• Journal of KIISE:Computing Practices and Letters
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• v.11 no.4
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• pp.381-392
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• 2005

Computing has been making a lot of progress in the quantity of data, today. It's going to be more difficult to get appropriate information as the number of data increases dramatically. Therefore it's more important to get meaningful information than to focus on the speed of processing. Semantic web enables an intelligent processing by adding semantic information to data, and it is useful to make ontology system. In this Paper, we implemented ontology Processing system which support function for ontology and efficient processing for practical service. We proposed system design for independent from storage, storing technique for RDB, caching technique by schema information and useful user interface.

• The Journal of the Korea Contents Association
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• v.14 no.7
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• pp.29-44
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• 2014

To provide context aware service, certain phenomena and situation information of the user should be detecting and monitoring using sensors. But, the sensor data has heterogeneity about system, syntax, structure, and semantics. So, it is difficult to apply to various services. To solve this issue, we should remove these heterogeneities and convert to context information that is easy to provide context aware services. Also, the existing context aware service mash-up environment require relevant sensor type, criteria of context, programing ability to define the service situation. So, it is difficult to create service for a non-technical user. Therefore, we propose ontology based user-centric service environment to provide context aware IoT services. It provide context awareness and user-desired services using data that acquired via IoT paradigm. The proposed environment consist of the ontology based semantic sensor data processing and the user-centric service environment. It provide convert the object data to the context information and service mash-up process to create user service in easy way.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.889-898
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• 2009

Currently, the amount of containers is growing up continuously. However, they still depend on humans checking or validating. In this situation, humans must participate in the systems. Situation-awareness technologies allow human participation to be minimized. The situation-awareness technologies provide data or service appropriate to the object's current state, and the state is recognized automatically by the system. They can automatically execute working processes without human intervention. We suggest a middleware system based on situation-awareness technologies using an ontology for the safety transportation of containers. The middleware is aware of the current state and sends the data required by an application. It can help build new applications by enhancing agility, and it can also support automated service processing by invoking the service required like fire-fighting, fixing container, and so on. Improving transportation of containers process automation with situation-awareness technologies reduces manpower requirements for checking and validating containers, and so saves logistics costs of container transportation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.331-333
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• 2010

최근 IT산업의 발전으로 인해 광범위한 정보가 존재하는 웹 기반 환경에서 원하는 정보의 검색과 검출을 위한 시멘틱 웹(Semantic Web) 기반의 온톨리지에 대하여 연구가 다양하게 진행 중이다. 본 논문에서는 온톨로지 기법을 이용하여 인간의 다양한 편의와 친환경적인 습지의 수질 관리에 대한 통합적이고 편리한 관리를 위해 WSN 기반의 습지 수질 관리에 특화된 온톨리지 설계 및 구축을 진행하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.152-157
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• 2006

상황 정보 관리 시스템은 외부에서 입력된 상황 정보의 숨겨진 의미를 파악하여 상황인지 에이전트 및 상황인지 브로커가 효과적으로 상황정보를 획득하도록 한다. 본 논문에서는 외부 환경으로부터 받은 상황정보의 숨겨진 의미를 파악하기 위해 DL 추론과 시간적 추론을 적용한 상황 정보 관리 시스템을 제안한다. 이를 위해서 3가지 부분에 초점을 두었다. 첫 번째, 외부에서 입력된 상황 정보를 효율적으로 표현하고 여러 에이전트간의 상황 정보 공유가 가능하도록 온톨로지 모델을 적용한다. 온톨로지로 표현된 상황정보는 정보의 속성을 제약함으로써 숨겨진 상황 정보를 추론할 수 있도록 해준다. 두 번째로 상황 정보의 관계를 추론할 수 있도록 서술 논리(Description Logic)를 적용한다. 마지막으로 상황 정보의 시간적 관계를 추론할 수 있도록 시간 논리(Temporal Logic)을 적용한다. 따라서 본 논문에서의 최종 목표는 상황 정보 관리 시스템 연구를 통해 상황인지 에이전트 및 상황인지 브로커에 활용이 가능한 온톨로지 기반 추론 기능을 보유하는 지능형 모듈의 기본 프레임워크를 구축하는 것이다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.9-20
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• 2011

