• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.21-29
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• 2011

U-health care services have been attracted to effectively solve some problems in promoting health and preparing aging society. Although the recent U-health care services have been developed to treat diseases, it requires environment information related to health for preventing fundamental diseases and for promoting health. In this study, a U-health environment service that reflects context recognition information is proposed. The proposed service draws environment information using local weather and healthcare information in users' residential areas. In the context recognition based U-health environment services, various services are provided to users not only health, living weather based menu, and exercise services but user location based warning messages for dangerous regions and remote emergency services. That is, based on such context recognition, some events that are to be occurred to users are detected and then it will provide proper services. Thus, it improves the satisfaction of U-health services and its service qualities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3524-3531
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• 2010

In order to supply suitable services to users in ubiquitous computing environments, it is important to consider both location and time information which is related to all object and user's activity. To do this, in this paper, we design a spatial-temporal ontology considering user context and propose a system architecture for active mining user activity and service pattern. The proposed system is a framework for active mining user activity and service pattern by considering the relation between user context and object based on trigger system.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.568-572
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• 2007

With the proliferation of advanced wireless network and sensor technologies, smart devices under USN(ubiquitous sensor network) environment are capable of collecting context information such as temperature, humidity, weight, and location about objects at real time. Therefore, applications must be able to analyze collected information and notify useful information to wanted users timely. This service can be realized by implementing an event-based middleware. In the middleware, event messages collected from physical environment will be filtered according to profiles that users define in advance and the result will be sent to the interested users. In this paper, we present XML-based event model, ECA-based profile model, and the architecture of an event-based middleware suitable to USN environment. We will also model and describe them using the examples of logistics area. By implementing the system based on the design above, the middleware enable applications or users to easily access to physical sources. The proposed middleware can also apply to not only logistics area but also other various areas under USN environment such as intelligent traffic control system, national disaster management system and u-medical system.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.119-132
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• 2005

The health care system revolutionized by the use of information and communication technologies. Computer information processing and electronic communication technologies play an increasingly important role in the area of health care. We propose a new role based access control model for pervasive health care systems, which changed location, time, environment information. Also our model can be solved the occurrence of an reduction authority problem to pervasive health care system at emergency environment. We propose a new role based access control model for pervasive health care systems, which combines role-to-role delegations, negative permission, context concept and dynamic context aware access control. With out approach we aim to preserver the advantages of RBAC and offer groat flexibility and fine-grained access control in pervasive healthcare information systems.

• Science of Emotion and Sensibility
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• v.25 no.3
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• pp.107-116
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• 2022

Purpose: Researchers have shown that aesthetic judgments of artworks depend on contexts, such as the authenticity of an artwork (Newman & Bloom, 2011) and an artwork's location of display (Kirk et al., 2009; Silveira et al., 2015). The present study aims to examine whether contextual information related to the creator, such as whether an artwork was created by a human or artificial intelligence (AI), influences viewers' preference judgments of an artwork. Methods: Images of Impressionist landscape paintings were selected as human-made artworks. AI-made artwork stimuli were created using Google's Deep Dream Generator by mimicking the Impressionist style via deep learning algorithms. Participants performed a preference rating task on each of the 108 artwork stimuli accompanied by one of the two creator labels. After this task, an art experience questionnaire (AEQ) was given to participants to examine whether individual differences in art experience influence their preference judgments. Results: Setting AEQ scores as a covariate in a two-way ANCOVA analysis, the stimuli with the human-made context were preferred over the stimuli with the AI-made context. Regarding the types of stimuli, the viewers preferred AI-made stimuli to human-made stimuli. There was no interaction effect between the two factors. Conclusion: These results suggest that preferences for visual artworks are influenced by the contextual information of the creator when the individual differences in art experience are controlled.

• Korean Institute of Interior Design Journal
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• no.40
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• pp.149-157
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• 2003

The placeness has been lost in space design since Modernism, especially Internationalism. Digital space design of today is one of the means to complement that. The purpose of this study is to grasp a trend in the expression of placeness, being appeared in digital space design process through case analysis. As the result of this study, the placeness in digital design process expressed by parametric elements had each effective internal algorithms. Especially, space design using digital process were expressed placeness by physical context such as topography, conditions of location, landscape, axis of road, traffic elements and climate. And social context were expressed by user experience through his cognition.

• MALSORI
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• no.50
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• pp.139-150
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• 2004

A Phonetic Tied-Mixture (PTM) model has been proposed as a way of efficient decoding in large vocabulary continuous speech recognition systems (LVCSR). It has been reported that PTM model shows better performance in decoding than triphones by sharing a set of mixture components among states of the same topological location[5]. In this paper we propose a Phonetic Tied-Mixture Syllable (PTMS) model which extends PTM technique up to syllables. The proposed PTMS model shows 13% enhancement in decoding speed than PTM. In spite of difference in context dependent modeling (PTM : cross-word context dependent modeling, PTMS : word-internal left-phone dependent modeling), the proposed model shows just less than 1% degradation in word accuracy than PTM with the same beam width. With a different beam width, it shows better word accuracy than in PTM at the same or higher speed.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.118-131
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• 2012

The existing electronic tagging system traces the location of a sex offender through communicating with GPS satellites and mobile phone base stations in order to prevent repeated crimes. However, the GPS satellite communication method does not work well in the interiors of downtown buildings or on the subways where it is difficult to receive satellite signals. In such cases, the location can be traced through communication with mobile phone base stations. But the distance between mobile phone base stations is several hundred meters, and as a result the margin of error for location tracing can be maximum of 2km in accuracy reduction. Take for example, if a kindergarten is located on the 2nd floor and a coffee shop and the sex offender are located on the 3rd floor in a 5-story building that is downtown, the existing electronic tagging system cannot trace the location of the sex offender as the GPS satellite communication does not work in the interior of the building and the exact floor that the sex offender is located on cannot be recognized through communication with mobile phone base stations. This occurrence is a big problem for the existing electronic tagging system, which is based on position recognition. Therefore, this study suggests a smart electronic tagging system that can monitor sex offenders by using a Ubiquitous Sensor Network in such extreme situations where position recognition is not possible.

• Journal of the Korean School Mathematics Society
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• v.9 no.2
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• pp.141-161
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• 2006

In this study, we classified word problems related to real life presented in elementary mathematics textbooks into five types of context problems(location, story, project, scrap, theme) suggested by Freudenthal(1991), and applied context problems to mathematics class to analyze the influence on students' mathematical belief and attitude. Also, we examined the types of context problems preferred according to academic performance and the reasons of preference within a group experiencing context problems. The results of the study are as follows. First, almost lessons in the mathematics textbook presents word problems related to real life, but the presenting method is inclined to a story type. Also, the problems with a story type are presented fragmentarily. Therefore, although these word problems are familiar to the students, they don't include contextual meanings and cannot induce enough mathematical motives and interests. Second, a lesson using context problems give a positive influence on their mathematics belief and attitude. It is also expected to give a positive influence on students' mathematics learning in the long run. Third, the preferred types of context problems and the reasons of preference are different according to the level of academic performance within the experimental group.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.84-95
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• 2009

The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.