Shimonoseki, Japan

Shimonoseki City University

www.shimonoseki-cu.ac.jp
Shimonoseki, Japan

Shimonoseki City University is a municipal university in Japan. Its campus is located in Daigaku-cho, Shimonoseki City, Yamaguchi Prefecture, Japan. Wikipedia.


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Bidin S.A.H.,University Technology of MARA | Lokman A.M.,University Technology of MARA | Mohd W.A.R.W.,University Technology of MARA | Tsuchiya T.,Shimonoseki City University
Procedia Computer Science | Year: 2017

The elderly population in Malaysia may increase to 15 percent from the country's population by the year 2030. This fact brings concern for the future prospect of the elderly care system in Malaysia, where there are possibilities of a robot being embedded into the life of the elderly. There have been many initiatives towards using robots as a therapeutic approach to improve the elderly Quality of Life (QoL). The relevant robotic studies for elderly are much associated with the Japanese Culture. However, there is a little study to investigate the feasibility of learning system using a robot among the elderly in Malaysia. The main objective of this study is to investigate the feasibility of using robots for elderly in Malaysia based on emotion requirement for the learning purposes. Persona approach will be used as a method to study on the three selected elderly from Tanjung Malim Elderly Activity Centre (PAWE). The result shows that majority of them are interested with the use of robot as learning assistant although they did not have any prior knowledge on robot learning before. "Interesting", "familiar" and "comfortable" emotion value seems to be an important aspect for the implementation of robot as their therapeutic learning approach. Further research will investigate on the possibility of Kansei robotic implementation via robot assisted learning suitable with elderly emotion as well as enhance their emotion wellbeing. © 2017 The Authors.


Yabuuchi Y.,Shimonoseki City University | Kawaura T.,Kansai Medical University
Smart Innovation, Systems and Technologies | Year: 2016

Japanese population is 128 million, and the population of younger than 15 years old is less than elderly people at least 65 years old. Then, Japanese population pyramid is distorted. While the population under 65 years old has reduced, the population 65 years old and above have increased. Japanese major health insurance society has reported that lifestyle-related medical costs are about 1,791 billion yen in fiscal medical expenses total about 1,184 billion yen. It becomes about 15% of the total. This is a great amount of costs which is able to be ignored. Therefore, we analyzed the relation between the medical expense and food intakes by a regression model, and the results have been reported in InMed-14. In addition,we have analyzed the relation between the numbers of outpatient and food intakes in five years by a regression model. It is because lifestyle is made by continuing food intakes. Although we have obtained the results by these analyzes, however we need to analyze the relationships between factors.Therefore, in this paper, we analyze the relation between these factors by a principal component analysis. © Springer International Publishing Switzerland 2016.


Yabuuchi Y.,Shimonoseki City University | Kawaura T.,Kansai Medical University
International Conference on Advanced Mechatronic Systems, ICAMechS | Year: 2014

Management systems and economic systems are complex because they involve human behaviors and are affected by many factors. When a system includes uncertainty such as those concerning human behaviors, a fuzzy system approach plays a pivotal role in its analysis. Therefore, many results concerning their work have been reported. Yabuuchi et al. have proposed a fuzzy autocorrelation model which uses the concept of soft computing for the Box-Jenkins model. Moreover, fuzzy random variables have been used for the fuzzy autocorrelation model and a predictive accuracy of the model improved. In this work, an improved fuzzy autocorrelation model by using fuzzy random variables will be compared with a fuzzy autocorrelation model by Japanese national consumer price index. And we will be confirmed the proposed model can be with high accuracy. © 2014 IEEE.


Yabuuchi Y.,Shimonoseki City University | Watada J.,Waseda University
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2011

Since management and economic systems are complex, it is hard to handle data obtained in management and economic areas. Hitherto, in the fields, much research has focused on the structure and analysis of such data. H. Tanaka et al. proposed a fuzzy regression model to illustrate the potential possibilities inherent in the target system. J. C. Bezdek proposed a switching regression model based on a fuzzy clustering model to separate mixed samples coming from plural latent systems and apply regression models to the groups of samples coming from each system. It is hard to illustrate a rough and moderate possibility of the target system. In this paper, to deal with the possibility of a social system, we propose a new fuzzy robust regression model.


