Thermography based breast cancer analysis using statistical features and fuzzy classifications

Medical thermography has proved to be useful in various medical applications including the detection of breast cancer where it is able to identify the local temperature increase caused by the high metabolic activity of cancer cells. It has been shown to be particularly well suited for picking up tumours in their early stages or tumours in dense tissue and outperforms other modalities such as mammography for these cases. In this paper we perform breast cancer analysis based on thermography, using a series of statistical features extracted from the thermograms quantifying the bilateral differences between left and right breast areas, coupled with a fuzzy rule-based classification system for diagnosis. Experimental results on a large dataset of nearly 150 cases confirm the efficacy of our approach that provides a classification accuracy of about 80%

Pilot VLBI Survey of SiO v=3 J=1--0 Maser Emission around Evolved Stars

In this Letter, we report detections of SiO v=3 J=1--0 maser emission in very long baseline interferometric (VLBI) observations towards 4 out of 12 long-period variable stars: WX Psc, R Leo, W Hya, and T Cep. The detections towards WX Psc and T Cep are new ones. We also present successful astrometric observations of SiO v=2 and v=3 J=1--0 maser emissions associated with two stars: WX Psc and W Hya and their position-reference continuum sources: J010746.0+131205 and J135146.8-291218 with the VLBI Exploration of Radio Astrometry (VERA). The relative coordinates of the position-reference continuum source and SiO v=3 maser spots were measured with respect to those of an SiO v=2 maser spot adopted as fringe-phase reference. Thus the faint continuum sources were inversely phase-referenced to the bright maser sources. It implies possible registration of multiple SiO maser line maps onto a common coordinate system with 10 microarcsecond-level accuracy.Comment: 5 Pages, 3 figures, Fig.3 and Tab. 2 were corrected; Publications of the Astronomical Society of Japan, Vol. 64, No. 6 issued on 2012 December 2

The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competitio

CHANGE DETECTION FOR AREA SURVEILLANCE USING A MOVING CAMERA

This paper tackles area surveillance with a moving camera by change detection. None of the existing datasets for change detection meets a surveillance scenario where a camera is mounted on a moving platform and pointed in the direction of moving. Thus, this paper creates a new dataset including several challenging points. For this dataset, this paper employs a composable method and proposes some components. To evaluate the proposed components, some corresponding classic methods were also tested on the dataset. As a result, the proposals outperformed them. Moreover, this paper investigated the relationship between the parameters of the components and their performance.This paper tackles area surveillance with a moving camera by change detection. None of the existing datasets for change detection meets a surveillance scenario where a camera is mounted on a moving platform and pointed in the direction of moving. Thus, this paper creates a new dataset including several challenging points. For this dataset, this paper employs a composable method and proposes some components. To evaluate the proposed components, some corresponding classic methods were also tested on the dataset. As a result, the proposals outperformed them. Moreover, this paper investigated the relationship between the parameters of the components and their performance

Effect of rule weights in fuzzy rule-based classification systems

Abstract—This paper examines the effect of rule weights in fuzzy rule-based classification systems. Each fuzzy IF–THEN rule in our classification system has antecedent linguistic values and a single consequent class. We use a fuzzy reasoning method based on a single winner rule in the classification phase. The winner rule for a new pattern is the fuzzy IF–THEN rule that has the maximum compatibility grade with the new pattern. When we use fuzzy IF–THEN rules with certainty grades (i.e., rule weights), the winner is determined as the rule with the maximum product of the compatibility grade and the certainty grade. In this paper, the effect of rule weights is illustrated by drawing classification boundaries using fuzzy IF–THEN rules with/without certainty grades. It is also shown that certainty grades play an important role when a fuzzy rule-based classification system is a mixture of general rules and specific rules. Through computer simulations, we show that comprehensible fuzzy rule-based systems with high classification performance can be designed without modifying the membership functions of antecedent linguistic values when we use fuzzy IF–THEN rules with certainty grades. Index Terms—Fuzzy reasoning, fuzzy rule-based systems, pattern classification, rule extraction. I