• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.89-92
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• 2005

Each 3D visualization program has its own different structure as for the purpose. This paper describes the design and development of an on-line 3D core data visualization program, $RocDis^{TM}$, for the nuclear simulator. It is possible to analyze the inside of the core status including neutron flux, relative power, moderator and fuel temperature in 3D distribution. Some of other essential information, axial flux distribution etc. could also display in 2D graphs. This program would be design, tuning and training for the simulator core model.

• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.32-39
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• 2019

A convolutional neural network (CNN) has been widely used in facial expression recognition (FER) because it can automatically learn discriminative appearance features from an expression image. To make full use of its discriminating capability, this paper suggests a simple but effective method for CNN based FER. Specifically, instead of an original expression image that contains facial appearance only, the expression image with facial geometry visualization is used as input to CNN. In this way, geometric and appearance features could be simultaneously learned, making CNN more discriminative for FER. A simple CNN extension is also presented in this paper, aiming to utilize geometric expression change derived from an expression image sequence. Experimental results on two public datasets (CK+ and MMI) show that CNN using facial geometry visualization clearly outperforms the conventional CNN using facial appearance only.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.37-38
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• 2015

A number of documents containing important and useful knowledge have been generated over time in the construction industry. Such text-based knowledge plays an important role in the construction industry for decision-making and business strategy development by being used as best practice for upcoming projects, delivering lessons learned for better risk management and project control. Thus, practical and usable knowledge creation from construction documents is necessary to improve business efficiency. This study proposes a knowledge creating system from construction documents using text mining and the design comprises three main steps - text mining preprocessing, weight calculation of each term, and visualization. A system prototype was developed as a pilot study of the system design. This study is significant because it validates a knowledge creating system design based on text mining and visualization functionality through the developed system prototype. Automated visualization was found to significantly reduce unnecessary time consumption and energy for processing existing data and reading a range of documents to get to their core, and helped the system to provide an insight into the construction industry.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.21-31
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• 2018

We introduces a system that enables fast and effective visualization of natural disaster data such as typhoons, tsunamis, floods, and flooding to help make informed decisions in disaster situations. Data containing disaster information consists of a few hundred megabytes to many tens and hundreds of gigabytes, which can not be handled by a PC. This system was implemented in the form of a client-server based service to generate and output results from high-performance servers. The server in a built-in, high-performance cluster handles client requests and sends the result of visualization to the client. Clients can receive the results in any form of images, videos, or 3D graphic model by specifying a desired time frame, effectively viewing the results with a user-friendly GUI.

• Journal of Welding and Joining
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• v.34 no.1
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• pp.54-58
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• 2016

In this research paper, suggest method of generate same bead as an actual measurement data in virtual welding conditions, exploit morphology information of the bead that acquired through robot welding. It has many multiple risk factors to Beginners welding training, by we make possible to train welding in virtual reality, we can reduce welding training risk and welding material to exploit bead visualization algorithm that we suggest so it will be expected to achieve educational, environmental and economical effect. The proposed method is acquire data to each case performing robot welding by set the voltage, current, working angle, process angle, speed and arc length of welding condition value. As Welding condition value is most important thing in decide bead form, we would selected one of baseline each item and then acquired metal followed another factors change. Welding type is FCAW, SMAW and TIG. When welding trainee perform the training, it's difficult to save all of changed information into database likewise working angle, process angle, speed and arc length. So not saving data into database are applying the method to infer the form of bead using a neural network algorithm. The way of bead's visualization is applying the spline algorithm. To accurately represent Morphological information of the bead, requires much of morphological information, so it can occur problem to save into database that is why we using the spline algorithm. By applying the spline algorithm, it can make simplified data and generate accurate bead shape. Through the research paper, the shape of bead generated by the virtual reality was able to improve the accuracy when compared using the form of bead generated by the robot welding to using the morphological information of the bead generated through the robot welding. By express the accurate shape of bead and so can reduce the difference of the actual welding training and virtual welding, it was confirmed that it can be performed safety and high effective virtual welding education.

• Journal of the Korea Computer Graphics Society
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• v.7 no.2
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• pp.21-28
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• 2001

As a result of the recent explosive growth of scientific data, extremely large volume datasets have become increasingly commonplace. While several texture-based volume rendering algorithms have been proposed, most of them focused on volumes smaller than the hardware's available texture memory. This paper presents a new parallel volume rendering scheme for very large static and time-varying data on a multipipe system architecture. Our scheme subdivides large volumes dynamically into smaller bricks, and assigns them adaptively to graphics pipes to minimize the costs of texture swapping. With the new method, Phong shaded images can be easily created by computing the gradients on the fly and using the color matrix feature of OpenGL. We report experimental results on an SGI Onyx2 for the various large datasets.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.95-103
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• 2009

Global interests for construction of 3 dimensional spatial information has risen due to development of measurement sensors and data processing technologies. In spite of criticism for the violation of personal privacy, CCTV cameras equipped in outdoor public space of urban area are used as a fundamental sensor for traffic management, crime prevention or hazard monitoring. For safety guarantee in urban environment and disaster prevention, a surveillance system integrating pre-constructed 3 dimensional spatial information with CCTV data or video sequence is needed for monitoring and observing emergent situation interactively in real time. In this study, we proposed applicability of the prototype system for web visualization based on X3D, an international standard of real time web visualization, by integrating 3 dimensional spatial information with video sequence.

• Electronics and Telecommunications Trends
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• v.28 no.1
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• pp.42-51
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• 2013

The R language is an open source programming language and a software environment for statistical computing and data visualization. The R language is widely used among a lot of statisticians and data scientists to develop statistical software and data analysis. The R language provides a variety of statistical and graphical techniques, including basic descriptive statistics, linear or nonlinear modeling, conventional or advanced statistical tests, time series analysis, clustering, simulation, and others. In this paper, we first introduce the R language and investigate its features as a data analytics tool. As results, we may explore the application possibility of the R language in the field of data analytics.

• Genomics & Informatics
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• v.18 no.4
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• pp.46.1-46.4
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• 2020

We developed the BaSDAS (Barcode-Seq Data Analysis System), a GUI-based pooled knockout screening data analysis system, to facilitate the analysis of pooled knockout screen data easily and effectively by researchers with limited bioinformatics skills. The BaSDAS supports the analysis of various pooled screening libraries, including yeast, human, and mouse libraries, and provides many useful statistical and visualization functions with a user-friendly web interface for convenience. We expect that BaSDAS will be a useful tool for the analysis of genome-wide screening data and will support the development of novel drugs based on functional genomics information.

• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.21-30
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• 2016

Risk management system should be able to support a decision making within a short time to analyze stream data in real time. Many analytical systems consist of CPU computation and disk based database. However, it is more problematic when existing system analyzes stream data in real time. Stream data has various production periods from 1ms to 1 hour, 1day. One sensor generates small data but tens of thousands sensors generate huge amount of data. If hundreds of thousands sensors generate 1GB data per second, CPU based system cannot analyze the data in real time. For this reason, it requires fast processing speed and scalability for analyze stream data. In this paper, we present a fast visualization technique that consists of hybrid database and GPU computation. In order to evaluate our technique, we demonstrate a visual analytics system that analyzes pipeline leak using sensor and tweet data.