656 resultados para display technology


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This study examines the case of Chinese consumer's intention to adopt the upcoming mobile technology, 3G. The qualitative study involved 45 in-depth intervie3ws undertaken in three major Chemise cities to explore what perceptions, beliefs and attitudes will influence their decisions about adopting 3G. Perceived beliefs about using 3G technology were found to be important determinants. Additionally, there was evidence of influences from their social network that could motivate the adoption behaviour, as well as influence from the secondary information sources, such as the media and the Internet. Finally, some constraints were identifies that may inhibit Chinese consumers' adoption of this technology.

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Insulin-like growth factor binding proteins (IGFBPs) are prime regulators of IGF-action in numerous cell types including the retinal pigment epithelium (RPE). The RPE performs several functions essential for vision, including growth factor secretion and waste removal via a phagocytic process mediated in part by vitronectin (Vn). In the course of studying the effects of IGFBPs on IGF-mediated VEGF secretion and Vn-mediated phagocytosis in the RPE cell line ARPE-19, we have discovered that these cells avidly ingest synthetic microspheres (2.0 μm diameter) coated with IGFBPs. Given the novelty of this finding and the established role for endocytosis in mediating IGFBP actions in other cell types, we have explored the potential role of candidate cell surface receptors. Moreover, we have examined the role of key IGFBP structural motifs, by comparing responses to three members of the IGFBP family (IGFBP-3, IGFBP-4 and IGFBP-5) which display overlapping variations in primary structure and glycosylation status. Coating of microspheres (FluoSpheres®, sulfate modified polystyrene filled with a fluorophore) was conducted at 37 °C for 1 h using 20 μg/mL of test protein, followed by extensive washing. Binding of proteins was confirmed using a microBCA assay. The negative control consisted of microspheres treated with 0.1% bovine serum albumin (BSA), and all test samples were post-treated with BSA in an effort to coat any remaining free protein binding sites, which might otherwise encourage non-specific interactions with the cell surface. Serum-starved cultures of ARPE-19 cells were incubated with microspheres for 24 h, using a ratio of approximately 100 microspheres per cell. Uptake of microspheres was quantified using a fluorometer and was confirmed visually by confocal fluorescence microscopy. The ARPE-19 cells displayed little affinity for BSA-treated microspheres, but avidly ingested large quantities of those pre-treated with Vn (ANOVA; p < 0.001). Strong responses were also observed towards recombinant formulations of non-glycosylated IGFBP-3, glycosylated IGFBP-3 and glycosylated IGFBP-5 (all p < 0.001), while glycosylated IGFBP-4 induced a relatively minor response (p < 0.05). The response to IGFBP-3 was unaffected in the presence of excess soluble IGFBP-3, IGF-I or Vn. Likewise, soluble IGFBP-3 did not induce uptake of BSA-treated microspheres. Antibodies to either the transferrin receptor or type 1 IGF-receptor displayed slight inhibitory effects on responses to IGFBPs and Vn. Heparin abolished responses to Vn, IGFBP-5 and non-glycosylated IGFBP-3, but only partially inhibited the response to glycosylated IGFBP-3. Our results demonstrate for the first time IGFBP-mediated endocytosis in ARPE-19 cells and suggest roles for the IGFBP-heparin-binding domain and glycosylation status. These findings have important implications for understanding the mechanisms of IGFBP actions on the RPE, and in particular suggest a role for IGFBP-endocytosis.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

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Bridges are an important part of society's infrastructure and reliable methods are necessary to monitor them and ensure their safety and efficiency. Bridges deteriorate with age and early detection of damage helps in prolonging the lives and prevent catastrophic failures. Most bridges still in used today were built decades ago and are now subjected to changes in load patterns, which can cause localized distress and if not corrected can result in bridge failure. In the past, monitoring of structures was usually done by means of visual inspection and tapping of the structures using a small hammer. Recent advancements of sensors and information technologies have resulted in new ways of monitoring the performance of structures. This paper briefly describes the current technologies used in bridge structures condition monitoring with its prime focus in the application of acoustic emission (AE) technology in the monitoring of bridge structures and its challenges.

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While a range of benefits to students participating in mooting have been identified by the legal education literature, there are impediments to students participating in mooting that have been revealed by recent surveys of law students at QUT. These impediments include time, geographical location and a failure to perceive the benefits of mooting. This paper will explore the benefits of using technology to overcome these impediments, evaluate technological options to facilitate distance mooting, such as the use of Second Life, Elluminate and video conferencing, and will recommend a trial of these options.

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This paper explores the philosophical origins of appropriation of Information Systems (IS) using Marxian and other socio-cultural theory. It provides an in-depth examination of appropriation and its application in extant IS theory. We develop a three-tier model using Marx’s foundational concepts and from this generate four propositions that we test in an empirical example of IS in anesthesia. Using Marxian theory, this paper seeks common ground among existing theories of technology appropriation in IS research. This work contributes to IS research by (1) opening philosophical discussions on appropriation and the human ↔ technology nexus, (2) drawing on these varying perspectives to propose a general conceptualization of technology appropriation and (3) providing a starting point towards a general causal model of technology appropriation.

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The mol­ecules of the title compound, C16H16O2, display an intra­molecular O—HO hydrogen bond between the hydroxyl donor and the ketone acceptor. Inter­molecular C—Hπ inter­actions connect adjacent mol­ecules into chains that propagate parallel to the ac diagonal. The chains are arranged in sheets, and mol­ecules in adjacent sheets inter­act via inter­molecular O—HO hydrogen bonds.

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In this paper, technology is described as involving processes whereby resources are utilised to satisfy human needs or to take advantage of opportunities, to develop practical solutions to problems. This study, set within one type of technology context, information technology, investigated how, through a one semester undergraduate university course, elements of technological processes were made explicit to students. While it was acknowledged in the development and implementation of this course that students needed to learn technical skills, technological skills and knowledge, including design, were seen as vital also, to enable students to think about information technology from a perspective that was not confined and limited to `technology as hardware and software'. This paper describes how the course, set within a three year program of study, was aimed at helping students to develop their thinking and their knowledge about design processes in an explicit way. An interpretive research approach was used and data sources included a repertory grid `survey'; student interviews; video recordings of classroom interactions, audio recordings of lectures, observations of classroom interactions made by researchers; and artefacts which included students' journals and portfolios. The development of students' knowledge about design practices is discussed and reflections upon student knowledge development in conjunction with their learning experiences are made. Implications for ensuring explicitness of design practice within information technology contexts are presented, and the need to identify what constitutes design knowledge is argued.