• 한국지능시스템학회논문지
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• 제11권7호
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• pp.598-602
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• 2001

Recently, due to the widely use of personal computers and internet, many computer users requested intelligent system that can cope with various types of requirements and user-friendly interfaces. Based on this background, researches on the intelligent agent are now activating in various fields. In this paper, we modeled, designed and implemented an intelligent agent system for pattern classification by adopting intelligent agent concepts. We also investigated the pattern classification method by utilizing some pattern classification algorithms for the common data. As a result, we identified that 300 3-dimensional data are applied to three pattern classification algorithms and returned correct results. Our system showed a distinguished user-friendly interface feature by adopting various agents including graphic agent.

• International Journal of Control, Automation, and Systems
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• 제1권2호
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• pp.257-261
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• 2003

In this study, we investigated the modeling and design of an Intelligent Agent System (IAS). To achieve this goal, we introduced several kinds of agents that exhibit intelligent features. These are the main agent, management agent, watcher agent, report agent and application agent. We applied the intelligent agent concept to two different application fields, i.e. the intelligent agent system for pattern classification and the intelligent agent system for bank asset management modeling.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(1)
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• pp.113-116
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• 2002

It is required to network to make more intelligent packet processing and forwarding for increasing bandwidth and various services. Classification provides these intelligent to network which is acquired by increasing number of rules in classification rule set. In this Paper, we propose a classification algorithm efficient to scalable rule set ahead as well as Present small rule set. This algorithm has competition to existing methods by performance and advantage that it is mixed with another algorithm because il does not change original shape of rule set.

• 한국IT서비스학회지
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• 제19권1호
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• pp.55-69
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• 2020

The Internet cyber space has become more important as it enters the intelligent information society of the 4th Industrial Revolution beyond the information age through the development of ICT, the expansion of personalized services through mobile and SNS, the development of IoT, big data, and artificial intelligence. The Internet has formed a new paradigm in human civilization, but it has focused only on the efficiency of its functions. Therefore, various side effects such as information divide, cyber terrorism, cyber violence, hacking, and personal information leakage are emerging. In this situation, facing the intelligent information society can lead to an uncontrollable chaos. Therefore, this study classifies the cyber dysfunction of intelligent information society and analyzes social cognition, suggests cyber dysfunction standard of intelligent information society, and examines the seriousness of dysfunction, and suggests technical research directions for future technologies and services. The dysfunctional classification of the intelligent information society was classified into five areas of cyber crime and terrorism, infringement of rights, intelligent information usage culture, intelligent information reliability, and social problems by FGI methodology. Based on the classification, the social perception of current and future cyber dysfunction severity was surveyed and it showed female is more sensitive than male about the dysfunction. A GAP analysis confirmed social awareness that the future society would be more serious about AI and cyber crime

• International Journal of Automotive Technology
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• 제7권7호
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• pp.827-832
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• 2006

Occupant classification and position detection have been significant research areas in intelligent safety systems in the automotive field. The detection and classification of seat occupancy open up new ways to control the safety system. This paper deals with a novel algorithm development, hardware implementation and testing of a prototype intelligent safety system for occupant classification and position detection for in-vehicle environment. Borland C++ program is used to develop the novel algorithm interface between the sensor and data acquisition system. MEMS strain gauge hermatic pressure sensor containing micromachined integrated circuits is installed inside the passenger seat. The analog output of the sensor is connected with a connector to a PCI-9111 DG data acquisition card for occupancy detection, classification and position detection. The algorithm greatly improves the detection of whether an occupant is present or absent, and the classification of either adult, child or non-human object is determined from weights using the sensor. A simple computation algorithm provides the determination of the occupant's appropriate position using centroidal calculation. A real time operation is achieved with the system. The experimental results demonstrate that the performance of the implemented prototype is robust for occupant classification and position detection. This research may be applied in intelligent airbag design for efficient deployment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.470-472
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• 2006

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as environment and health, industry scene system monitoring, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modem learning techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes having the capability of simple processing and wireless communication. The proposed system is able to perform context classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to intelligent dust collecting system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.205-208
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• 1997

