• Korean Journal of Pharmacognosy
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• v.33 no.2 s.129
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• pp.120-123
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• 2002

The possibility of Galla Rhois(GR) water extract as an antithrombotic agent was investigated. The effect of GR on platelet aggregation in human platelet-rich plasma(PRP) induced by collagen and ADP in vitro and coagulation parameters in a pathological model induced by endotoxin and hydrocortisone acetate(HA) in vivo were examined. In platelet aggregation assay, GR extract significantly inhibited platelet aggregation induced by collagen and ADP in a dose-dependent manner. GR extract significantly increased the number of platelet and shortened prothrombin time(PT) and activated thromboplastin time(APTT) as compared with the control in pathological model induced by endotoxin and HA. Also, GR extract significantly increased fibrinogen level as compared with the control in a pathological model induced HA. These results suggest that GR may be a promising antithrombotic agent.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.977-981
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• 2000

The traditional client-server model RPC and mobile agents have been used for interprocess communication between processes in different hosts. The performances of two mechanisme were analyzed in the literature [4, 6, 9]. But the security services which extensively affect the performance of systems because of low speed have not been considered. We propose two performance models considering the security services for the RPC and the mobile agent Through the analysis of the models, we show that the execution time of the mobile agent takes less than the RPC In the environment considering security services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5685-5700
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• 2018

Cyber intelligence, surveillance, and reconnaissance (ISR) has become more important than traditional military ISR. An agent used in cyber ISR resides in an enemy's networks and continually collects valuable information. Thus, this agent should be able to determine what is, and is not, useful in a short amount of time. Moreover, the agent should maintain a classification rate that is high enough to select useful data from the enemy's network. Traditional feature selection algorithms cannot comply with these requirements. Consequently, in this paper, we propose an effective hybrid feature selection method derived from the filter and wrapper methods. We illustrate the design of the proposed model and the experimental results of the performance comparison between the proposed model and the existing model.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.165-180
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• 2019

As game industry prospers, the negative side of games becomes highlighted as well as its contributions to economy growth. In spite of strong arguments for the necessity to regulations as a means to decrease addiction or overindulgence, research has produced future suggestions rather than quantifiable evidence. In this paper, we propose adopting a simulation approach in addition to quantitative approaches to better understand optimal regulatory levels since a simulation approach can visualize unexpected side effects of regulations. In this study, we suggest the application of an agent-based model (ABM) as a smart service to measure the effects of regulatory policies. We review cases applying ABM in various domains and consider the possibility of using an ABM to understand the effectiveness of web board-game regulations. We find that the ABM approach would be useful in several areas, such as the analysis of regulatory effects that reflect a variety of characteristics, the measurement of micro-regulatory effects, and the simulation of regulations.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.461-470
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• 2005

A dynamic supply chain that is composed of many different companies with different rent roles and interests allows free joining and secession. Buyers place orders simultaneously and manufacturers should compete each other for the orders. The purpose of our paper is how to find the optimal formation of supply chain ill a global viewpoint while allowing each member company to pursue his local goal The dynamic nature of supply chain formation causes the variation of cost depending on how many orders a manufacturer would accept. We propose a multi-agent based negotiation protocol that efficiently leads to the formation of optimal supply chain without giving up maximization of the individual profit in multi-agent environment of the make-to-order industry. The goal of the negotiation is to form a supply chain to minimize the overall sum of manufacturers' manufacturing cost, and earliness cost and tardiness cost based on SET model. We compare the negotiation protocol with Branch & Bound method. Finally, the validity and performance of buyer's negotiation has been tested experimentally.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.467-470
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• 2004

