MORISHITA Shin

Organization

Faculty of Environment and Information Sciences, Division of Artificial Environment and Information

Title

Professor

Research Fields, Keywords

Intelligent material, Neural network, Vibration control, Cellular Automata, Cell dynamics

Mail Address

E-mail address



写真a

The Best Research Acheivement as Researcher Life 【 display / non-display

  • 【Published Thesis】 Controllable Squeeze Film Damper (An application of Electro-Rheological Fluid )  1992

    【Published Thesis】 Low-intensity Pulsed Ultrasound Activates the Phosphatidylinositol 3 Kinase/Akt Pathway and Stimulates the Growth of Chondrocytes in Three-dimensional Cultures: a Basic Science Study  2008

Graduating School 【 display / non-display

  •  
    -
    1978.03

    Yokohama National University   Faculty of Engineering   Graduated

Graduate School 【 display / non-display

  • 1978.04
    -
    1983.03

    The University of Tokyo  Graduate School, Division of Engineering  Doctor Course  Completed

Degree 【 display / non-display

  • Doctor of Engineering -  The University of Tokyo

External Career 【 display / non-display

  • 2001.10
    -
    2018.03

    Yokohama City University. Visiting Professor  

  • 1991.04
    -
    1997.03

    University of Tokyo   Institute of Industrial Science   Researcher  

  • 1991.01
    -
    1991.02

    Massachusetts Institute of Technology,   Visiting Scholar  

  • 1990.04
    -
    1990.12

    Princeton University   Visiting Fellow  

  • 1983.04
    -
    1985.09

    Toyohashi Institute Technology, Research Associate   Research Assistant  

Academic Society Affiliations 【 display / non-display

  • 1982.04
     
     
     

    Japan Society of Mechanical Engineers

Field of expertise (Grants-in-aid for Scientific Research classification) 【 display / non-display

  • Dynamics/Control

  • Design engineering/Machine functional elements/Tribology

 

Books 【 display / non-display

  • Biomedical Applications of Vibrations and Acoustics in Therapy, Bioeffects and Modeling

    Ahmed Al-Jumaily, etc (Part: Joint Work , Range: Chapter 4: Effeccts of Mechanical Vibration on Cultured Osteoblasts )

    アメリカ機械学会  2008 ISBN: 9780791802755

Thesis for a degree 【 display / non-display

  • ジャーナル軸受内油膜の動的特性

    森下 信 

      1983.03  [Refereed]

    No Setting   Single Work

Papers 【 display / non-display

  • The effect of medium sloshing on cell proliferation

    YAMAMOTO Taichi, MORISHITA Shin

    The Proceedings of the Dynamics & Design Conference ( The Japan Society of Mechanical Engineers )  2018 ( 0 )   2018.08

    Joint Work

     View Summary

    <p>The effect of long term medium flow on bone cell proliferation was investigated experimentally. Mechanical stimulation is known to increase bone density and strength in our bodies due to the responses of cells inside bones. It is reported that cultured bone cell density is increased by mechanical vibration and its effect is dependent on the frequency. However, how cells respond to mechanical vibration is still unknown. A variety of chemical or physical phenomena should be induced by mechanical vibration. In order to understand the mechanism, we need to find out which of the phenomena largely affects cell proliferation. Previous experiment by our group has indicated that medium sloshing, one of the frequency dependent phenomena, affects bone cell proliferation. In this paper, in order to understand how the sloshing affects cell proliferation, we focused on one of the sloshing-induced phenomena, medium flow. Bone cells were cultured under medium flow which is generated by micro-pumps. Time over change of the cell density was measured and compared with that of controls and vibrations. The obtained result indicates that bone cell proliferation is increased by medium flow and its effect is about a half of that of mechanical vibration.</p>

    DOI CiNii

  • Pseudo random wave response of a Vibration Control System using Swarm Intelligence

    HIURA Takuya, MORISHITA Shin

    The Proceedings of the Dynamics & Design Conference ( The Japan Society of Mechanical Engineers )  2018 ( 0 )   2018.08

    Joint Work

     View Summary

    <p>The response of the vibration control system using swarm intelligence for pseudo random wave has been investigated. As an example of swarm intelligence, a swarm of ants can find an optimal route between their nest and the food in various environment using special pheromone. In this sense, the network of agents in a swarm may have some kind of intelligence or higher function appeared in a simple agent, which is defined as the swarm intelligence. The concept of swarm intelligence may be applied in diverse engineering fields such as flexible pattern recognition, adaptive control system, or intelligent monitoring system, because some kind of intelligence may emerge on the network without any special control system. In previous studies, the swarm intelligence was applied to a mechanical vibration control system composed of a network of units equipped sensors and actuators. Five units composed of a displacement sensor and a variable dynamic damper were placed on each mass of the five degree-of-freedom lumped mass system. A unit composed of a sensor was placed on the basement. Each unit was connected to each other to exchange information of state variables measured by sensors on each unit. Because the network of units configured as a mutual connected network, a kind of artificial intelligence, the network of units could memorize the several expected vibration-controlled patterns and could produce the signal to the actuators on the unit to reduce the vibration of target system. In this study, pseudo random wave response of a vibration control system was simulated. The results showed that the vibration control system could reduce the vibration, especially the response to first natural frequency compared with ON-OFF controller.</p>

