• Spatial Information Research
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• v.21 no.5
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• pp.43-51
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• 2013

In this study, the concept of spatial big data and effective ways to build a spatial big data system are presented. Big Data is defined as 3V(volume, variety, velocity). Spatial big data is the basis for evolution from 3V's big data to 6V's big data(volume, variety, velocity, value, veracity, visualization). In order to build an effective spatial big data, spatial big data system building should be promoted. In addition, spatial big data system should be performed a national spatial information base, convergence platform, service providers, and providers as a factor of production. The spatial big data system is made up of infrastructure(hardware), technology (software), spatial big data(data), human resources, law etc. The goals for the spatial big data system build are spatial-based policy support, spatial big data platform based industries enable, spatial big data fusion-based composition, spatial active in social issues. Strategies for achieving the objectives are build the government-wide cooperation, new industry creation and activation, and spatial big data platform built, technologies competitiveness of spatial big data.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.255-262
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• 2002

The Virtual Reality (VR) is an appealing subject which can be applied to various areas because of its merit - removal of time limits and space. Recently, as the technology of xDSL spreads widely, a concern of VR is on the on-line service of 3D model data in real time. But, the immensity of 3D model is an obstacle to achieve these endeavors. To solve these problems, the image based VR technique is applied. The proposed method in this paper is one of solutions on the immensity problem of 3D model data in the on-line services. This paper exploits the mixed technique of image based VR and surface rendering based on volume rendering. By using the proposed method, we can solve the immensity problem. Consequently, tole service user can explore virtual 2D volume model with almost equal to reality of 3D volume model. Furthermore, this paper explains a method to implement this service on general web environments. Of course, to fulfill these procedures, additional skills which reduce consuming time in data mining are also mentioned. The contribution of this paper is to provide a practical method for handling of large volume data web service in real-time. illustrative examples are presented to show the effectiveness of the proposed method.

• Journal of the Korea Computer Graphics Society
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• v.24 no.1
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• pp.9-16
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• 2018

In this paper, we introduce a visualization framework for cell image data obtained from optical diffraction tomography (ODT), including a method for representing cell morphology in 3D virtual environment and a color mapping protocol. Unlike commonly known volume data sets, such as CT images of human organ or industrial machinery, that have solid structural information, the cell image data have rather vague information with much morphological variations on the boundaries. Therefore, it is difficult to come up with consistent representation of cell structure for visualization results. To obtain desired visual representation of cellular structures, we propose an interactive visualization technique for the ODT data. In visualization of 3D shape of the cell, we adopt a volume rendering technique which is generally applied to volume data visualization and improve the quality of volume rendering result by using empty space jittering method. Furthermore, we provide a layer-based independent rendering method for multiple transfer functions to represent two or more cellular structures in unified render window. In the experiment, we examined effectiveness of proposed method by visualizing various type of the cell obtained from the microscope which can capture ODT image and fluorescence image together.

• Korea Trade Review
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• v.42 no.2
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• pp.277-296
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• 2017

More than 95% of imports and exports in the World are being transported by vessels. In other words, marine transportation accounts for a large portion of share in the world trade. The purpose of this study is to analyze factors of seaborne trade volume according to items affecting on the world economy. This study conducted a linear regression analysis between seaborne trade volume and the world economy (world GDP) to estimate the correlation between them. Panel data analysis and random effects model analysis have been applied to examine the effect of seaborne trade volume. For this study, the seaborne trade volume is categorized into 10 items, and estimated how much global GDP will be affected when the trade volume changes. In addition, the granger causality test was conducted to verify the relationship between seaborne trade volume and the world GDP. As a result, seaborne trade volume and the world GDP were mutually influenced each other. However, seaborne trade volume affects the world economy more significantly. The items affecting world economic growth include petroleum products, crude oil, chemical products, and so on. The estimated value of the coefficients of petroleum products, crude oil and chemical products were 1.014, 1.013 and 1.010, respectively. The estimated value 1.014 of petroleum products means that the growth rate is 1.014 times higher than the current world GDP growth rate when the seaborne trade volume of petroleum products increased by one unit Lastly, this study examines the seaborne trade volume of 10 categories and then verifies whether the growth rate of world GDP will increase when the volume of seaborne trade increased. This study is expected to provide policy-makers with useful information about formulating policies related to international trade.

