• Spatial Information Research
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• v.19 no.5
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• pp.13-25
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• 2011

Until now, most of the Web GIS system has been developed with one-sided service type that provides pre-built spatial information to users. Recently, however, interactive web system is getting attention because users can create directly spatial information contents that meet their needs. In line with this trend, this study had a aim to develop a UGC(User Generated Contents) support system for marine science researchers who can generate spatial data by themselves on the web. The main advantage of this system is that it provides marine survey data and marine spatial information that needed to work for marine science research. Furthermore, it provides the functions of extracting of coastline as point data for their marine study area, and making of the spatial planning map for marine field survey work and marine science thematic maps for exploratory analysis after research survey. Such kinds of interactive UGC support system gives researchers a chance for utilizing marine spatial information more easily. Therefore, it is expected that the improving of the efficiency of research works, as well as increasing of the utilization of marine spatial data.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.186-187
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• 2021

Education in Korean universities is rapidly expanding to online education due to COVID-19. In response to such changes, this study proposed a means of improving the learning management system of Korean universities and analyzed the effects of using the system. The important results of this study are as follows: the learning management system was composed of 'pre-class learning,' 'team activity,' and 'participation learning' to support team-based learning. The effects that the users (instructors, learners) can obtain by adopting team-based learning and using the system were analyzed. The study concludes that for instructors, teaching work may be alleviated. For learners, it was demonstrated that they could more easily access and use data required for their education.

• Health Policy and Management
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• v.24 no.4
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• pp.312-321
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• 2014

Background: To evaluate the quality of chronic care provided by public health centers located in a South Korean metropolitan city using a modified Assessment of Chronic Illness Care (ACIC). Methods: We conducted self-evaluation surveys and collected data using a modified ACIC from twenty five public health centers. Cultural validity of the original ACIC was examined by the public health and nursing science experts. Based on expert reviews, cognitive interviews, pre-test results, five items of the original ACIC that were not relevant were deleted. The response scale was changed from twelve-point Likert scale to Guttman scale but its scoring system was maintained. Results: Eighty eight percent of public health centers in this study reported that their overall quality of chronic care was at a limited or basic level. About 68% of the centers reported that the organization was as reasonably good or fully developed to provide chronic care. On the other hand, 96% of the public health centers reported that the clinical information system was at a very limited or basic support level. The decision support, the integration of Chronic Care Model components, the delivery system design, the community linkages, and the self-management support were evaluated as limited or basic level of support by more than half of the public health centers, respectively. Conclusion: In a metropolitan area of South Korea, quality of chronic care in public health centers was not found to reach acceptable levels of services. It is critical to enhance the quality of chronic care in public health centers.

• Journal of KIISE
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• v.42 no.11
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• pp.1452-1458
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• 2015

Korean Morphological Analysis is a difficult process. Because Korean is an agglutinative language, one of the most important processes in Morphological Analysis is Morpheme Recovery. There are some methods using Heuristic rules and Pre-Analyzed Partial Words that were examined for this process. These methods have performance limits as a result of not using contextual information. In this study, we built a Korean morpheme recovery system using deep learning, and this system used word embedding for the utilization of contextual information. In '들/VV' and '듣/VV' morpheme recovery, the system showed 97.97% accuracy, a better performance than with SVM(Support Vector Machine) which showed 96.22% accuracy.

• The Journal of Information Systems
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• v.30 no.2
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• pp.105-126
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• 2021

Purpose The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation. Design/methodology/approach This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data. Findings This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1048-1052
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• 2004

The ubiquitous environment is to support people in their everyday life in an inconspicuous and unobtrusive way. This requires that information of the person and her preferences, liking, and habits are 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. The system architecture is composed of 4 domain models that can perform some pre-defined tasks independently. And we suggest the hybrid algorithm combined with fuzzy and Bayesian network to reason what information is suitable for user environment. Finally, we apply to agent based RGA(Research Guide Assistant).

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.37-40
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• 2000

A fast method of Hangul address word verification is presented in this Paper. Pre-segmentation and recognition by DP matching is adopted in this paper. An address line image is over-segmented by analyzing the topology of connected components and the projection profile. A fast individual Hangul character verifier was developed by applying SVM (Support Vector Machine). The segmentation hypothesis was represented by lattice structure, and a best path search by dynamic programming generates the most probable segmentation path and the final verification score. The word verifier was tested on 310 address image DB, and it show the possibility of improvements of this method.

• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.171-181
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• 2007

Ubiquitous computing is a vision of our future computing lifestyle in which computer systems seamlessly integrate into our everyday lives, providing services and information in anywhere and anytime fashion. Augmented reality (AR) can naturally complement ubiquitous computing by providing an intuitive and collaborative visualization and simulation interface to a three-dimensional information space embedded within physical reality. This paper presents a service framework and its applications for providing context-aware u-car maintenance services using augmented reality, which can support a rich set of ubiquitous services and collaboration. It realizes bi-augmentation between physical and virtual spaces using augmented reality. It also offers a context processing module to acquire, interpret and disseminate context information. In particular, the context processing module considers user's preferences and security profile for providing private and customer-oriented services. The prototype system has been implemented to support 3D animation, TTS (Text-to-Speech), augmented manual, annotation, and pre- and post-augmentation services in ubiquitous car service environments.

• Korean Journal of Computational Design and Engineering
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• v.11 no.1
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• pp.49-56
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• 2006

In this study, the modeling support system was developed which can make easy and fast FE-modeling and verify the results of static and durability analysis for the lower arm, one of the important parts in automobile suspension module. It took into account of the whole complicated design processes verifying the durability coefficients evaluated by fatigue analysis, which should be used to satisfy a design criteria. To guide the FE-modeling the drive page was constructed by using HTML and XML, which was based on expert's know-hows. It is able to integrate the processes to design the lower arm in practice, so that the standardization of its FE-Modeling is achieved, consequently. The 3 dimensional CAD's geometrical data were changed automatically into pre-defined shell elements under the concept of mesh-offset technique, and then welding elements were treated to connect between target and basic surfaces constructed by the shell elements. This system has also a user interface to control boundary and load ing conditions applied in performing of the static and durability analysis, in which many load cases can be applied simply with the MPCs driven by just few mouse clicks. These were implemented on the platform of MSC.Patran and utilized ANSYS, MSC.Nastran and MSC.Fatigue as the solver of the analysis performed. The developed system brings not only significant decreasing of man-hours required in FE-modeling process, but also obtaining of satisfied qualities in analyzed results. It will be integrated in a part of virtual prototyping module of the developing e-engineering framework.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.2
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• pp.122-129
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• 2014

In this study, emotion-classification gathered from users was performed, classification-experiments were then conducted using SVM(Support Vector Machine) and K-means algorithm. Total 15 numbers of channels; CP6, Cz, FC2, T7. PO4, AF3, CP1, CP2, C3, F3, FC6, C4, Oz, T8 and F8 among 32 members of the channels measured were adapted in Brain signals which indicated obvious the classification of emotions in previous researches. To extract emotion, watching DVD and IAPS(International Affective Picture System) which is a way to stimulate with photos were applied and SAM(Self-Assessment Manikin) was used in emotion-classification to users' emotional conditions. The collected users' Brain-wave signals gathered had been pre-processing using FIR filter and artifacts(eye-blink) were then deleted by ICA(independence component Analysis) using. The data pre-processing were conveyed into frequency analysis for feature extraction through FFT. At last, the experiment was conducted suing classification algorithm; Although, K-means extracted 70% of results, SVM showed better accuracy which extracted 71.85% of results. Then, the results of previous researches adapted SVM were comparatively analyzed.