• Journal of the Korea Society for Simulation
• /
• v.20 no.4
• /
• pp.105-114
• /
• 2011

The roadmap-based planning is a path planning method which is used widely for a goal-directed movement in Robotics and has been applied to the world of computer animation such as computer games. However it is unnatural for computer characters to follow the path planned by the roadmap method as it is performed in Robotics. Flocking which is used for realistic and natural movements in computer animation enables character's movement by using a few simple rules without planning unlike the roadmap method. However it is impossible to achieve a goal-directed movement with flocking only because it does not keep states. In this paper we propose a simulation method which combines planning based on the road map with reactive actions for natural movements along the path planned. We define and implement steering behaviors for a leader which are needed to follow the trajectory naturally by analysing characteristics of roadmap-based paths and for the rest of members which follow the leader in various manners by detecting obstacles. The simulations are performed and demonstrated by using the implemented steering behaviors on every possible combination of roadmap-based path planning methods and models of configuration spaces. We also show that the detection of obstacle-collisions can be done effectively because paths are planned in the configuration space in which a moving object is reduced to a point.

• 한국정보통신설비학회:학술대회논문집
• /
• 2005.08a
• /
• pp.259-262
• /
• 2005

Ground resistance measurement is an elementary technique for the evaluation of grounding system. There are main environmental factors to consider for correct measurement but the problem is that it is practically most cases to measure ground resistance unable to know the factors. This paper presents a methodology toward true value of resistance in the unknown circumstances, utilizing the defined term 'variation rate' of potential difference curve appearing in the distance to a current probe as in the three point fall-of-potential method which comprises the characteristics of environmental factors. This methodology is a induced result from the previous demostrated studies.

• Journal of Food Hygiene and Safety
• /
• v.27 no.4
• /
• pp.395-400
• /
• 2012

In this study, we analyzed the database for items reported to Korea Food and Drug Administration as for manufactured health/functional food during 2010. There were 183 health functional food products manufactured in domestic having over 2 functional ingredients (hereinafter, combinational health functional food) among total 7319 products. Among 183 products, there were 177 products having over two kinds of functional ingredient and 6 products were over 3 ingredients. The most commonly used functional ingredients in the combinational health functional food were Garcinia cambogia extracts which were used in 41 products, Octacosanol and Saw Palmetto extract. When we searched the safety information for the pair of ingredients used in combinational health functional food using several database, there were no reports for safety concern. However, as there are still safety concerns when intake various functional ingredients at once, we suggested to enforce the reporting system of adverse event in order to strength safety management of health functional food. With these complement, the safety management of health functional food might be achieved including a combinational products.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.2
• /
• pp.214-224
• /
• 2024

Sonobuoys are disposable devices that utilize sound waves for information gathering, detecting engine noises, and capturing various acoustic characteristics. They play a crucial role in accurately detecting underwater targets, making them effective detection systems in anti-submarine warfare. Existing sonobuoy deployment methods in multistatic systems often rely on fixed patterns or heuristic-based rules, lacking efficiency in terms of the number of sonobuoys deployed and operational time due to the unpredictable mobility of the underwater targets. Thus, this paper proposes an optimal sonobuoy placement strategy for Unmanned Aerial Vehicles (UAVs) to overcome the limitations of conventional sonobuoy deployment methods. The proposed approach utilizes reinforcement learning in a simulation-based experimental environment that considers the movements of the underwater targets. The Unity ML-Agents framework is employed, and the Proximal Policy Optimization (PPO) algorithm is utilized for UAV learning in a virtual operational environment with real-time interactions. The reward function is designed to consider the number of sonobuoys deployed and the cost associated with sound sources and receivers, enabling effective learning. The proposed reinforcement learning-based deployment strategy compared to the conventional sonobuoy deployment methods in the same experimental environment demonstrates superior performance in terms of detection success rate, deployed sonobuoy count, and operational time.