8 resultados para Bicycle Paths.

em University of Queensland eSpace - Australia


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Two studies investigated how both degree of identification and the individual's position within the group influence aspects of group loyalty. The authors considered ingroup position in terms of both the individual's current position within a group and expectations concerning the likelihood that one's position might change., in the future. Peripheral group members learned that their acceptance by other group members would improve in the future or that they could expect rejection by other group members. Various indices of group loyalty (ingroup homogeneity, motivation to work for the group, and evaluation of a motivated group member) showed that when group members anticipated future rejection, the lower the identification the less loyal they were. In contrast, those who expected future acceptance were more loyal (more motivated to work for the group) the lower their identification. Current group behavior depends on both intragroup future expectations and level of identification.

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Over the last decade, the international business literature has placed ever-greater emphasis on the role that learning and innovation play in determining multinational and multinational subsidiary performance. The present research seeks to understand the organizational paths leading to such desirable outcomes as greater learning, increased innovation and improved performance. Using a model tested with data collected through a survey of managers in subsidiaries of multinational firms, we find dual, independent paths to improved performance - one through networking and inter-unit learning and the other through subsidiary autonomy and innovation. A particular feature of these findings is that they can be shown to be robust after controlling for a wide range of environmental pressures and firm and industry factors. However, in the absence of environmental controls the dual path finding is rejected. These conflicting findings support the imperative to test models that include a diverse range of environmental pressures so that the true effects of organizational factors on learning, innovation and performance can be identified.

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Single shortest path extraction algorithms have been used in a number of areas such as network flow and image analysis. In image analysis, shortest path techniques can be used for object boundary detection, crack detection, or stereo disparity estimation. Sometimes one needs to find multiple paths as opposed to a single path in a network or an image where the paths must satisfy certain constraints. In this paper, we propose a new algorithm to extract multiple paths simultaneously within an image using a constrained expanded trellis (CET) for feature extraction and object segmentation. We also give a number of application examples for our multiple paths extraction algorithm.

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In this paper we propose a range of dynamic data envelopment analysis (DEA) models which allow information on costs of adjustment to be incorporated into the DEA framework. We first specify a basic dynamic DEA model predicated on a number or simplifying assumptions. We then outline a number of extensions to this model to accommodate asymmetric adjustment costs, non-static output quantities, non-static input prices, and non-static costs of adjustment, technological change, quasi-fixed inputs and investment budget constraints. The new dynamic DEA models provide valuable extra information relative to the standard static DEA models-they identify an optimal path of adjustment for the input quantities, and provide a measure of the potential cost savings that result from recognising the costs of adjusting input quantities towards the optimal point. The new models are illustrated using data relating to a chain of 35 retail department stores in Chile. The empirical results illustrate the wealth of information that can be derived from these models, and clearly show that static models overstate potential cost savings when adjustment costs are non-zero.

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Timinganalysis of assembler code is essential to achieve the strongest possible guarantee of correctness for safety-critical, real-time software. Previous work has shown how timingconstrain ts on controlflow paths through high-level language programs can be formalised using the semantics of the statements comprisingthe path. We extend these results to assembler-level code where it becomes possible to not only determine timingconstrain ts, but also to verify them against the known execution times for each instruction. A minimal formal model is developed with both a weakest liberal precondition and a strongest postcondition semantics. However, despite the formalism’s simplicity, it is shown that complex timingb ehaviour associated with instruction pipeliningand iterative code can be modelled accurately.

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A program can be decomposed into a set of possible execution paths. These can be described in terms of primitives such as assignments, assumptions and coercions, and composition operators such as sequential composition and nondeterministic choice as well as finitely or infinitely iterated sequential composition. Some of these paths cannot possibly be followed (they are dead or infeasible), and they may or may not terminate. Decomposing programs into paths provides a foundation for analyzing properties of programs. Our motivation is timing constraint analysis of real-time programs, but the same techniques can be applied in other areas such as program testing. In general the set of execution paths for a program is infinite. For timing analysis we would like to decompose a program into a finite set of subpaths that covers all possible execution paths, in the sense that we only have to analyze the subpaths in order to determine suitable timing constraints that cover all execution paths.