• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.11 no.1
• /
• pp.1-7
• /
• 2011

Most of expert systems use the text-oriented knowledge bases. However, knowledge management using the knowledge bases is considered as a huge burden to the knowledge workers because it includes some troublesome works. It includes chasing and/or checking activities on Consistency, Redundancy, Circulation, and Refinement of the knowledge. In those cases, we consider that they could reduce the burdens by using relational database management systems-based knowledge management infrastructure and convert the knowledge into one of easy forms human can understand. Furthermore they could concentrate on the knowledge itself with the support of the systems. To meet the expectations, in this study, we have tried to develop a general-purposed knowledge conversion tool for expert systems. Especially, this study is focused on the knowledge conversions among text-oriented knowledge base, relational database knowledge base, and decision tree.

• Journal of Information Processing Systems
• /
• v.15 no.5
• /
• pp.1192-1200
• /
• 2019

Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.

• 한국ITS학회:학술대회논문집
• /
• 2008.11a
• /
• pp.351-354
• /
• 2008

• 한국ITS학회:학술대회논문집
• /
• 2008.11a
• /
• pp.565-569
• /
• 2008

• 한국ITS학회:학술대회논문집
• /
• 2003.11a
• /
• pp.73-75
• /
• 2003

• 한국ITS학회:학술대회논문집
• /
• 2010.05a
• /
• pp.1-4
• /
• 2010

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.04a
• /
• pp.273-273
• /
• 2007

지문인식에 관한 전반적인 사항 즉 센서발전추이와 센서 종류, 적응 알고리즘을 소개하고 관련 제품과 산업 분야에 대한 다양한 적용과 응용을 제시하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.1 no.2
• /
• pp.55-64
• /
• 1991

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1995.10a
• /
• pp.55-123
• /
• 1995

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.4
• /
• pp.69-72
• /
• 1998

We introduce a concept of a 'fuzzy' map between sets by modifying the concetp of the extension principle introduced by Dubois and Prade in [1] and by using this we generalize Goguen's and Zadeh's extension principles in [2] and [3].