    DOI CiNii

  • Damping Characteristics of Micro Mass-Spring System

    HAMADA Shohei, MORISHITA Shin

    The Proceedings of the Dynamics & Design Conference ( The Japan Society of Mechanical Engineers )  2018 ( 0 )   2018.08

    Joint Work

     View Summary

    <p>In this study, a very small mass-spring system was constructed and its damping characteristic was studied experimentally. In the field of dynamics, the dominant theory will change depending on the size of an object. The mathematical model relevant to the motion of an object is called Newtonian dynamics, but it is only an approximation. Even in the case the size is not so small as governed by quantum mechanics, the influence of inertia, viscous force, or electro-static force will change when a dynamic system is miniaturized. Therefore, it is necessary to estimate these dynamic effects quantitatively to treat a very small physical system as represented by micro-machine. In this paper, a small mass-spring system was constructed and the free vibration experiment in the vacuum chamber was conducted to clarify its damping properties. The diameter of wire of the coil spring was around 20 μm, and the diameter of coil spring was around 400 μm. As a result, it was revealed experimentally that the air resistance is too large to ignore in micro scale.</p>

    DOI CiNii

  • Simulation of object transportation by a robotic swarm with learning ability

    ISHIDU Ryota, MORISHITA Shin

    The Proceedings of the Dynamics & Design Conference ( The Japan Society of Mechanical Engineers )  2018 ( 0 )   2018.08

    Joint Work

     View Summary

    <p>A transportation simulation of multiple objects to the appropriate goals by a robotic swarm has been performed with learning ability of the swarm. It is often observed that each insect in a colony seems to have its own agenda, and the group as a whole appears to be highly organized. By swarming, social insects achieve difficult tasks that an insect cannot manage alone. This collective behavior emerged from a group of social insects has been called "swarm intelligence". Applications of swarm intelligence show high robustness and scalability, but, when it comes to applying to some intelligent task, the adjusting process of the parameters for a desired cooperative behavior may be a difficult, time-consuming task for a human designer. On the other hand, the artificial neural networks are known to have the learning ability. In this study, the swarm behavior in nature was simulated by "Boids" model. Boids model was known to be able to simulate the motion of a flock of birds by simple rules. Using this model, a cooperative transportation task has been simulated. The cooperative transportation task is to transport some objects by a swarm. In addition, the task of decision-making problem about transportation goal has been added. In this problem, the swarm of Boids makes a decision about the goal from the size of an object, considering each Boids as a unit of artificial neural networks, the network of Boids maps to the transportation destinations. Additionally, the back-propagation method has been applied to learn the appropriate goals. As a result, it is shown that the artificial swarm acquires the learning ability how to decide an appropriate goal for given objects.</p>

    DOI CiNii

  • Effects of Learning Patterns on a Vibration Control Performance using Swarm Intelligence

    Takuya Hiura and Shin Morishita

    Proceedings of 14th International Conference on Motion and Vibration Control   2018   2018.08  [Refereed]

    Joint Work

     View Summary

    The performance of a vibration control system based on a concept of “swarm intelligence” has been studied. There are various examples of the swarm intelligence in the nature, a swarm of ants, birds, or fish. In this sense, the network of agents in a swarm may have some kind of intelligence or higher function appeared in a simple agent, which is defined as the swarm intelligence. The concept of swarm intelligence may be applied in diverse engineering fields such as flexible pattern recognition, adaptive control system, or intelligent monitoring system, because some kind of intelligence may emerge on the network without any special control system. In previous studies, the swarm intelligence was applied to a mechanical vibration controlling system composed of a network of units equipped sensors and actuators. In this study, the relationship between the patterns given to the control system in the learning procedure and its vibration reduction performance was investigated. The principal patterns were selected for learning process of the network from the vibration mode of the model in this paper. The simulation results showed that the control system learning the patterns from vibration mode could reduce vibration amplitude more effectively than the system learning the pattern designed so that the amplitude of mass might be reduced at a different mass position.

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Review Papers 【 display / non-display

  • Development of Evacuation Simulator by Cellular Automata

      172   16 - 21   2013.09

    Introduction and explanation (scientific journal)   Joint Work

  • Rheological Property of Smart Fluid and Application Technique

    Journal of Korea Fluid Power System Society   1 ( 1 ) 40 - 49   2004.03

    Introduction and explanation (scientific journal)   Joint Work

  • Introduction to Science of Complex Systems

      49 ( 1 ) 17 - 22   2004.01

    Introduction and explanation (scientific journal)   Single Work

Grant-in-Aid for Scientific Research 【 display / non-display

  • Grant-in-Aid for Scientific Research(B)

    Project Year: 2015.04  -  2018.03 

  • Grant-in-Aid for challenging Exploratory Research

    Project Year: 2015.04  -  2016.03 

  • Grant-in-Aid for challenging Exploratory Research

    Project Year: 2014.04  -  2015.03 

  • Grant-in-Aid for challenging Exploratory Research

    Project Year: 2013.04  -  2014.03 

  • Grant-in-Aid for challenging Exploratory Research

    Project Year: 2012.04  -  2013.03 

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Social Contribution(Extension lecture) 【 display / non-display

  • ACRI 2014

    2014.09