• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.589-600
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• 2005

Application developers need effective reuseable methodology to meet rapidly changes and variety of users requirements. Product Line and CBD(Component Based Development) offer the great benefits on quality and productivity for developing the software that is mainly associate with reusable architectures and components in a specific domain and rapidly changing environments. Product line can dynamically focus on the commonality and variety feature model among the products. The product line uses the feature modeling for discovering, analyzing, and mediating interactions between products. Reusable architectures include many variety plans and mechanisms. In case of those architecture are use in product version for a long time, It is very important in architecture product line context for product line design phase. Application developer need to identify the proper location of architecture changing for variety expression. It is lack of specific variety managements to design the product line architecture until nowdays. In this paper, we define various variety types to identify the proper location of architecture changing for variety expression and to design the reusable architecture. We also propose architecture variety on feature model and describe variety expression on component relations. We implemented the web learning system based on the methodology. We finally describe how these methodology may assist in increasing the efficiency, reusability, productivity and quality to develop an application. In the future, we are going to apply the methodology into various domain and suggest international and domestic's standardization.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.573-590
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• 2020

This study presents the current status of DECOVALEX-2023 project Task G and our research results so far. Task G, named 'Safety ImplicAtions of Fluid Flow, Shear, Thermal and Reaction Processes within Crystalline Rock Fracture NETworks (SAFENET)' aims at developing a numerical method to simulate the fracture creation and propagation, and the coupled thermohydro-mechanical processes in fracture in crystalline rocks. The first research step of Task G is a benchmark simulation, which is designed for research teams to make their modelling codes more robust and verify whether the models can represent an analytical solution for displacements of a single rock fracture. We reproduced the mechanical behavior of rock and embedded single fracture using a three-dimensional grain-based distinct element model for the simulations. In this method, the structure of the rock was represented by an assembly of rigid tetrahedral grains moving independently of each other, and the mechanical interactions at the grains and their contacts were calculated using 3DEC. The simulation results revealed that the stresses induced along the embedded fracture in the model were relatively low compared to those calculated by stress analysis due to stress redistribution and constrained fracture displacements. The fracture normal and shear displacements of the numerical model showed good agreement with the analytical solutions. The numerical model will be enhanced by continuing collaboration and interaction with other research teams of DECOVALEX-2023 Task G and validated using various experiments in a further study.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.21-29
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• 2012

We have proposed an ontology-based translation mashup system for foreigner to enjoy Korean cultural information without any language barrier(linguistic problem). In order to utilize public information, we use a mobile public information open API of Seoul metropolitan city. Google AJAX language API is used for translations of public information. We apply an ontology to minimize errors caused by the translations. For ontology modeling, we analyze the public information domain and define classes, relations and properties of cultural vocabulary ontology. We generate ontology instances for titles, places and sponsors which are the most frequently occurring translation errors. We compare the accuracy of translations through our experiment. Through the experimental results using the proposed ontology-based translation mashup system, we verify the validity of the system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.380-388
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• 2017

The services of the IoT environment should constantly collect situation information, and perform appropriate actions according to the situation. Therefore, there is a need for a method that can express collected situation information. In this paper, we propose a situation information model based on ontology for IoT environment. Since the proposed model is ontology based, it supports semantic interoperability. We also build an upper-level ontology to model common situation information of various IoT domains. It is easy to understand and use because it expresses situation information consistently by expressing person, environment, and thing constituting IoT environment as class and defining properties indicating the situation. In addition, since the situation information need to reflect dynamic situation, it has a feature to model the creation time and the life time of the situation information so as to judge the validity of the information. The proposed ontology model is described using OWL, and the service can be described based on the constructed ontology.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.3
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• pp.275-283
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• 2005

Ontologies are the core components of the Semantic Web and knowledge-based systems. But it is difficult to find useful ontologies in actual domains. In order to build useful domain ontology, the conceptualization of the domain knowledge by knowledge experts of the specific domain and the specification of conceptualized knowledge with formal languages by ontology designers are required. In addition, structured and detailed guidelines and methods should be provided to be shared by the development team members. However, existing ontology building methodologies define and describe the skeletal structure of the whole building process at the top-layer. We build a useful academic ontology that is based on the conceptual knowledge structure in the domain of philosophy, and propose a detailed methodology to build a text ontology based on Topic Maps. Our methodology consists of two phases, ontology modelling and ontology implementation. We implement a philosophy knowledge portal to support retrieving and navigating of the philosophy knowledge.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.450-453
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• 2011

