• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.57-60
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• 2009

국내 소비시장의 일부분인 재래시장은 현대화와 정보화로 인해 소비자가 감소함에 따라 시설개선, 홍보이벤트 등 외형적인 부분에 중점적으로 변화가 일어나고 있다. 하지만, 소비자들의 편리성을 고려한 서비스에 대해서는 그 대책이 미흡한 실정이다. 이에 따라 본 논문에서는 재래시장의 활성화를 위하여 이기종 센서 및 RFID 태그를 통해 재래시장의 실시간 정보를 얻고, 이를 소비자 및 판매자의 정보와 함께 규칙/사례기반추론 방식을 이용하여 다양한 맞춤형 서비스를 제공할 수 있는 상황인식 기반의 u-CMIS(ubiquitous-Conventional Market Information System) 모델을 제안한다. 본 논문에서 제안하는 u-CMIS 모델은 소비자가 재래시장을 효율적으로 이용할 수 있도록 기존의 온라인 마켓과 모바일 온라인마켓을 통해 언제 어디서나 실시간으로 재래시장의 정보 및 맞춤형 서비스를 제공받을 수 있으며, 이를 통해 소비시간을 단축하거나 물품을 저렴하게 구입할 수 있을 것이다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.31-36
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• 2005

Intelligent Space (iSpace) is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment comes to have intelligence. In iSpace, the locations of multiple humans and other objects are obtained and tracked by using multiple camera and color-based method. In addition, we describe a context-aware information system which is based on Spatial-Knowledge-Tags (SKT). SKT system enables humans to access information and data by using spatial location of human and stored information in storage. The proposed tracking method is applied to the intelligent environment and its performance is verified by the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.476-479
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• 2005

The information available on the Internet has become widely used, primarily due to the ability of Web based E-Commerce and M-Commerce Retrieval Engines to find useful information for users. However, present day Commerce Retrieval Engines are far from perfect because they return results based on simple user keyword matches without any regard for the concepts in which the user is interested. In this thesis, we design and evaluate a Recommender system for web context aware based information retrieval using user profiles. Also, we designed personalization framework in ubiquitous environment based both e-commerce and m-commerce and presented the interaction of user profile including User XQuery pattern in semantic web.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1498-1504
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• 2016

The progress of mobile computing technology is bringing a large amount of multimedia contents such as image. Thus, we need an image retrieval system which searches semantically relevant image. In this paper, we propose a semantic image annotation and retrieval in mobile environments. Previous mobile-based annotation approaches cannot fully express the semantics of image due to the limitation of current form (i.e., keyword tagging). Our approach allows mobile devices to annotate the image automatically using the context-aware information such as temporal and spatial data. In addition, since we annotate the image using RDF(Resource Description Framework) model, we are able to query SPARQL for semantic image retrieval. Our system implemented in android environment shows that it can more fully represent the semantics of image and retrieve the images semantically comparing with other image annotation systems.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.6
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• pp.281-288
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• 2017

In Smart-cities, various types of integrated services must be linked to provide services to applications. Therefore, flexibility must be ensured between services so that various services can be efficiently provided. In order to secure the flexibility among services, it is very important to have a function to dynamically discover and invoke a desired service by searching for a semantic service by reflecting a recognized context through real-time context-aware in smart-cities. To date, quite a number of semantic service discovery techniques have been developed. However, they have not been verified as suitable for use in the smart-city domain. In this study, we tried to verify the existing ones to use a suitable one. We tested most of existing semantic service discovery techniques, but we found that none of them is suitable to our research. Therefore, we developed our own semantic service discovery technique. This paper introduces our work and presents the performance evaluation results that demonstrate that our developed works well and show good performance. For the performance evaluation, the experimental system was actually constructed and the real performance was measured. In the experiment, we implemented the semantic service discovery scenario that dynamically searches and calls the services needed to provide fire accident management services in smart cities.

• Journal of KIISE:Software and Applications
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• v.34 no.8
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• pp.763-771
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• 2007

As software is widely used on various environments today, there is an increasing need for adaptive software. Adaptive software is robust and flexible software that modifies its own behavior in response to the changes in its environment. Due to time constraints, high complexity and so on, it is hard to acquire context information from environment. So, when implementing software, it is common to think easily acquired data to be the environments. This research proposes an adaptive software framework that assumes plane images to be environments. Plane images are easy to acquire and have enough complexity. From this, our framework is able to acquire context information, reasons with action rule, and acts on the result of reasoning. Stand on this framework, implements software that plays a simple game automatically.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.19-26
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• 2014

An ensemble classifier system is a widely-used multi-classifier system, which combines the results from each classifier and, as a result, achieves better classification result than any single classifier used. Several methods have been used to build an ensemble classifier including boosting, which is a cascade method where misclassified examples in previous stage are used to boost the performance in current stage. Boosting is, however, a serial method which does not form a complete feedback loop. In this paper, proposed is context sensitive SVM ensemble (CASE) which adopts SVM, one of the best classifiers in term of classification rate, as a basic classifier and clustering method to divide feature space into contexts. As CASE divides feature space and trains SVMs simultaneously, the result from one component can be applied to the other and CASE achieves better result than boosting. Experimental results prove the usefulness of the proposed method.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.35-48
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• 2017

There are many and various devices like sensors, displays, smart phone, etc. in smart environment. And contents can be provided by using these devices. Vast amounts of contents are provided to users, but in most environments, there are no regard for user or some simple elements like location and time are regarded. So there's a limit to provide meaningful contents to users. In this paper, I suggest the contents recommendation system that can recommend contents to users by reasoning context of users, devices and contents. The contents recommendation system suggested in this paper recommend the contents by calculating the user preferences using the situation reasoned with the contextual data acquired from various devices and the user profile received from the user directly. To organize this process, the method on how to model ontology with domain knowledge and how to design and develop the contents recommendation system are discussed in this paper. And an application of the contents recommendation system in Centum City, Busan is introduced. Then, the evaluation methods how the contents recommendation system is evaluated are explained. The evaluation result shows that the mean absolute error is 0.8730, which shows the excellent performance of the proposed contents recommendation system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.72-81
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• 2011

In this paper, we propose adaptive convergence security policies and management technologies to improve security assurance in the home networking environment. Many security issues may arise in the home networking environment. Examples of such security issues include the user privacy, the service security, the integrated networking security, the middleware security and the device failure. All these security issues, however, should be fulfilled in phase due to many difficulties including deployment cost and technical complexity. For instance, fundamental security requirements such as authentication, access control and prevention of crime and disaster should be addressed first. Then, supplementary security policies and diverse security management technologies should be fulfilled. In this paper, we classify these requirements into three categories, a service authentication, a user authentication and a device authentication, and propose security policies and management technologies for each requirement. Since the home gateway is responsible for interconnection of many home devices and external network access, a variety of context information could be collected from such devices.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.40-42
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• 2011

Smart hand-held devices like iPhone, iPad, Andriod and other mobile-OS machines are becoming a well known part of our daily lives. Utilization of these devices has gone beyond the expectations of their inventors. Evolution of Apple's iOS from a mobile phone Operating System to a wholesome platform for Portable Gaming is an adequate proof. Using these smart devices people are downloading applications from numerous online App Stores. Utilizing remote storage facilities and confining themselves to computing power far below than an entry level laptop, netbooks have emerged. Google's idea of Chrome OS coupled with Google's AppEngine is an eye-opener for researchers and developers. Keeping all these industry-proven innovations in mind we are proposing a Context-Driven Cloud-Oriented Application Architecture for smart devices. This architecture enables our smart devices to behave smarter by utilizing very less of local resources.