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Transactions of the Institute of Systems, Control and Information Engineers Vol. 26 (2013), No. 11

ISIJ International
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ONLINE ISSN: 2185-811X
PRINT ISSN: 1342-5668
Publisher: THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

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Transactions of the Institute of Systems, Control and Information Engineers Vol. 26 (2013), No. 11

On Second Statistical Moments for Capricious Vague Perceptions

Tokuo Fukuda

pp. 375-381

Abstract

In this paper, the author investigates the statistical moments such as expectations and variancesfor a class of fuzzy random sets, where the fuzzy random set is considered as a model of the capriciousvague perception of a crisp phenomenon or a crisp random phenomenon.First, the class of fuzzy random sets, which has been proposed by author[1–3], where the vagueperception of a crisp phenomenon fluctuates slightly but randomly by the state of a capriciousperson’s mind, is refined and its expectation and variance are introduced.Secondly, the refined class of fuzzy random sets is extended to the models for the capricious vagueperceptions of crisp random phenomena, and their expectations and variances are investigated fromthe viewpoint of the multi-valued logic.

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On Second Statistical Moments for Capricious Vague Perceptions

Optimal Vaccination Strategy under Saturated Treatment using the Stochastic SIR Model

Masaaki Ishikawa

pp. 382-388

Abstract

This paper is concerned with the control strategy by vaccination of the infectious disease spreadin the populations consisting of the susceptible, the infected and the recovered (SIR). In the realisticspread of the infectious disease, changes in the environment and the weather cause some kinds ofrandom fluctuations in the infection and the recovery rates, etc. Moreover, medical facilities havegenerally the maximal capacity for treatment of diseases. Taking these facts into consideration, wepropose the stochastic infectious model with vaccination and saturated treatment, and we considerthe stochastic optimal vaccination problem for the SIR model with saturated treatment using thestochastic maximum principle and the four-step scheme. We construct a feasible optimal vaccinationsystem. By numerical simulations, we validate the efficacy of the optimal vaccination strategy.

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Optimal Vaccination Strategy under Saturated Treatment using the Stochastic SIR Model

Monotone Smoothing Spline Curves Using Normalized Uniform Cubic B-splines

Hiroyuki Fujioka, Hiroyuki Kano

pp. 389-397

Abstract

This paper considers a problem on the non-negative derivative constraints on the cubic smoothingspline curves using normalized uniform B-splines as the basis functions. In particular, we derive acondition for monotonic constraints over interval based on the study of Fritsch and Carlon. Moreover,we present how these results are incorporated in the optimal smoothing spline problems. Theperformance is examined by a numerical example.

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Monotone Smoothing Spline Curves Using Normalized Uniform Cubic B-splines

State Estimation Approach for Depth Sensor's Posture Attached to a Vehicle or a Human Body

Masahiro Tanaka

pp. 398-406

Abstract

The author has been developing a navigation system for safety for mobile robots, mobility scooters and pedestrians by using depth sensors which can capture range data of image size. If the geometrical relation between the sensor and the space is completely known, each point of the captured range data can be classified into three groups: upper than the ground, on the ground, and lower than the ground. However, it is essential to be able to deal with the unpredictable change of the posture of the sensor due to the movement of the attached body. The author already developed a real-time estimation scheme of the posture including pitch angle, roll angle, and height from the observed data in the framework of optimization. In this paper, the author proposes an estimation scheme based on the state space model and apply Extended Kalman filter for the same application problem. We will compare the algorithms by experimental results and will show the usefulness of the proposed algorithm.

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State Estimation Approach for Depth Sensor's Posture Attached to a Vehicle or a Human Body

An Experimental Study on Coupled Balancing Tasks between Human Subjects and Artificial Controllers

Shigeki Matsumoto, Katsutoshi YoShida, Atsushi Higeta

pp. 407-414

Abstract

In this paper, we experimentally study cooperative human balancing tasks performed by a pair ofa human subject and an artificial controller, based on the coupled inverted pendula (CIP) model. Inorder to examine what kind of influence does the feedback gain of the controller on dynamic stabilitiesof the cooperative balancing tasks, we experimentally estimate Lyapunov exponents of balancingerrors of the system of human subject and artificial controller, in which the human subject is incooperation with the artificial controller having several different feedback gains. The result impliesthat the human subject seems to try to make the artificial controller minimally or neutrally stable.

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An Experimental Study on Coupled Balancing Tasks between Human Subjects and Artificial Controllers

Further Investigation of a Gaussian Sum Filter Based on Stochastic Equivalent Linearization

Sueo Sugimoto, Yukihiro Kubo, Masaharu Ohashi

pp. 415-424

Abstract

We proposed a stochastic (or statistical) Equivalent linearization - Gaussian Sum Filter(: EqGSFilter) for discrete time nonlinear Systems. Subsequently, in this paper, we investigate and showthe further results related to the EqGS Filter. Especially we discuss a method to apply Gauss-Hermite quadrature rules for evaluation of the conditional expected values of the quantities requiredto design the EqGS filter. Finally, we show the estimation results of AR modeling comparison withthe extended Kalman and the equivalent linearization filters.

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Further Investigation of a Gaussian Sum Filter Based on Stochastic Equivalent Linearization

Prediction of Regional Ionospheric Models with AR Model for GNSS Positioning in Japan

Masaharu Ohashi, Keisuke Nishimoto, Yasukihiro Kubo, Sueo Sugimoto

pp. 425-432

Abstract

In this paper, the ionospheric models for GNSS (Global Navigation Satellite System) positioningin the local area like as Japan are investigated and the prediction models are discussed. The ionosphericdelay is modeled by applying SCHA (Spherical Cap Harmonic Analysis). It is well knownthat the ionosphere varies according to solar activity. Therefore, ionospheric effect on GNSS positioningvaries with not only the position but also the local time, and it has a periodicity. The periodiccharacteristics of the ionosphere are investigated by SCHA ionospheric models. The purpose of thisresearch is to predict the ionospheric delay model for the real time positioning. Based on our investigation,the ionospheric delays are predicted with AR (Auto-Regression) model. Furthermore thecapability for ionospheric model prediction is discussed. In the experiments, the proposed predictionmodels are compared with Klobuchar model.

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Prediction of Regional Ionospheric Models with AR Model for GNSS Positioning in Japan

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