Future warfare paradigm is changing to network-centric warfare and effects-based operations. In order to find first and strike the enemy in the battlefield, friendly unit requires real-time target acquisition, intelligence collection, accurate situation assessment, and timely decision. The rapid development in advanced sensor technology and wireless networks requires a significant change in operational concepts of the battlefield surveillance. In particular, the introduction of a battlefield surveillance sensor network system is a big challenge to the ground forces which have lack of automated information collection assets. Therefore this paper proposes an ontology-based context-aware framework for the battlefield surveillance sensor network system which is needed for early finding the enemy and visualizing the battlefield in the ground force operations. Compared with the performance of existing systems, the one of the proposed framework has shown highly positive results by applying the context systems evaluation method. The framework has also proven to be satisfactory by the structured evaluation method using device collaboration. Since the proposed ontology-based context-aware framework has a lot of advantages in terms of scalability and reusability, the ground force's reconnaissance and surveillance system can be widely applied to expand in the future. And, ontology-based model has some weak points such as ontology data size, processing time, and limitation of network bandwidth. However, these problems can be resolved by customizing properly to fit the mission and characteristics of the unit. Moreover, development of the next-generation communication infrastructure can expedite the intelligent surveillance and reconnaissance service and may be expected to contribute greatly to expanding the information capacity.

• Journal of KIISE
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• v.42 no.3
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• pp.295-306
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• 2015

MOnCa2 is a framework for building intelligent smartphone applications based on smartphone sensors and ontology reasoning. In previous studies, MOnCa determined and inferred user situations based on sensor values represented by ontology instances. When this approach is applied, recognizing user space information or objects in user surroundings is possible, whereas determining the user's physical context (travel behavior, travel destination) is impossible. In this paper, MOnCa2 is used to build recognition models for travel behavior and routes using smartphone sensors to analyze the user's physical context, infer basic context regarding the user's travel behavior and routes by adapting these models, and generate high-level context by applying ontology reasoning to the basic context for creating intelligent applications. This paper is focused on approaches that are able to recognize the user's travel behavior using smartphone accelerometers, predict personal routes and destinations using GPS signals, and infer high-level context by applying realization.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.460-469
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• 2006

Recently, a demand of adaptive multimedia service, which supports multimedia service migration according to user's location and characteristics of user device, is increased. In this paper, we propose a service migration system, which becomes aware of user device using intelligent agent. And we design and implement the ontology-based intelligent agent, which is aware of the context in its environment. Moreover, we implement a context reasoning system using location information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.188-194
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• 2007

We propose a new ad hoc multicast routing protocol for based on the ontology scheme called inference network. Ontology knowledge-based is one of the structure of context-aware. We will have developed an algorithm that will design multi-hierarchy Layered networks to simulate a desired system.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.254-263
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• 2006

Ontology-based context models are widely used in ubiquitous computing environment because they have advantages in the acquisition of conceptual context through inferencing, context sharing, and context reusing. Among the benefits, inferencing enables context-aware applications to use conceptual contexts which cannot be acquired by sensors. However, inferencing causes processing delay and thus becomes the major obstacle to the implementation of context-aware applications. The delay becomes longer as the amount of contexts increases. In this paper, we propose a context pre-fetching method to reduce the size of contexts to be processed in a working memory in attempt to speed up inferencing. For this, we extend the query-tree method to identify contexts relevant to the queries of a context-aware application. Maintaining the pre-fetched contexts optimal in a working memory, the processing delay of inference reduces without the loss of the benefits of ontology-based context model. We apply the proposed scheme to our ubiquitous computing middleware, Active Surroundings, and demonstrate the performance enhancement by experiments.