R. Ruelas

A defuzzification method respecting the fuzzification

Abstract When designing a fuzzy controller, the first thing to do is to choose input and output fuzzifications. The next step consists of building the fuzzy rules table describing the behaviour of the controller. Finally, in order to convert the fuzzy output in a usable form, we need to select a defuzzification strategy. This selection can be realized by testing one by one the defuzzification methods available in the literature, and taking the best one in terms of output error. However, this approach is not theoretically convincing. This selection can also be realized by considering the following logical criterion: fuzzification and defuzzification are, by nature, two complementary processes. In other words, the choice of a defuzzification strategy must be made with respect to the output fuzzification. In this paper, we present a defuzzification method which takes into account the parameters of the fuzzification in order to respect it.

Images sub-segmentation with the PFCM clustering algorithm

In this work we propose a method for sub-segmentation of images using the PFCM clustering algorithm. The sub-segmentation consists of finding, within the clusters found using the segmentation process, those data less representative, or atypical data, belonging to the clusters. These data represent, in many cases, the zones of interest during image analysis. Two different examples are used in order to show the results, and the advantages of identifying those elements of data forced to belong to a cluster, of which they are the less representative and, therefore may contain information of great interest in particular applications.

Study of the Pull-In Voltage for MEMS Parallel Plate Capacitor Actuators

This paper provides new investigation for the static and dynamic behavior of a MEMS parallel plate capacitor derived by analytical and numerical design modeling programs developed in Matlab. One significant finding is about the role, which has so far overlooked in many analyses, of a dielectric layer normally placed on top of the ground electrode to avoid short circuiting risks. It is demonstrated in this paper that this layer produces an increased force between electrodes that in turns decreases the well-known pull-in voltage, V pi , as compared to the one calculated when this dielectric layer is not considered on the systems static analysis. Expressions for the static V pi and its corresponding maximum stable electrode swing x pi are derived to take the above effect into account. The system dynamic analysis is done with a user-friendly Simulink interface constructed to allow easy introduction of capacitor design dimensions, material parameter values and voltage signal stimuli. The impact of any combination of these parameters on the electro-mechanical system behavior, that is, the voltage-electrode position dependence data can be easily extracted and become of help for design decision making on the early design stages of this type of structures. This modeling tool interface is based on solving the full differential equation that describes the free electrode displacement without relying on linearizing the inverse quadratic electrode separation dependence of the electro-static force term. This approach intrinsically takes into account the voltage dependant k -spring softening effect derived precisely from a linearizing simplification. Finally, by applying a saw-tooth voltage waveform, the dynamic pull-in voltage and the maximum stable electrode travel range are observed to go well beyond the predicted static pull-in voltage and travel range values.

Dynamic behavior modeling of MEMS parallel plate capacitors

This work presented dynamic behaviors of a MEMS parallel plate capacitor using analytical and numerical methods. The differential equation describing the electrode displacement is solved by using a Matlab/Simulink interface developed to serve as a practical fill-the-box design tool. The systems dynamic instability condition (at the pull-in voltage, V/sub dpi/) is reached at much higher bias levels as compared with the static case. We presented the dynamic behavior and the frequency limiting cases for sine and pulse input bias waveforms. For high frequency, the results are given both in analytical and numerical forms.

Color image segmentation by partitional clustering algorithms

This paper presents the results of some partitional clustering algorithms applied to the segmentation of color images in the RGB space. As more information is involved in the algorithm, and the distance measure is more flexible, the better the results. The selected algorithms for this work are the K-means, the FCM, the GK-B, and the GKPFCM. The GKPFCM gives the better results when all the algorithms are applied to the segmentation of two images, an image of bananas and the other one of tomates at different stages of ripeness in both cases. The results are interesting as it is possible to identify the objects, to determine the degree of ripeness, and to estimate the amount and proportion of ripe objects for a possible decision-making.

