Masayuki Takeda

An Improved Evacuation Guidance System Based on Ant Colony Optimization

This paper proposes an evacuation guidance method for use in disaster situations. The method is based on ant colony optimization (ACO). We have implemented the method as ACO-based evacuation system in a simulator and examined the feasibility of the system. Since we cannot depend on the communication infrastructures with a disaster occurs, we make the system utilize mobile ad hoc network (MANET). We expect the ACO-based evacuation system produces quasi-optimized evacuation paths by the cooperation of multiple agents, while MANET provides communication between agents in the environment lacking of network infrastructure. Even though a number of ACO-based guidance systems have been developed, there are still some questions whether evacuees who follow the evacuation paths given by ACO are really safe. We examined how safe following these paths is by simulations, and found that they were not safe in some cases. As a result, in this paper, we propose an improved ACO-based evacuation system that equips deodorant pheromone to actively erase ACO pheromone traces when dangerous locations are found. Our simulation results show the use of deodorant pheromone can improve the safety level of the evacuation guidance system without degrading evacuation efficiency.

ism : improvisation supporting systems with melody correction and key vibration

This paper describes improvisation support for musicians who do not have sufficient improvisational playing experience. The goal of our study is to enable such players to learn the skills necessary for improvisation and to enjoy it. In achieving this goal, we have two objectives: enhancing their skill for instantaneous melody creation and supporting their practice for acquiring this skill. For the first objective, we developed a system that automatically corrects musically inappropriate notes in the melodies of users’ improvisations. For the second objective, we developed a system that points out musically inappropriate notes by vibrating corresponding keys. The main issue in developing these systems is how to detect musically inappropriate notes. We propose a method for detecting them based on the N-gram model. Experimental results show that this N-gram-based method improves the accuracy of detecting musically inappropriate notes and our systems are effective in supporting unskilled musicians’ improvisation.