1,720,983 research outputs found
Generating fuzzy models from deep knowledge: robustness and interpretability issues
No full textThe most problematic issues in fuzzy modeling of nonlinear system dynamics deal with robustness and interpretability. Traditional data-driven approaches, especially when the data set is not adequate, may lead to a model that results to be either unable to reproduce the system dynamics or numerically unstable or unintelligible. This paper demonstrates that Qualitative Reasoning plays a crucial role to significantly improve both robustness and interpretability. In the modeling framework we propose both fuzzy partition of input-output variables and the fuzzy rule base are built on the available deep knowledge represented through qualitative models. This leads to a clear and neat model structure that does describe the system dynamics, and the parameters of which have a physically significant meaning. Moreover, it allows us to properly constrain the parameter optimization problem, with a consequent gain in numerical stability. The obtained substantial improvement of model robustness and interpretability in "actual" physical terms lays the groundwork for new application perspectives of fuzzy models
Qualitative models in medical diagnosis
No full textDiagnostic systems based solely on associative knowledge are able to draw accurate conclusions in acceptable times but they do not capture all the available medical knowledge. Some of this knowledge, even if incomplete, is sufficiently precise to allow the formulation of qualitative models. The aim of this paper is to show how qualitative models can be exploited in a medical diagnostic system. We present a system, NEOANEMIA, that integrates first generation knowledge representation formalisms (frames and production rules) with qualitative pathophysiological models to diagnose hematologic disorders causing anemia. To this end, qualitative models of iron metabolism, erythropoietin metabolism, and red cell production and destruction have been formulated. The key ideas of our work are: abducing diagnostic hypotheses from observed problem features, modeling pathophysiological systems with dynamic qualitative models, predicting pathophysiological behaviours by qualitative model simulation, comparing clinical observations against simulation results, and when necessary, incrementally creating and testing multiple diagnostic hypotheses. In this way the performance of a diagnostic expert system can be highly enhanced. © 1990
A hybrid input-output approach to model metabolic systems: An application to intracellular thiamine kinetics
No full textModels of the dynamics of complex metabolic systems offer potential benefits to the deep comprehension of the system under study as well as for the performance of certain tasks. Unfortunately, dynamic modeling of a great deal of metabolic systems may be problematic due to the incompleteness of the available knowledge about the underlying mechanisms and to the lack of an adequate observational data set. In theory, a valid alternative to classical structural modeling through ordinary differential equations could be represented by input-output approaches, But, in practice, such methods, which learn the nonlinear dynamics of the system from input-output data, fail when the experimental data set is poor either in size or in quality. Such a situation is not rare in the case of metabolic systems. This paper deals with a hybrid approach which aims at overcoming the problems addressed above. More specifically, it allows us to solve the identification problems of the intracellular thiamine kinetics in the intestine tissue. The method, which is half way between the structural and input-output approach, uses the outcomes of file simulation of a qualitative structural model to build a good initialization of a fuzzy system identifier. Such an initialization allows us to efficiently cope with both the incompleteness of knowledge and the inadequacy of the available data set, and to derive an input-output model of the intracellular thiamine kinetics in the intestine tissue. The comparison of the predictions of the intracellular thiamine kinetics obtained by the application of such a model with those obtained by traditional approaches, namely compartmental models, neural networks, and fuzzy systems, highlighted a better performance of our model. As the structural assumptions are relaxed, we obtained a model slightly less informative than a purely structural one but robust enough to be used as a simulator. The paper also discusses the interpretative potential offered by such a model, as tested on diabetic subject
Learning from biomedical time series through the integration of qualitative models and fuzzy systems
No full textOur work deals with a method for the identification of the dynamics of nonlinear (patho-)physiological systems by learning from data. The key idea which underlies our approach consists in the integration of qualitative modeling methods with fuzzy logic systems. The major advantage which derives from such an integrated framework lies in its capability both to represent the structural knowledge of the system at study and to determine, by exploiting the available experimental data, a functional approximation of the system dynamics that can be used as a reasonable predictor of the patient's future state. We have successfully applied our method in the identification of the intracellular kinetics of thiamine from data collected in the intestine cells
Modeling incidental sequences in high environmental risk industrial plants: some simulation experiments
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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