching. In response to similar criticism from stakeholders, in 2011 Queensland University of Technology began a project, entitled REFRAME, to review its approach to evaluation, particularly the student survey system it had been using for the past five years. This presentation will outline the scholarly, evidence based methodology used to undertake institution-wide change, meet the needs of stakeholders suitable to the cultural needs of the institution. It is believed that this approach is broadly applicable to other institutions contemplating change with regard to evaluation of learning and teaching.
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The decisions people make about medical treatments have a great impact on their lives. Health care practitioners, providers and patients often make decisions about medical treatments without complete understanding of the circumstances. The main reason for this is that medical data are available in fragmented, disparate and heterogeneous data silos. Without a centralised data warehouse structure to integrate these data silos, it is highly unlikely and impractical for the users to get all the information required on time to make a correct decision. In this research paper, a clinical data integration approach using SAS Clinical Data Integration Server tools is presented.
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This project has provided a new understanding of the passenger experience in Australian international airport departure terminals. A novel understanding of the passenger experience developed by observing the activities passengers carried out on their day of travel, and interviewing passengers and staff members. The development of the Taxonomy of Passenger Activities (TOPA) has been an important outcome of this research. It provides a new understanding of the airport passenger experience at departure. The Taxonomy of Passenger Activities identifies the activities that improve the experience of passengers and the processing efficiency of the airport terminal.
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Background A large animal model is required for assessment of minimally invasive, tissue engineering based approaches to thoracic spine fusion, with relevance to deformity correction surgery for human adolescent idiopathic scoliosis. Here we develop a novel open mini–thoracotomy approach in an ovine model of thoracic interbody fusion which allows assessment of various fusion constructs, with a focus on novel, tissue engineering based interventions. Methods The open mini-thoracotomy surgical approach was developed through a series of mock surgeries, and then applied in a live sheep study. Customized scaffolds were manufactured to conform with intervertebral disc space clearances required of the study. Twelve male Merino sheep aged 4 to 6 years and weighing 35 – 45 kg underwent the abovementioned procedure and were divided into two groups of six sheep at survival timelines of 6 and 12 months. Each sheep underwent a 3-level discectomy (T6/7, T8/9 and T10/11) with randomly allocated implantation of a different graft substitute at each of the three levels; (i) polycaprolactone (PCL) based scaffold plus 0.54μg rhBMP-2, (ii) PCL-based scaffold alone or (iii) autograft. The sheep were closely monitored post- operatively for signs of pain (i.e. gait abnormalities/ teeth gnawing/ social isolation). Fusion assessments were conducted post-sacrifice using Computed Tomography and hard-tissue histology. All scientific work was undertaken in accordance with the study protocol has been approved by the Institute's committee on animal research. Results. All twelve sheep were successfully operated on and reached the allotted survival timelines, thereby demonstrating the feasibility of the surgical procedure and post-operative care. There were no significant complications and during the post-operative period the animals did not exhibit marked signs of distress according to the described assessment criteria. Computed Tomographic scanning demonstrated higher fusion grades in the rhBMP-2 plus PCL-based scaffold group in comparison to either PCL-based scaffold alone or autograft. These results were supported by histological evaluation of the respective groups. Conclusion. This novel open mini-thoracotomy surgical approach to the ovine thoracic spine represents a safe surgical method which can reproducibly form the platform for research into various spine tissue engineered constructs (TEC) and their fusion promoting properties.
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A novel in-cylinder pressure method for determining ignition delay has been proposed and demonstrated. This method proposes a new Bayesian statistical model to resolve the start of combustion, defined as being the point at which the band-pass in-cylinder pressure deviates from background noise and the combustion resonance begins. Further, it is demonstrated that this method is still accurate in situations where there is noise present. The start of combustion can be resolved for each cycle without the need for ad hoc methods such as cycle averaging. Therefore, this method allows for analysis of consecutive cycles and inter-cycle variability studies. Ignition delay obtained by this method and by the net rate of heat release have been shown to give good agreement. However, the use of combustion resonance to determine the start of combustion is preferable over the net rate of heat release method because it does not rely on knowledge of heat losses and will still function accurately in the presence of noise. Results for a six-cylinder turbo-charged common-rail diesel engine run with neat diesel fuel at full, three quarters and half load have been presented. Under these conditions the ignition delay was shown to increase as the load was decreased with a significant increase in ignition delay at half load, when compared with three quarter and full loads.
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The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching.