• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2284-2290
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• 2015

The use of human actions as context for object class recognition is quite effective in enhancing the recognition performance despite the large variation in the appearance of objects. We propose an efficient method that integrates human action information into object class recognition using a Bayesian appraoch based on a simple probabilistic graph model. The experiment shows that by using human actions ac context information we can improve the performance of the object calss recognition from 8% to 28%.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.63-69
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• 2016

In this paper, we proposed the location tracking system based on MS-Based/Assisted(Mobile Station-Based and Assisted) location trigger service model with context-awareness for the intelligent location tracking of moving objects. It provides the proper resulting value that matches the context of users through the analysis about the situation of the user, physical environment, computing resource and the existing information on user input. In order to provide real-time data, we proposed the location tracking system which realizes the intelligent information such as the expecting arrival time and passing the specific area of the moving object by adopting the location trigger. So, it derives to minimize the costs of communication for the mobile object tracking applications. The proposed location tracking system based on context-awareness can be used for realtime monitoring, intelligent alarm/action, setting up of the optimized moving path, dynamic adjustment of strategies and policies. So it has the advantage to develop the application system which is aimed at optimization of the object tracking and movement.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1159-1166
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• 2010

Today, detecting the location of moving object has been traced as various methods in our world. In this paper, we preset the system to improve the estimation accuracy utilizing detail localization using radar sensor based on WSN and situational awareness for a calibration (context aware) database, Rail concept. A variety of existing location tracking method has a problem with receiving of data and accuracy as tracking methodology, and since these located data are the only data to be collected for location tracing, the context aware or monitering as the surrounding environment is limited. So, in this paper, we enhanced the distance aware accuracy using radar sensor utilizing the Doppler effect among the distance measuring method, estimated the location using the Triangulation algorithm. Also, since we composed the environment data(temperature, illuminancem, humidity, noise) to entry of the database, it can be utilized in location-based service according to the later action information inference and positive context decision. In order to verify the validity of the suggested method, we give a few random situation and built test bed of designed node, and over the various test we proved the utilizing the context information through route tracking of moving and data processing.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.709-713
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• 2009

Recently, a lot of research that applies data acquired from devices such as cameras and RFIDs to context aware services is being performed in the field on Life-Log and the sensor network. A variety of analytical techniques has been proposed to recognize various information from the raw data because video and audio data include a larger volume of information than other sensor data. However, manually watching a huge amount of media data again has been necessary to create supervised data for the update of a class or the addition of a new class because these techniques generally use supervised learning. Therefore, the problem was that applications were able to use only recognition function based on fixed supervised data in most cases. Then, we proposed a method of acquiring supervised data from a video sharing site where users give comments on any video scene because those sites are remarkably popular and, therefore, many comments are generated. In the first step of this method, words with a high utility value are extracted by filtering the comment about the video. Second, the set of feature data in the time series is calculated by applying functions, which extract various feature data, to media data. Finally, our learning system calculates the correlation coefficient by using the above-mentioned two kinds of data, and the correlation coefficient is stored in the DB of the system. Various other applications contain a recognition function that is used to generate collective intelligence based on Web comments, by applying this correlation coefficient to new media data. In addition, flexible recognition that adjusts to a new object becomes possible by regularly acquiring and learning both media data and comments from a video sharing site while reducing work by manual operation. As a result, recognition of not only the name of the seen object but also indirect information, e.g. the impression or the action toward the object, was enabled.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.149-157
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• 2019

Recent research has been actively carried out on systems that want to optimize resource utilization by analyzing the intended behavior and pattern of behavior of objects (users, consumers). A service system that applies information about an object's location or behavior must include a location trigger processing system for tracking an object's real-time location. In this paper, we analyze design problems for the implementation of a context-awareness based location trigger system, and present system models based on analysis details. For this purpose, this paper introduces the concept of location trigger for intelligent location tracking techniques about moving situations of objects, and suggests a mobile agent system with active rules that can perform monitoring and appropriate actions based on sensing information and location context information, and uses them to design and implement the location trigger system for context-awareness based location services. The proposed system is verified by implementing location trigger processing scenarios and trigger service and action service protocols. In addition, through experiments on mobile agents with active rules, it is suggested that the proposed system can optimize the role and function of the application system by using rules appropriate to the service characteristics and that it is scalable and effective for location-based service systems. This paper is a preliminary study for the establishment of an optimization system for utilizing resources (equipment, power, manpower, etc.) through the active characteristics of systems such as real-time remote autonomous control and exception handling over consumption patterns and behavior changes of power users. The proposed system can be used in system configurations that induce optimization of resource utilization through intelligent warning and action based on location of objects, and can be effectively applied to the development of various location service systems.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.5
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• pp.497-519
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• 2003

