319 resultados para Estoppel by representation

em Queensland University of Technology - ePrints Archive


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The topic of designers’ knowledge and how they conduct design process has been widely investigated in design research. Understanding theoretical and experiential knowledge in design has involved recognition of the importance of designers’ experience of experiencing, seeing, and absorbing ideas from the world as points of reference (or precedents) that are consulted whenever a design problem arises (Lawson, 2004). Hence, various types of design knowledge have been categorized (Lawson, 2004), and the nature of design knowledge continues to be studied (Cross, 2006); nevertheless, the study of the experiential aspects embedded in design knowledge is a topic not fully addressed. In particular there has been little emphasis on the investigation of the ways in which designers’ individual experience influences different types of design tasks. This research focuses on the investigation of the ways in which designers inform a usability design process. It aims to understand how designers design product usability, what informs their process, and the role their individual experience (and episodic knowledge) plays within the design process. This paper introduces initial outcomes from an empirical study involving observation of a design task that emphasized usability issues. It discusses the experiential knowledge observed in the visual representations (sketches) produced by designers as part of the design tasks. Through the use of visuals as means to represent experiential knowledge, this paper presents initial research outcomes to demonstrate how designers’ individual experience is integrated into design tasks and communicated within the design process. Initial outcomes demonstrate the influence of designers’ experience in the design of product usability. It is expected that outcomes will help identify the causal relationships between experience, context of use, and product usability, which will contribute to enhance our understanding about the design of user-product interactions.

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Recognizing the need to offer alternative methods of brief interventions, this study developed correspondence treatments for low-dependent problem drinkers and evaluated their impact. One hundred and twenty-one problem drinkers were recruited by media advertisements and were randomly allocated to a full cognitive behavioural treatment programme (CBT) or to a minimal intervention condition (MI) that gave information regarding alcohol misuse and instructions to record drinking. As predicted, CBT was more effective than MI in reducing alcohol consumption over the 4-month controlled trial period. CBT produced a 50% fall in consumption, bringing the average intake of subjects within recommended maximum levels. Treatment gains at 6 months were well maintained to 12 months. High levels of consumer satisfaction, a high representation of women and a substantial participation from isolated rural areas attested to the feasibility of the correspondence programme as an alternative treatment. However, some drinking occasions still involved high intake for a significant subgroup of subjects, and this issue will be addressed in future programmes. The results supported the use of correspondence delivery as a means of promoting early engagement and equity of access between city and country areas.

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This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.

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We argue that web service discovery technology should help the user navigate a complex problem space by providing suggestions for services which they may not be able to formulate themselves as (s)he lacks the epistemic resources to do so. Free text documents in service environments provide an untapped source of information for augmenting the epistemic state of the user and hence their ability to search effectively for services. A quantitative approach to semantic knowledge representation is adopted in the form of semantic space models computed from these free text documents. Knowledge of the user’s agenda is promoted by associational inferences computed from the semantic space. The inferences are suggestive and aim to promote human abductive reasoning to guide the user from fuzzy search goals into a better understanding of the problem space surrounding the given agenda. Experimental results are discussed based on a complex and realistic planning activity.

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Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform the issue of data mining tasks on multidimensional databases. Association rules describe associations between items in the same transactions (intra) or in different transactions (inter). Association mining attempts to find interesting or useful association rules in databases: this is the crucial issue for the application of data mining in the real world. Association mining can be used in many application areas, such as the discovery of associations between customers’ locations and shopping behaviours in market basket analysis. Association mining includes two phases. The first phase, called pattern mining, is the discovery of frequent patterns. The second phase, called rule generation, is the discovery of interesting and useful association rules in the discovered patterns. The first phase, however, often takes a long time to find all frequent patterns; these also include much noise. The second phase is also a time consuming activity that can generate many redundant rules. To improve the quality of association mining in databases, this thesis provides an alternative technique, granule-based association mining, for knowledge discovery in databases, where a granule refers to a predicate that describes common features of a group of transactions. The new technique first transfers transaction databases into basic decision tables, then uses multi-tier structures to integrate pattern mining and rule generation in one phase for both intra and inter transaction association rule mining. To evaluate the proposed new technique, this research defines the concept of meaningless rules by considering the co-relations between data-dimensions for intratransaction-association rule mining. It also uses precision to evaluate the effectiveness of intertransaction association rules. The experimental results show that the proposed technique is promising.

