• Korean Journal of Computational Design and Engineering
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• v.11 no.5
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• pp.365-374
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• 2006

The ubiquitous environment is to support people in their everyday life in an inconspicuous and unobtrusive way. This environment requires information such as the person, his/her preferences, and habits which is available in the ubiquitous system. In this paper, we propose the context aware system that can provide the tailored information service for user in ubiquitous computing environment. Our system architecture is divided into 4 domain models such as context awareness, presentation, interface and inference domain. Each domain model can perform some predefined tasks independently. And we suggest the hybrid algorithm combined with fuzzy and Bayesian method in order to reason what is the suitable information for user. We show the possibility for the real application through applying the system to the TGA (Tour Guide Assistant) for Kyoungju historical site.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.655-660
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• 2009

The context prediction algorithms are not suitable to provide real-time personalized service for users in context-awareness environment. The algorithms have problems like time delay in training data processing and the difficulties of implementation in real-time environment. In this paper, we propose a prediction algorithm with user modeling to shorten of processing time and to improve the prediction accuracy in the context prediction algorithm. The algorithm uses moving path of user contexts for context prediction and generates user model by time-series analysis of user's moving path. And that predicts the user context with the user model by sequence matching method. We compared our algorithms with the prediction algorithms by processing time and prediction accuracy. As the result, the prediction accuracy of our algorithm is similar to the prediction algorithms, and processing time is reduced by 40% in real time service environment.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.165-172
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• 2023

Heterogeneous computing is a technology that utilizes different types of processors to perform parallel processing. It maximizes task processing and energy efficiency by leveraging various computing resources such as CPUs, GPUs, and FPGAs. On the other hand, edge computing has developed with IoT and 5G technologies. It is a distributed computing that utilizes computing resources close to clients, thereby offloading the central server. It has evolved to intelligent edge computing combined with artificial intelligence. Intelligent edge computing enables total data processing, such as context awareness, prediction, control, and simple processing for the data collected on the edge. If heterogeneous computing can be successfully applied in the edge, it is expected to maximize job processing efficiency while minimizing dependence on the central server. In this paper, experiments were conducted to verify the feasibility of various parallel programming models on high-end and low-end edge devices by using benchmark applications. We analyzed the performance of five parallel programming models on the Raspberry Pi 4 and Jetson Orin Nano as low-end and high-end devices, respectively. In the experiment, OpenACC showed the best performance on the low-end edge device and OpenSYCL on the high-end device due to the stability and optimization of system libraries.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.19-30
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• 2012

The context aware service is the service to provide useful information to the users by recognizing surroundings around people who receive the service via computer based on computing and communication, and by conducting self-decision. But CAS(Context Awareness System) shows the weak point of small-scale context awareness processing capacity due to restricted mobile function under the current mobile environment, memory space, and inference cost increment. In this paper, we propose a mobile cloud context system with using Google App Engine based on PaaS(Platform as a Service) in order to get context service in various mobile devices without any subordination to any specific platform. Inference design method of the proposed system makes use of knowledge-based framework with semantic inference that is presented by SWRL rule and OWL ontology and Jess with rule-based inference engine. As well as, it is intended to shorten the context service reasoning time with mapping the regular reasoning of SWRL to Jess reasoning engine by connecting the values such as Class, Property and Individual which are regular information in the form of SWRL to Jess reasoning engine via JessTab plug-in in order to overcome the demerit of queries reasoning method of SparQL in semantic search which is a previous reasoning method.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.63-70
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• 2008

As the number of cell phone users become growing, some researchers have presented that the imprudent use of mobile phones exerts harmful influence on electronic devices such as medical appliances, takeoff and landing system of aircraft. In this paper, we propose a usage model based on context-awareness which can be applied to mobile devices. The model controls the usage of both mobile devices themselves and mobile contents according to some context information like location, time, the circumference noise, etc. The proposed usage control model includes a dynamic role-based access control approach. To show the effectiveness of the proposed model, we have implemented a prototype system on an embedded board and PC server, and evaluated the performance of the system.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.167-177
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• 2009

This paper is about our experience of developing a context-aware exhibit guide system called MyGuide by applying Simtext development methodology. In particular, we introduce some issues to be considered in development process, the way that we solved them, and other things related to context. In requirements elicitation phase, we reduced the complexity of requirements by separating business logic requirements and context-awareness related requirements. After that, we modeled context, and designed software architecture, classes, and database in sequence during design phase. We considered system requirements and context modeling issues for context modeling because it influences class and database design.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.659-664
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• 2006

The Context-Aware system is the core technology in the Ubiquitous Computing Environment. Recently, the practical use of a sensor is magnified and the application fields of it are gradually extended in order to collect necessary context information. Context-Aware service integrates the context information which is collected by sensors, and then provides, a suitable service to a user through the process of analysis and reasoning. This service is studied in a variety of fields such as marketing, medical treatment, education and so on. In this paper, we analyze the method of recognizing surrounding context and the result of the awareness by using differential and structural property of multiple valued logic function; propose the model that provides appropriate service depending on the change of surrounding contort; confirm the applicability of the Context-aware system by showing the example of application.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.542-551
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• 2009

We proposed the context based user profile which is aware of its user's situation and based on user's situation it recommends personalized services. The user profile which consists of (context, service) pair can be acquired by the context and the service usage of a user; it then can be used to recommend personalized services for the user. In this paper, we show how they can be evolved without previously known user information so that not to violate privacy during the learning phase; in the result our user profile can be applied to any new environment without any modification to model only except context profiles. Using context-awareness based user profile, the service usage pattern of a user can be learned by the union of contexts and the preferred services can be recommended by the current environments. Finally, we evaluate the precision of proposed approach using simulation with data sets of UCI depository and Weka tool-kit.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.542-546
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• 2007

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.125-132
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• 2009

The goal of our research is to develop a smart context-aware guide system that provides a smart and personalized guide services based on implicit awareness of context. As a context-aware guide application, we have developed a location-aware smart bus guide system for Seoul based on PDA and GPS. It guides users to the nearby bus stops and provides users with information about the bus lines at the bus stops.