Yabuuchi Y.,Shimonoseki City University | Watada J.,Waseda University
ICIC Express Letters | Year: 2010

The objective of a fuzzy regression model is to illustrate the potentialpossibilities of the target system. In the interval fuzzy regression model,system possibilities are measured by the width of the interval indicated by themodel. If the center of the model coincides with the center of the possibilitydistribution, more information could be obtained about the possibilities of thetarget system. As the model should be intuitive, this would make the proposedmodel more user-friendly and broadly applicable. In this paper, we use thepopulation of a district and its number of households as a numerical example,and we use a basin area and a drift distance in Japan as an application of ourmodel to check its features. ICIC International © 2010.


Yabuuchi Y.,Shimonoseki City University | Watada J.,Waseda University
6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 | Year: 2012

Economic analyses are typical methods based on time-series data or cross-section data. Economic systems are complex because they involve human behaviors and are affected by many factors. When a system includes such uncertainty, as those concerning human behaviors, a fuzzy system approach plays a pivotal role in such analysis. In this paper, we propose a fuzzy autocorrelation model with confidence intervals of fuzzy random time-series data. This confidence intervals has an essential role in dealing with fuzzy random data on our fuzzy autocorrelation model which we have presented. We analyze tick-by-tick data of stock dealing and compare two time-series models, a fuzzy autocorrelation model proposed by us, and a new fuzzy time-series model which we propose in this paper. © 2012 IEEE.


Matsumoto Y.,Shimonoseki City University | Watada J.,Waseda University
Smart Innovation, Systems and Technologies | Year: 2016

Rough set theory was proposed by Z. Pawlak in 1982. This theory has high capability to mine knowledge based on decision rules from a database, a web base, a set and so on. The decision rule is widely used for data analysis as well. In this paper the decision rule is employed to reason for an unknown object. That is, the rough set theory is applied to analysis of economic time series data. An example shown in the paper indicates how to acquire knowledge from time series data. At the end we suggest its application to predictions. © Springer International Publishing Switzerland 2016.


Yabuuchi Y.,Shimonoseki City University | Watada J.,Waseda University
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2012

A possibilistic regression model illustrates the potential possibilities inherent in the target system by including all data in the model. Tanaka and Guo employ exponential possibility distribution to build a model, while Inuiguchi et al. and Tajima are independently working on coinciding between the center of a possibility distribution and the center of a possibilistic regression model. Typically, samples influence and distort the shape of the model if they are far from the center of data. Yabuuchi and Watada have developed a model for describing the system possibility using the center of a possibilistic fuzzy regression model and an approach that mends the distortion of the model. The objective of this paper is to analyze the Japanese economy using our model, and to show the usefulness of our model by analysis results.


Yabuuchi Y.,Shimonoseki City University
ICIC Express Letters | Year: 2015

One of the advantages of the fuzzy regression model proposed by H. Tanaka is that it can provide an intuitive understanding of a possibilistic system by analyzing its intervals. However, an interval fuzzy regression model is sensitive to unusual samples, and the center of the model does not coincide with the center of the possibility distribution. Yabuuchi and Watada proposed a fuzzy robust regression model to describe the possibility distribution of a system using the center of a fuzzy regression model, and introduced an approach for fxing distortions in such a model. Such a model is constructed by maximizing the sum of the possibility grades derived from an obtained model and its data. However, in order to obtain a model, it is necessary to dene its parameters. In addition, the center of the data distribution may have some relationship with the centroid of the model. In this paper, we compare two fuzzy robust regression models: one is possibility grade-based and the other is centroid-based, using numerical examples. © 2015 ICIC International.


Yabuuchi Y.,Shimonoseki City University
6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 | Year: 2012

A fuzzy regression model illustrates the potential possibilities inherent in the target system by including all data in the model. Tanaka and Guo employ exponential possibility distribution to build a model, while Inuiguchi et al. and Tajima are independently working on coinciding between the center of a possibility distribution and the center of a fuzzy regression model. Typically, samples influence and distort the shape of the model if they are far from the center of data. Yabuuchi and Watada have developed a model for describing the system possibility using the center of a fuzzy regression model and an approach that mends the distortion of the model. This model is a fuzzy regression model building through possibility maximization. The objective of this paper is to analyze the Japanese economy using our model, and to show the usefulness of our model by analysis results. © 2012 IEEE.

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