• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.427-432
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• 2005

This paper is concerned with a simultaneous design of TSK (Takagi-Sugeno-Kang)-linguistic fuzzy models with uncertain model output and the computationally efficient representation. For this purpose, we use the fundamental idea of linguistic models introduced by Pedrycz and develop their comprehensive design framework. The design process consists of several main phases such as (a) the automatic generation of the linguistic contexts by probabilistic distribution using CDF (conditional density function) and PDF (probability density function) (b) performing context-based fuzzy clustering preserving homogeneity based on the concept of fuzzy granulation (c) augment of bias term to compensate bias error (d) combination of TSK and linguistic context in the consequent part. Finally, we contrast the performance of the enhanced models with other fuzzy models for automobile MPG predication data and coagulant dosing process in a water purification plant.

• Journal of Information Technology Applications and Management
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• v.9 no.3
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• pp.13-30
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• 2002

ebXML (Electronic Business using extensible Markup language), sponsored by UN/CEFACT and OASIS, is a modular suite of specifications that enables enterprises of any size and in any geographical location to conduct business over the Internet. Using ebXML, companies now have a standard method to exchange business messages, conduct trading relationships, communicate data In common terms and define and resistor business processes. It is the mission of ebXML that provides an open XML-based infrastructure enabling the global use of electronic business information in an interoperable, secure and consistent manner by all parties for creating a single e1ectronic electronic market. This paper briefly overviews the concept of core component, context, assembly rule and context rule. Then, It designs by standard specifications of ebXML core component commonly used in an industry and among industries, and assembles business messages by using XML schema. Therefore, it suggests the mechanism which effectively exchanges business messages among the trading partners. This paper designs core component by using only three business messages of retail industry : orders, dispatch report, sales report.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.725-726
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• 2008

In this paper, we introduce an ubiWarehouse system for the management of automobile parts. Because automotive parts are very various in kinds according to companies, models and manufacture year, it's hard to find exactly the desired parts and to control goods in stock. To solve this problem, we propose the model of context recognizer in which context data are expressed in a systematic type of 5W1H. And initial context data are grouped and integrated, and some conflict context information is solved. Finally user's intention is interpreted and served. As a result, the proposed system can be used to enhance conveniency and correctness of the management of various kinds of part's.

• English Language & Literature Teaching
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• v.10 no.1
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• pp.77-106
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• 2004

This study aims to investigate how the four college students interact with one another to discuss and construct meaning in a small reading group. Additionally, this study attempts to examine how the participants played their roles in the group. Data sources consisted of transcripts of the students' interactions, questionnaires and informal interviews, and the researchers' observation notes. The data revealed that the participants contributed fairly steadily to the interactions by checking with own grammatical knowledge, providing lexical information, understanding the micro level context, and presenting the macro level context. Several pedagogical implications are presented for the practical classroom. Findings of the study suggest effective ways to implement group activities in reading classes and a teacher's role for optimum group learning.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.1-17
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• 2007

A virtual enterprise (VE) can be mapped into a multi-agent system (MAS) that consists of various agents with specific role(s), communicating with each other to accomplish common goal(s). However, a MAS for enacting VE requires more advanced mechanism such as context that can guarantee autonomy and dynamism of VE members considering heterogeneity and complex structure of them. This paper is to suggest a context-based MAS as a platform for constructing and managing virtual enterprises. In the Context-based MAS a VE is a collection of Actor, Interaction (among Actors), Actor Context, and Interaction Context. It can raise the speed and correctness of decision-making and operation of VE enactment using context, i.e., information about the situation (e.g., goal, role, task, time, location, media) of Actors and Interactions, as well as simple data of their properties. The Context-based MAS for VE we proposed('VECoM') may consists of Context Ontology, Context Model, Context Analyzer, and Context Reasoner. The suggested approach and system is validated through an example where a VE tries to find a partner that could join co-development of new technology.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.83-88
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• 1999

In this paper, a novel gray-scale lossless image coder combining context-based minimum mean squared error (MMSE) prediction and entropy coding is proposed. To obtain context of prediction, this paper first defines directional difference according to sharpness of edge and gradients of localities of image data. Classification of 4 directional differences forms“geometry context”model which characterizes two-dimensional general image behaviors such as directional edge region, smooth region or texture. Based on this context model, adaptive DPCM prediction coefficients are calculated in MMSE sense and the prediction is performed. The MMSE method on context-by-context basis is more in accord with minimum entropy condition, which is one of the major objectives of the predictive coding. In entropy coding stage, context modeling method also gives useful performance. To reduce the statistical redundancy of the residual image, many contexts are preset to take full advantage of conditional probability in entropy coding and merged into small number of context in efficient way for complexity reduction. The proposed lossless coding scheme slightly outperforms the CALIC, which is the state-of-the-art, in compression ratio.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.41-46
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• 2008

In ubiquitous computer environment, by improving the computer's access to context information for dynamic service adaptation, we can increase richness of communication in human computer interaction and make it possible to produce more useful computational services. We need new data structure in order to flexible apply dynamic information to current context information repository and enhance the communication ability between human and computer. In this paper, we proposed to C-A-V (Category-Attribute-Value) context metadata structure required to support dynamic service adaptation for increasing communication ability in user-centric environments. We also classify the context metadata, as well as define its relationship with other context information on the basis of the application services, changes in the external environments.

• The Journal of Society for e-Business Studies
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• v.11 no.2
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• pp.13-30
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• 2006

Web services are independent on a platform and are suitable in the Ubiquitous environment which an interaction for each device. Ubiquitous web services can use various applied service in any network neighborhood or terminal. Main characteristic of Ubiquitous is context-awareness. Therefore, Ubiquitous web services must include context-aware control process and protect user privacy because context-aware environment collects privacy data. But current web services standard is not specially designed in respect of context-communication. Therefore, the framework which can add flexibility in transmission of context is required. Our Framework can give extension for context and can communicate flexibly Context information for every session. Therefore, Our Framework can solve overhead problem of context in SOAP message and protect user's privacy according to user preference.

• Journal of Software Engineering Society
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• v.24 no.1
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• pp.19-26
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• 2011

Since smart phones have various embedded sensors and high portability/usability, they have emerged as suitable targets to collect information and to provide intelligent services. That is, with a smart phone, we can collect information about user's circumstances and phone usage from sensors and infer his/her current state which is the significant basis for context-aware services. However, a service system should be founded on a context model to ensure reasonable context-awareness, because context information the system needs depends on its target services. Therefore, in this paper, we propose a hierarchical mobile context model for context inference of smart phone users in their daily life. We classify high-level context which can be draw from sensing data into three levels, Context-Behavior-Situation, and define inference methods for each level. With our mobile context model, we can user's meaningful context in his/her daily life besides simple actions or states.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.110-115
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• 2006

In pure P2P environment, it is possible to provide service by using a little real-time information without using accumulated information. But in case of using only a little information that was locally collected, quality of recommendation service can be fallen-off. Therefore, it is necessary to study a method to improve qualify of recommendation service by using users' context information. But because a great volume of users' context information can be recognized in a moment, there can be a scalability problem and there are limitations in supporting differentiated services according to fields and items. In this paper, we solved the scalability problem by clustering context information per each service field and classifying it per each user, using SOM. In addition, we could recommend proper services for users by quantifying the context information of the users belonging to the similar classification to the service requester among classified data and then using collaborative filtering.