757 resultados para cloud computing accountability


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This research studied distributed computing of all-to-all comparison problems with big data sets. The thesis formalised the problem, and developed a high-performance and scalable computing framework with a programming model, data distribution strategies and task scheduling policies to solve the problem. The study considered storage usage, data locality and load balancing for performance improvement in solving the problem. The research outcomes can be applied in bioinformatics, biometrics and data mining and other domains in which all-to-all comparisons are a typical computing pattern.

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This article argues that an indigenous approach to communication research allows us to re-think academic approaches of engaging in and evaluating participatory communication research. It takes as its case study the Komuniti Tok Piksa project undertaken in the Highlands of Papua New Guinea. The project explores ways in which visual methods when paired with a community action approach embedded within an indigenous framework can be used to facilitate social change through meaningful participation. It involves communities to narrate their experiences in regard to HIV and AIDS and assists them in designing and recording their own messages. Local researchers are trained in using visual tools to facilitate this engagement with the communities.

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Location management problem that arise in mobile computing networks is addressed. One method used in location management is to designate sonic of the cells in the network as "reporting cells". The other cells in the network are "non-reporting cells". Finding an optimal set of reporting cells (or reporting cell configuration) for a given network. is a difficult combinatorial optimization problem. In fact this is shown to be an NP-complete problem. in an earlier study. In this paper, we use the selective paging strategy and use an ant colony optimization method to obtain the best/optimal set of reporting cells for a given a network.

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The advent of cloud technology involving low subscription overheads cost has provided small and medium-sized enterprises (SMEs) with the opportunity to adopt new cloud-based corporate-wide systems (i.e., cloud ERP). This technology, operating through subscription-based services, has now provided SMEs with a complete range of IT applications that were once restricted to larger organisations. As anecdotal evidences suggest, SMEs are increasingly adopting cloud-based ERP software. The selection of an ERP is a complex process involving multiple stages and stakeholders, suggesting the importance of closer examination of cloud ERP adoption in SMEs. Yet, prior studies have predominantly treated technology adoption as a single activity and largely ignored the issue of ERP adoption in SMEs. Understanding of the process nature of the adoption and the factors that are important in each stage of the adoption potentially may result in guiding SMEs to make well-informed decisions throughout the ERP selection process. Thus, our study proposes that the adoption of cloud ERP should be examined as a multi-stage process. Using the Theory of Planned Behaviour (TPB) and Ettlie’s adoption stages, as well as employing data gathered from 162 owners of SMEs, our findings show that the factors that influence the intention to adopt cloud ERP vary significantly across adoptive stages.

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Minimum Description Length (MDL) is an information-theoretic principle that can be used for model selection and other statistical inference tasks. There are various ways to use the principle in practice. One theoretically valid way is to use the normalized maximum likelihood (NML) criterion. Due to computational difficulties, this approach has not been used very often. This thesis presents efficient floating-point algorithms that make it possible to compute the NML for multinomial, Naive Bayes and Bayesian forest models. None of the presented algorithms rely on asymptotic analysis and with the first two model classes we also discuss how to compute exact rational number solutions.

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Ubiquitous computing is about making computers and computerized artefacts a pervasive part of our everyday lifes, bringing more and more activities into the realm of information. The computationalization, informationalization of everyday activities increases not only our reach, efficiency and capabilities but also the amount and kinds of data gathered about us and our activities. In this thesis, I explore how information systems can be constructed so that they handle this personal data in a reasonable manner. The thesis provides two kinds of results: on one hand, tools and methods for both the construction as well as the evaluation of ubiquitous and mobile systems---on the other hand an evaluation of the privacy aspects of a ubiquitous social awareness system. The work emphasises real-world experiments as the most important way to study privacy. Additionally, the state of current information systems as regards data protection is studied. The tools and methods in this thesis consist of three distinct contributions. An algorithm for locationing in cellular networks is proposed that does not require the location information to be revealed beyond the user's terminal. A prototyping platform for the creation of context-aware ubiquitous applications called ContextPhone is described and released as open source. Finally, a set of methodological findings for the use of smartphones in social scientific field research is reported. A central contribution of this thesis are the pragmatic tools that allow other researchers to carry out experiments. The evaluation of the ubiquitous social awareness application ContextContacts covers both the usage of the system in general as well as an analysis of privacy implications. The usage of the system is analyzed in the light of how users make inferences of others based on real-time contextual cues mediated by the system, based on several long-term field studies. The analysis of privacy implications draws together the social psychological theory of self-presentation and research in privacy for ubiquitous computing, deriving a set of design guidelines for such systems. The main findings from these studies can be summarized as follows: The fact that ubiquitous computing systems gather more data about users can be used to not only study the use of such systems in an effort to create better systems but in general to study phenomena previously unstudied, such as the dynamic change of social networks. Systems that let people create new ways of presenting themselves to others can be fun for the users---but the self-presentation requires several thoughtful design decisions that allow the manipulation of the image mediated by the system. Finally, the growing amount of computational resources available to the users can be used to allow them to use the data themselves, rather than just being passive subjects of data gathering.