MANPro-based control is a novel control paradigm aimed at intelligent manufacturing systems on the basis of mobile agent-based negotiation process (MANPro). MANPro is a negotiation mechanism based on the agent-based control architecture and, especially, it adapts a mobile agent system called N-agent for the negotiation process. N-agent travels around the network of distributed manufacturing systems to acquire information, and it makes a decision for system control according to the obtained information. MANPro includes communication architecture and information architecture for intelligent shop floor control. MANPro also considers the following issues: (1) negotiation mechanism, (2) single-agent internal strategic policies, and (3) information model. Communication architecture concerns the first issue of the negotiation mechanism. It provides information exchanging mechanism with functional modules. In specific, N-agent is equipped with an intelligent reasoning engine with a built-in knowledge base. This reasoning engine is closely related to the single-agent internal strategic policies of the second issue. Finally, ontology-based information architecture addresses information models and provides a framework for information modeling on negotiation. In this paper, these three issues are addressed in detail and a framework of MANPro-based control is also proposed.

• Journal of the Society of Disaster Information
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• v.15 no.3
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• pp.402-408
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• 2019

Purpose: The study want to verify application the medium expantion foam extinguisher of expantion foam rate and fire extinguishing Performance test because the medium expansion system can maintain the discharge distance less affected by air currents, and the foam agent can be used efficiently. Method: For the study, the medium-expansion testing apparatus was manufactured and with synthetic surfactant foam agent of (class B) fire extinguishing model, and Fire Performance was analyzed for foam expansion rate and the fire agent consumption was measured and analyzed. Results: We measured the medium-spray testing apparatus and found that the expansion rate was 26.1 times. The test results of a 20-unit fire extinguishing model show that the extinguishing time is faster than the high and low foam expansion. It has been analyzed that it is possible to apply a hand-operated with a hose reel or medium expansion apparatus. Conclusion: Considering that the foaming agent and the extinguishing performance of the medium foam ratio are excellent, It is necessary to introduce the technical standards of medium foam agent for the introduction of hand-operated equipment, such as hose reel or portable medium foam apparatus.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.165-177
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• 2008

An important issue in Multiagent reinforcement learning is how an agent should learn its optimal policy in a dynamic environment where there exist other agents able to influence its own performance. Most previous works for Multiagent reinforcement learning tend to apply single-agent reinforcement learning techniques without any extensions or require some unrealistic assumptions even though they use explicit models of other agents. In this paper, a Naive Bayesian based policy model of the opponent agent is introduced and then the Multiagent reinforcement learning method using this model is explained. Unlike previous works, the proposed Multiagent reinforcement learning method utilizes the Naive Bayesian based policy model, not the Q function model of the opponent agent. Moreover, this learning method can improve learning efficiency by using a simpler one than other richer but time-consuming policy models such as Finite State Machines(FSM) and Markov chains. In this paper, the Cat and Mouse game is introduced as an adversarial Multiagent environment. And then effectiveness of the proposed Naive Bayesian based policy model is analyzed through experiments using this game as test-bed.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1256-1284
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• 2011

Although a existing consumer market have been studied in depth in the new technology product market, the market research on the overall level of value chain to consist of consumers, distributors, and manufacturers is weak. Therefore, in this paper consumers' purchase of new technology products were simulated and analyzed by a consumer selection model and a multi-agent model, which consist of consumers, distributors and manufacturers. Our research was focused on customer preference study in new technology product market by using conjoint analysis and discrete choice model. And changes in consumer behavior based on adoption of new technologies and offering of incentives were analyzed by ABM (Agent-based Model). In conclusion, the market share of technology products was risen when provision of incentives corresponding to inventory level and demand for new technology products occurred at the same time.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.169-178
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• 2010

Agent based simulation is an approach for the analysis of a system's long term behavior where the entities in the system behave independently by their own judgement and memory, but influence each other to cope with given environment. In this paper we developed an agent based simulation model for the analysis of behavioral mechanism of team formation. In the process of team formation members' mutual preference is an important factor although each member can join up with one's own will. Also a team performance can vary by the member's own experience. We implemented the developed model using Netlogo 4.1, and verified the model by simulation. From the simulation results we found that the model successfully performed necessary functions using behavioral rules, judgments, and evolutionary processes by memory. As a further study we will be able to apply the model for analyzing various ecological behavior of team formation.