• 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.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.80-92
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• 2007

For the pervasive computing in ubiquitous environment, it is very important to manage the context model to provide pertinent context knowledge to context-aware applications. The context model should be able to support efficiently the context knowledge reusing and sharing as well as reasoning. Previous works focus mainly on the context knowledge representation scheme for reasoning. This paper proposes a context knowledge modeling scheme especially for reusing and sharing. This scheme provides well-established principles and guides for 1) context knowledge modularization and hierarchization, and for 2) context knowledge identification and organization. Once the context models are built according to the scheme, the structure of the context model and the meanings of the context knowledge elements become clear and consistent, so that context-aware applications can share and reuse the context knowledge in easy and error-reduced manner. This paper also discusses the implementation of a context model and an application for Presentation Helper scenario running on a software middleware system (CAMUS) for ubiquitous service robots which is being developed by ETRI Korea.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.613-615
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• 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 Information Processing Systems
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• v.10 no.4
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• pp.581-588
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• 2014

To facilitate the implementation of a wide variety of context-aware applications based on mobile devices, general-purpose context-aware framework that applications can use by calling is needed. The context-aware framework is a middleware that performs the sensing, reasoning, and retrieving based on the knowledge base. The knowledge base must systematically represent the information required on the behavior of the context-aware framework, such as context information and reasoning information. It must also provide functions for storage and retrieval. To date, previous research on the representation of the context information have been carried out, but studies on the unified representation of the knowledge base has seen little progress. This study defines the knowledge base as the unified context information, and proposes the UniOWL, which can do a good job of representing it. UniOWL is based on OWL and represents the information that is necessary for the operation of the context-aware framework. Therefore, UniOWL greatly facilitates the implementation of the knowledge base on a context-aware framework.

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

• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.691-700
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• 2006

To support context-aware services in ubiquitous computing environments, there are required dynamic context managing, context reasoning and context modeling technologies. In previous researches, context services are designed using context ontology used in context aware middleware. So, context service cannot change the context ontology in execution time. 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. As the middleware is implemented on the OSGi framework, it can cause interoperability among devices such as computers, PDAs, home appliances and sensors. It can also support the development and operation of context aware services, which are required in the ubiquitous computing environment.

• Journal of the HCI Society of Korea
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• v.8 no.1
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• pp.11-17
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• 2013

Context aware systems are those systems that are aware about the environment and perform productive functions automatically by reducing human computer interactions(HCI). In this paper, we present common architecture principles of context-aware systems to explain the important aspects of context aware systems. Our study focuses on identifying common concepts in pervasive computing approaches, which allows us to devise common architecture principles that may be shared by many systems. The principles consists of context sensing, context modeling, context reasoning, context processing, communication modelling and resource discovery. Such an architecture style can support high degree of reusability among systems and allows for design flexibility, extensibility and adaptability among components that are independent of each other. We also propose a new architecture based on broker-centric middleware and using ontology reasoning mechanism together with an effective behavior based context agent that would be suitable for the design of context-aware architectures in future systems. We have evaluated the proposed architecture based on the design principles and have done an analyses on the different elements in context aware computing based on the presented system.

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

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.437-447
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• 2011

Ubiquitous Computing is required to define models for broad context information occurrence by surrounding environment and to study how to model a mechanism for selectively collecting useful pieces of context information and providing relevant intelligent services. Further, studies are also required as to process of context information, and its maintenance and reasoning. However, current context-aware research area still lacks modeling technique that reflects the characteristics of ontology effectively for providing relevant intelligent services. It has also limitation about context reasoning and interoperability among context information. Therefore, this paper proposes ontology-based context-aware modeling technique and framework enabling efficient specification of context information for providing intelligent context-aware services that support context management and reasoning.

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