• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.295-304
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• 2003

In this paper, we proposed a hardware-oriented Genetic Algorithm Processor(GAP) based on subpopulation architecture for high-performance convergence and reducing computation time. The proposed architecture was applied to enhancing population diversity for correspondence to premature convergence. In addition, the crossover operator selection and linear ranking subpop selection were newly employed for efficient exploration. As stochastic search space selection through linear ranking and suitable genetic operator selection with respect to the convergence state of each subpopulation was used, the elapsed time of searching optimal solution was shortened. In the experiments, the computation speed was increased by over $10\%$ compared to survival-based GA and Modified-tournament GA. Especially, increased by over $20\%$ in the multi-modal function. The proposed Subpop GA processor was implemented on FPGA device APEX EP20K600EBC652-3 of AGENT 2000 design kit.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.235-242
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• 2004

As e-business being rapidly developed the importance of security is on the rise in network. Intrusion detection systems which are a core security system detect the network intrusion trial. As intrusions become more sophisticated, it is beyond the scope of any one IDS to deal with them. Thus we placed multiple IDS agents in the network and the information helpful for detecting the intrusions is shared among these agents to cope effectively with attackers. Each agent cooperates through the BBA (Black Board Architecture) and CNP (Contract Net Protocol) for detecting intrusions. In this paper, we propose the effective method comparing the blackboard architecture to contract net protocol.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.965-974
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• 2003

Today's network consists of a large number of routers and servers running a variety of applications. In this paper, we have designed and constructed the general simulation environment of network security model composed of multiple IDSs agent and a firewall agent which coordinate by CNP (Contract Net Protocol). The CNP, the methodology for efficient integration of computer systems on heterogeneous environment such as distributed systems, is essentially a collection of agents, which cooperate to resolve a problem. Command console in the CNP is a manager who controls the execution of agents or a contractee, who performs intrusion detection. In the knowledge-based network security model, each model of simulation environment is hierarchically designed by DEVS (Discrete Event system Specification) formalism. The purpose of this simulation is the application of rete pattern-matching algorithm speeding up the inference cycle phases of the intrusion detection expert system. we evaluate the characteristics and performance of CNP architecture with rete pattern-matching algorithm.

• Journal of KIISE:Software and Applications
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• v.34 no.8
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• pp.689-696
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• 2007

It is important issue for software architects to estimate performance of software in the early phase of the development process due to the need to verify non-functional requirements and estimation of performance in various stages of architectural design. In order to analyze performance of software, there are many approaches to translate software architecture represented by Unified Modeling Language, into analytical models. However, in the development of agent-based systems, these approaches ignore or simplify the crucial details of the underlying performance of the agent platform. In this paper, we propose performance prediction methodology for agent based system using formal semantic descriptions, and then, we transform the descriptions into queuing network model which model reflects performance of hardware and software platform. We prove the accuracy of proposed methodology using prototype implementation. The accuracy is summarized at 80%.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.4
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• pp.17-24
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• 2022

This study aims to identify the Spatial Changes and the main agent of space creation in Samrye Area during the Japanese Occupation Period. As for the urban space in the Samrye area, the urban space was expanded to the Hujeong-ri area from the construction of the Jeonbuk light railway. Before 1914, the urban space of Samrye was formed around Samrye Station in Samrye-ri, which oversees Samrye-do from the Goryeo Dynasty to the Joseon Dynasty, but when Samrye Station of Jeonbuk light railway was established in Hujeong-ri in 1914, the foundation of a ladder-type street network visible from the central space of the current Samrye area was formed until the 1930s. And it was the Japanese and Korean landowners who took the lead in the construction of the Jeonbuk light railway, not the government, who expanded the urban space of Samnye from Samrye-ri to Hujeong-ri. The background of the establishment of Jeonbuk light railway is the reason why Dongsan Farm has difficulty in transporting rice to the Honam Line during the rice harvest. At that time, Park Ki-soon, famous as the land king, took charge of the established chairman of the railroad installation and established it, and with the establishment of Samrye Station, the access road was connected to his farm. In addition, a new road was built on the farm land that owned the Hujeong-ri area to the Seoul-Mokpo Interroad in Samrye-ri, thereby expanding the urban space. In other words, unlike Gunsan and Iksan, which were built under the leadership of the Japanese colonial eran government, the urban space in Samrye area was expanded by a farmer who grew up as a large landowner based on agriculture, which was the economic base at the time.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.777-784
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• 2017

