• Title/Summary/Keyword: dataset visualization

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Towards Texture-Based Visualization of Multivariate Dataset

  • Mehmood, Raja Majid;Lee, Hyo Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.582-585
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    • 2014
  • Visualization is a science which makes the invisible to visible through the techniques of experimental visualization and computer-aided visualization. This paper presents the practical aspects of visualization of multivariate dataset. In this paper, we will briefly discuss a previous research work and introduce a new visualization technique which will help us to design and develop a visualization tool for experimental visualization of multivariate dataset. Our newly developed visualization tool can be used in various domains. In this paper, we have chosen a software industry as an application domain and we used the multivariate dataset of software components computed by VizzMaintenance. VizzMaintenance is software analysis tool which give us multiple software metrics of open source Java based programs. Main objective of this research is to develop a new visualization tool for large multivariate dataset which will be more efficient and easy to perceive by viewer. Perception is very important for our research work and we have decided to test the perception level of our proposed visualization approach by researchers of our research lab.

Method for Importance based Streamline Generation on the Massive Fluid Dynamics Dataset (대용량 유동해석 데이터에서의 중요도 기반 스트림라인 생성 방법)

  • Lee, Joong-Youn;Kim, Min Ah;Lee, Sehoon
    • The Journal of the Korea Contents Association
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    • v.18 no.6
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    • pp.27-37
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    • 2018
  • Streamline generation is one of the most representative visualization methods to analyze the flow stream of fluid dynamics dataset. It is a challenging problem, however, to determine the seed locations for effective streamline visualization. Meanwhile, it needs much time to compute effective seed locations and streamlines on the massive flow dataset. In this paper, we propose not only an importance based method to determine seed locations for the effective streamline placements but also a parallel streamline visualization method on the distributed visualization system. Moreover, we introduce case studies on the real fluid dynamics dataset using GLOVE visualization system to evaluate the proposed method.

GLOVE: Distributed Shared Memory Based Parallel Visualization Tool for Massive Scientific Dataset (GLOVE: 대용량 과학 데이터를 위한 분산공유메모리 기반 병렬 가시화 도구)

  • Lee, Joong-Youn;Kim, Min Ah;Lee, Sehoon;Hur, Young Ju
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.6
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    • pp.273-282
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    • 2016
  • Visualization tool can be divided by three components - data I/O, visual transformation and interactive rendering. In this paper, we present requirements of three major components on visualization tools for massive scientific dataset and propose strategies to develop the tool which satisfies those requirements. In particular, we present how to utilize open source softwares to efficiently realize our goal. Furthermore, we also study the way to combine several open source softwares which are separately made to produce a single visualization software and optimize it for realtime visualization of massiv espatio-temporal scientific dataset. Finally, we propose a distributed shared memory based scientific visualization tool which is called "GLOVE". We present a performance comparison among GLOVE and well known open source visualization tools such as ParaView and VisIt.

Visualization of Medical Images Using Visualization Toolkit (VTK를 이용한 의료영상의 가시화)

  • Choi, H.G.;Tack, G.R.
    • Proceedings of the KOSOMBE Conference
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    • v.1998 no.11
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    • pp.113-114
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    • 1998
  • In this paper, visualization of Visible Human data offered by NLM(National Library of Medicine) is performed using $VTK^{TM}$. Computed Tomography Data set(axial, $587\times341\times256$, and the distance between slices 1mm) is used throughout the study. Before the actual visualization routine, 8 bit-reader class of VTK is developed to transform CT data to VTK dataset. After that, the visualization procedures are done to display 3D image on PC. VTK is freeware, not a commercial software. The results of VTK show relatively good image quality and slower processing time compared with the commercial softwares like IAP, IDL, AVS. Thus if processing time is not the critical factor, VTK is worthy to be used in visualization of the medical images.

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Translation of 3D CAD Data to X3D Dataset Maintaining the Product Structure (3차원 CAD 데이터의 제품구조를 포함하는 X3D 기반 데이터로의 변환 기법)

  • Cho, Gui-Mok;Hwang, Jin-Sang;Kim, Young-Kuk
    • The KIPS Transactions:PartA
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    • v.18A no.3
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    • pp.81-92
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    • 2011
  • There has been a number of attempts to apply 3D CAD data created in the design stage of product life cycle to various applications of the other stages in related industries. But, 3D CAD data requires a large amount of computing resources for data processing, and it is not suitable for post applications such as distributed collaboration, marketing tool, or Interactive Electronic Technical Manual because of the design information security problem and the license cost. Therefore, various lightweight visualization formats and application systems have been suggested to overcome these problems. However, most of these lightweight formats are dependent on the companies or organizations which suggested them and cannot be shared with each other. In addition, product structure information is not represented along with the product geometric information. In this paper, we define a dataset called prod-X3D(Enhanced X3D Dataset for Web-based Visualization of 3D CAD Product Model) based on the international standard graphic format, X3D, which can represent the structure information as well as the geometry information of a product, and propose a translation method from 3D CAD data to an prod-X3D.

