• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1871-1874
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• 2003

Knowledge-based numeric open caption recognition is proposed that can recognize numeric captions generated by character generator (CG) and automatically superimpose a modified caption using the recognized text only when a valid numeric caption appears in the aimed specific region of a live sportscast scene produced by other broadcasting stations. in the proposed method, mesh features are extracted from an enhanced binary image as feature vectors, then a valuable information is recovered from a numeric image by perceiving the character using a multiplayer perceptron (MLP) network. The result is verified using knowledge-based hie set designed for a more stable and reliable output and then the modified information is displayed on a screen by CG. MLB Eye Caption based on the proposed algorithm has already been used for regular Major League Base-ball (MLB) programs broadcast five over a Korean nationwide TV network and has produced a favorable response from Korean viewer.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.4
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• pp.5-23
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• 2014

This study reports the first step in the Classification-based Search and Knowledge Discovery (CSKD) project, which aims to combine information organization and retrieval approaches for building digital library applications. In this study, we explored the generation and application of a faceted vocabulary as a potential mechanism to enhance knowledge discovery. The faceted vocabulary construction process revealed some heuristics that can be refined in follow-up studies to further automate the creation of faceted classification structure, while our concept search application demonstrated the utility and potential of integrating classification-based approach with retrieval-based approach. Integration of text- and classification-based methods as outlined in this paper combines the strengths of two vastly different approaches to information discovery by constructing and utilizing a flexible information organization scheme from an existing classification structure.

• 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.

• Journal of the Korea Society for Simulation
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• v.10 no.4
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• pp.51-64
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• 2001

It is quite necessary that an organization's information network should be equipped with a proper security system based on its scale and importance. One of the effective methods is to use the simulation model for deciding which security policy and mechanism is appropriate for the complex network. Our goal is to build a foundation of knowledge-based modeling and simulation environment for the network security. With this environment, users can construct the abstracted model of security mechanisms, apply various security policies, and quantitatively analyze their security performance against possible attacks. In this study, we considered security domain from several points of view and implemented the models based on a systematic modeling approach. We enabled the model to include knowledge in modular fashion and provided well-defined guidelines for transforming security policy to concrete rule set.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.254-259
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• 2008

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

• Journal of the Korean Society of Safety
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• v.7 no.2
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• pp.14-23
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• 1992

A methodology for developing an object description system based on functional-structure of chemical plant is proposed. A knowledge base for chemical plant fault diagnosis is also organized in a generic fashion using the heuristic knowledge of human operators. A plant can be seen as a hierarchical set of subsystems. Each subsystem is called a SCOPE. The state of the plant and the behavior of each subsystem is managed by the SCOPES. A computer-based system based on thls methodology and knowledge base has been developed and applied to the subprocess of ethylene plant to evaluate the effectiveness of the methodology.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.258-263
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• 2005

Haplotype-based analysis using high-density SNP markers have gained a great attention in evaluating genes in gene analysis and various clinical situations. However, there has been no research on disease diagnostic modeling based on SNPs analysis to our knowledge. The purpose of this study is to explore how knowledge discovery techniques are applied in medical informatics area and proposes a Case Based Reasoning (CBR) technique for diagnosis of gastric caner using Single Nucleotide Polymorphism(SNP).

• Computers and Concrete
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• v.23 no.4
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• pp.255-265
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• 2019

The potential of using genetic programming to predict engineering data has caught the attention of researchers in recent years. The present paper utilized weighted genetic programming (WGP), a derivative model of genetic programming (GP), to model the compressive strength of concrete. The calculation results of Abrams' laws, which are used as the design codes for calculating the compressive strength of concrete, were treated as the inputs for the genetic programming model. Therefore, knowledge of the Abrams' laws, which is not a factor of influence on common data-based learning approaches, was considered to be a potential factor affecting genetic programming models. Significant outcomes of this work include: 1) the employed design codes positively affected the prediction accuracy of modeling the compressive strength of concrete; 2) a new equation was suggested to replace the design code for predicting concrete strength; and 3) common data-based learning approaches were evolved into knowledge-based learning approaches using historical data and design codes.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.1
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• pp.85-104
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• 2022

In this study, in line with the era of the fourth industrial revolution, general concepts, technologies, trends, and examples of virtual reality and augmented reality were examined, and based on this, a plan that could be applied to libraries in the future was proposed. As a result of the study, first, it is necessary to construct a smart space as an experiential play space that can satisfy cultural desires transcending time and space by providing immersive contents using 4th technology such as VR and AR. Second, it is necessary to expand experiential cultural support services through VR, AR and MR. Third, to develop educational contents based on augmented reality technology. In order to apply and activate virtual reality and augmented reality in libraries in the future, based on a survey of librarians and users of public libraries, a survey on the application status, satisfaction, and demand of current public libraries should be conducted.

• Educational Technology International
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• v.9 no.2
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• pp.79-95
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• 2008

This paper aims to investigate modeling scripts based on the mode of group interaction in a computer-supported collaborative learning environment. Based on a literature review, this paper assumes that group interaction and its mode would have strong influence on the online collaborative learning process, and furthermore lead learners to create and share significant knowledge within a group. This paper deals with two different modes of group interaction- distributed and shared interaction. Distributed interaction depends on the external representation of individual knowledge, while shared interaction is concerned with sharing knowledge in group action. In order to facilitate these group interactions, this paper emphasizes the utilization of appropriate CSCL scripts, and then proposes the conceptual framework of CSCL scripts which integrate the existing scripts such as implicit, explicit, internal and external scripts. By means of the model regarding CSCL scripts based on the mode of group interaction, the implications for research on the design of CSCL scripts are explored.