Kyosuke Takahashi

A mobile application system for sightseeing guidance using augmented reality

Recently, the development of the communications networks for mobile phones has led to the services to provide sightseeing information via mobile phone at tourist sites. However, existing tourist information guide contents such as web and guide books provide information in one direction especially in non-activated sightseeing. In this study, an attempt is made to develop a mobile application system for sightseeing guidance to solve these problems. With this application system, users can post sightseeing information and share it by using mobile phones. This will enable them to improve the sightseeing information. Furthermore, the proposed application system uses augmented reality. Augmented reality is a technology which enhances a real environment with virtual objects. Therefore, at the sight spot, the application system can be used as a sightseeing guidance system that superimposes annotations on a real world. Especially, the proposed application system presents virtual tour guides and route so as to be able to assist their tour. In this study, an experiment in Takatsuki city is presented to demonstrate the validity of the proposed application.

A proposal of district impact analysis method and application to the action plan for logistics function

In a large scale disaster, regional organizations must strategically cooperate with the others to recover and reconstruction disaster regions. A District Continuity Plan (DCP) and its action plan are required for each organization to facilitate cooperative actions after a disaster. However, to build consensus among DCP developer is difficult because important bases of the organization are different. In order to solve the problems, it is effective a decision support system which enable to present a specific recovery plan for action plan. In this study an attempt is made to propose a District Impact Analysis (DIA) method using a genetic algorithm and a concept of the development action plan based on live design. Several recovery planning of road access and logistics functions are presented to demonstrate the effectiveness and applicability of the proposed method. Language: ja

Analysis of Evolution Mechanism for Multi-agent Optimization Method

In recent years, many researchers focus on metha-heuristics as a method to large-scale and complicated optimization problems. in these problems, an optimization method requires versatility and applicability to a characteristic of design space by combining appropriate global and local searches. Multi-Agent Optimization (MAO) is a method based on Multi-Agent System, and it has been proposed to satisfy these requirements. in this method, agents which represent solution candidates evolve by their autonomous actions and interaction with each other. through these features, it is expected that MAO can perform global search with whole agents and local search with each agent efficiently. However, it is not clear what parameters are more effective to the evolution of MAO. in this paper, an attempt is made to verify the applicability of MAO to optimization problems by clarifying effects of its parameters with numerical experiments.