고화질의 디지털 카메라 및 스마트폰, 감시용 카메라의 보급 등으로 인해 최근 패턴 인식 및 이미지 프로세싱 분야에서 고화질의 이미지 및 비디오를 처리해야 하는 경우가 많아지고 있다. 특히 차량 번호판 감지 등과 같은 객체 인식 분야의 경우, 고화질의 이미지로 인해 그만큼 인식에 필요한 계산 비용이 증가하게 되었는데 따라서 이러한 계산 비용을 효율적으로 줄이기 위한 기법이 요구되고 있다. 또한 기존의 차량 번호판 감지의 도메인과는 다르게 도로 상에서의 실시간 차량 번호판 감지의 필요성이 대두되고 있기에 본 논문에서는 도로 상에서의 실시간 번호판 감지 시스템을 위한 차량 번호판 주변정보 기반의 효율적인 윈도우 슬라이딩(window sliding) 방법을 제안한다. 본 논문의 시스템은 총 3단계로, (1) SVM(Supported Vector Machine) 을 통한 차량 번호판 주위 정보에 대한 학습, (2) 도로 상의 번호판 위치 확률 모델링을 통한 탐색 공간의 감소, (3) $context_{plate}$분류기를 통한 OCS(operator context scanning)의 수행이다. 이와 같은 $context_{plate}$분류기와 OCS를 통해 번호판 검출을 위한 윈도우 슬라이딩의 수가 크게 줄었음을 알 수 있었으며, 또한 번호판의 정보를 건너뛰지 않고, 신뢰성 있게 접근함을 알 수 있었다.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1417-1426
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• 2004

As Ubiquitous commerce is coming personalization service is getting interested. And also the recommendation method which offers useful information to customer becomes more important. However, most of them depend on specific method and are restricted to the E-commerce. For applying these recommendation methods into U-commerce, first it is necessary that the extended context modeling and systematic connection of the methods to complement strength and weakness of recommendation methods in each commercial transaction. Therefore, we propose a mod-eling technique of context information related to personal activation in commercial transaction and show incremental preference analysis method, using preference tree which is closely connected to recommendation method in each step. And also, we use an XML indexing technique to effi-ciently extract the recommendation information from a preference tree.

• Management & Information Systems Review
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• v.37 no.4
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• pp.41-62
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• 2018

As the volume of unstructured data increases through various social media, Internet news articles, and blogs, the importance of text analysis and the studies are increasing. Since text analysis is mostly performed on a specific domain or topic, the importance of constructing and applying a domain-specific dictionary has been increased. The quality of dictionary has a direct impact on the results of the unstructured data analysis and it is much more important since it present a perspective of analysis. In the literature, most studies on text analysis has emphasized the importance of dictionaries to acquire clean and high quality results. However, unfortunately, a rigorous verification of the effects of dictionaries has not been studied, even if it is already known as the most essential factor of text analysis. In this paper, we generate three dictionaries in various ways from 39,800 news articles and analyze and verify the effect each dictionary on the accuracy of document classification by defining the concept of Intrinsic Rate. 1) A batch construction method which is building a dictionary based on the frequency of terms in the entire documents 2) A method of extracting the terms by category and integrating the terms 3) A method of extracting the features according to each category and integrating them. We compared accuracy of three artificial neural network-based document classifiers to evaluate the quality of dictionaries. As a result of the experiment, the accuracy tend to increase when the "Intrinsic Rate" is high and we found the possibility to improve accuracy of document classification by increasing the intrinsic rate of the dictionary.

• Journal of KIISE:Software and Applications
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• v.27 no.3
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• pp.227-240
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• 2000

The research of the variability gains more gravity in component-based software development, because it helps to extend the reusability of the component. A domain-specific component supports the more variability, the wider scope that the component can be applied to. However, the more variability included in a component, It makes the size of a component bigger, and the cost to construct the component is rises. As a result, this disturbs making an optimized system. In this paper, we classify the variability into 3 types, according to their features. And we propose some implementation techniques for each type based COM. Moreover, we also propose a process to analysis and design the variability with their artifacts, which includes some tasks from variability extraction to implementation of it. This proposed process can be applied as a part of the component developing process.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1566-1574
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• 2008

Researches of current information searching focus on providing personalized results as well as matching needed queries in an enormous amount of information. This paper aims at discovering hidden knowledge to provide personalized and inferred search results based on the ontology with categorized concepts and relations among data. The current searching occasionally presents too much redundant information or offers no matching results from large volumes of data. To lessen this disadvantages in the information searching, we propose an inference algorithm that supports associated and inferred searching through the Jess engine based on the OWL ontology constraints and knowledge expressed by SWRL with association rules. After constructing the personalized preference ontology for domains such as restaurants, gas stations, bakeries, and so on, it shows that new knowledge information generated from the ontology and the rules is provided with an example of the domain of gas stations.