Science and technology is an essential ingredient of the progress in modern society. Measurements enable action and actions enable results. Non-Destructive Evaluation (NDE) - the science and technology of measurements without affecting the Properties and performance of the test object is an interdisciplinary domain area of high significance far ensuring quality, productivity and safety thus enabling better qualify of lift to the inhabitants on this planet. The test object can be material, component, plant, earth, environment etc. Total qualify management, total productivity management, concurrent engineering and many other essential ingredients of success in plant engineering and manufacturing industry are dependent on NDE far success and good returns on investments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.573-576
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• 2014

In this paper, it provides social network service using context-aware for tourism. For this the service requires Anthropomorphic natural process. The service object need to provide the function analyzing, storing and processing user action. In this paper, it provides an algorithm to analysis with personalized context aware for users. Providing service is an algorithm providing social network, helped by 'Friend recommendation algorithm' which to make relations and 'Attraction recommendation algorithm' which to recommend somewhere significant. Especially when guide is used, server analysis history and location of users to provide optimal travel path, named 'Travel path recommendation algorithm'. Such as this tourism social network technology can provide more user friendly service. This proposed tour guide system is expected to be applied to a wider vary application services.

• Journal of Science Education
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• v.43 no.2
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• pp.239-257
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• 2019

This study attempts to understand the context of shared learning in the trading zone formed by teachers from different backgrounds and the process in which this shared learning varies in the educational context, focusing on the case of 'Woodwork Science Education Study Group.' To do this, data was collected through in-depth interviews with eight teachers who participated in the 'Woodworking Science Education Research Group' and analyzed their responses based on grounded theory. As a result, the causal conditions of the teachers' research group were 'various contexts of entering the trading zone' and the central phenomenon was 'encounter with learning in the trading zone.' Contextual conditions affecting this phenomenon were 'woodwork as a boundary object and individual transfiguration experience,' and action/interaction strategy was 'various efforts and influences in the field.' The intervention condition was 'practical effort and experience in educational field.' Final result in this model is 'the new practice of learning shared in the trading zone.' In selective coating, it was found that the practice of the teacher's research group appears as four types of' 'Extracurricular creative experience type,' 'career education type,' 'curricula education type,' and 'school management type.' The results of this study suggest that the shared learning and antonymous practice among teachers in the teachers' research group as trading zone do not only meet their learning needs but also lead to various teaching practices in the individual teachers' context of education and improve the diversity and quality of education.

• The Research Journal of the Costume Culture
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• v.27 no.6
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• pp.582-598
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• 2019

Intermedia is a term that refers to the convergence of different media. It has not only enabled the delivery of brand message but also developed interactive communication in a contemporary fashion show context. This study investigates the presentation methods of contemporary fashion shows affected by intermedia. We examined the research and theory related to intermedia and fashion shows by accessing articles since the 2000s concerning 252 shows by 30 designers that tended to demonstrate the use of intermedia. Our analysis highlighted four particular characteristics: "medium scalability" (the unity of art and fashion and the unity of life and fashion); "synesthetic flow" (the audience's emotional immersion, represented by the actual performance and performances of the models); "participatory accessibility" (performance participation through action and instrumental support); and "immaterial symbolization" (an intuitive symbol that emphasizes both the direct outward appearance and the metaphorical symbolism so that the object is expressed in a figurative sense). From these results, we identified considerable synergy between the characteristics of intermedia and contemporary fashion shows. Therefore, it might be useful to conduct an experimental study on this area of research.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.920-927
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• 2009

Many schedule delays and cost overruns in interior construction are caused by a lack of understanding in detailed and complicated interior works. To minimize these potential impacts in interior construction, a systematic approach for project managers to detect discrepancies at early stages and take corrective action through use of visualized data is required. This systematic implementation is still challenging: monitoring is time-consuming due to the significant amount of as-built data that needs to be collected and evaluated; and current interior construction progress reports have visual limitations in providing spatial context and in representing the complexities of interior components. To overcome these issues, this research focuses on visualization and computer vision techniques representing interior construction progress with photographs. The as-planned 3D models and as-built photographs are visualized in a 3D walk-through model. Within such an environment, the as-built interior construction elements are detected through computer vision techniques to automatically extract the progress data linked with Building Information Modeling (BIM). This allows a comparison between the as-planned model and as-built elements to be used for the representation of interior construction progress by superimposing over a 3D environment. This paper presents the process of representing and detecting interior construction components and the results for an ongoing construction project. This paper discusses implementation and future potential enhancement of these techniques in construction.