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In this literature, fault detection of an induction motor is carried out using the information of stator current. After preprocessing actual data, Fourier and Wavelet transforms are applied to detect characteristics under the healthy and various faulted conditions. The most reliable phase current among 3-phase currents is selected by the fuzzy entropy. Data are trained with a neural network system, and the fault detection algorithm is carried out under the unknown data. The results of the proposed approach based on Fourier and Wavelet transformations show that the faults are properly classified into six categories. [ABSTRACT FROM AUTHOR]

Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the HSI model. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colorimetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The fuzzy ART algorithm is used to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction. [ABSTRACT FROM AUTHOR]

In this paper, passport recognition and face verification methods which can automatically recognize passport codes and discriminate forgery passports to improve efficiency and systematic control of immigration management are proposed. Adjusting the slant is very important for recognition of characters and face verification since slanted passport images can bring various unwanted effects to the recognition of individual codes and faces. The angle adjustment can be conducted by using the slant of the straight and horizontal line that connects the center of thickness between left and right parts of the string. Extracting passport codes is done by Sobel operator, horizontal smearing, and 8-neighbornood contour tracking algorithm. The proposed RBF network is applied to the middle layer of RBF network by using the fuzzy logic connection operator and proposing the enhanced fuzzy ART algorithm that dynamically controls the vigilance parameter. After several tests using a forged passport and the passport with slanted images, the proposed method was proven to be effective in recognizing passport codes and verifying facial images. [ABSTRACT FROM AUTHOR]

Gastric cancer is a great part of the cancer occurrence and the mortality from cancer in Korea, and the early detection of gastric cancer is very important in the treatment and convalescence. This paper, for the early detection of gastric cancer, proposes the analysis system of an endoscopic image of the stomach, which detects the abnormal region by using the change of color in the image and by providing the surface tissue information to the detector. While advanced inflammation and cancer may be easily detected, early inflammation and cancer are difficult to detect and requires more attention to be detected. This paper, at first, converts the endoscopic image to the image of the IHb(Index of Hemoglobin) model and removes noises incurred by illumination and, automatically detects the regions suspected as cancer and provides the related information to the detector, or provides the surface tissue information for the regions appointed by the detector. This paper does not intend to provide the final diagnosis of the detected abnormal regions as gastric cancer, but it intends to provide a supplementary mean to reduce the load and mistaken diagnosis of the detector, by automatically detecting the abnormal regions not easily detected by the human eye and this provides additional information for the diagnosis. The experiments using practical endoscopic images for performance evaluation showed that the proposed system is effective in the analysis of endoscopic image of the stomach. [ABSTRACT FROM AUTHOR]

In this study, the datamining application was achieved for fault detection and diagnosis of induction motors based on wavelet transform and classification models with current signals. Energy values were calculated from transformed signals by wavelet and distribution of the energy values for each detail was used in comparing similarity. The appropriate details could be selected by the fuzzy similarity measure. Through the similarity measure, features of faults could be extracted for fault detection and diagnosis. For fault diagnosis, neural network models were applied, because in this study, it was considered which details are suitable for fault detection and diagnosis. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches. [ABSTRACT FROM AUTHOR]

This article describes a modeling approach based on an operator's knowledge without a mathematical model of the system, and the optimization of the controller. The system used in this experiment could not easily be modeled by mathematical methods and could not easily be controlled by conventional systems. The controller was designed based on input-output data, and optimized under a predefined performance criterion. [ABSTRACT FROM AUTHOR]

Data mining is the exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules. Data mining consists of several tasks and each task uses a variety of methodologies. Some of these tasks are suited for a top-down method called hypothesis testing and others are suited for a bottom-up method called knowledge discovery. In this paper, we report our research procedures and results that concern and relate ozone concentration data in various factors and attributes. We use the general steps of directed knowledge discovery methodologies and intelligent modeling techniques. Next, we construct ozone concentration prediction system in order to reduce various adverse effects on human beings and life on the earth. [ABSTRACT FROM AUTHOR]

In this paper, the selection of a data set from a universal set is carried out using a fuzzy entropy function. According to the definition of fuzzy entropy, the fuzzy entropy function is proposed and that function is proved through definitions. The proposed fuzzy entropy function calculates the certainty or uncertainty value of a data set; hence we can choose the data set that satisfies certain bounds or references. Therefore a reliable data set can be obtained using the proposed fuzzy entropy function. With a simple example we verify that the proposed fuzzy entropy function selects the reliable data set. [ABSTRACT FROM AUTHOR]