[in Japanese]

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[in Japanese]

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This paper proposes a region extraction method for aortic aneurysm of computed tomography angiography (CTA) of a patient. The concept of Neuro-Fuzzy inference that refers the experimental law of interpreting CTA image of a skilled radiation technologist is adopted as region growing condition. Gaussian membership functions of Neuro-Fuzzy inference are optimized by using genetic algorithm. The experimental results showed that the proposed method is available method for the extraction of the aortic aneurysmal region from one slice of CTA image.

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A new robust semi-active method is proposed to suppress various multimodal vibrations. The robust control consists of Mamdani method and semi-active threshold control. We demonstrate it to be applicable to multimodal vibration suppression for vibrating structures. Our proposed control only requires the information of natural frequencies for the real-time feedback control. We carried out experiments of vibration suppression using our Mamdani-logic-based control and conventional threshold control, and compared their suppression performances. The experiment indicates that our proposed control can adapt to conditions outside the assumed range of excitations. The proposed control displays good robustness when faced with sudden changes in vibrations, and also displays high suppression performance.

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The high-speed catamaran boat used by this study has attached trim tabs to the stern both sides as the anti-rolling device for reducing the rolling. A PD control was initially employed in the system, and the observed data from the instrument showed the anti-rolling effect. However no significant improvement was observed for passengers although instrumental data showed good results. Therefore, it is not evaluated highly as the -rolling device. In this paper, fuzzy control system is applied to the anti-rolling device of a high-speed catamaran boat in order to improve the passenger comfort. Measurements of rolling data using the real ship were carried out. From the analysis results of the frequency analysis, the presented fuzzy control system suppressed the rolling of ship about 60% in maximum peak than the PD control. Also, crews have felt the anti-rolling effect of the fuzzy control, and it showed that this system provided good comfort ride.

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This study deals with the design of an integration-proportional derivative (I-PD) controller with respect to an unspecified plant. Herein, for a plant represented by a Takagi-Sugeno fuzzy model, we designed an I-PD controller by the coefficient diagram method (CDM), which provides a good balance of stability, response, and robustness. The output of the fuzzy model is determined by a transfer function. This approach enables us to determine the parameters of the I-PD controller. Finally, the effectiveness of the proposed method is confirmed by simulation results.

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In this research, a fuzzy controller system is used as a key technique to design a machine controller. A fuzzy system can be designed using fuzzy sets, which can be represented using linguistic descriptions of natural language. These natural languages are able to capture human knowledge in fuzzy rules. A fuzzy controller system consists of fuzzy rules and the fuzzy inference techniques. Recently, research on fuzzy control has demonstrated the benefits of machine control using fuzzy rules. Through our research, we were able to verify that fuzzy control can be applicable to a line tracing car, which is running at a high speed. When carrying out our research, the adjustments and setup of the fuzzy controller required much time. In order to apply another Fuzzy controller to our line tracing car, we designed a simple inference system, and setup a Differential Evolution (DE) as a search algorithm. The DE was able to search a candidate solution of the fuzzy label. In addition, the auto-tuned fuzzy inference system can be controlled smoothly. In this paper, we present the search results of the simulation experiment and compare the results between the fuzzy controller and the auto-tuned controller using a DE.

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This paper proposes an explicit algorithm for a newsboy problem with shortage costs dependent on consumers' demands derived from a fuzzy reasoning method. The newsboy problem is the most standard and important problem in inventory problems, and it is widely used in practical production companies and supply chain networks. However, it is difficult to set the shortage cost as a fixed value due to word of mouth and psychological aspects of consumer and decision maker. On the other hand, the decision maker has some rules to the shortage cost. Therefore, in order to set the shortage cost appropriately considering the above-mentioned cases, the fuzzy reasoning method, particularly the Product-Sum-Gravity method, is introduced, and the explicit optimal condition of the proposed model is obtained. Furthermore, by comparing the proposed model with previous models, some features of the proposed model are also obtained.

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