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Transactions of the Institute of Systems, Control and Information Engineers Vol. 34 (2021), No. 11

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

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  29. Vol. 9 (1996)

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  30. Vol. 8 (1995)

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  32. Vol. 6 (1993)

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  33. Vol. 5 (1992)

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  34. Vol. 4 (1991)

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  35. Vol. 3 (1990)

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  36. Vol. 2 (1989)

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  37. Vol. 1 (1988)

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Transactions of the Institute of Systems, Control and Information Engineers Vol. 34 (2021), No. 11

The Stability Analysis of the Stochastic Infectious Model under Subclinical Infections and the Influence of the Random Noise on Its Stability

Masaaki Ishikawa

pp. 279-286

DOI:

10.5687/iscie.34.279

Abstract

The stability of the stochastic infectious models under subclinical infections and the influence of the random noise on the stability are considered in this paper. As we all know, the corona virus (COVID-19) has a great impact on economy and society since December 2019. Many people have still been suffering from COVID-19 infection. The control of COVID-19 infection is an emergent issue in epidemiology. One of characteristics of COVID-19 infection is the existence of subclinical infections. Hence, we analyze the stability of the infectious disease under subclinical infections in this paper. In the realistic spread of the infectious disease, environmental change and individual difference cause some kinds of random fluctuations in the model parameters. So, we introduce the random fluctuation into consideration in the model construction and we propose the stochastic infectious models with subclinical infections. Since the stability analysis of the infectious model is effective in the control of the spread of the infectious disease, we analyze the stability of the stochastic infectious model with subclinical infections. By numerical simulations, we show the efficacy of the stability theorems derived in this paper and consider the influence of the random noise on the stability using the Lyapunov exponent.

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The Stability Analysis of the Stochastic Infectious Model under Subclinical Infections and the Influence of the Random Noise on Its Stability

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Ris

Gain Scheduling for Sampled-data State Estimation over Lossy Networks

Kenji Sugimoto, Toshitaka Aihara, Masaki Ogura, Kenta Hanada

pp. 287-293

DOI:

10.5687/iscie.34.287

Abstract

This paper proposes a design method for sampled-data state estimator over lossy networks. When a measurement signal loss is detected, the proposed estimator switches gains and continues to update the estimate based upon last received measurement. The gains are computed in advance by means of a common solution of linear matrix inequalities so that the estimation is suboptimal with respect to the mean square error in the steady state. The effectiveness of the proposed method is illustrated/evaluated via numerical simulations.

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Gain Scheduling for Sampled-data State Estimation over Lossy Networks

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Three Degree-of-freedom Modeling of the Random Fluctuation Arising in Human-bicycle Balance

Katsutoshi Yoshida, Mikinori Ito, Hayate Kaido, Yoshikazu Yamanaka

pp. 294-302

DOI:

10.5687/iscie.34.294

Abstract

A novel three degree-of-freedom (DOF) fluctuation model that accurately reproduces the probability density functions (PDFs) of human-bicycle balance motions is proposed. We experimentally obtain the time series of the roll angular displacement, wheel's lateral displacement, steering angular displacement, and each velocity of them. Constructing the PDFs of these time series as training data, we identify the model parameters through the use of particle swarm optimization (PSO) that minimizes the squared residuals between the experimental participants' PDFs and those simulated by our model. Over 97% PDF fitnesses were obtained for all participants, indicating that our proposed model can successfully simulate the measured human PDFs.

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Three Degree-of-freedom Modeling of the Random Fluctuation Arising in Human-bicycle Balance

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Identifying an Egg-Containing Follicle by Displacement Analysis of the Follicle Border

Kohei Okishio, Yoshiharu Koya, Hidehiko Matsubayashi, Tomomoto Ishikawa

pp. 303-309

DOI:

10.5687/iscie.34.303

Abstract

The number of births in Japan has been declining over the past few years, and this declining birthrate has become a social problem. An infertility treatment known as the in-vitro fertilization (IVF) has been developed as a countermeasure, in which a doctor visually confirms the follicles through an ultrasonogram, extracts them one by one to check whether they have eggs, and performs artificial insemination. As, the presence of the egg cannot be confirmed from the ultrasonogram, it is often observed that follicles that do not contain eggs are unnecessarily extracted. Therefore, this study effectively determines the presence or the absence of an egg by analyzing the displacement of the follicle border. First, the candidate points for the follicle border are determined, and then the candidate points that are unlikely to be the border points are removed. The border is estimated after extracting the candidate points of the border using the difference in the brightness values near the border. The presence or absence of the egg is determined based on the displacement of the border with respect to the initial centroid. The accuracy of this method can be improved by increasing the amount of data in a future study.

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Identifying an Egg-Containing Follicle by Displacement Analysis of the Follicle Border

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