606 resultados para technology acceptance model (TAM)


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This paper proposes a new multi-resource multi-stage mine production timetabling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints are considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times; equipment-assignment-dependent operational times; etc. The model also provides the availability and usage of equipment units at multiple operational stages such as drilling, blasting and excavating stages. The problem is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level.

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Purpose This paper aims to use the Model of Goal-Directed Behavior (MGB) to examine the factors affecting consumers’ continued use of emerging technology-based self-services (TBSSs) with credence qualities. Professional services, which traditionally require specialized knowledge and high levels of interpersonal interaction to produce owing to their credence qualities, are increasingly delivered via self-service technologies. Health services delivered via mobile devices, for example, facilitate self-care without direct involvement from health professionals. Design/methodology/approach A mental health service delivered via the Internet and mobile phone, myCompass, was selected as the research context. Twenty interviews were conducted with users of myCompass and the data were thematically analyzed. Findings The findings of the study showcase the unique determinants of consumers’ continued use of TBSSs with credence qualities relative to the more routine services which have been the focus of extant research. The findings further provide support for the utility of the MGB in explaining service continuance, although the importance of distinguishing between extrinsic and intrinsic motivational components of behavioral desire and capturing the impact of social influence beyond subjective norms is also highlighted. Originality/value This study contributes to recent research examining differences in consumer responses across TBSSs and behavioral loyalty to these services. It also provides empirical evidence for broadening and deepening the MGB within this behavioral domain.

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Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.

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Changes to the redox status of biological systems have been implicated in the pathogenesis of a wide variety of disorders including cancer, Ischemia-reperfusion (I/R) injury and neurodegeneration. In times of metabolic stress e.g. ischaemia/reperfusion, reactive oxygen species (ROS) production overwhelms the intrinsic antioxidant capacity of the cell, damaging vital cellular components. The ability to quantify ROS changes in vivo, is therefore essential to understanding their biological role. Here we evaluate the suitability of a novel reversible profluorescent probe containing a redox-sensitive nitroxide moiety (methyl ester tetraethylrhodamine nitroxide, ME-TRN), as an in vivo, real-time reporter of retinal oxidative status. The reversible nature of the probe's response offers the unique advantage of being able to monitor redox changes in both oxidizing and reducing directions in real time. After intravitreal administration of the ME-TRN probe, we induced ROS production in rat retina using an established model of complete, acute retinal ischaemia followed by reperfusion. After restoration of blood flow, retinas were imaged using a Micron III rodent fundus fluorescence imaging system, to quantify the redox-response of the probe. Fluorescent intensity declined during the first 60 min of reperfusion. The ROS-induced change in probe fluorescence was ameliorated with the retinal antioxidant, lutein. Fluorescence intensity in non-Ischemia eyes did not change significantly. This new probe and imaging technology provide a reversible and real-time response to oxidative changes and may allow the in vivo testing of antioxidant therapies of potential benefit to a range of diseases linked to oxidative stress

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Nondeclarative memory and novelty processing in the brain is an actively studied field of neuroscience, and reducing neural activity with repetition of a stimulus (repetition suppression) is a commonly observed phenomenon. Recent findings of an opposite trend specifically, rising activity for unfamiliar stimuli—question the generality of repetition suppression and stir debate over the underlying neural mechanisms. This letter introduces a theory and computational model that extend existing theories and suggests that both trends are, in principle, the rising and falling parts of an inverted U-shaped dependence of activity with respect to stimulus novelty that may naturally emerge in a neural network with Hebbian learning and lateral inhibition. We further demonstrate that the proposed model is sufficient for the simulation of dissociable forms of repetition priming using real-world stimuli. The results of our simulation also suggest that the novelty of stimuli used in neuroscientific research must be assessed in a particularly cautious way. The potential importance of the inverted-U in stimulus processing and its relationship to the acquisition of knowledge and competencies in humans is also discussed

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A holistic consideration of innovation and associated activities is still very new to consulting engineering firms. This research will have benefits for both industry and academia. The final outcome of this research is a prioritised decision making innovation model that can be used by consulting engineering firms to make informed decisions by investing in appropriate innovation activities that positively impact project performance. This helps by using an informed approach towards investing rather than 'hit-and-miss' trialling.

