925 resultados para FRACTAL DIMENSION
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An alternative explanation for the modes of failure of large scale failures of open pit walls to those of classical slope stability theory is proposed that makes use of the concept of a transition zone, which is described by a modified Prandtls prism.
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It is widely recognised that the effective application of logistics and supply chain management (SCM) has a vital role to play in European economic recovery. Experience suggests that success in achieving higher levels of supply chain integration (SCI) depends on both physical and technical components (the hard-wiring), as well as human and behavioural components (the soft-wiring). There is significant evidence that the latter has been largely neglected by the logistics and SCM community. Furthermore, it appears that the majority of supply chain improvement initiatives by practitioners have been primarily concerned with technological, structural and process issues. This chapter argues that the difficulties often encountered in attempting to put logistics and SCM theory into practice are largely a consequence of a lack of focus and understanding of the people dimension. Based on this discussion, it offers some suggestions for improvement in this area to supply chain professionals.
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This article deals with a number of supply chain management (SCM) issues: SCM’s “Big Idea” – integration, Divergence of Theory and Practice - the limitations of “hard-wiring”, The “Human Chain”, The Way Forward – asking the right question?
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Aaker's (1997) brand personality framework has become influential across many streams of brand personality research, but it fails to capture an important dimension that reflects consumer's anxious feelings towards brands. Consumers are increasingly evaluating brands through expressions of negative emotive language. For example, the BP oil spillage in the Gulf of Mexico stimulated negative emotions among consumers. This paper is the first to thoroughly incorporate a brand personality dimension reflective of consumer anxious tense and frustrated feelings towards brands. From the extant literature we propose and define negative brand personality. Four adjacent studies were conducted to explore, purify and refine in what form negative brand personality traits exist among consumers. This paper concludes with a conceptual model detailing the antecedent constructs to negative brand personality and behavioral consequences. © 2012.
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* The authors thank the “Swiss National Science Foundation” for its support.
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The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.
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We report an empirical analysis of long-range dependence in the returns of eight stock market indices, using the Rescaled Range Analysis (RRA) to estimate the Hurst exponent. Monte Carlo and bootstrap simulations are used to construct critical values for the null hypothesis of no long-range dependence. The issue of disentangling short-range and long-range dependence is examined. Pre-filtering by fitting a (short-range) autoregressive model eliminates part of the long-range dependence when the latter is present, while failure to pre-filter leaves open the possibility of conflating short-range and long-range dependence. There is a strong evidence of long-range dependence for the small central European Czech stock market index PX-glob, and a weaker evidence for two smaller western European stock market indices, MSE (Spain) and SWX (Switzerland). There is little or no evidence of long-range dependence for the other five indices, including those with the largest capitalizations among those considered, DJIA (US) and FTSE350 (UK). These results are generally consistent with prior expectations concerning the relative efficiency of the stock markets examined. © 2011 Elsevier Inc.
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Mathematics Subject Classification: 44A05, 46F12, 28A78
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Often the designer of ROLAP applications follows up with the question “can I create a little joiner table with just the two dimension keys and then connect that table to the fact table?” In a classic dimensional model there are two options - (a) both dimensions are modeled independently or (b) two dimensions are combined into a super-dimension with a single key. The second approach is not widely used in ROLAP environments but it is an important sparsity handling method in MOLAP systems. In ROLAP this design technique can also bring storage and performance benefits, although the model becomes more complicated. The dependency between dimensions is a key factor that the designers have to consider when choosing between the two options. In this paper we present the results of our storage and performance experiments over a real life data cubes in reference to these design approaches. Some conclusions are drawn.
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2002 Mathematics Subject Classification: 62J05, 62G35.
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2002 Mathematics Subject Classification: 35L40
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2000 Mathematics Subject Classification: 68T01, 62H30, 32C09.