• Title/Summary/Keyword: heatmap visualization

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QCanvas: An Advanced Tool for Data Clustering and Visualization of Genomics Data

  • Kim, Nayoung;Park, Herin;He, Ningning;Lee, Hyeon Young;Yoon, Sukjoon
    • Genomics & Informatics
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    • v.10 no.4
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    • pp.263-265
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    • 2012
  • We developed a user-friendly, interactive program to simultaneously cluster and visualize omics data, such as DNA and protein array profiles. This program provides diverse algorithms for the hierarchical clustering of two-dimensional data. The clustering results can be interactively visualized and optimized on a heatmap. The present tool does not require any prior knowledge of scripting languages to carry out the data clustering and visualization. Furthermore, the heatmaps allow the selective display of data points satisfying user-defined criteria. For example, a clustered heatmap of experimental values can be differentially visualized based on statistical values, such as p-values. Including diverse menu-based display options, QCanvas provides a convenient graphical user interface for pattern analysis and visualization with high-quality graphics.

A Visualization System for Multiple Heterogeneous Network Security Data and Fusion Analysis

  • Zhang, Sheng;Shi, Ronghua;Zhao, Jue
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.6
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    • pp.2801-2816
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    • 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.

Evaluation of temperature effects on brake wear particles using clustered heatmaps

  • Shin, Jihoon;Yim, Inhyeok;Kwon, Soon-Bark;Park, Sechan;Kim, Min-soo;Cha, YoonKyung
    • Environmental Engineering Research
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    • v.24 no.4
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    • pp.680-689
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    • 2019
  • Temperature effects on the generation of brake wear particles from railway vehicles were generated, with a particular focus on the generation of ultrafine particles. A real scale brake dynamometer test was repeated five times under low and high initial temperatures of brake discs, respectively, to obtain generalized results. Size distributions and temporal patterns of wear particles were analyzed through visualization using clustered heatmaps. Our results indicate that high initial temperature conditions promote the generation of ultrafine particles. While particle concentration peaked within the range of fine sized particles under both low and high initial temperature, an additional peak occurred within the range of ultrafine sized particles only under high initial temperature. The timing of peak occurrence also differed between low and high initial temperature conditions. Under low initial temperature fine sized particles were generated intensively at the latter end of braking, whereas under high initial temperature both fine and ultrafine particles were generated more dispersedly along the braking period. The clustered correlation heatmap divided particle sizes into two groups, within which generation timing and concentration of particles were similar. The cut-off point between the two groups was approximately 100 nm, confirming that the governing mechanisms for the generation of fine particles and ultrafine particles are different.

Visualization of movie recommendation system using the sentimental vocabulary distribution map

  • Ha, Hyoji;Han, Hyunwoo;Mun, Seongmin;Bae, Sungyun;Lee, Jihye;Lee, Kyungwon
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.5
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    • pp.19-29
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    • 2016
  • This paper suggests a method to refine a massive collective intelligence data, and visualize with multilevel sentiment network, in order to understand information in an intuitive and semantic way. For this study, we first calculated a frequency of sentiment words from each movie review. Second, we designed a Heatmap visualization to effectively discover the main emotions on each online movie review. Third, we formed a Sentiment-Movie Network combining the MDS Map and Social Network in order to fix the movie network topology, while creating a network graph to enable the clustering of similar nodes. Finally, we evaluated our progress to verify if it is actually helpful to improve user cognition for multilevel analysis experience compared to the existing network system, thus concluded that our method provides improved user experience in terms of cognition, being appropriate as an alternative method for semantic understanding.

Visualization Model for Security Threat Data in Smart Factory based on Heatmap (히트맵 기반 스마트팩토리 보안위협 데이터 시각화 모델)

  • Jung, In-Su;Kim, Eui-Jin;Kwak, Jin
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.284-287
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    • 2021
  • 4차 산업혁명으로 인해 제조산업에 인공지능, 빅데이터와 같은 ICT 기술을 활용한 스마트팩토리의 제조 공정 자동화 및 장치 고도화 연구가 진행되고 있다. 제조 공정 자동화를 위해 스마트팩토리의 각 계층별 장치들이 유기적으로 연결되고 있으며, 이로 인해 발생 가능한 보안위협도 증가하고 있다. 스마트팩토리에서는 SIEM 등의 장비가 보안위협 데이터를 수집·분석·시각화하여 대응하고 있다. 보안위협 데이터 시각화에는 그리드 뷰, 피벗 뷰, 그래프, 차트, 테이블을 활용한 대시보드 형태로 제공하고 있지만, 이는 스마트팩토리 전 계층의 보안위협 데이터 확인에 대한 가시성이 부족하다. 따라서, 본 논문에서는 스마트팩토리 보안위협 데이터를 CVSS 점수 기반의 Likelihood와 보안위협 데이터 기반의 Impact를 활용하여 위험도를 도출하고, 히트맵 기반 스마트팩토리 보안위협 데이터 시각화 모델을 제안한다.

