• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.64-75
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• 2007

Service discovery protocols is software components to find specific services or resources on network. The SLP defined by IETF protocol is a framework for automatic service discovery on IP based networks. Automatic service discovery is an important component on ubiquitous computing environment. This paper proposes a service discovery architecture named as SLPA(Service Location Protocol based on AMAAM). AMAAM(Mobility Agent Advertisement Mechanism) is an aggregation-based Mobile IP implementation in MANET. In SLPA, the role of the directory agent is assigned to the mobility agent in AMAAM. The mobility agent periodically beacons an advertisement message which contains both the advertisement of the directory agent in SLP and the advertisement of the mobility agent in Mobile IP. For evaluating the functional correctness of SLPA and the overhead of maintaining a service directory of SLPA. We simulate SLPA using ns-2 and analyze the overhead of control overheads for the aggregation. Through the simulation experiments we show the functional correctness of the proposed architecture and analyze the performance results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1468-1473
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• 2005

In this paper, I proposed the INTelligent Agent System by Kohonen's Self Organizing Neural Network (INTAS). INTAS creates each user's profile from the information. Based on it, learning community grouping suitable to each individual is automatically executed by using unsupervised learning algorithm. In INTAS, grouping and learning are automatically performed on real time by multiagents, regardless of the number of learners. A new framework has been proposed to generate multiagents, and it is a feature that efficient multiagents can be executed by proposing a new negotiation mode between multiagents..

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.190-194
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• 1998

In this paper, we introduce the micro robot soccer playing system as a standard test bench for the study on the multiple agent system. Our method is based on following viewpoints. They are (1) any complex behavior such as cooperation among agents must be completed by sequential basic actions of concerned agents. (2) those basic actions can be well defined, but (3) how to organize those actions in current time point so as to result in a new stale beneficial to the end aim ought to be achieved by a kind of self-learning self-organization strategy.

• ICROS
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• v.3 no.4
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• pp.40-44
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• 1997

이 글에서는 국제적인 연구 개발 과제인 홀로닉 제조시스템에 대하여 개념, 목표와 현황과 HMS에서의 핵심 연구 내용을 기술하였다. 홀로닉 시스템의 개념은 소프트웨어 agent와 agent-based 시스템과 유사하다. 그러나, 가장 큰 차이점은 제조 공정을 조직화하여 표현하는 홀론과 홀론 조직은 부분과 전체의 관계를 더욱 잘 표시할 수 있다는 점이다. HMS 회원사에 의하여 개발되는 모델 시스템들을 통하여 HMS 개념의 중요성과 지능형 제조 시스템에 응용될 수 있다는 점이 확인될 수 있을 것이다.

• Food Science and Biotechnology
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• v.14 no.4
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• pp.487-492
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• 2005

Simple competition plate bioassays of Pichia anomala SKM-T and Galactomyces geotrichum SJM-59 were conducted to evaluate their potential as biological control agents that inhibit growth of Botrytis cinerea during post-harvest storage of strawberries (Fragaria ${\times}$ ananassa Duche, Red-Pearl). Occurrence rates of fungi on the surface of yeast-treated strawberries were evaluated during storage at $4^{\circ}C$. P. anomala SKM-T and G. geotrichum SJM-59 showed antifungal activities on agar plate, and P. anomala SKM-T maintained its desirable antifungal activity on surface of strawberries and its physicochemical properties during storage. Sensory evaluation was based on kinesthetics and consumer acceptability. Due to its potential antifungal activity, P. anomala SKM-T could function as biological control agent against spoilage fungi during post-harvest storage of strawberries.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.622-626
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• 2012

This paper presents synchronization of LTV (Linear Time-Varying) MAS (Multi-Agent Systems) with heterogeneous time-varying disturbances under a fixed, connected, and undirected communication network. All the agents can collect only relative state information from their neighborhoods. To achieve synchronization of the MAS, an integral control scheme is proposed based on relative state information between agents.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1309-1314
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• 2003

