• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.71-73
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• 2012

최근 웹 2.0과 시맨틱 웹의 대중화와 더불어 Open API와 링크드 데이터를 이용한 시맨틱 웹 융복합(매쉬업) 서비스가 주목을 받고 있다. 다양한 링크드 데이터와 Open API들을 조합함으로써 새로운 서비스들을 쉽고 빠르게 만드는 것이 가능하기 때문이다. 하지만 사용자가 링크드 데이터와 Open API 서비스를 사용하기 위해서는 서비스 입력 값이나 출력값 등의 해당 정보를 얻어야 하며 이를 위해 링크드 데이터와 Open API를 제공해 주는 사이트를 직접 방문해야만 하는 불편함을 가지게 된다. 본 논문에서는 시맨틱 웹 매쉬업 서비스를 위한 통합 링크드 데이터 및 Open API 관리 시스템을 설계하고 구현하였다. 제안한 시스템에서 사용자는 사전 지식 없이 통합 관리 시스템을 통해 원하는 링크드 데이터와 Open API 서비스를 검색하고 실행할 수 있다. 또한 실행된 결과는 XML 형태로 저장되어 추후 매쉬업 시 재사용이 가능하도록 한다.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.672-674
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• 2000

There are various ways in classification methodologies of data mining such as neural networks but the result should be explicit and understandable and the classification rules be short and clear. Rough set theory is a effective technique in extracting knowledge from incomplete and inconsistent information and makes an offer classification and approximation by various attributes with effect. This paper discusses granularity of knowledge for reasoning of uncertain concepts by using generalized rough set approximations based on hierarchical granulation structure and uses hierarchical classification methodology that is more effective technique for classification by applying core to upper level. The consistency rules with minimal attributes is discovered and applied to classifying real data.

• International Journal of Reliability and Applications
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• v.10 no.1
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• pp.1-15
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• 2009

Even though the impact of manufacturing quality to reliability is not considered much as well as that of design area, a major cause of an early failure of the product is known as manufacturing problem. This research applies two different types of neural network algorithms, the Back propagation (BP) algorithm and Learning Vector Quantization (LVQ) algorithm, to identify and classify the nonrandom variation pattern on the control chart based on knowledge-based diagnosis of dimensional variation. The performance and efficiency of both algorithms are evaluated to choose the better pattern recognition system for auto body assembly process. To analyze hundred percent of the data obtained by Optical Coordinate Measurement Machine (OCMM), this research considers an application in which individual observations rather than subsample means are used. A case study for analysis of OCMM data in underbody assembly process is presented to demonstrate the proposed knowledge-based pattern recognition system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.44-51
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• 2003

Knowledge acquisition is a bottleneck in knowledge-based system implementation. Decision tree induction is a useful machine learning approach for extracting classification knowledge from a set of training examples. Many real-world data contain fuzziness due to observation error, uncertainty, subjective judgement, and so on. To cope with this problem of real-world data, there have been some works on fuzzy classification rule learning. This paper makes a survey for the kinds of fuzzy classification rules. In addition, it presents a fuzzy classification rule learning method based on decision tree induction, and shows some experiment results for the method.

• ETRI Journal
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• v.41 no.4
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• pp.515-527
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• 2019

This paper discusses the design, implementation, and potential use of an ontology-based mobile pediatric consultation and monitoring system, which is a smart healthcare expert system for pediatric patients. The proposed system provides remote consultation and monitoring of pediatric patients during their illness at places distant from medical service areas. The system not only shares instant medical data with a pediatrician but also examines the data as a smart medical assistant to detect any emergency situation. In addition, it uses an inference engine to infer instant suggestions for performing certain initial medical treatment steps when necessary. The applied methodologies and main technical contributions have three aspects: (a) pediatric consultation and monitoring ontology, (b) semantic Web rule knowledge base, and (c) inference engine. Two case studies with real pediatric patients are provided and discussed. The reported results of the applied case studies are promising, and they demonstrate the applicability, effectiveness, and efficiency of the proposed approach.

• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.153-162
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• 2007

In this paper, we propose a knowledge-based method for generating CNC torch path for laser cutting of the outlines of planar shapes. The proposed method consists of two main phases: laser cutting knowledge construction and CNC torch path generation using the knowledge. In the first phase, cutting experiments are conducted on various operating parameters, and then empirical data are stored and analyzed to make up the knowledge of laser cutting. With this knowledge, we can inquire what a kerf width is for specific operating parameters. In the second phase, using the knowledge of laser cutting, CNC torch path is generated for cutting the outlines of the given planar shapes. This phase is basically based on the offset generation of each outline by a sequence of arc splines, where the offset distance is the same as the half of the kerf width determined from the constructed knowledge. The proposed method based on laser cutting knowledge makes full use of arc interpolators in CNC torch path generation. The method can efficiently reduce the number of path segments while keeping the torch path within the desired accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5654-5668
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• 2018

Driven by security and real-time demands of Internet of Things (IoT), the timing of fog computing and edge computing have gradually come into place. Gateways bear more nearby computing, storage, analysis and as an intelligent broker of the whole computing lifecycle in between local devices and the remote cloud. In fog computing, the edge broker requires X-aware capabilities that combines software programmability, stream processing, hardware optimization and various connectivity to deal with such as security, data abstraction, network latency, service classification and workload allocation strategy. The prosperous of Field Programmable Gate Array (FPGA) pushes the possibility of gateway capabilities further landed. In this paper, we propose a software-defined gateway (SDG) scheme for fog computing paradigm termed as Fog Computing Zero-Knowledge Gateway that strengthens data protection and resilience merits designed for industrial internet of things or highly privacy concerned hybrid cloud scenarios. It is a proxy for fog nodes and able to integrate with existing commodity gateways. The contribution is that it converts Privacy-Enhancing Technologies rules into provable statements without knowing original sensitive data and guarantees privacy rules applied to the sensitive data before being propagated while preventing potential leakage threats. Some logical functions can be offloaded to any programmable micro-controller embedded to achieve higher computing efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1381-1387
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• 2014

According to continuous development of information technology, it is needed to make convergence of other disciplines such as humanities and area studies. Among convergence fields related to information technology and humanities/area studies, electronic cultural atlas represents various digitalized cultural information on electronic map using spatial data such as points, lines, and polygons through time, spatial, and subject axises. Knowledge map is to represent special academic information based on electronic cultural atlas. In details, knowledge map can provide integrated information sharing and spread because academic information associated with electronic cultural atlas and data related to per subjects, regions, and period become organically connected. Therefore, knowledge map may be utilized to promote scholastic research and diffuse research result. In this paper, we describe basic concept and composition of knowledge map and propose design method to construct knowledge map.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.1
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• pp.9-17
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• 1992

This paper represents the expert system for selecting the superstructure types of bridges in the part of a preliminary bridge design. The system is implemented with the expert system tool called K-CLIPS which uses the production system for knowledge representation and provides the mechanism of forward chaining. This expert system is composed of a knowledge base, data base and a knowledge module built by the tool which consists of the knowledges on design procedures. During symbolic processing the data base supports the sub system in knowledge base.

• Journal of Computing Science and Engineering
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• v.1 no.1
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• pp.74-94
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• 2007

Nowadays, sharing data among organizations is often required during the business collaboration. Data mining technology has enabled efficient extraction of knowledge from large databases. This, however, increases risks of disclosing the sensitive knowledge when the database is released to other parties. To address this privacy issue, one may sanitize the original database so that the sensitive knowledge is hidden. The challenge is to minimize the side effect on the quality of the sanitized database so that non-sensitive knowledge can still be mined. In this paper, we study such a problem in the context of hiding sensitive frequent itemsets by judiciously modifying the transactions in the database. Unlike previous work, we consider the quality of the sanitized database especially on preserving the non-sensitive frequent itemsets. To preserve the non-sensitive frequent itemsets, we propose a border-based approach to efficiently evaluate the impact of any modification to the database during the hiding process. The quality of database can be well maintained by greedily selecting the modifications with minimal side effect. Experiments results are also reported to show the effectiveness of the proposed approach.