Traditionally, classification of remote sensed image data is one of the important works for image data analysis procedure. So, many researchers devote their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new classification method for remote sensed image data that use rough set theory. Using indiscernibility relation of rough sets, we show that can classify image data very easily.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.248-251
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• 1997

In this paper, We propose the concept of approximate Classification in the field of two group discriminan analysis. In our approach, an attribute space is divided into three subspaces. Two subspaces are for given two group and one subspace is for a boundary area between the two groups. We propose Approximate Pattern Classification with Rough set. We also propose learning procedures of neural networks for approximate classification. We propose two weighting methods which lead to possibility analysis and necessity analysis. We illustrate the proposed methods by numerical examples.

• 한국공간정보시스템학회 논문지
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• 제11권1호
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• pp.157-168
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• 2009

우리가 살아가는 삶속에 깊숙이 파고든 공간정보는 유비쿼터스 시대에 맞춰 지능형 공간정보로 진화하고 있다. 또한 이를 이용한 다양한 서비스 모델이 소개되고 있다. 하지만 이러한 서비스에 대하여 사용자와 제공자에게 동시에 설명할 수 있는 분류체계는 존재하지 않는다. 이에 다양한 지능형 공간정보 서비스들을 체계적으로 분류할 수 있는 체계가 필요한 실정이다. 본 연구에서는 지능형 공간정보의 개념을 소개하고 공간정보 서비스들의 특성을 고려한 서비스 분류 체계를 개발하였다. 개발된 지능형 공간정보 서비스분류 매트릭스는 지능수준 척도, 공간정보 정확도, 서비스 영역을 기준으로 하였다. 본 연구에서 제안한 서비스 분류 매트릭스는 두 가지 관점에서 활용될 수 있다. 첫째, 지능형 공간정보의 수요가 늘어나면서 유사한 기능만을 가진 채 실수요를 반영하지 못하고 중복된 서비스들이 나타나는 현실을 개선시킬 수 있다. 둘째, 공간정보 산업의 현황을 들여다보고 새로 진입하게 되는 서비스의 목표 선정이나 미래의 발전 방향을 제시할 수 있다. 이러한 활용을 토대로 서비스 분류 매트릭스는 새로운 블루오션 창출과 같이 공간정보 사업 활성화를 이루는데 도움이 될 수 있다. 하지만, 서비스 분류 매트릭스는 향후 개발될 다양한 서비스를 적용하는데 있어 문제점이 없도록 수정과 보완이 필요하다. 그리고 분류 매트릭스는 궁극적으로 서비스 로드맵을 작성하기 위한 자료로 활용되거나 참조모델로서 활용될 수 있도록 해야 할 것이다. 하여 U-City의 미래를 더욱 밝게 할 것이다.

• 융합정보논문지
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• 제9권3호
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• pp.134-139
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• 2019

현대 사회의 발전이 급속하게 진행됨에 따라 이를 뒷받침 하는 사회 전반의 기술들도 전보다 한층 진보되고 지능화되고 있다. 특히 보안 분야에서도 기존의 공격보다 더 정교하고 지능화된 공격들이 새로 생성되고 있고 그 피해 상황도 전보다 몇 배나 크게 발생되고 있다. 기존의 침입에 대한 분류체계를 현시점에 맞게 재정립하고 분류할 필요가 있고, 현재 작동하고 있는 침입탐지 및 감지 시스템들에 이런 분류체계를 적용하여 지능화된 침입에 능동적으로 대응하여 침입 피해를 최소화하는 것이 요구되고 있다. 본 논문에서는 현재 지능적인 공격에 의해 발생하는 침입 유형을 분석하여, 목적하는 시스템의 서비스 안전성, 신뢰성, 가용성을 보장하기 위한 새로운 침입 상황분류 모델을 제안하고, 이 분류 모델을 사용하여 조기에 침입을 감지하여 침입 피해를 최소화하고 보다 능동적인 대응이 가능한 스마트한 침입 인지 시스템을 설계하고 구현하는 연구에 토대를 마련한다.