In the architectural space, the user's behavior is the most important factor in evaluating the quality of architecture. Normally, the evaluation of user behavioral performance was carried out after a building was completed. Recently, interest in and efforts at pre-simulation based on information technology are accelerating. However, since existing user simulation technology is concerned mainly with simply escaping from a large space, it is impossible to simulate the behavior of multiple users in an architectural space. The present study strives to develop a human-figured intelligent agent for advanced user simulation based on ontology. The main purpose of the study is to employ the intelligent behaviors of a NPC(Non-player Character) to infer the ontology of both spatial and user information. In this paper, we intend to integrate ontology inference technology into the virtual space. And also, this study suggest the ontology visualization technology which illustrate the ontology-based information and their change in the spatial information.

• Smart Media Journal
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• v.12 no.9
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• pp.60-71
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• 2023

A microservice architecture that accommodates the heterogeneity of various development environments and enables flexible maintenance can secure business agility to manage services in line with rapidly changing requirements. Due to the nature of MSA, where communication between microservices within a service is frequent, the boundary security that has been used in the past is not sufficient in terms of security, and a Zerotrust system is required. In addition, as the size of microservices increases, definition of access control policies according to the API format of each service is required, and difficulties in policy management increase, such as unnecessary governance overhead in the process of redistributing services. In this paper, we propose a microservice architecture that centrally manages policies by separating access control decision and enforcement with a general-purpose policy engine called OPA (Open Policy Agent) for collective and flexible policy management in Zerotrust security-applied environments.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7757-7759
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• 2013

Physicians, in order to study the causes of cancer, detect cancer earlier, prevent or determine the effectiveness of treatment, and specify the reasons for the treatment ineffectiveness, need to access accurate, comprehensive, and timely cancer data. The cancer care environment has become more complex because of the need for coordination and communication among health care professionals with different skills in a variety of roles and the existence of large amounts of data with various formats. The goals of health care systems in such a complex environment are correct health data management, providing appropriate information needs of users to enhance the integrity and quality of health care, timely access to accurate information and reducing medical errors. These roles in new systems with use of agents efficiently perform well. Because of the potential capability of agent systems to solve complex and dynamic health problems, health care system, in order to gain full advantage of E- health, steps must be taken to make use of this technology. Multi-agent systems have effective roles in health service quality improvement especially in telemedicine, emergency situations and management of chronic diseases such as cancer. In the design and implementation of agent based systems, planning items such as information confidentiality and privacy, architecture, communication standards, ethical and legal aspects, identification opportunities and barriers should be considered. It should be noted that usage of agent systems only with a technical view is associated with many problems such as lack of user acceptance. The aim of this commentary is to survey applications, opportunities and barriers of this new artificial intelligence tool for cancer care information as an approach to improve cancer care management.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.192-199
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• 2003

Agents in multi-agent systems (MAS ) are required to achieve their own goals. An agent s goal, however, can conflict with others either when agents compete with each other to achieve a common goal or when they have to use a set of limited resources to accomplish agents divergent goals. In either case, agents need to be designed to reach a mutual acceptable state where they can avoid any goal conflicts through negotiation with others to achieve their goals. In this paper, we consider a BDI agent architecture where belief, desire, and intention are the three major components for agents mental attitudes and represent resource-bounded BDI agents in logic programming framework. We propose a negotiation algorithm for BDI agents solving their problems without goal conflicts in distributed cooperative environments. Finally, we describe a simple scenario to show the effectiveness of the negotiation algorithm implemented in a negotiation meta-language.

• Journal of IKEEE
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• v.23 no.4
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• pp.1187-1194
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• 2019

This paper proposes a CNN architecture as value function network of an artificial intelligence Othello game agent and its learning scheme using reinforcement learning algorithm. We propose an approach to construct the value function network by using CNN to learn the records of professional players' real game and an approach to enhance the network parameter by learning from self-play using reinforcement learning algorithm. The performance of value function network CNN was compared with existing ANN by letting two agents using each network to play games each other. As a result, the winning rate of the CNN agent was 69.7% and 72.1% as black and white, respectively. In addition, as a result of applying the reinforcement learning, the performance of the agent was improved by showing 100% and 78% winning rate, respectively, compared with the network-based agent without the reinforcement learning.