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This thesis provides two main contributions. The first one is BP-TRBAC, a unified authorisation model that can support legacy systems as well as business process systems. BP-TRBAC supports specific features that are required by business process environments. BP-TRBAC is designed to be used as an independent enterprise-wide authorisation model, rather than having it as part of the workflow system. It is designed to be the main authorisation model for an organisation. The second contribution is BP-XACML, an authorisation policy language that is designed to represent BPM authorisation policies for business processes. The contribution also includes a policy model for BP-XACML. Using BP-TRBAC as an authorisation model together with BP-XACML as an authorisation policy language will allow an organisation to manage and control authorisation requests from workflow systems and other legacy systems.

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An important uncertainty when estimating per capita consumption of, for example, illicit drugs by means of wastewater analysis (sometimes referred to as “sewage epidemiology”) relates to the size and variability of the de facto population in the catchment of interest. In the absence of a day-specific direct population count any indirect surrogate model to estimate population size lacks a standard to assess associated uncertainties. Therefore, the objective of this study was to collect wastewater samples at a unique opportunity, that is, on a census day, as a basis for a model to estimate the number of people contributing to a given wastewater sample. Mass loads for a wide range of pharmaceuticals and personal care products were quantified in influents of ten sewage treatment plants (STP) serving populations ranging from approximately 3500 to 500 000 people. Separate linear models for population size were estimated with the mass loads of the different chemical as the explanatory variable: 14 chemicals showed good, linear relationships, with highest correlations for acesulfame and gabapentin. De facto population was then estimated through Bayesian inference, by updating the population size provided by STP staff (prior knowledge) with measured chemical mass loads. Cross validation showed that large populations can be estimated fairly accurately with a few chemical mass loads quantified from 24-h composite samples. In contrast, the prior knowledge for small population sizes cannot be improved substantially despite the information of multiple chemical mass loads. In the future, observations other than chemical mass loads may improve this deficit, since Bayesian inference allows including any kind of information relating to population size.

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This paper presents a literature review and indicative findings that are part of ongoing research into aging and technology. The review finds that research on older technology users has contributed valuable information on the impact of age-related changes on technology use, as well as older adults’ acceptance and adoption of contemporary technologies. However, the majority of the research has been conducted from the perspective of age-related differences in use and performance, or it is medically-focused, examining the potential of technology to improve an individual’s quality of life (QoL), for example. Research on older people and technology does not adequately address the integration of technology into the everyday lives of older people. This paper identifies that there is substantial opportunity to examine older users’ everyday information and communication technology (ICT) use, and to inform technology design beyond measures of performance, usability and adoption.

