Robust diagnosis of discrete event systems against intermittent loss of observations

In the usual approaches to fault diagnosis of discrete event systems it is assumed that not only all sensors work properly but also all information reported by sensors always reaches the diagnoser. Any bad sensor operation or communication failure between sensors and the diagnoser can be regarded as loss of observations of events initially assumed as observable. In such situations, it may be possible that either the diagnoser stands still or report some wrong information regarding the fault occurrence. In this paper we assume that intermittent loss of observations may occur and we propose an automaton model based on a new language operation (language dilation) that takes it into account. We refer to this problem as robust diagnosability against intermittent loss of observations (or simply robust diagnosability, where the context allows). We present a necessary and sufficient condition for robust diagnosability in terms of the language generated by the original automaton and propose two tests for robust language diagnosability, one that deploys diagnosers and another one that uses verifiers. We also extend the results to robust codiagnosability against intermittent loss of observations.     

A Fuzzy Logic intelligent agent for Information Extraction: Introducing a new Fuzzy Logic-based term weighting scheme

In this paper, we propose a novel method for Information Extraction (IE) in a set of knowledge in order to answer to user consultations using natural language. The system is based on a Fuzzy Logic engine, which takes advantage of its flexibility for managing sets of accumulated knowledge. These sets may be built in hierarchic levels by a tree structure. The aim of this system is to design and implement an intelligent agent to manage any set of knowledge where information is abundant, vague or imprecise. The method was applied to the case of a major university web portal, University of Seville web portal, which contains a huge amount of information. Besides, we also propose a novel method for term weighting (TW). This method also is based on Fuzzy Logic, and replaces the classical TF-IDF method, usually used for TW, for its flexibility.     

Cascaded warped-FIR and FIR filter structure for loudspeaker equalization with low computational cost requirements

This paper proposes an improved filter structure and methodology for the equalization of loudspeakers and other audio systems. It employs a cascaded structure of a finite impulse response (FIR) filter and a warped-FIR filter in order to obtain the best performance of both types of filters. In the task of loudspeaker equalization, FIR filters achieve excellent resolution and equalization at high frequencies, but at low frequencies the resolution obtained is too poor when evaluated in a logarithmic frequency axis, that could only be improved using high order filters. To solve this lack of resolution at low frequencies, warped-FIR filters have been employed, but at the expense of decreasing the resolution of the filter at high frequencies and increasing the complexity of the filter structure and its computational cost. The proposed combination of both types of filters, combined with the correct selection of their orders, and the λ value for the warped-FIR filter, allows the FIR filter to maintain its good resolution at high frequencies and achieve enough resolution at low frequencies with the warped-FIR filter. In this way, lower order filters with lower computational cost could be obtained than when using FIR or warped-FIR only. This approximation attains a more uniform resolution of the filter when evaluated in octaves, behaving much more like human hearing, than the linear frequency resolution obtained when employing only FIR filters.     

Towards a framework for multiple artificial neural network topologies validation by means of statistics

Artificial neural networks (ANNs) are flexible computing tools that have been applied to a wide range of domains with a notable level of accuracy. However, there are multiple choices of ANNs classifiers in the literature that produce dissimilar results. As a consequence of this, the selection of this classifier is crucial for the overall performance of the system. In this work, an integral framework is proposed for the optimization of different ANN classifiers based on statistical hypothesis testing. The framework is tested in a real ballistic scenario. The new quality measures introduced, based on the Student t‐test, and employed throughout the framework, ensure the validity of results from a statistical standpoint; they reduce the appearance of experimental errors or the appearance of possible randomness. Results show the relevance of this framework, proving that its application improves the performance and efficiency of multiple classifiers.     

Fourier transform IR and differential scanning calorimetry study of curing of trifunctional amino‐epoxy resin

The curing process was studied for a trifunctional epoxy resin, triglycidyl‐p‐aminophenol, using the hardener 4,4′‐diaminodiphenylsulfone. Two curing cycles were carried out: one following the manufacturer's guidelines (2 h at 80°C, 1 h at 100°C, 4 h at 150°C, and 24 h at 200°C) and another proposed in this study, in which the two stages at low temperatures were excluded. Fourier transform IR spectroscopy was used to quantify the conversion of different functional groups (primary amine, secondary amine, epoxide, hydroxyl and ether functional groups), and these conversions could be used to infer the type of reactions that took place. These results allowed us to analyze the evolution of the curing process over time and the influence of the curing cycle. Furthermore, the enthalpy of the curing process was determined using differential scanning calorimetry, and from this the thermal conversion for the whole process was evaluated. By taking into account the autocatalytic kinetic model, the rate constants were evaluated. The glass‐transition temperatures were also estimated by applying different curing cycles to the resin. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 1524–1535, 2005     

"Transient structures": the effects of practice and distractor grouping on within-dimension conjunction searches

It has been stated that whereas between-dimension (color x orientation) conjunctions can be searched in a "parallel" fashion, within-dimension (color x color) conjunctions are necessarily searched in a "serial self-terminating" fashion (Wolfe et al., 1990). We explored the effects of practice (within 1-h experimental session) and distractor grouping on within-dimension conjunction search tasks. In Experiments 1 and 3, the stimuli were rectangles formed by two adjacent squares; in Experiment 2, the stimuli were plus signs formed by two segments and an intersection. In Experiments 1 and 2, observers were assigned to one of two experimental conditions: In one, all the distractors shared a simple feature (the color blue); in the other, distractors did not share that simple feature. In the first condition, search became more efficient with practice and observers' performance was characterized by a shallow reaction time (RT) x set size slope; in the second condition, observers' performance did not improve as much with practice. We propose that the differential effects of practice between these two experimental conditions can be explained in terms of distractor grouping induced by the shared color of the distractors. Experiment 3 showed that, with practice, a shallow RT x set size slope characterized observers' search for a color x color target among four different distractors that shared a common color. The present results contradict a main tenet of some current visual search models--namely, that within-dimension conjunctions cannot be searched in parallel, and question the validity of using RT x set size slope functions to distinguish between preattentive versus attentive search.     

Characteristic locus method robustness improvement through optimal static normalizing pre‐compensation

Controlled systems designed by using the characteristic locus method can be very sensitive to small perturbations in the plant input and output at the frequencies where the plant transfer matrix is far from normal. In order to improve the closed‐loop system robustness, previous work proposes the design of a dynamic normalizing pre‐compensator followed by the design of a commutative controller for the pre‐compensated plant. The restriction on its structure and the need for approximation by a stable rational transfer matrix were among the limitations of the dynamic pre‐compensator. This paper shows that it suffices to design a static pre‐compensator that makes the pre‐compensated plant as closely as possible to a normal matrix in a frequency band containing the crossover frequency. The pre‐compensator is found by solving an optimization problem, whose solution is obtained directly by computing either a singular value decomposition of a real matrix or the spectral decomposition of a symmetric matrix, depending on whether normalization is to be achieved in one or more frequencies. Numerical examples illustrate the theoretical results of the paper. Copyright © 2009 John Wiley & Sons, Ltd.     

The recovery of design intent in reverse engineering problems

This article presents a method of reverse engineering applied to the particular case of a cam in order to recover the form and dimensions of the design of the original piece, which take into account: design intent, general knowledge of the problem, different geometric and dimensional restrictions, and the digitized point cloud. Rather than by employing complex mathematical algorithms, a fit is achieved by drawing a parametric outline that complies with the design intent, and by adjusting the different parameters through successive approximations using commercial CAD software commands.