• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.21-26
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• 2003

The visualization of three dimensional geophysical data is forcing a revolution in the way of working, and allowing the discovery and production of hydrocarbons at much lower costs than previously thought possible. There are many aspects of this revolution that are behind the scenes, such as the database structure, the storage and retrieval of data, and the exchange of data among programs. Also the user had changes where the interpreter (or manager, or processor) actually looks at and somehow interacts with the data. The use of opacity in volume rendering, and how its judicious application can assist in imaging geologic features in three dimensional seismic data. This revolutionary development of new technology is based on the philosophy of synergy of inter-disciplines of the oil industry. Group interaction fostered by large room visualization environments enables the integration of disciplines we strive for, by putting the petrophysicist, geologist, geophysicist, and reservoir engineer in one place, looking at one image together, without jargon or geography separating them. All these tools developed in the oil industry can be applied into the civil engineering industry also such as the prior geological and geophysical survey of the constructions. Many examples will show how three dimensional geophysical technology might make a revolution in the oil business industry now and in future. This change can be considered as a fusion process at data, information, and knowledge levels.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.311-318
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• 2009

Interactive terrain visualization is an important research area with applications in GIS, games, virtual reality, scientific visualization and flight simulators, besides having military use. This is a complex and challenging problem considering that some applications require precise visualizations of huge data sets at real-time rates. In general, the size of data sets makes rendering at real-time difficult since the terrain data cannot fit entirely in memory. In this paper, we suggest the effective Real-time LOD(level-of-detail) algorithm for displaying the huge terrain data and processing mass geometry. We used a hierarchy structure with $4{\times}4$ and $2{\times}2$ tiles for real-time rendering of mass volume DEM which acquired from Digital map, LiDAR, DTM and DSM. Moreover, texture mapping is performed to visualize realistically while displaying height data of normalized Giga Byte level with user oriented terrain information and creating hill shade map using height data to hierarchy tile structure of file type. Large volume of terrain data was transformed to LOD data for real time visualization. This paper show the new LOD algorithm for seamless visualization, high quality, minimize the data loss and maximize the frame speed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.1-8
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• 2017

The purpose of this study is to propose a cache structure for processing large-volume building information modeling (BIM) geometry data,whereit is difficult to allocate physical memory. As the number of BIM orders has increased in the public sector, it is becoming more common to visualize and calculate large-volume BIM geometry data. Design and review collaboration can require a lot of time to download large-volume BIM data through the network. If the BIM data exceeds the physical free-memory limit, visualization and geometry computation cannot be possible. In order to utilize large amounts of BIM data on insufficient physical memory or a low-bandwidth network, it is advantageous to cache only the data necessary for BIM geometry rendering and calculation time. Thisstudy proposes acache structure for efficiently rendering and calculating large-volume BIM geometry data where it is difficult to allocate enough physical memory.

• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.18-25
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• 2023

In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.77-81
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• 2015

The unit price contracting is the standard contracting method for highway projects in the U.S. As a result, state highway agencies have collected a large amount of historical bid data that they can use to determine engineer's estimates for future projects. The estimator must carefully consider various characteristics of a new project such as its location to determine an engineer's estimate as accurate as possible before bid letting. Higher cost estimates can result in the loss of the available budget and lower cost estimates may lead to deferral and delay of projects. The study uses the historical bid data obtained from Iowa Department of Transportation and develops a Geographic Information System (GIS) tool to visually show the variation of unit prices over the map using a spatial interpolation technique. The interpolation map can be used to estimate the unit price of the item at any location across Iowa. This noble method allows the estimator to effectively and fully utilize the historical bid data in a very time efficient manner and determine more accurate cost estimation.

