Linguistic quantifiers modeled by Sugeno integrals

Since quantifiers have the ability of summarizing the properties of a class of objects without enumerating them, linguistic quantification is a very important topic in the field of high level knowledge representation and reasoning. This paper introduces a new framework for modeling quantifiers in natural languages in which each linguistic quantifier is represented by a family of fuzzy measures, and the truth value of a quantified proposition is evaluated by using Sugeno's integral. This framework allows us to have some elegant logical properties of linguistic quantifiers. We compare carefully our new model of quantification and other approaches to linguistic quantifiers. A set of criteria for linguistic quantification was proposed in the previous literature. The relationship between these criteria and the results obtained in the present paper is clarified. Some simple applications of the Sugeno's integral semantics of quantifiers are presented. © 2006 Elsevier B.V. All rights reserved

Decision-making: a laboratory-based case study in conceptual design

The engineering design process may be seen as a series of interrelated operations that are driven by decisions: each operation is carried out as the consequence of an associated decision. Hence, an effective design process relies heavily upon effective decision-making. As a consequence, supporting decision-making may be a significant means for achieving design process improvements. This thesis concentrates on how to support selection-type decision-making in conceptual engineering design. [Continues.

Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

BackgroundUsing knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms?ResultsOur existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important.ConclusionsWith some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels

Functional enrichment of utopian distribution of plant life-forms

Adaptive fuzzy neural inference systems are used to illustrate the primary nodal number of plant life-forms. Categorization of two candidate areas is carried out using the water-energy dynamic (for Ecuador, South America) and Macedonia, Southern Europe), within which the life-form spectra are distributed. Genetic optimization methods are used to expand the primary nodal number to the complete number of life-form categories. The distribution of the elements exhibits a stochastic, binomial distribution and the utopia line and curve are summarized which enhance accuracy of the climatic data and of the consequent numbers of plant species occurrences. Expansion of the distribution of each life-form category is approximated within the Z utopia hyperplane with use of the functional approximation algorithm. This process gives additional structure and informative value to the Z plane, enhancing our ability to make informed policy decisions concerning species and ecosystem conservation

MULTI-CRITERIONAL CHOICE OF AN ALTERNATIVE UNDER THE RULES OF FUZZY PRODUCTS WITH SOME RELIABILITY DEGREE

One of the main problems of decision-making tasks is the need to take into account subjective expert assessments, the complete consistency of which is rare, and the choice of the best alternative. The complexity of the connections between the many-sided aspects of the decision-making situation and the lack of an accurate forecast of the consequences leads to the fact that when assessing and choosing alternatives, it is possible, and often necessary, to use and process qualitatively fuzzy estimates. In decision-making situations, when at least one of the elements (outcomes, criteria, preferences, expert opinions, etc.) is described qualitatively, indistinctly, there are problems of multi-criteria decision-making with fuzzy initial information. Let’s consider the solution to the problem of multi-criteria choice based on the rules of fuzzy conditional inference, which have the form of fuzzy statements, the conditions and conclusions of which, along with expert assessments of the criteria, are presented in the form of interval fuzzy numbers of the second type (IT2FN). The convolution of private implications in each statement is made according to Lukasiewicz's rule. To reduce the type and defuzzify the resulting IT2FN, the Karrnik-Mendel algorithm was used to construct the minimum and maximum centroids of nested fuzzy sets of the first type, which give an estimate of the utility interval for each alternative. To refine the obtained utility estimates, under conditions of incomplete definiteness of statements, using the generalized Bayesian inference mechanism, adjusted estimates of the utility intervals of alternatives are constructed. By comparing these intervals, a larger interval is determined and the corresponding alternative is taken as a solution to the problem under consideration. The application of the proposed approach to solving the problem of multicriteria selection of the most corroded section of a gas pipeline with ambiguous expert opinions is shown. To date, specific practical and theoretical results have been obtained for decision-making problems with fuzzy initial informatio

'Tell Us Only What You Know': Evidentiality in the Discourse of Participants in Spanish Trials

