653 resultados para multi-theoretical


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Contemporary cities no longer offer the same types of permanent environments that we planned for in the latter part of the twentieth century. Our public spaces are increasingly temporary, transient, and ephemeral. The theories, principles and tactics with which we designed these spaces in the past are no longer appropriate. We need a new theory for understanding the creation, use, and reuse of temporary public space. Moe than a theory, we need new architectural tactics or strategies that can be reliably employed to create successful temporary public spaces. This paper will present ongoing research that starts that process through critical review and technical analysis of existing and historic temporary public spaces. Through the analysis of a number of public spaces, that were either designed for temporary use or became temporary through changing social conditions, this research identifies the tactics and heuristics used in such projects. These tactics and heuristics are then analysed to extract some broader principles for the design of temporary public space. The theories of time related building layers, a model of environmental sustainability, and the recycling of social meaning, are all explored. The paper will go on to identify a number of key questions that need to be explored and addressed by a theory for such developments: How can we retain social meaning in the fabric of the city and its public spaces while we disassemble it and recycle it into new purposes? What role will preservation have in the rapidly changing future; will exemplary temporary spaces be preserved and thereby become no longer temporary? Does the environmental advantage of recycling materials, components and spaces outweigh the removal or social loss of temporary public space? This research starts to identify the knowledge gaps and proposes a number of strategies for making public space in the age of temporary, recyclable, and repurposing of our urban infrastructure; a way of creating lighter, cheaper, quicker, and temporary interventions.

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Information Technology (IT) value is amongst the most important concepts in the Information Systems (IS) research field. Yet, a clear, well-formulated conceptualization of IT value, cumulatively built upon, is lacking. Drawing from the Facet Theory literature, this paper broaches several meta-theoretical considerations addressing an “ideal” conceptualization of IT value. We argue these considerations may shed light on the advancement of IT value conceptualization methodology.

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This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

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High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

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This paper presents a new approach to web browsing in situ- ations where the user can only provide the device with a sin- gle input command device (switch). Switches have been de- veloped for example for people with locked-in syndrome and are used in combination with scanning to navigate virtual keyboards and desktop interfaces. Our proposed approach leverages the hierarchical structure of webpages to operate a multi-level scan of actionable elements of webpages (links or form elements). As there are a few methods already exist- ing to facilitate browsing under these conditions, we present a theoretical usability evaluation of our approach in com- parison to the existing ones, which takes into account the average time taken to reach any part of a web page (such as a link or a form) but also the number of clicks necessary to reach the goal. We argue that these factors contribute together to usability. In addition, we propose that our ap- proach presents additional usability benefits.

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This paper presents a performance-based optimisation approach for conducting trade-off analysis between safety (roads) and condition (bridges and roads). Safety was based on potential for improvement (PFI). Road condition was based on surface distresses and bridge condition was based on apparent age per subcomponent. The analysis uses a non-monetised optimisation that expanded upon classical Pareto optimality by observing performance across time. It was found that achievement of good results was conditioned by the availability of early age treatments and impacted by a frontier effect preventing the optimisation algorithm from realising of the long-term benefits of deploying actions when approaching the end of the analysis period. A disaggregated bridge condition index proved capable of improving levels of service in bridge subcomponents.

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Non-rigid image registration is an essential tool required for overcoming the inherent local anatomical variations that exist between images acquired from different individuals or atlases. Furthermore, certain applications require this type of registration to operate across images acquired from different imaging modalities. One popular local approach for estimating this registration is a block matching procedure utilising the mutual information criterion. However, previous block matching procedures generate a sparse deformation field containing displacement estimates at uniformly spaced locations. This neglects to make use of the evidence that block matching results are dependent on the amount of local information content. This paper presents a solution to this drawback by proposing the use of a Reversible Jump Markov Chain Monte Carlo statistical procedure to optimally select grid points of interest. Three different methods are then compared to propagate the estimated sparse deformation field to the entire image including a thin-plate spline warp, Gaussian convolution, and a hybrid fluid technique. Results show that non-rigid registration can be improved by using the proposed algorithm to optimally select grid points of interest.

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Students explored variation and expectation in a probability activity at the end of the first year of a 3-year longitudinal study across grades 4-6. The activity involved experiments in tossing coins both manually and with simulation using the graphing software, TinkerPlots. Initial responses indicated that the students were aware of uncertainty, although an understanding of chance concepts appeared limited. Predicting outcomes of 10 tosses reflected an intuitive notion of equiprobability, with little awareness of variation. Understanding the relationship between experimental and theoretical probability did not emerge until multiple outcomes and representations were generated with the software.

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Successful management of design changes is critical for the efficient delivery of construction projects. Building Information Modeling (BIM) is envisioned to play an important role in integrating design, construction and facility management processes through coordinated changes throughout the project life-cycle. BIM currently provides significant benefits in coordinating changes across different views in a single model, and identifying conflicts between different discipline-specific models. However, current BIM tools provide limited support in managing changes across several discipline-specific models. This paper describes an approach to represent, coordinate, and track changes within a collaborative multi-disciplinary BIM environment. This approach was informed by a detailed case study of a large, complex, fast-tracked BIM project where we investigated numerous design changes, analyzed change management processes, and evaluated existing BIM tools. Our approach characterises design changes in an ontology to represent changed component attributes, dependencies between components, and change impacts. It explores different types of dependencies amongst different design changes and describes how a graph based approach and dependency matrix could assist with automating the propagation and impact of changes in a BIM-based project delivery process.