• 정보보호학회논문지
• /
• 제27권1호
• /
• pp.147-162
• /
• 2017

IT 환경의 변화 속에서 다양한 서비스와 기기의 출현으로 인하여, IT 규모의 증가와 더불어 데이터의 복잡도가 높아지면서 많은 조직에서 보안 상황 인지를 위한 대량의 데이터 분석 및 처리에 어려움을 겪고 있다. 이에, 조직의 위험관리에 있어서 보안 상황의 인지와 대응이 늦어지는 문제의 해결을 위해, 시각화를 통한 보안 상황 인지 효과의 향상을 제안한다. 이를 위해, 본 연구에서는 시각화와 관련한 다양한 관점에서의 선행 연구를 통해 사용자 유형, 상황 인지 단계, 정보 시각화의 속성 등을 고려하여 효과적 시각화를 위한 평가 요인과 대안을 선정하고 AHP 계층 모델을 수립하였다. 이를 토대로, 다 기준 의사결정 문제의 해결을 위한 AHP 기법을 활용하여 효과적 시각화를 위한 요인과 요인별 대안의 중요도를 산정함으로써, 시각화의 목적 및 사용자 유형에 따라 보안 상황의 인지 효과를 향상할 수 있는 시각화 방안을 제시하고자 한다.

• 동력기계공학회지
• /
• 제9권4호
• /
• pp.45-50
• /
• 2005

Characteristics of flows at T-junction duct with and without orifices are investigated in this paper. Experiments and PIV visualization were carried out for several flow rates. Two-dimensional PIV experimental apparatus was decided by numerical analysis. PIV visualization was also coded to visualize flow fields at junctions for two-dimensional case. For the PIV visualization system, Grey-Level Cross-Correlation particle tracking algorithm was used to calculate the flow fields. Vinyl chloride polymer particles of $100{\sim}150{\mu}m$ of diameter are used in this visualization. The PIV visualization results showed relatively good agreement with Experimental data.

• Journal of Information Technology Applications and Management
• /
• 제14권4호
• /
• pp.75-96
• /
• 2007

The effects of information quality and the importance of information have been reported in the Information Systems (IS) literature. However, little has been learned about the impact of information visualization types and contextual information on decision quality. Therefore, this study investigated the interaction effects of these variables on decision quality by conducting a laboratory experiment. Based on two types of information visualization and the availableness of contextual information, this study had a $2{\times}2$ factorial design. The dependent variables used to measure the outcomes of decision quality were decision accuracy and time. The results demonstrated that the effects of contextual information on decision quality were significant. In addition, there was a significant main effect of information visualization on decision accuracy. The findings suggest that decision makers can expect to improve their decision quality by enhancing information visualization types and contextual information. This research may extend a body of research examining the effects of factors that can be tied to human decision-making performance.

• 한국데이타베이스학회:학술대회논문집
• /
• 한국데이타베이스학회 2008년도 연합학회학술대회
• /
• pp.211-224
• /
• 2008

As a lot of information and media are given to users in Internet space nowadays, users feel disoriented or "lost in space" intensively. So it is suggested that we have the system to reduce information overload and to propose effective and efficient information. In this study we present a visualizing technique which uses fisheye views on data adjacency to combine global context and local details for presentation of many results in limited space. Data Adjacency on graph theory is applied to set up degree of interest which is main focus in fisheye views. Graph theory is useful to solve the problem resulted from various combinational optimization, especially it has advantages to analyze issues in information space like Internet. To test the usability of the proposed visualization technique, we compared the effectiveness of different visualization techniques. Results show that our method is evaluated with respect to less time and high satisfaction for a task accomplishment.

• 한국전산유체공학회:학술대회논문집
• /
• 한국전산유체공학회 2002년도 춘계 학술대회논문집
• /
• pp.158-163
• /
• 2002

In the present study a 3D data visualization and analysis program with stereoscopic viewing is introduced. The GUI of the program is based on Qt-library, while all the graphic rendering is performed with OpenGL library. The program allocates memory dynamically according to the data size so that the problem size is only limited by the computer's hardware memory. The stereoscopic viewing is realized by carefully-calibrated projection and color-masking of red and blue color for the left and right eye, and the only hardware needed for the stereoscopic visualization of 3D data is a cheap and easily-available red/blue glasses. Further work for addition of more functions and options to the present program will be continued.

• 지능정보연구
• /
• 제8권2호
• /
• pp.159-175
• /
• 2002

웹 마이닝은 e-Business 환경하에서 존재하는 대량의 웹 데이터에 데이터 마이닝 기법을 적용하여 유용하고 이해 가능한 정보를 추출해내는 과정을 의미하는데, 성공적인 e-Business전개를 위한 핵심적인 기술이다. 본 논문은 인공지능 기법에 기반한 웹마이닝 기술을 활용하여 e-Business상의 온라인 고객의 특성을 분석할 수 있는 data visualization system과 구매 판매 예측시스템의 효과적인 구조와 핵심적인 분석절차를 제안하였다.

• 한국멀티미디어학회논문지
• /
• 제18권1호
• /
• pp.65-70
• /
• 2015

Particle accelerator has mainly used in nuclear field only because of the large scale of the facility. However, since laser-plasma particle accelerator which has smaller size and spends less cost developed, the availability of this accelerator is expended to various research fields such as industrial and medical. This paper suggests a visualization system to control the laser-plasma particle accelerator efficiently. This system offers real-time 3D images via convert HDF file comes from plasma data obtained from PIC simulation into OpenGL texture type to analyse and modify plasma data. After that, it stores high-resolution rendering images of the data with external renderer hereafter.

• 국제학술발표논문집
• /
• The 1th International Conference on Construction Engineering and Project Management
• /
• pp.1036-1041
• /
• 2005

Treemaps, a space filling visualization technique, displays a massive data set of hierarchical data interactively on a single computer screen by mapping it to a matrix of rectangles. It allows users to visually inspect and manipulate data to find new relationships or discrepancies that are to difficult to find using traditional techniques. This paper applies treemaps to the evaluation of highway project bids, which contain hundreds or thousands of elements arranged in a hierarchical structure. Through a case study, treemaps are shown to be a potentially effective tool for bid evaluation by both contractors and State or Federal highway officials.

• 한국건축시공학회:학술대회논문집
• /
• 한국건축시공학회 2022년도 봄 학술논문 발표대회
• /
• pp.73-74
• /
• 2022

Concrete structures occupy the largest proportion of modern infrastructure, and concrete structures often have cracking problems. Existing concrete crack diagnosis methods have limitations in crack evaluation because they rely on expert visual inspection. Therefore, in this study, we design a deep learning model that detects, visualizes, and outputs cracks on the surface of RC structures based on image data by using a CNN (Convolution Neural Networks) model that can process two- and three-dimensional data such as video and image data. do. An experimental study was conducted on an algorithm to automatically detect concrete cracks and visualize them using a CNN model. For the three deep learning models used for algorithm learning in this study, the concrete crack prediction accuracy satisfies 90%, and in particular, the 'InceptionV3'-based CNN model showed the highest accuracy. In the case of the crack detection visualization model, it showed high crack detection prediction accuracy of more than 95% on average for data with crack width of 0.2 mm or more.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권6호
• /
• pp.2801-2816
• /
• 2016

Owing to their low scalability, weak support on big data, insufficient data collaborative analysis and inadequate situational awareness, the traditional methods fail to meet the needs of the security data analysis. This paper proposes visualization methods to fuse the multi-source security data and grasp the network situation. Firstly, data sources are classified at their collection positions, with the objects of security data taken from three different layers. Secondly, the Heatmap is adopted to show host status; the Treemap is used to visualize Netflow logs; and the radial Node-link diagram is employed to express IPS logs. Finally, the Labeled Treemap is invented to make a fusion at data-level and the Time-series features are extracted to fuse data at feature-level. The comparative analyses with the prize-winning works prove this method enjoying substantial advantages for network analysts to facilitate data feature fusion, better understand network security situation with a unified, convenient and accurate mode.