• 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.

• 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.

• 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.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.225-232
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• 2009

Context-aware technologies for ubiquitous computing are necessary to study the representation of gathered context-information appropriately, the understanding of user's intention using context-information, and the offer of pertinent services for users. In this paper, we propose the WS-CAM(Web Services based Context-Aware Middleware) framework for context-aware computing. WS-CAM provides ample power of expression and inference mechanisms to various context-information using an ontology-based context model. We also consider that WS-CAM is the middleware-independent structure to adopt web services with characteristic of loosely coupling as a matter of communication of context-information. In this paper, we describe a scenario for lecture services based on the ubiquitous computing e e e e e e to verify the utilization of WS-CAM We also show an example of middleware-independent system expansion to display the merits of web-based services. WS-CAM for lecture services represented context-information itodomaits as OWL-based ontology model effectively, and we confirmed the information is inferred to high level context-information by user-defined rules. We also confirmed the context-information is transferred to application services middleware-independently using various web methods provided by web services.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.27-44
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• 2008

Owl-based ontology is useful to realize the context-aware services which are composed of the distributed and self-configuring modules. Many ontology-based inference engines are developed to infer useful information from ontology. Since these engines show the uniqueness in terms of speed and information richness, it's difficult to ensure stable operation in providing dynamic context-aware services, especially when they should deal with the complex and big-size ontology. To provide a best inference service, the purpose of this paper is to propose a novel methodology of context-aware engine selection in a contextually prompt manner Case-based reasoning is applied to identify the causality between context and inference engined to be selected. Finally, a series of experiments is performed with a novel evaluation methodology to what extent the methodology works better than competitive methods on an actual context-aware service.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1157-1170
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• 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 Korea Institute of Information Security & Cryptology
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• v.15 no.2
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• pp.37-52
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• 2005

Traditional access control models like role-based access control model are insufficient in security needs in ubiquitous computing environment because they take no thought of access control based on user's context or environment condition. In these days, although researches on context-aware access control using user's context or environment conditions based on role-based access control are emerged, they are on the primary stage. We present context definitions md an access control model to provide more flexible and dynamic context-aware access control based on role-based access control. Specially, we describe the conflict problems occurred in the middle of making an access decision. After classifying the conflict problems, we show some resolutions to solve them. In conclusion, we will lay the foundations of the development of security policy and model assuring right user of right object(or resource) and application service through pre-defined context and context classification in ubiquitous computing environments. Beyond the simplicity of access to objects by authorized users, we assure that user can access to the object, resource, or service anywhere and anytime according to right context.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1230-1237
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• 2009

In this paper, we develop a design methodology of Granular-based Radial Basis Function Neural Networks(GRBFNN) by context-based clustering. In contrast with the plethora of existing approaches, here we promote a development strategy in which a topology of the network is predominantly based upon a collection of information granules formed on a basis of available experimental data. The output space is granulated making use of the K-Means clustering while the input space is clustered with the aid of a so-called context-based fuzzy clustering. The number of information granules produced for each context is adjusted so that we satisfy a certain reconstructability criterion that helps us minimize an error between the original data and the ones resulting from their reconstruction involving prototypes of the clusters and the corresponding membership values. In contrast to "standard" Radial Basis Function neural networks, the output neuron of the network exhibits a certain functional nature as its connections are realized as local linear whose location is determined by the values of the context and the prototypes in the input space. The other parameters of these local functions are subject to further parametric optimization. Numeric examples involve some low dimensional synthetic data and selected data coming from the Machine Learning repository.