A Case Study of Economic Infographic by Beautiful Visualization Method

  • Hua, Zheng-yang;Kim, Se-hwa
    • Proceedings of the Korea Contents Association Conference
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    • 2012.05a
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    • pp.339-340
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    • 2012
  • As the flood of huge data, simply static traditional diagram cannot help reader understand these dataset. Economic data analysis needs a lot of time to clearly understood. The purpose of this study is by using beautiful visualization method to analysis economic infographic displayed huge data easily, quickly and aesthetically.

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Scientific and Technical Visualization for Ocean Process Simulations (해양과정시뮬레이션의 과학기술적가시화)

  • Choi Byung Ho
    • 한국전산유체공학회:학술대회논문집
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    • 1999.05a
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    • pp.1-10
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    • 1999
  • This paper briefly introduces the work done up to 1998 during the past twenty years for numerical modeling of ocean process focussing on the neighbouring seas of Korean Peninsula. Modeling of global ocean dynamics has also been performed as a pathway to understand the regional ocean dynamics. The ocean simulation produces a vast amount of multidimensional multivariate dataset therefore adoption of scientific and technical visualization techniques were essential to properly understand the physics involved.

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Knowledge Model for Disaster Dataset Navigation

  • Hwang, Yun-Young;Yuk, Jin-Hee;Shin, Sumi
    • Journal of Information Science Theory and Practice
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    • v.9 no.4
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    • pp.35-49
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    • 2021
  • In a situation where there are multiple diverse datasets, it is essential to have an efficient method to provide users with the datasets they require. To address this suggestion, necessary datasets should be selected on the basis of the relationships between the datasets. In particular, in order to discover the necessary datasets for disaster resolution, we need to consider the disaster resolution stage. In this paper, in order to provide the necessary datasets for each stage of disaster resolution, we constructed a disaster type and disaster management process ontology and designed a method to determine the necessary datasets for each disaster type and disaster management process step. In addition, we introduce a method to determine relationships between datasets necessary for disaster response. We propose a method for discovering datasets based on minimal relationships such as "isA," "sameAs," and "subclassOf." To discover suitable datasets, we designed a knowledge exploration model and collected 651 disaster-related datasets for improving our method. These datasets were categorized by disaster type from the perspective of disaster management. Categorizing actual datasets into disaster types and disaster management types allows a single dataset to be classified as multiple types in both categories. We built a knowledge exploration model on the basis of disaster examples to ensure the configuration of our model.

A Study on Strategic Factors for the Application of Digitalized Korean Human Dataset (한국인의 인체정보 활용을 위한 전략적 요인에 관한 연구)

  • Park, Dong-Jin;Lee, Sang-Tae;Lee, Sang-Ho;Lee, Seung-Bok;Shin, Dong-Sun
    • Journal of Digital Convergence
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    • v.8 no.2
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    • pp.203-216
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    • 2010
  • This study corresponds to an exploratory survey that identifies and organizes important decision factors for establishing R&D strategic portfolio in the application of digitalized Korean human-dataset. In the case of countries that have performed the above, the digitalized human-dataset and its visualization application development research are regarded as strategic R&D projects selected and supervised in national level. To achieve the goal of this study, we organize a professional group that reviews articles, suggests research topics, considers alternatives and answers questionnaires. With this study, we draw and refine the detailed factors; these are reflected during a strategic planning phase that includes R&D vision setting, SWOT analysis and strategy development, research area and project selection. In addition to this contribution for supporting the strategic planning, the study also shows the detailed research area's definition/scope and their priorities in terms of importance and urgency. This addition will act as a guideline for investigating further research and as a framework for assessing the current status of research investment.

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From TMJ to 3D Digital Smile Design with Virtual Patient Dataset for diagnosis and treatment planning (가상환자 데이터세트를 기반으로 악관절과 심미를 고려한 진단 및 치료계획 수립)

  • Lee, Soo Young;Kang, Dong Huy;Lee, Doyun;Kim, Heechul
    • Journal of the Korean Academy of Esthetic Dentistry
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    • v.30 no.2
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    • pp.71-90
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    • 2021
  • The virtual patient dataset is a collection of diagnostic data from various sources acquired from a single patient into a coordinate system of three-dimensional visualization. Virtual patient dataset makes it possible to establish a treatment plan, simulate various treatment procedures, and create a treatment planning delivery device. Clinicians can design and simulate a patient's smile on the virtual patient dataset and select the optimal result from the diagnostic process. The selected treatment plan can be delivered identically to the patient using manufacturing techniques such as 3D printing, milling, and injection molding. The delivery of this treatment plan can be linked to the final prosthesis through mockup confirmation through provisional restoration fabrication and delivery in the patient's mouth. In this way, if the diagnostic data superimposition and processing accuracy during the manufacturing process are guaranteed, 3D digital smile design simulated in 3D visualization can be accurately delivered to the real patient. As a clinical application method of the virtual patient dataset, we suggest a decision-making method that can exclude occlusal adjustment treatment from the treatment plan through the digital occlusal pressure analysis. A comparative analysis of whole-body scans before and after temporomandibular joint treatment was suggested for adolescent idiopathic scoliosis patients with temporomandibular joint disease. Occlusal plane and smile aesthetic analysis based on the virtual patient dataset was presented when treating patients with complete dentures.