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Senda, Yasuhiro,Blomqvist, Janne,Nieminen, Risto M. The Korean Vacuum Society 2017 Applied Science and Convergence Technology Vol.26 No.1
We investigated the stability of ionic configurations of the tip of the cantilever in non-contact AFM.; For this, we used a computational model that couples the ionic motion of the MgO surface and the oscillating cantilever. The motion of ions was connected to the oscillating cantilever using a coupling method that had been recently developed. The adhesive process on the ionic MgO surface leads to energy dissipation of the cantilever. It is shown that limited types of ionic configurations of the tip are stable during the adhesive process. Based on the present computational model, we discuss the adhesive mechanism leading to energy dissipation.
Yasuhiro Senda,Janne Blomqvist,Risto M. Nieminen 한국진공학회 2017 Applied Science and Convergence Technology Vol.26 No.1
We investigated the stability of ionic configurations of the tip of the cantilever in non-contact AFM.; For this, we used a computational model that couples the ionic motion of the MgO surface and the oscillating cantilever. The motion of ions was connected to the oscillating cantilever using a coupling method that had been recently developed. The adhesive process on the ionic MgO surface leads to energy dissipation of the cantilever. It is shown that limited types of ionic configurations of the tip are stable during the adhesive process. Based on the present computational model, we discuss the adhesive mechanism leading to energy dissipation.
Dynamics of Relationship: For Goal-Oriented Control of Group Behavior
Yoshiaki Senda,Ivan Tanev,Katsunori Shimohara 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
When a critical amount of pedestrians herd together, pedestrians are showed several series of group behaviors. Existing dynamical model can duplicate pedestrian’s group behavior. But we create dynamical model in each case. Why do we need to create dynamical model in each case? We believe that we don’t understand what are the assumed forces and interactions. Our challenge is to explain forces and interactions between pedestrians in a more detailed, primitive level. We are using Direct-Vision-Based Reinforcement Learning to construct the primitive model. This learning system needs not a priori assumption ? only a reward.