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Media reportage often act as interpretations of accountability policies thereby making the news media a part of the policy enactment process. Within such a process, their role is that of policy reinforcement rather than policy construction or contestation. This paper draws on the experiences of school leaders in regional Queensland, Australia, and their perceptions of the media frames that are used to report on accountability using school performance. The notion of accountability is theorised in terms of media understandings of ‘holding power to account’, and forms the theoretical framework for this study. The methodological considerations both contextualise aspects of the schools involved in the study, and outline how ‘framing theory’ was used to analyse the data. The paper draws on a number of participant experiences and newspaper accounts of schools to identify the frames that are used by the press when reporting on school performance. Three frames referring to school performance are discussed in this paper: those that rank performance such as league tables; frames that decontextualise performance isolating it from school circumstances and levels of funding; and frames that residualise government schools.

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Stochastic volatility models are of fundamental importance to the pricing of derivatives. One of the most commonly used models of stochastic volatility is the Heston Model in which the price and volatility of an asset evolve as a pair of coupled stochastic differential equations. The computation of asset prices and volatilities involves the simulation of many sample trajectories with conditioning. The problem is treated using the method of particle filtering. While the simulation of a shower of particles is computationally expensive, each particle behaves independently making such simulations ideal for massively parallel heterogeneous computing platforms. In this paper, we present our portable Opencl implementation of the Heston model and discuss its performance and efficiency characteristics on a range of architectures including Intel cpus, Nvidia gpus, and Intel Many-Integrated-Core (mic) accelerators.

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As technology continues to become more accessible, miniaturised and diffused into the environment, the potential of wearable technology to impact our lives in significant ways becomes increasingly viable. Wearables afford unique interaction, communication and functional capabilities between users, their environment as well as access to information and digital data. Wearables also demand an inter-disciplinary approach and, depending on the purpose, can be fashioned to transcend cultural, national and spatial boundaries. This paper presents the Cloud Workshop project based on the theme of ‘Wearables and Wellbeing; Enriching connections between citizens in the Asia-Pacific region’, initiated through a cooperative partnership between Queensland University of Technology (QUT), Hong Kong Baptist University (HKBU) and Griffith University (GU). The project was unique due to its inter-disciplinary, inter-cultural and inter-national scope that occurred simultaneously between Australia and Hong Kong.

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Among the iterative schemes for computing the Moore — Penrose inverse of a woll-conditioned matrix, only those which have an order of convergence three or two are computationally efficient. A Fortran programme for these schemes is provided.

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Abstract is not available.

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Despite the rhetoric of schools serving the needs of specific communities, it is evident that the work of teachers and principals is shaped by government imperatives to demonstrate success according to a set of standard ‘benchmarks’. In this chapter, we draw from our current study of new forms of educational leadership emerging in South Australian public primary schools to explore the ways in which test-based accountability requirements are being mediated by principals in schools that serve high poverty communities. Taking an institutional ethnography approach we focus on the everyday work of a principal and a literacy leader in one suburban primary school to show the complexity of the impact of national testing on practices of literacy leadership. We elaborate on the inescapable textual framings and tasks faced by the principal and literacy leader, and those that they create and modify – such as a common literacy agreement and ‘literacy chats’ between a literacy leader and classroom teacher – in order to ‘hold on to ethics’. We argue that while leaders’ and teachers’ everyday work is regulated by ‘ruling relations’ (Smith, 1999), it is also organic and responsive to the local context. We conclude with a reflection on the important situated work that school leaders do in mediating trans-local policies that might otherwise close down possibilities for engaging ethically with students and their learning in a particular school.

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A rank-augmnented LU-algorithm is suggested for computing a generalized inverse of a matrix. Initially suitable diagonal corrections are introduced in (the symmetrized form of) the given matrix to facilitate decomposition; a backward-correction scheme then yields a desired generalized inverse.