An Improvement to the Possibilistic Fuzzy c-Means Clustering Algorithm

In this work we propose to use the Gustafson-Kessel (GK) algorithm within the PFCM (Possibilistic Fuzzy c-Means), such that the cluster distributions have a better adaptation with the natural distribution of the data. The PFCM, proposed by Pal et al. on 2005, is founded on the fuzzy membership degrees of the FCM and the typicality values of the PCM. Nevertheless, this algorithm uses the Euclidian distance which gives circular clusters. So, incorporating the GK algorithm and the Mahalanobis measure for the calculus of the distance, we have the possibility to get ellipsoidal forms as well, allowing a better representation of the clusters.

Air pollution analysis with a PFCM clustering algorithm applied in a real database of Salamanca (Mexico)

Over the last ten years, Salamanca has been considered among the most polluted cities in México. Nowadays, there is an Automatic Environmental Monitoring Network (AEMN) which measures air pollutants (Sulphur Dioxide (SO2), Particular Matter (PM10), Ozone (O3), etc.), as well as environmental variables (wind speed, wind direction, temperature, and relative humidity), and it takes a sample of the variables every minute. The AEM Network is mainly based on three monitoring stations located at Cruz Roja, DIF, and Nativitas. In this work, we use the PFCM (Possibilistic Fuzzy c Means) clustering algorithm as a mean to get a combined measure, from the three stations, looking to provide a tool for better management of contingencies in the city, such that local or general action can be taken in the city according to the pollution level given by each station and the combined measure. Besides, we also performed an analysis of correlation between pollution and environmental variables. The results show a significative correlation between pollutant concentrations and some environmental variables. So, the combined measure and the correlations can be used for the establishment of general contingency thresholds.

Silicon solar cell efficiency improvement employing the photoluminescent, down-shifting effects of carbon and CdTe quantum dots

We report the synthesis and characterization of Carbon and CdTe quantum dots (QDs), as well as the observed improvement in the power conversion efficiency (PCE) of photovoltaic devices upon the incorporation of the synthesized aforementioned nanostructures. Even though C quantum dots were observed to have a relatively smaller influence on solar cell performance, they are considered to be a more attractive option due to their affordability and minimal impact in the environment that could ultimately promote their widespread utilization on photovoltaic structures.

An Open On-Board CBTC Controller Based on N-Version Programming

A new method of controlling trains based on constant communications with each train is known as communications based train control (CBTC). This method allows more traffic and trains closer together at the same time improving safety. This paper looks at an open on-board CBTC controller for subway cars using a modified model of n-version programming to create a system that guarantees the highest level of safety, at the same time performing the on-board functions required by CBTC

Improvement of the Image Sub-Segmentation for Identification and Differentiation of Atypical Regions

A new sub-segmentation method has been proposed in 2009 which, in digital images, help us to identify the typical pixels, as well as the less representative pixels or atypical of each segmented region. This method is based on the Possibilistic Fuzzy c-Means (PFCM) clustering algorithm, as it integrates absolute and relative memberships. Now, the segmentation problem is related to isolate each one of the objects present in an image. However, and considering only one segmented object or region represented by gray levels as its only feature, the totality of pixels is divided in two basic groups, the group of pixels representing the object, and the others that do not represent it. In the former group, there is a sub-group of pixels near the most representative element of the object, the prototype, and identified here as the typical pixels, and a sub-group corresponding to the less representative pixels of the object, which are the atypical pixels, and generally located at the borders of the pixels representing the object. Besides, the sub-group of atypical pixels presents greater tones (brighter or towards the white color) or smaller tones (darker or towards black color). So, the sub-segmentation method offers the capability to identify the sub-region of atypical pixels, although without performing a differentiation between the brighter and the darker ones. Hence, the proposal of this work contributes to the problem of image segmentation with the improvement on the detection of the atypical sub-regions, and clearly recognizing between both kind of atypical pixels, because in many cases only the brighter or the darker atypical pixels are the ones that represent the object of interest in an image, depending on the problem to be solved. In this study, two real cases are used to show the contribution of this proposal; the first case serves to demonstrate the pores detection in soil images represented by the darker atypical pixels, and the second one to demonstrate the detection of microcalcifications in mammograms, represented in this case by the brighter atypical pixels.