If an agent has a learning ability using previous knowledge, then it is expected that the agent can speed up learning by interacting with environment. In this paper, we present an improved reinforcement learning algorithm using domain knowledge which can be represented by problem-independent features and their classifiers. Here, neural networks are employed as knowledge classifiers. To show the validity of our proposed algorithm, computer simulations are illustrated, where navigation problem of a mobile robot and a micro aerial vehicle(MAV) are considered.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.1-17
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• 2001

This paper deals with an agent-based decision-supporting system for Taguchi experiment planning. Among the four major parts of Taguchi experiment, the planning phase includes the most important decision-making issues such as determination of experiment objectives, quality characteristics, and control factors. The planning phase, however, has not been paid proper attention by experiment designers. In this research, an agent-based decision-supporting system for Taguchi experiment planning has been developed to facilitate the planning tasks of experiment designer. The decision-supporting system is composed of two agent-based mechanisms. The first employs an Internet agent that collects the domain knowledge from knowledge providers who may be distributed in remote places. Another agent then visualizes the collected knowledge and reports it to the experiment designer. Engineers who would normally have difficulties in collaborating because of limitations on their time or because they are in different places can easily work together in the same experiment team and brainstorm to make good decisions. The second agent-based mechanism offers context-sensitive advice generated by another intelligent agent during the experiment planning process. it prevents the experiment designer from making improper decisions, which will increase the feasibility of the experiment and minimize the unnecessary expense of time and resources.

• Journal of the Korean Graphic Arts Communication Society
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• v.25 no.1
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• pp.43-52
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• 2007

Offset printing is one of the well known printing technique of lithographic process and consists of image area and 'non-image area on a flat image carrier. The surface tension of dampening water can be controlled by adding IPA after mixing of raw water and etching solution. The etching solution contains a surfactant for reducing surface energy, a clean agent for non-imaging area, wetting agent for protecting non-imaging area from oil components like ink and also an emulsifying agent for controlling emulsification. In this study, the present situation of dampening water maintenance has examined by collecting dampening water using at domestic companies. The pH related to dampening water, conductivity, contact angle, emulsification curve are measured to define the current situation of dampening water control of each companies and to analyze the relationship among measured properties. In the study most of companies among 16 printing companies tested controlling dampening water through pH value. However, the quality of printing has varied depending upon conductivity, contact angle, IPA content, and emulsification value. The control of dampening water should be carry at the state of the standard when adding proper ratio of etching solution. It would be more effective when pH or conductivity control carries out in parallel with controlling dampening water. Therefore the concept that pH5.5 is correct is based concept. Based on these initial tests it is defined that the standardization of dampening water control is required.

• Wind and Structures
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• v.39 no.4
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• pp.271-285
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• 2024

The multiple-fan wind tunnel is an important facility for reproducing target wind field. Existing control methods for the multiple-fan wind tunnel can generate wind speeds that satisfy the target statistical characteristics of a wind field (e.g., power spectrum). However, the frequency-domain features cannot well represent the nonstationary winds of extreme storms (e.g., downburst). Therefore, this study proposes a multiple-fan wind tunnel control scheme based on Deep Reinforcement Learning (DRL), which will completely transform into a data-driven closed-loop control problem, to reproduce the target wind field in the time domain. Specifically, the control scheme adopts the Deep Deterministic Policy Gradient (DDPG) paradigm in which the strong fitting ability of Deep Neural Networks (DNN) is utilized. It can establish the complex relationship between the target wind speed time series and the current control strategy in the DRL-agent. To address the fluid memory effect of the wind field, this study innovatively designs the system state and control reward to improve the reproduction performance based on historical data. To validate the performance of the model, we established a simplified flow field based on Navier Stokes equations to simulate a two-dimensional numerical multiple-fan wind tunnel environment. Using the strategy of DRL decision maker, we generated a wind speed time series with minor error from the target under low Reynolds number conditions. This is the first time that the AI methods have been used to generate target wind speed time series in a multiple-fan wind tunnel environment. The hyperparameters in the DDPG paradigm are analyzed to identify a set of optimal parameters. With these efforts, the trained DRL-agent can simultaneously reproduce the wind speed time series in multiple positions.