• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.71-74
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• 2009

The data-flow paradigm has been employed in various application areas. It is particularly useful where large data-streams must be processed, for example in video and audio processing, or for scientific visualization. A video-based 3D reconstruction system should process multiple synchronized video streams. The system exhibits many properties that can be targeted using a data-flow approach that is naturally divided into a sequence of processing tasks. In this paper we introduce our concept to apply the data-flow approach to a multi-video 3D reconstruction system.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.85-93
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• 2007

This paper describes a compression scheme for volumetric video data(3D space X 1D time) there each frame of the volume is decompressed and rendered in real-time. Since even one frame size of volume is very large, runtime decompression can be a bottleneck for real-time playback of time-varying volume data. To increase the run-time decompression speed and compression ratio, we decompose the volume into small blocks and only update significantly changing blocks. The results show that our compression scheme compromises decompression speed and image quality well enough for interactive time-varying visualization.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.555-566
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• 2017

For multivariate datasets with large number of variables, classical dimensional reduction methods such as principal component analysis may not be effective for data visualization. The underlying reason is that the dimensionality of the space of variables is often larger than two or three, while the visualization to the human eye is most effective with two or three dimensions. This paper proposes a working procedure which first partitions the variables into several "latent" clusters, explores individual data subsets, and finally integrates findings. We use R pakacage "ClustOfVar" for partitioning variables around latent dimensions and the principal component biplot method to visualize within-cluster patterns. Additionally, we use the technique for embedding supplementary variables to figure out the relationships between within-cluster variables and outside variables.

• Genomics & Informatics
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• v.6 no.3
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• pp.126-129
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• 2008

The robust identification and comprehensive profiling of copy number alterations (CNAs) is highly challenging. The amount of data obtained from high-throughput technologies such as array-based comparative genomic hybridization is often too large and it is required to develop a comprehensive and versatile tool for the detection and visualization of CNAs in a genome-wide scale. With this respective, we introduce a software framework, CGHscape that was originally developed to explore the CNAs for the study of copy number variation (CNV) or tumor biology. As a standalone program, CGHscape can be easily installed and run in Microsoft Windows platform. With a user-friendly interface, CGHscape provides a method for data smoothing to cope with the intrinsic noise of array data and CNA detection based on SW-ARRAY algorithm. The analysis results can be demonstrated as log2 plots for individual chromosomes or genomic distribution of identified CNAs. With extended applicability, CGHscape can be used for the initial screening and visualization of CNAs facilitating the cataloguing and characterizing chromosomal alterations of a cohort of samples.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.553-560
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• 2008

The amount of image data used in medical institution is increasing rapidly with great development of medical technology. Therefore, an automation method that use image processing description, rather than manual macrography of doctors, is required for the analysis large medical data. Specially, medical image registration, which is the process of finding the spatial transform that maps points from one image to the corresponding points in another image, and 3D analysis and visualization skills for a series of 2D images are essential technologies. However, a high establishment cost raise a budget problem, and hence small scaled hospitals hesitate importing these medical visualizing system. In this paper, we propose a visualization system which allows user to manage datasets and manipulates medical images registration using an open source graphics tool - VTK(Visualization Tool Kit). The propose of our research is to get more accurate 3D diagnosis system in less expensive price, compared to existing systems.

• Journal of the Korean Society of Visualization
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• v.8 no.2
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• pp.40-44
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• 2010

Thermal comfort inside a passenger car has been receiving large attention in automobile industries. Especially, the performance of windshield defroster is important in the design of a car to ensure passenger comport and safety. Thereby, better understanding on the ventilation flow along the vehicle windshield is essential to evaluate the performance of windshield defroster. However, most previous studies dealt with the defrost flow using CFD (computational fluid dynamics) calculations or scale-down model experiments. In this study, a real commercial automobile was used to investigate the flow discharged from the vehicle defroster and the ventilation flow along the windshield using a PIV velocity field measurement technique. The experimental data would be useful to understand the flow characteristics in detail and also can be used to validate numerical predictions.

• International Journal of CAD/CAM
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• v.3 no.1_2
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• pp.111-117
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• 2003

The paper presents an efficient algorithm based on ROAM for visualization of large scale terrain models in real-time. The quality and smoothness of the terrain data visualization within a 3D interactive environment is preserved, while the complexity of the algorithm is kept on a reasonable level. The main contribution of the paper is an introduction of a number of efficient techniques such as implicit coordinates method within the patch array representing ROAM and the viewpoint dependent triangle rendering method for dynamic level of detail (LOD) updates. In addition, the paper presents experimental comparison of a variety of culling techniques, including a newly introduced method: relational position culling. These techniques are incorporated in the visualization software, which allows to achieve more realistic terrain representation and the real-time level of detail reduction.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.352-362
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• 2017

This paper proposes an algorithm for automatically converting and displaying rainfall radar data on a 3D GIS platform. The weather information displayed like rainfall radar data is updated frequently and large-scale. Thus, in order to efficiently display the data, an algorithm to convert and output the data automatically, rather than manually, is required. In addition, since rainfall data is extracted from the space, the use of the display image fused with the 3D GIS data representing the space enhances the visibility of the user. To meet these requirements, this study developed the Auto Data Converter application that analyzes the raw data of the rainfall radar and convert them into a universal format. In addition, Unity 3D, which has good development accessibility, was used for dynamic 3D implementation of the converted rainfall radar data. The software applications developed in this study could automatically convert a large volume of rainfall data into a universal format in a short time and perform 3D modeling effectively according to the data conversion on the 3D platform. Furthermore, the rainfall radar data could be merged with other GIS data for effective visualization.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.106.3-106
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• 2001

Financial institutions survive on the ability to collect and react to data. Today´s financial community is bombarded by massive amounts of information from real time data-feeds, risk management systems, and other intelligent sources. The large quantities of numerical data are virtually impossible to understand quickly. Humans have the ability to understand pictures instantaneously. Thus, by converting data into pictures, and using colour, size, shape, and pattern to define relationships, individuals can rapidly process complex Information.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.351-359
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• 2014

The log data generated by security equipment have been synthetically analyzed on the ESM(Enterprise Security Management) base so far, but due to its limitations of the capacity and processing performance, it is not suited for big data processing. Therefore the another way of technology on the big data platform is necessary. Big Data platform can achieve a large amount of data collection, storage, processing, retrieval, analysis, and visualization by using Hadoop Ecosystem. Currently ESM technology has developed in the way of SIEM (Security Information & Event Management) technology, and to implement security technology in SIEM way, Big Data platform technology is essential that can handle large log data which occurs in the current security devices. In this paper, we have a big data platform Hadoop Ecosystem technology for analyzing the security log for sure how to implement the system model is studied.