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Similar to most other creative industries, the evolution of the music industry is heavily shaped by media technologies. This was equally true in 1999, when the global recorded music industry had experienced two decades of continuous growth largely driven by the rapid transition from vinyl records to Compact Discs. The transition encouraged avid music listeners to purchase much of their music collections all over again in order to listen to their favourite music with ‘digital sound’. As a consequence of this successful product innovation, recorded music sales (unit measure) more than doubled between the early 1980s and the end of the 1990s. It was with this backdrop that the first peer-to-peer file sharing service was developed and released to the mainstream music market in 1999 by the college student Shawn Fanning. The service was named Napster and it marks the beginning of an era that is now a classic example of how an innovation is able to disrupt an entire industry and make large swathes of existing industry competences obsolete. File sharing services such as Napster, followed by a range of similar services in its path, reduced physical unit sales in the music industry to levels that had not been seen since the 1970s. The severe impact of the internet on physical sales shocked many music industry executives who spent much of the 2000s vigorously trying to reverse the decline and make the disruptive technologies go away. At the end, they learned that their efforts were to no avail and the impact on the music industry proved to be transformative, irreversible and, to many music industry professionals, also devastating. Thousands of people lost their livelihood, large and small music companies have folded or been forced into mergers or acquisitions. But as always during periods of disruption, the past 15 years have also been very innovative, spurring a plethora of new music business models. These new business models have mainly emerged outside the music industry and the innovators have been often been required to be both persuasive and persistent in order to get acceptance from the risk-averse and cash-poor music industry establishment. Apple was one such change agent that in 2003 was the first company to open up a functioning and legal market for online music. iTunes Music Store was the first online retail outlet that was able to offer the music catalogues from all the major music companies; it used an entirely novel pricing model, and it allowed consumers to de-bundle the music album and only buy the songs that they actually liked. Songs had previously been bundled by physical necessity as discs or cassettes, but with iTunes Music Store, the institutionalized album bundle slowly started to fall apart. The consequences had an immediate impact on music retailing and within just a few years, many brick and mortar record stores were forced out of business in markets across the world. The transformation also had disruptive consequences beyond music retailing and redefined music companies’ organizational structures, work processes and routines, as well as professional roles. iTunes Music Store in one sense was a disruptive innovation, but it was at the same time relatively incremental, since the major labels’ positions and power structures remained largely unscathed. The rights holders still controlled their intellectual properties and the structures that guided the royalties paid per song that was sold were predictable, transparent and in line with established music industry practices.

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This article presents a ‘knowledge ecosystem’ model of how early career academics experience using information to learn while building their social networks for developmental purposes. Developed using grounded theory methodology, the model offers a way of conceptualising how to empower early career academics through 1) agency (individual and relational) and 2) facilitation of personalised informal learning (design of physical and virtual systems and environments) in spaces where developmental relationships are formed including programs, courses, events, community, home and social media. It is suggested that the knowledge ecosystem model is suitable for use in designing informal learning experiences for early career academics.

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This paper is a qualitative, practice based study describing the use of the Focus-Action-Reflection (FAR) Guide (Harrison and Treagust, 2000) to address the shortcomings of a pedagogical analogical model in Year 10 Science. The aim of this paper is to present my experience of the FAR Guide in relation to an analogical model that gave rise to perceived shortcomings by both teachers and students. This study found the FAR Guide to be a highly valuable tool, transforming the presentation of the analogical model, and enabling students to develop a deeper understanding of the nature of scientific knowledge.

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Through both theory and practice, this practice-based research develops and tests the idea that courtyard housing can deliver sustainable, compact housing in rapidly growing subtropical cities. It proposes a contemporary urban design model that incorporates urban design courtyard housing prototypes. These prototypes can be further developed by architects and urban designers for similar climatic conditions across the world.

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This work is focused on the player experience and the design of artificial intelligence (AI) to meet player expectations in a competitive video game context. The original contribution of this research is a new approach to designing games and AI opponents that are more enjoyable for players to interact with, particularly in First Person Shooter (FPS) video games. This approach is modeled in detail and implemented in a prototype game AI called ThreatBot. The results show that the new AI design is more enjoyable to compete against, particularly with regards to player's perceived levels of competence.

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The article describes a generalized estimating equations approach that was used to investigate the impact of technology on vessel performance in a trawl fishery during 1988-96, while accounting for spatial and temporal correlations in the catch-effort data. Robust estimation of parameters in the presence of several levels of clustering depended more on the choice of cluster definition than on the choice of correlation structure within the cluster. Models with smaller cluster sizes produced stable results, while models with larger cluster sizes, that may have had complex within-cluster correlation structures and that had within-cluster covariates, produced estimates sensitive to the correlation structure. The preferred model arising from this dataset assumed that catches from a vessel were correlated in the same years and the same areas, but independent in different years and areas. The model that assumed catches from a vessel were correlated in all years and areas, equivalent to a random effects term for vessel, produced spurious results. This was an unexpected finding that highlighted the need to adopt a systematic strategy for modelling. The article proposes a modelling strategy of selecting the best cluster definition first, and the working correlation structure (within clusters) second. The article discusses the selection and interpretation of the model in the light of background knowledge of the data and utility of the model, and the potential for this modelling approach to apply in similar statistical situations.