• Journal of the Korea Society of Computer and Information
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• v.9 no.1
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• pp.55-62
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• 2004

The computer security is considered important due to the side effect generated from the expansion of computer network and rapid increase of the use of internet. Therefore, Intrusion detection system has been an active research area to reduce the risk from intruders. A number of advantages of using mobile agent computing paradigms have been Proposed. These advantages include : overcoming network latency, reducing network load, executing asynchronously and autonomously, adapting dynamically, and operating in heterogeneous environments. Many information security models have been proposed to mitigate agent-to-agent. agent-to-platform, and platform-to-agent element risks . In these paper, We have an object which is that through intrusion detection system development, the mobile agent is managed and through the analysis of performance data. the best environment is served.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.697-701
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• 1995

The network encironment includes a number of autonomous agents which are widely distributed, have different platforms, and change very dynamically. The information system operated on this environment must solve some basic problems; restrictive client-server models, heterogeneous systems, and intellignet agents. We are using KQML for knowledge management. Java language provides solutions against a strong server dependency and a heterogenous troubles. We introduce KQML as an agent communication language and JATLite as a java agent template. these increase an efficiency of communication on network and enable us to use resources distributed in world wide web. Also, we describe a new agent system architecture and implement it through an example scenario

• International conference on construction engineering and project management
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• 2011.02a
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• pp.439-444
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• 2011

As construction projects have been getting larger and more complex, a single individual or organization cannot have complete knowledge or the abilities to handle all matters. Collaborative practices among heterogeneous individuals, which are temporarily congregated to carry out a project, are required in order to accomplish project objectives. These organizational knowledge creation processes of project teams should be understood from the active and dynamic viewpoint of how they create information and knowledge rather than from the passive and static input-process-output sequence. To this end, agent-based modeling and simulation which is built from the ground-up perspective can provide the most appropriate way to systematically investigate them. In this paper, agent-based modeling and simulation as a research method and a medium for representing theory is introduced. To illustrate, an agent-based simulation of the evolution of collaboration in large-scale project teams from a game theory and social network perspective is presented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.808-813
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• 2003

Maintaining agility and responsiveness m designing and manufacturing activities are the key issues for manufacturing companies to cope with global competition. Distributed design and control systems are regarded as an efficient solution for agility and responsiveness. However, distributed nature of a manufacturing system complicates production activities such as design, simulation, scheduling, and execution control. Especially, existing simulation systems have limited external integration capabilities, which make it difficult to implement complex control mechanisms for the distributed manufacturing systems. Moreover, integration and coupling of heterogeneous components and models are commonly required for the simulation of complex distributed systems. In this paper, a collaborative and adaptive simulation architecture is proposed as an open framework for simulation and analysis of the distributed manufacturing enterprises. By incorporating agents with their distributed characteristics of autonomy, intelligence, and goal-driven behavior, the proposed agent-based simulation architecture can be easily adapted to support the agile and distributed manufacturing systems. The architecture supports the coordination and cooperation relations, and provides a communication middleware among the participants in simulation.

• Journal of Integrative Natural Science
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• v.1 no.2
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• pp.127-132
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• 2008

This project follows the heterogeneous agent market segmented model of Landon-Lane and Occhino (2007) with using Korean data, M1 and GDP deflator from 1882:I to 2007:II. This paper estimates parameters with Monte Carlo Markov Chain. The fraction of traders, ${\lambda}$, in Korea is 15.64%. The quarterly preferences discount factor's, ${\beta}$, posterior mean is 0.9922. The posterior mean of the inverse of the elasticity of the labor supply to the real wage, ${\varphi}$, is 0.0316. The elasticity of the labor supply to the real wage has a very large value. By Hansen (1985) and Christiano and Eichenbaum (1992) and Cooley and Hansen (1989), models having large elasticity of the aggregate labor supply better match macroeconomic data.

• KDI Journal of Economic Policy
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• v.41 no.2
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• pp.1-39
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• 2019

This paper utilizes a life-cycle overlapping-generations model to quantify the welfare effects of plans to postpone the depletion of the National Pension Fund. In order for the model to incorporate the rapidly changing demographic structure of Korea fully, we build and calibrate a model in transition directly. The model is considered suitable for analyzing the effects of demographic changes on the Korean economy and the effects of plans to change the National Pension System. According to a simulation of the model, to postpone the depletion of the National Pension Fund for 30 years, the premium rate must be increased to 18.3% from the current rate of 9%. By postponing the depletion of the fund reserve, young and future generations gain significantly at the expense of the older generations. The simulation results should be, however, interpreted as meaning that the current system is unjustifiably partial to the older generations. Moreover, given the current premium rate, it is desirable to strengthen the income-redistribution function of the National Pension System.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.407-418
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• 2023

The Multi-Object Goal Visual Navigation(MultiOn) is a visual navigation task in which an agent must visit to multiple object goals in an unknown indoor environment in a given order. Existing models for the MultiOn task suffer from the limitation that they cannot utilize an integrated view of multimodal context because use only a unimodal context map. To overcome this limitation, in this paper, we propose a novel deep neural network-based agent model for MultiOn task. The proposed model, MCFMO, uses a multimodal context map, containing visual appearance features, semantic features of environmental objects, and goal object features. Moreover, the proposed model effectively fuses these three heterogeneous features into a global multimodal context map by using a point-wise convolutional neural network module. Lastly, the proposed model adopts an auxiliary task learning module to predict the observation status, goal direction and the goal distance, which can guide to learn the navigational policy efficiently. Conducting various quantitative and qualitative experiments using the Habitat-Matterport3D simulation environment and scene dataset, we demonstrate the superiority of the proposed model.