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

• Proceedings of the Korean Information Science Society Conference
• /
• 2004.10b
• /
• pp.613-615
• /
• 2004

유비쿼터스 컴퓨팅 환경에서 가장 중요한 이슈중의 하나는 상황인지(Context-Aware)가 가능한 환경을 구축하는 것이다. Context-Aware 환경이 구축되면 주변의 상황을 감지하여 특정 어플리케이션을 실행한다거나, 시스템을 재구성하는 등의 일을 수행할 수 있다. 그동안 이런 상황인지가 가능한 환경을 Context-Aware 미들웨어를 통해 구현하려는 연구가 많이 수행되었다. Context-Aware 미들웨어를 구현하기 위해 무엇보다도 중요한 것은 실제 세계의 다양한 종류의 상황을 컴퓨팅 환경에 적용시키는 것이다. 그러나 현실 세계에서 Context의 종류는 거의 무한하다고 할 수 있다. 기술이 발전하게 되면서 인지 가능한 Context의 종류도 무한정 늘어나게 될 것이다 또한 실제 세계에서의 Context들은 추상적인 경우가 많이 있다. 그러나 Context가 추상적이라 해도 다른 Context 정보를 이용해서 구체화 할 수 있다. 이런 과정을 위해 Conte지들을 계층적으로 관리해야 할 필요가 있다. 본 논문에서는 Context-Aware 미들웨어를 구현할 때 Context들의 이런 여러 가지 특성들을 고려해서 Context Type을 관리랄 수 있는 하나의 객체를 제안하고, 다른 방법들과 비교, 분석해 보았다.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.2
• /
• pp.25-32
• /
• 2016

In this paper, we design a middleware for context-awareness which provides compound contexts from diverse sensors on a mobile device. Until now, most of context-aware application developers have taken responsibility for context processing from sensing data. Such application-level context processing causes heavily redundant data processing and leads to significant resource waste in energy as well as computing. In the proposed scheme, we define primitive and compound context map which consists of relavant sensors and features. Based on the context definition, each application demands a context of interest to the middleware, and thus similar context-aware applications inherently share context information and procesing within the middleware. We show that the proposed scheme significantly reduces the resource amounts of cpu, memory, and battery, and that the performance gain gets much more when multiple applications which need similar contexts are running.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.4
• /
• pp.1157-1170
• /
• 2007

LBS must manage various context data and make the best use of this data for application service in ubiquitous environment. Conventional mobile object data management architecture did not consider process of context data. Therefore a new mobile data management framework is needed to process location context data. In this paper, we design a new context management framework for a location based application service. A suggestion framework is consisted of context collector, context manager, rule base, inference engine, and mobile object context database. It describes a form of rule base and a movement process of inference engine that are based on location based application scenario. It also presents an embodiment instance of interface which suggested framework is applied to location context interference of mobile object.

• Journal of The Korean Association For Science Education
• /
• v.14 no.3
• /
• pp.304-311
• /
• 1994

Four science concepts were selected from high school science textbook to investigate the differences in priorities of students knowledge activated during solving earth science problems in laboratory and earth science environmental contexts. Two items, one for laboratory context and the other for earth environmental context, were developed for earth selected concept The subjects were constituted of 192 students in 11th grade and 196 in 12th grade in one senior high school. Students' responses were categorized using graph models and analyzed in terms of 'Common Activated Knowledge'(CAK). and 'Specific Activated Knowledge'(SAK) across students' cognitive frames, grades, and sex. As contextual differences of the problems increased, context effects in priorities of CAK were reported in favor of laboratory context, on the contrary those of SAK in favor of earth environmental context. Context effects were reported across cognitive frames, especially students with laboratory cognitive frames showed more significant context effects than others. Lower graders and girls showed relatively large context effects. The results of this study showed that science concepts learned in a laboratory context are not easily transferred to earth environmental context. Therefore, special instructional strategies should be developed to overcome the context effect s according to activated knowledges with high priorities in laboratory and earth environmental context.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.06d
• /
• pp.344-349
• /
• 2007

유비쿼터스 환경에서 사용자의 편의성을 증대하기 위해 상황인지 기술이 필요하며 댁내의 다양한 기기의 정보를 수집하여 현재 상태를 파악하고 그에 맞는 서비스를 제공해야 한다. 하지만 다양한 종류의 디바이스, 센서, 서비스에 따라 생성하는 데이터의 형태와 의미가 다르기 때문에 이를 활용하는데 어려움이 있다. 본 논문은 다양한 기기와 환경에서 발생하는 데이터를 처리하여 사용자의 패턴을 수집하고 활용할 수 있는 연구 모델을 제안하고 구현한다. 구성요소는 실제 환경과 유사하게 Context를 생성할 수 있는 Emulator와 수집된 Context를 활용하여 패턴을 찾는 패턴 수집 서버와 수집된 데이터를 표현하는 시각화 도구로 구성된다. Emulator는 댁내에 존재할 수 있는 다양한 종류의 Context를 정의하고 서로간의 관계에 따라 Context를 생성하고 패턴 수집 서버는 Emulator에서 생성한 불완전한 Context를 통합하여 완전한 Context를 생성한다. 그리고 생성된 Context를 통해서 사용자의 서비스 이용패턴, Fault, Conflict를 발견했다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.8
• /
• pp.2881-2894
• /
• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• KSCI Review
• /
• v.14 no.1
• /
• pp.165-173
• /
• 2006

To support service based on context-aware in ubiquitous computing environment, there are required context managing, context reasoning and context modeling technologies. In this paper, we propose a hierarchical ontology-based context management model and design a context-aware middleware based on this model for supporting active application adaptability and reflecting users' requirements dynamically in contextual changes. It also provides efficient support for inferencing, interpreting, acquiring and discovering various contexts to build context-aware services and presents a resolution method for context conflict which is occurred in execution of service. The proposed middleware can support the development and operation of various context-aware services, which are required in the ubiquitous computing environment.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.2
• /
• pp.119-124
• /
• 2016

According to the expansion of smartphone penetration and development of wearable device, personal context information can be easily collected. To use this information, the context aware recommender system has been actively studied. The key issue in this field is how to deal with the context information, as users are influenced by different contexts while rating items. But measuring the similarity among contexts is not a trivial task. To solve this problem, we propose context aware post-filtering to apply the context compensation. To be specific, we calculate the compensation for different context information by measuring their average. After reflecting the compensation of the rating data, the mechanism recommends the items to the user. Based on the item recommendation list, we recover the rating score considering the context information. To verify the effectiveness of the proposed method, we use the real movie rating dataset. Experimental evaluation shows that our proposed method outperforms several state-of-the-art approaches.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.333-336
• /
• 2005

The advance of wireless telecommunication and observation technologies leads developing sensor and sensor network for serving the context information continuously. Besides, in order to understand and cope with the context awareness based on the sensor network, it is becoming important issue to deal with plentiful data transmitted from various sensors. Therefore, we propose a context awareness system to deal with the plentiful sensor data in a vast area such as the prevention of a forest fire, the warning system for detecting environmental pollution, and the analysis of the traffic information, etc. The proposed system consists of the context acquisition to collect and store various sensor data, the knowledge base to keep context information and context log, the rule manager to process context information depending on user defined rules, and the situation information manager to analysis and recognize the context, etc. The proposed system is implemented for managing renewable energy data management transmitted from a large scale area.