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RatSLAM is a vision-based SLAM system based on extended models of the rodent hippocampus. RatSLAM creates environment representations that can be processed by the experience mapping algorithm to produce maps suitable for goal recall. The experience mapping algorithm also allows RatSLAM to map environments many times larger than could be achieved with a one to one correspondence between the map and environment, by reusing the RatSLAM maps to represent multiple sections of the environment. This paper describes experiments investigating the effects of the environment-representation size ratio and visual ambiguity on mapping and goal navigation performance. The experiments demonstrate that system performance is weakly dependent on either parameter in isolation, but strongly dependent on their joint values.

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The outcome of interspecific hybridization between native and invasive species depends on the relative frequencies of parental taxa and viability of hybrid progeny. We investigated individual and population level consequences of hybridization between the Australian native, Senecio pinnatifolius, and the exotic S. madagascariensis, with AFLP markers and used this information to simulate the expected outcome of hybridization.A high frequency (range 8.3-75.6 %) of hybrids was detected in open pollinated seeds of both species, but mature hybrids were absent from sympatric populations indicating that sympatric populations represent tension zones. A hybridization advantage was observed for S. madagascariensis,where significantly more progeny than expected were sired based on proportional representation of the two species in sympatric populations. Simulations indicated S. pinnatifolius could be replaced in sympatric populations if hybridization was density dependent.For this native-exotic pair, prezygotic isolating barriers are weak, but low hybrid viability maintains a strong postzygotic barrier to introgression. Due to asymmetric hybridization, S. pinnatifolius appears under threat from demographic swamping, and local extinction is possible where it occurs in sympatry with S. madagascariensis.

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Children often have difficulties in learning spatial representations. This study investigated the effect of four different instructional formats on learning outcomes and strategies used when dealing with spatial tasks such as assembly procedures. It was hypothesised that instructional material that imposed least extraneous cognitive load would facilitate enhanced learning. Forty secondary students were presented with four types of instruction; orthographic drawing, isometric drawing, physical model and, isometric and physical model together. The findings provide evidence to suggest that working from physical models caused least extraneous cognitive load compared to the isometric and orthographic groups. The model group took less time, had more correctly completed models, required fewer extra looks, spent less time studying the instruction and made fewer errors. Problem decomposition, forward working and attending to information in the foreground of the graphical representation strategies were analysed.

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Nationally, there is much legislation regulating land sale transactions, particularly in relation to seller disclosure of information. The statutes require strict compliance by a seller failing which, in general, a buyer can terminate the contract. In a number of instances, when buyers have sought to exercise these rights, sellers have alleged that buyers have either expressly or by conduct waived their rights to rely upon these statutes. This article examines the nature of these rights in this context, whether they are capable of waiver and, if so, what words or conduct might be sufficient to amount to waiver. The analysis finds that the law is in a very unsatisfactory state, that the operation of those rules that can be identified as having relevance are unevenly applied and concludes that sellers have, in the main, been unsuccessful in defeating buyers' statutory rights as a result of an alleged waiver by those buyers.

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Many traffic situations require drivers to cross or merge into a stream having higher priority. Gap acceptance theory enables us to model such processes to analyse traffic operation. This discussion demonstrated that numerical search fine tuned by statistical analysis can be used to determine the most likely critical gap for a sample of drivers, based on their largest rejected gap and accepted gap. This method shares some common features with the Maximum Likelihood Estimation technique (Troutbeck 1992) but lends itself well to contemporary analysis tools such as spreadsheet and is particularly analytically transparent. This method is considered not to bias estimation of critical gap due to very small rejected gaps or very large rejected gaps. However, it requires a sufficiently large sample that there is reasonable representation of largest rejected gap/accepted gap pairs within a fairly narrow highest likelihood search band.

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The increasing capability of mobile devices and social networks to gather contextual and social data has led to increased interest in context-aware computing for mobile applications. This paper explores ways of reconciling two different viewpoints of context, representational and interactional, that have arisen respectively from technical and social science perspectives on context-aware computing. Through a case study in agile ridesharing, the importance of dynamic context control, historical context and broader context is discussed. We build upon earlier work that has sought to address the divide by further explicating the problem in the mobile context and expanding on the design approaches.