Development and User Study on Visualization Tools of Origin-Destination Data for Social Problems (Origin-Destination 기반 시각화 도구의 개발 및 사회 문제 해결을 위한 사용자 연구)

  • Changki Kim;Sungjin Hwang;Hansung Kim;Sugie Lee;Jaehyuk Cha;Kwanguk (Kenny) Kim
    • Journal of the Korea Computer Graphics Society
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    • v.30 no.3
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    • pp.9-22
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    • 2024
  • Mobility data is important to understand social phenomena and problem. Previous studies have utilized Origin-Destination (OD) visualization methods to represent human's mobility. However, the effectiveness of visualization tools as a method for understanding social phenomena remains unexplored. Therefore, in this study, we developed a visualization tool called SeoulOD-Vis to facilitate understanding social issues. It included three different modules: map visualization, condition selection, and detailed information presentation. We recruited 28 participants to evaluate the SeoulOD-Vis and compared it with a publicly available visualization tool. The results suggested that the SeoulOD-Vis had higher usability and problem-solving performances. Interview results suggested that it attributed to its 'condition selection' and 'detailed information presentation' modules. Our results will contribute to develop visualization tools to solve social problems using mobility data.

Analysis of Visual Attention in Bank Brand Logo using Eye-Tracking (시선추적장치를 활용한 은행 브랜드 로고의 시각적 주의집중도 분석 연구)

  • Park, Min Hee;Hwang, Mi Kyung;Kim, Chee Yong;Kwon, Mahn Woo
    • Journal of Korea Multimedia Society
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    • v.23 no.9
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    • pp.1210-1218
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    • 2020
  • This study selected brand logos of six South Korean and Chinese banks including KB, IBK, SH, ICBC, ABC, and SISB, conducted Eye Tracking experiment among 36 South Korean and Chinese university students(Nine male and female students, respectively), and analyzed the difference of visual attention of consumers on bank brand logo, symbol, Korean/Chinese character logo types as well as the difference of visual attention of these consumers on English logo types. Results were represented by using statistics and visualization including GAZEPLOT, HEATMAP, and visual expression. Results showed that most generally gazed logo types more often and longer than symbols when they watched bank brand logos. A slight difference was observed between both groups in terms of gazing English logo types. This study has a implication that it proposed the possibility of drawing quantitative and reliable outcomes by utilizing eye tracking device and approaching in an objective standpoint beyond a methodological aspect on bank brand logo primarily leaning over the analysis of case research or design development. Moreover, findings are expected to serve as basic data for proposing the direction of special bank brand logo design and marketing strategies.

Imaging Magnetic Flux Leakage based Steel Plate Damage for Steel Structure Diagnosis (강구조물 진단을 위한 누설자속 기반 강판 손상의 이미지화)

  • Kim, Hansun;Kim, Ju-Won;Yu, Byoungjoon;Kim, Wonkyu;Park, Seunghee
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.23 no.7
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    • pp.129-136
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    • 2019
  • In this study, the magnetic flux leakage technique was applied to diagnose steel plate damage, imaging technique was applied through those signals. Steel plate specimens with different thicknesses were prepared for the imaging the magnetic flux leakage signal, and 6 different depths of damage were artificially processed at the same locations on each specimen. The sensor head consist hall sensor and magnetization yoke was fabricated to magnetize the steel plate specimen and measure the magnetic flux leakage signal. In order to remove the noise and increase the resolution of the image in the signal collected from the hall sensor, various of signal processing was performed. P-P value was analyzed for each channel to analyze the magnetic flux leakage signals measured from each damaged part. Based on the above processed signals and analysis, it was converted into heatmap image. Through this, it was possible to identify the damage on the steel plate at glance by imaging magnetic flux leakage signal.

UX evaluation of MyData-based financial asset management app - Focusing on Data Visualization (마이데이터 기반 금융 자산관리 앱 사용성 평가 - 데이터 시각화를 중심으로 -)

  • Kim, Eun Young;Han, Soo Jin
    • Journal of the Korea Convergence Society
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    • v.12 no.12
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    • pp.223-233
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    • 2021
  • MyData industry became possible with the revision of the three data-related bills on August 2020, and from February 2021, each individual can make MyData financial service through the app provided by MyData providers. In this study, in order to understand the user experience trend of MyData-based financial asset management apps in the user-centered financial service era, the usability evaluation of 11 apps from 8 MyData providers was conducted for 300 adults, then average value comparison, radial graph analysis, and heatmap analysis were conducted. In app design preference, asset list type was the most preferred type, followed by asset comparison·list type. As for the expected perception of the future benefits that can be enjoyed through My Data, 'diversification of convenient services' was the highest at 45.3%, and as a negative factor felt by users, personal information-related factors were the highest at 71.4%. The results of this study can be used as basic data for the development and improvement of user interfaces for MyData platforms.