• Journal of Information Processing Systems
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• v.2 no.2
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• pp.124-129
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• 2006

With the explosive increase in the generation and utilization of spatiotemporal data sets, many research efforts have been focused on the efficient handling of the large volume of spatiotemporal sets. With the remarkable growth of ubiquitous computing technology, mining from the huge volume of spatiotemporal data sets is regarded as a core technology which can provide real world applications with intelligence. In this paper, we propose a 3-tier knowledge discovery framework for spatiotemporal data mining. This framework provides a foundation model not only to define the problem of spatiotemporal knowledge discovery but also to represent new knowledge and its relationships. Using the proposed knowledge discovery framework, we can easily formalize spatiotemporal data mining problems. The representation model is very useful in modeling the basic elements and the relationships between the objects in spatiotemporal data sets, information and knowledge.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.6
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• pp.183-193
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• 2003

Most construction works on the soft ground adopt instrumentation to manage settlement and stability of the embankment. The rapid progress of the information technologies and the digital data acquisition on the soft ground instrumentation has led to the fast-growing amount of data. Although valuable information about the behaviour of the soft ground may be hiding behind the data, most of the data are used restrictedly only for the management of settlement and stability. One of the critical issues on soft ground instrumentation is the long-term settlement prediction. Some observational settlement analysis methods are used for this purpose. But the reliability of the analysis results is remained in vague. The knowledge could be discovered from a large volume of experiences on the observational settlement analysis. In this article, we present a database to store settlement records and data mining procedure. A large volume of knowledge about observational settlement prediction were collected from the database by applying the filtering algorithm and knowledge discovery algorithm. Statistical analysis revealed that the reliability of observational settlement analysis depends on stay duration and estimated degree of consolidation.

• Journal of Biomedical Engineering Research
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• v.27 no.1
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• pp.6-13
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• 2006

Ultrasound visualization is a typical diagnosis method to examine organs, soft tissues and fetus data. It is difficult to visualize ultrasound data because the quality of the data might be degraded by artifact and speckle noise, and gathered with non-linear sampling. Rendering speed is too slow since we can not use additional data structures or procedures in rendering stage. In this paper, we use several visualization methods for fast rendering of ultrasound data. First method, denoted as adaptive ray sampling, is to reduce the number of samples by adjusting sampling interval in empty space. Secondly, we use early ray termination scheme with sufficiently wide sampling interval and low threshold value of opacity during color compositing. Lastly, we use bilinear interpolation instead of trilinear interpolation for sampling in transparent region. We conclude that our method reduces the rendering time without loss of image quality in comparison to the conventional methods.

• Radiation Oncology Journal
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• v.27 no.4
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• pp.240-248
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• 2009

Purpose: To provide a simple research tool that may be used to analyze a dose volume histogram from different radiation therapy planning systems for NTCP (Normal Tissue Complication Probability), OED (Organ Equivalent Dose) and so on. Materials and Metohds: A high-level computing language was chosen to implement Niemierko's EUD, Lyman-Kutcher-Burman model's NTCP, and OED. The requirements for treatment planning analysis were defined and the procedure, using a developed GUI based program, was described with figures. The calculated data, including volume at a dose, dose at a volume, EUD, and NTCP were evaluated by a commercial radiation therapy planning system, Pinnacle (Philips, Madison, WI, USA) for comparison. Results: The volume at a special dose and a dose absorbed in a volume on a dose volume histogram were successfully extracted using DVH data of several radiation planning systems. EUD, NTCP and OED were successfully calculated using DVH data and some required parameters in the literature. Conclusion: A simple DVH analyzer program was developed and has proven to be a useful research tool for radiation therapy.

• Review of Culture and Economy
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• v.20 no.2
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• pp.119-147
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• 2017

This study analyzes Big Data to understand the economic influence of K-Beauty which is expected as a fast-growing industry. Because the content of K-beauty is mainly transmitted over the Internet, Big Data about K-Beauty in the database of online services can show interest and engagement in K-Beauty. The export volume of the beauty industry and the number of foreign tourist in Korea were used as dependent variables. The volume of Google search and the volume of YouTube page view were independent variables. According to the result of a multi-regression analysis, the volume of Google search of K-Beauty had a positive influence on both dependent variables, even after controlling for GDP (Gross Domestic Product) and distances between nations. When it comes to the volume of YouTube page view of K-Beauty, it had a positive relationship with the export volume of the beauty industry, whereas there was no significant relationship between the volume of YouTube page view and the number of foreign tourists. The result indicates that the content of K-Beauty has a significant impact on the beauty industry. Moreover, this empirical study shows that web search and YouTube search have a positive relationship with the economical aspect. These results can be used to discuss public relations strategy to promote K-Beauty industry.

• Journal of Korea Game Society
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• v.9 no.4
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• pp.89-96
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• 2009

In general, the size of volume data is large since it has logical 3D structure so it takes long time to manipulate. Much work has been done to improve processing speed of volume data. In this paper, we propose a interlaced scanning volume rendering that reduce computation time by using temporal coherence with minimum loss of image quality. It renders a current frame by reusing information of previous frame. Conventional volume raycasting renders each frame by casting rays on every pixels. On the other hand, our methods divided an image into n-pixel blocks, then it casts a ray on a pixel of a block per each frames. Consequently, it generates an image by accumulating pixel values of previous n frames. The quality of rendered image of our method is better than that of simple screen space subsampling method since it uses afterimage effect of human cognitive system, and it is n-times faster that the previous one.