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Vachkov G.,Yamaguchi University | Uchino E.,Fuzzy Logic Systems Institute FLSI
Smart Innovation, Systems and Technologies | Year: 2012

This paper is dealing with the problem of tissue characterization of the plaque in the coronary arteries by processing the data from the intravascular ultrasound catheter. The similarity analysis method in the paper is applied in the frame of the moving window approach, which scans all cells in the matrix data from one cross section of the artery. The center-of-gravity model is used for evaluating the dissimilarity between any given pairs of data sets, belonging to pairs of windows. As a computational strategy, the use of weighted values of dissimilarity within the cells belonging to one window is proposed in the paper, rather than simply using an equal mean value for all cells in the window. The similarity results from each cross section of the artery are displayed as gray scale image, where the darker areas denote the more similar areas to a predefined region of interest. The simulation results from the tissue characterization of a real data set show that the weighted moving window approach gives a sharper resolution of the similarity results that are closer to the real results, compared to the simple mean value approach. This suggests that the weighted moving window approach can be applied to real medical diagnosis. © Springer-Verlag Berlin Heidelberg 2012. Source


Tasan A.S.,Dokuz Eylul University | Gen M.,Fuzzy Logic Systems Institute FLSI | Gen M.,Hanyang University
Computers and Industrial Engineering | Year: 2012

The vehicle routing problem with simultaneous pick-up and deliveries, which considers simultaneous distribution and collection of goods to/from customers, is an extension of the capacitated vehicle routing problem. There are various real cases, where fleet of vehicles originated in a depot serves customers with pick-up and deliveries from/to their locations. Increasing importance of reverse logistics activities make it necessary to determine efficient and effective vehicle routes for simultaneous pick-up and delivery activities. The vehicle routing problem with simultaneous pick-up and deliveries is also NP-hard as a capacitated vehicle routing problem and this study proposes a genetic algorithm based approach to this problem. Computational example is presented with parameter settings in order to illustrate the proposed approach. Moreover, performance of the proposed approach is evaluated by solving several test problems. © 2011 Elsevier Ltd. All rights reserved. Source


Yamakawa T.,Fuzzy Logic Systems Institute FLSI | Miki T.,Kyushu Institute of Technology
Studies in Fuzziness and Soft Computing | Year: 2015

Nine basic fuzzy logic functions can be represented by the Bounded- Difference(s) and theAlgebraic Sum(s). In current mode electronic circuits, the Algebraic Sum is implemented only by connecting wires (wired sum), and the Bounded Difference done by current difference and prevention of negative current. These fuzzy logic functions are implemented in the form of CMOS integrated circuits. The design criteria are also presented. © 2015 Springer International Publishing Switzerland Source


Tasan A.S.,Dokuz Eylul University | Gen M.,Fuzzy Logic Systems Institute FLSI
40th International Conference on Computers and Industrial Engineering: Soft Computing Techniques for Advanced Manufacturing and Service Systems, CIE40 2010 | Year: 2010

The vehicle routing problem with simultaneous pick-up and deliveries, which considers simultaneous distribution and collection of goods to/from customers, is an extension of the capacitated vehicle routing problem. There are numerous real cases, that fleet of vehicles originated in a depot serves customers with pick-up and deliveries from/to their locations. Increasing importance of reverse logistics activities make it necessary to determine efficient and effective vehicle routes for simultaneous pick-up and delivery activities. The vehicle routing problem with simultaneous pick-up and deliveries is also NP-hard as capacitated vehicle routing problem and this study proposes a genetic algorithm based approach to this problem. Computational example is given for an illustrative in order to illustrate the performance of the proposed approach. Source


Misawa H.,Kyushu Institute of Technology | Horio K.,Kyushu Institute of Technology | Horio K.,Fuzzy Logic Systems Institute FLSI | Morotomi N.,University of Occupational and Environmental Health Japan | And 2 more authors.
IEICE Transactions on Information and Systems | Year: 2012

In the present paper, we address the problem of extrapolating group proximities from member relations, which we refer to as the group proximity problem. We assume that a relational dataset consists of several groups and that pairwise relations of all members can be measured. Under these assumptions, the goal is to estimate group proximities from pairwise relations. In order to solve the group proximity problem, we present a method based on embedding and distribution mapping, in which all relational data, which consist of pairwise dissimilarities or dissimilarities between members, are transformed into vectorial data by embedding methods. After this process, the distributions of the groups are obtained. Group proximities are estimated as distances between distributions by distribution mapping methods, which generate a map of distributions. As an example, we apply the proposed method to document and bacterial flora datasets. Finally, we confirm the feasibility of using the proposed method to solve the group proximity problem. Copyright © 2012 The Institute of Electronics, Information and Communication Engineers. Source

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