Concept-based retrieval of object-oriented class components for software reuse.

Having identified software components which are potentially reusable and described in such a way that anyone wish to reuse them would be able to do so, the problem arises as to how to organize the total collection of all such components and related descriptions. A good system classification not only provides the basis for cataloging the components, but also provides a means for finding a particular candidate held in the reuse library. This thesis describes a methodology of classifying, structuring and retrieving object-oriented classes based on a method for data analysis called Formal Concept Analysis (FCA). In this methodology, a class is classified and retrieved using the type information plus variable access behavior of methods (in short, composite type) available in the class, and a class library is then viewed as a many-valued context. This many-valued context is transformed into a one-valued context, incorporating behavior of methods into the context via conceptual scaling, and Ganter\u27s concept-generation algorithm is applied to this context, which leads to a lattice structure of all concepts. (Abstract shortened by UMI.) Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .S54. Source: Masters Abstracts International, Volume: 39-02, page: 0532. Adviser: Young G. Park. Thesis (M.Sc.)--University of Windsor (Canada), 2000

Epistemic and Ontic Quantum Realities

Quantum theory has provoked intense discussions about its interpretation since its pioneer days. One of the few scientists who have been continuously engaged in this development from both physical and philosophical perspectives is Carl Friedrich von Weizsaecker. The questions he posed were and are inspiring for many, including the authors of this contribution. Weizsaecker developed Bohr's view of quantum theory as a theory of knowledge. We show that such an epistemic perspective can be consistently complemented by Einstein's ontically oriented position

Do scenario context and question order influence WTP? The application of a model of uncertain WTP to the CV of the morbidity impacts of air pollution

This paper presents a general framework for modelling responses to contingent valuation questions when respondents are uncertain about their ‘true’ WTP. These models are applied to a contingent valuation data set recording respondents’ WTP to avoid episodes of ill-health. Two issues are addressed. First, whether the order in which a respondent answers a series of contingent valuation questions influences their WTP. Second, whether the context in which a good is valued (in this case the information the respondent is given concerning the cause of the ill-health episode or the policy put into place to avoid that episode) influences respondents’ WTP. The results of the modelling exercise suggest that neither valuation order nor the context included in the valuation scenario impact on the precision with which respondents answer the contingent valuation questions. Similarly, valuation order does not appear to influence the mean or median WTP of the sample. In contrast, it is shown that in some cases, the inclusion of richer context significantly shifts both the mean and median WTP of the sample. This result has implications for the application of benefits transfer. Since, WTP to avoid an episode of ill-health cannot be shown to be independent of the context in which it is valued, the validity of transferring benefits of avoided ill-health episodes from one policy context to another must be called into question

Ignorance and indifference

The epistemic state of complete ignorance is not a probability distribution. In it, we assign the same, unique, ignorance degree of belief to any contingent outcome and each of its contingent, disjunctive parts. That this is the appropriate way to represent complete ignorance is established by two instruments, each individually strong enough to identify this state. They are the principle of indifference (PI) and the notion that ignorance is invariant under certain redescriptions of the outcome space, here developed into the 'principle of invariance of ignorance' (PII). Both instruments are so innocuous as almost to be platitudes. Yet the literature in probabilistic epistemology has misdiagnosed them as paradoxical or defective since they generate inconsistencies when conjoined with the assumption that an epistemic state must be a probability distribution. To underscore the need to drop this assumption, I express PII in its most defensible form as relating symmetric descriptions and show that paradoxes still arise if we assume the ignorance state to be a probability distribution. Copyright 2008 by the Philosophy of Science Association. All rights reserved

Analysis of Implicit Uncertain Systems. Part I: Theoretical Framework

This paper introduces a general and powerful framework for the analysis of uncertain systems, encompassing linear fractional transformations, the behavioral approach for system theory and the integral quadratic constraint formulation. In this approach, a system is defined by implicit equations, and the central analysis question is to test for solutions of these equations. In Part I, the general properties of this formulation are developed, and computable necessary and sufficient conditions are derived for a robust performance problem posed in this framework