• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.63-66
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• 2007

기존의 홈네트워크 시스템에서 사용자의 단순한 명령을 통해 서비스를 제공하는 기술은 이미 구현되어 있다. 그렇지만 가정이라는 환경은 이렇게 단순한 환경이기보다, 다수의 가족 구성원으로 이루어져 있으며 그에 따른 다양한 명령과 상황이 존재하고 있다. 이러한 다변화된 특성에 맞추어 사용자의 단순 명령보다 한 단계 높은 수준으로 사용자의 욕구를 능동적으로 추론해 낼 수 있는 모델의 제안이 필요하다. 본 논문에서 베이지안 네트워크를 활용하여 사용자의 주변 환경 정보로 규정된 Context를 인식하고 인식된 결과를 통해 사용자가 요구하는 적합한 서비스(Context-based Service)를 추론해 낼 수 있는 모델을 제시하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.19-27
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• 2010

Many security issues occur in cloud computing service environment such as authentication, access control, and so on. In this paper, we propose an effective authentication and access control model which provide integrated management and control when we access various resources in cloud computing environment. To address these problems, we suggest a context-aware single sign-on and access control system using context-awareness, integrated authentication, access control, and OSGi service platform in cloud computing environment. And we show design and implementation of context-aware single sign-on and access control system. Also we verified the flexibility and convenience of the proposed system through multi fact based integrated authentication in cloud computing environment. We could provide flexible and secure seamless security service by user context in cloud computing environment.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.1-12
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• 2013

Context-awareness is a computing technology that automatically delivers useful services to users based on their situation. Most previous studies on context-awareness adopted the view that the user simply is a consumer of what the developer creates. Few studies addressed catering to the need of personalized services for the user. They are either too complex for the user to grasp or unable to express many useful services due to their weak expressive power. To address these issues, we propose Dobby as a new model and architecture for user-driven context-aware service development. Dobby enables the user to create services that are more suited to his personal preferences. We argue that Dobby offers an enhanced method for defining personalized context-aware services over existing methods.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.529-536
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• 2004

Smart homes integrated with sensors, actuators, wireless networks and context-aware middleware will soon become part of our daily life. This paper describes a context-aware middleware providing an automatic home service based on a user's preference. The context-aware middle-ware utilizes 6 basic data for learning and predicting the user's preference on the multimedia content : the pulse, the body temperature, the facial expression, the room temperature, the time, and the location. The six data sets construct the context model and are used by the context manager module. The log manager module maintains history information for multimedia content chosen by the user. The user-pattern learning and pre-dicting module based on a neural network predicts the proper home service for the user. The testing results show that the pattern of an in-dividual's preferences can be effectively evaluated and predicted by adopting the proposed context model.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.265-272
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• 2014

This study suggests a system for preventing and coping with diverse industrial accidents available for taking place in the industrial field by designing a context-aware system of the solar cell equipment with the use of multi-sensor. It installs multi-sensor in the surrounding and major positions of the solar cell equipment, acquires data on the surrounding situations and solar cell equipment from this device, and then save it into the local memory and transmits it to the server. The saved data recognizes a situation based on the context-aware algorithm and judges depending on the perceived result. An administrator comes to have environment available for monitoring the status on the production field and equipments with real time according to the judged outcome through the context-aware algorithm. The context-aware system in the industrial field, which is put today in the ubiquitous environment, will become a service of offering appropriate information for dealing with industrial accidents through real-time inspection.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.434-443
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• 2016

Users can set manually Android phone to do particular tasks on some situations. This type of setting is inconvenient, and also provide with unnecessary services, which don't consider users' situation. In this research, we design and implement a context-aware automatic task setting application. Users can get context-aware service by setting desired tasks based on contexts using this system. We design a language for describing context-action rules, and statically check validity of context-action rules by performing syntax and semantic check.

• Proceedings of the Korea Society of Design Studies Conference
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• 2005.10a
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• pp.116-117
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• 2005

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.676-686
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• 2010

An URC (Ubiquitous Robot Companion) is aimed for providing the best service according to situational information that it recognizes. In order to offer human-friendly and intelligent services, a robot middleware requires the technique to automate and control URC service processes, which are based on context-awareness. In this paper, we propose a context-aware workflow system to provide web services based URC services according to situational information. The proposed system offers a platform-independent command object model to control heterogeneous URCs, and supports web services based context-aware URC services. Therefore, the proposed system can increase the reliability of URC services in ubiquitous network environment, on which the diverse URC robots and platforms exist. And it can enhance the flexibility and adaptability of the functional and structural changes of URC systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1120-1127
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• 2008

This paper presents implementation of localization system using UWB (Ultra-Wide Band) sensors and its experimental results along with development of context-aware services. In order for precise measurement of position, we experimented various conditions of pitch angles, yaw angles, number of sensors, height of tags along with measuring errors at each installation. As an application examples of the location tracking system, we developed an intelligent health training management system based on context-aware technology. The system provides appropriate training schedule to a trainee by recognizing position of the trainee and current status of gymnastic equipments and note the usage of the equipment through a personal digital assistant (PDA). Error compensation on position data and moving direction of the trainee was necessary for context-aware service. Hence, we proposed an error compensation algorithm using velocity of the trainee. Experimental results showed that proposed algorithm had made error data reduce by 30% comparing with the data without applying the algorithm.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.185-193
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• 2010

With the emergence of ubiquitous computing era, various models for providing personalized service have been proposed, and, especially, several recommendation service schemes have been proposed to give tailored services to users proactively. However, the previous recommendation service schemes utilize a wide range of data without and filtering and consider the limited context-aware information to predict user preferences so that they are not adequate to provide personalized service to users. In this paper, we propose an adaptive recommendation service scheme which proactively provides suitable services based on the current context. We use accumulated interaction contexts (IC) between users and devices for predicting the user's preferences and recommend adaptive service based on the current context by utilizing clustering and collaborative filtering. The clustering algorithm improves efficiency of the recommendation service by focusing and analyzing the data that is collected from the locations nearby the users. Collaborative filtering guarantees an accurate recommendation, even when the data is insufficient. Finally, we evaluate the performance and the reliability of the proposed scheme by simulations.