• Journal of the HCI Society of Korea
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• v.1 no.2
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• pp.51-58
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• 2006

Information visualization, generally speaking, consists of three steps: transform from raw data to data model, visual mapping from data model to visual structure, and transform from visual structure to information model. In this paper, we propose a visual mapping method from spatiotemporal table information, which is related to events in large-scale building, to 3D map metaphor. The process has also three steps as follows. First, after analyzing the table attributes, we carefully define a context to fully represent the table-information. Second, we choose meaningful attribute sets from the context. Third, each meaningful attribute set is mapped to one well defined visual structure. Our method has several advantages. First, users can intuitively achieve non-spatial information through the 3D map which is a powerful spatial metaphor. Second, this system shows various visual mapping method applicable to other data models in the form of table, especially GIS. After describing the whole concept of our visual mapping, we will show the results of implementation for several requests.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1279-1290
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• 2017

R's {shiny} package provides an environment for creating web applications with only R scripts. Shiny does not require knowledge of a separate web programming language and its development is very easy and straightforward. In addition, Shiny has a variety of extensibility, and its functions are expanding day by day. Therefore, the presentation of high-quality results is an excellent tool for R-based analysts. In this paper, we present actual cases of large data analysis using Shiny. First, geological anomaly zone is extracted by analyzing topographical data expressed in the form of contour lines by analysis related to spatial data. Next, we will construct a model to predict major diseases by 16 cities and provinces nationwide using weather, environment, and social media information. In this process, we want to show that Shiny is very effective for data visualization and analysis.

• Geophysics and Geophysical Exploration
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• v.7 no.2
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• pp.105-108
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• 2004

Immersive virtual reality has been used in areas of oil and gas exploration for visualization and analysis of various spatial data, such as wireline logs, 3-dimensional seismic data volume, formational boundaries, fault, and some other reservoir characteristics. Although virtual reality is a valuable tool in this area, in most cases, it requires a large budget. This paper describes the construction of a single screen, passive stereo, virtual reality, display system based on commodity, or otherwise, low-cost components. The core elements of the system are a PC with a two-channel 3-D graphics, two projects, and a polarized stereo. There are many options available for the major elements of such a system, and the basic system can be modified or adapted to many different styles of use.

• Journal of the Korea Computer Graphics Society
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• v.24 no.2
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• pp.21-28
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• 2018

We present interactive methods for visualizing the cloud height data and the backscatter data collected from ceilometers in the three-dimensional virtual space. Because ceilometer data is high-dimensional, large-size data associated with both spatial and temporal information, it is highly improbable to exhibit the whole aspects of ceilometer data simply with static, two-dimensional images. Based on the three-dimensional rendering technology, our visualization methods allow the user to observe both the global variations and the local features of the three-dimensional representations of ceilometer data from various angles by interactively manipulating the timing and the view as desired. The cloud height data, coupled with the terrain data, is visualized as a realistic cloud animation in which many clouds are formed and dissipated over the terrain. The backscatter data is visualized as a three-dimensional terrain which effectively represents how the amount of backscatter changes according to the time and the altitude. Our system facilitates the multivariate analysis of ceilometer data by enabling the user to select the date to be examined, the level-of-detail of the terrain, and the additional data such as the planetary boundary layer height. We demonstrate the usefulness of our methods through various experiments with real ceilometer data collected from 93 sites scattered over the country.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.679-691
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• 2002

Volume visualization is an important subarea of scientific visualization, and is concerned with techniques that are effectively used in generating meaningful and visual information from abstract and complex volume datasets, defined in three- or higher-dimensional space. It has been increasingly important in various fields including meteorology, medical science, and computational fluid dynamics, and so on. On the other hand, virtual reality is a research field focusing on various techniques that aid gaining experiences in virtual worlds with visual, auditory and tactile senses. In this paper, we have developed a visualization system for CAVE, an immersive 3D virtual environment system, which generates stereoscopic images from huge human volume datasets in real-time using an improved volume visualization technique. In order to complement the 3D texture-mapping based volume rendering methods, that easily slow down as data sizes increase, our system utilizes an image-based rendering technique to guarantee real-time performance. The system has been designed to offer a variety of user interface functionality for effective visualization. In this article, we present detailed description on our real-time stereoscopic visualization system, and show how the Visible Korean Human dataset is effectively visualized on CAVE.