El objetivo de esta propuesta es explorar el uso de la evidencialidad en los juicios españoles y su relación con las convenciones del género y los roles de los participantes en estos eventos discursivos. Para ello, basamos nuestro estudio en un análisis cuantitativo-cualitativo de un corpus transcrito de ensayos orales en español. La evidencialidad es una categoría semántico-funcional que incluye dispositivos lingüísticos que marcan la fuente de información detrás de las declaraciones del hablante. El marcado explícito de la fuente no es obligatorio en español; sin embargo, en géneros específicos (legal, parlamentario y académico), se convierte en una poderosa herramienta argumentativa para negociar la validez de las ideas. Analizamos cómo los diferentes participantes en los ensayos hicieron uso de expresiones evidenciales. Se puede observar que los hablantes con conocimiento experto sobre las convenciones de género (juristas) emplearon la evidencialidad de manera diferente a la forma en que lo hicieron los participantes laicos. Se pueden observar algunas diferencias a nivel de los tipos de evidencialidad. Por ejemplo, las inferencias genéricas y el informe de leyes y guiones son típicos del discurso de los juristas, mientras que los participantes legos, en particular los testigos, se refirieron más a menudo a información basada en la observación. Además, nuestro análisis sugirió que los juristas eran más propensos a explotar las construcciones probatorias con fines argumentativos o estratégicos. Por ejemplo, el razonamiento lógico basado en información supuestamente conocida o compartida puede usarse para degradar el compromiso del hablante o para mitigar y atenuar el desacuerdo. Se pueden observar algunas diferencias a nivel de los tipos de evidencialidad. Por ejemplo, las inferencias genéricas y el informe de leyes y guiones son típicos del discurso de los juristas, mientras que los participantes legos, en particular los testigos, se refirieron más a menudo a información basada en la observación. Además, nuestro análisis sugirió que los juristas eran más propensos a explotar las construcciones probatorias con fines argumentativos o estratégicos. Por ejemplo, el razonamiento lógico basado en información supuestamente conocida o compartida puede usarse para degradar el compromiso del hablante o para mitigar y atenuar el desacuerdo. Se pueden observar algunas diferencias a nivel de los tipos de evidencialidad. Por ejemplo, las inferencias genéricas y el informe de leyes y guiones son típicos del discurso de los juristas, mientras que los participantes legos, en particular los testigos, se refirieron más a menudo a información basada en la observación. Además, nuestro análisis sugirió que los juristas eran más propensos a explotar las construcciones probatorias con fines argumentativos o estratégicos. Por ejemplo, el razonamiento lógico basado en información supuestamente conocida o compartida puede usarse para degradar el compromiso del hablante o para mitigar y atenuar el desacuerdo. se refiere más a menudo a información basada en la observación. Además, nuestro análisis sugirió que los juristas eran más propensos a explotar las construcciones probatorias con fines argumentativos o estratégicos. Por ejemplo, el razonamiento lógico basado en información supuestamente conocida o compartida puede usarse para degradar el compromiso del hablante o para mitigar y atenuar el desacuerdo. se refiere más a menudo a información basada en la observación. Además, nuestro análisis sugirió que los juristas eran más propensos a explotar las construcciones probatorias con fines argumentativos o estratégicos. Por ejemplo, el razonamiento lógico basado en información supuestamente conocida o compartida puede usarse para degradar el compromiso del hablante o para mitigar y atenuar el desacuerdo

Weighted Constraints in Fuzzy Optimization

Many practical optimization problems are characterized by some flexibility in the problem constraints, where this flexibility can be exploited for additional trade-off between improving the objective function and satisfying the constraints. Especially in decision making, this type of flexibility could lead to workable solutions, where the goals and the constraints specified by different parties involved in the decision making are traded off against one another and satisfied to various degrees. Fuzzy sets have proven to be a suitable representation for modeling this type of soft constraints. Conventionally, the fuzzy optimization problem in such a setting is defined as the simultaneous satisfaction of the constraints and the goals. No additional distinction is assumed to exist amongst the constraints and the goals. This report proposes an extension of this model for satisfying the problem constraints and the goals, where preference for different constraints and goals can be specified by the decision-maker. The difference in the preference for the constraints is represented by a set of associated weight factors, which influence the nature of trade-off between improving the optimization objectives and satisfying various constraints. Simultaneous weighted satisfaction of various criteria is modeled by using the recently proposed weighted extensions of (Archimed

Explainable pattern modelling and summarization in sensor equipped smart homes of elderly

In the next several decades, the proportion of the elderly population is expected to increase significantly. This has led to various efforts to help live them independently for longer periods of time. Smart homes equipped with sensors provide a potential solution by capturing various behavioral and physiological patterns of the residents. In this work, we develop techniques to model and detect changes in these patterns. The focus is on methods that are explainable in nature and allow for generating natural language descriptions. We propose a comprehensive change description framework that can detect unusual changes in the sensor parameters and describe the data leading to those changes in natural language. An approach that models and detects variations in physiological and behavioral routines of the elderly forms one part of the change description framework. The second part comes from a natural language generation system in which we identify important health-relevant features from the sensor parameters. Throughout this dissertation, we validate the developed techniques using both synthetic and real data obtained from the homes of the elderly living in sensor-equipped facilities. Using multiple real data retrospective case studies, we show that our methods are able to detect variations in the sensor data that are correlated with important health events in the elderly as recorded in their Electronic Health Records.Includes bibliographical reference