• Journal of the Optical Society of Korea
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• v.18 no.2
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• pp.151-155
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• 2014

Although various ophthalmic imaging methods, including fundus photography and optical coherence tomography, have been applied for effective diagnosis of ocular diseases with high spatial resolution, most of them are limited by shallow imaging penetration depth and a narrow field of view. Also, many of those imaging modalities are optimized to provide microscopic anatomical information, while functional or cellular information is lacking. Compared to other ocular imaging modalities, photoacoustic imaging can achieve relatively deep penetration depth and provide more detailed functional and cellular data based on photoacoustic signal generation from endogenous contrast agents such as hemoglobin and melanin. In this paper, array-based ultrasound and photoacoustic imaging was demonstrated to visualize pigmentation in the eye as well as overall ocular structure. Fresh porcine eyes were visualized using a real-time ultrasound micro-imaging system and an imaging probe supporting laser pulse delivery. In addition, limited photoacoustic imaging field of view was improved by an imaging probe tilting method, enabling visualization of most regions of the retina covered in the ultrasound imaging.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.67-72
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• 2015

Recently, studies that interact with human and things through motion recognition are increasing due to the expansion of IoT(Internet of Things). This paper proposed the system that recognizes the user's logical activity in home environment by attaching some sensors to various objects. We employ Arduino sensors and appreciate the logical activity by using the physical activitymodel that we processed in the previous researches. In this System, we can cognize the activities such as watching TV, listening music, talking, eating, cooking, sleeping and using computer. After we produce experimental data through setting virtual scenario, then the average result of recognition rate was 95% but depending on experiment sensor situation and physical activity errors the consequence could be changed. To provide the recognized results to user, we visualized diverse graphs.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.392-394
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• 1998

데이터 웨어하우스 시스템은 의사 결정의 지원에 필요한 요약, 분석 작업을 수행하여 다양한 고품질의 정보 서비스를 사용자에게 제공한다[1]. 이러한 데이터 웨어하우스에 사용자가 질의를 요청할 경우 다차원 모델을 고려해 보면 여러 테이블을 조인해야 할 경우가 발생하고 이때 방대한 양의 사실 테이블을 가지고 있는 데이터 웨어하우스는 질의 처리시 성능 저하를 초래 할 수 있다. 그러므로 본 연구에서는 사용자의 질의에서 자주 요구되는 집계사실을 미리 저장하여 데이터 웨어하우스에 대한 질의 처리 성능향상을 기대할 수 있도록 집계사실이 저장될 효율적인 집계 테이블 생성에 따른 설계와 구현을 한다. 이를 수행하기 위해 본 논문에는 집계 사실의 저장방법에 대해 살펴보고, 집계 계획에 근거한 집계테이블 생성 인터페이스의 프로토타입 설계 및 구현을 살펴본다. 이렇게 함으로서 사용자의 의사결정에 필요한 정보를 데이터 웨어하우스에서 더욱 신속하게 얻을 수 있다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.818-830
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• 2000

Automation tools for program analysis are needed in order to program understand and maintain, extract the characteristics of object-oriented program such as class name, member function and data member. In this paper, we carried out design and implementation of the automation tool for effective maintenance of object-oriented software. Being based on Reverse Engineering, this approach extracts class relationship information from C++ source code and generates object-oriented model of class diagram using UML as the standard object-oriented methodology. Therefore, this paper provides developers visualized including class information, definitions of classes, inheritance relationships, set relationships, and simple reference relationships. Finally in this paper, we propose a method that construct class relationship information to table in analysis state and make form of table construction to link form so tat developers can perform understanding and maintaining program efficiently. And this method enable to restructure and reuse in object-oriented model.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.346-348
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• 2003

In this study, we attempted to estimate the discharge of the Amazon River branches from JERS-1/SAR images, which are independent of the weather. We visualized some traces of the Amazon River branches, transformed river shapes into a one-dimensional signal, and calculated the characteristics of the river shapes such as the meandering wavelength and the amplitude with Fourier and wavelet analysis. Then, we related the characteristics of the river shapes with the existing discharge data and derived some regression equations. Finally, we estimated the discharge of the Amazon River branches from the SAR images.

• Journal of the Korean Society of Visualization
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• v.16 no.3
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• pp.35-39
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• 2018

In multiphase systems, surface wettability is one of dominant design parameters to enhance system performance. Since surface wettability can be maximized and minimized with micro-textured surfaces, therefore micro-textured surfaces are widely countered in various research and engineering fields. In this study, for better understanding of micrometer scaled surface wettability, spreading phenomena is experimentally investigated on the hydrophilic micro-textured surfaces. By photolithography and conventional dry etching method, there are prepared the surfaces with uniformly arrayed micro-pillars. The interfacial motions of a water droplet on the test sections are visualized by high speed camera in top view. On the basis of visualization data, it is analyzed the relation between dynamic coefficient and geometrical features on micro-textured surfaces.

• Health Policy and Management
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• v.29 no.2
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• pp.138-145
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• 2019

Background: The purpose of this study is supposed to figure out the keyword network from 2009 to 2018 with social network analysis and provide the research data that can help the Korea government's policy making on smoking cessation. Methods: First, frequency analysis on the keyword was performed. After, in this study, I applied three classic centrality measures (degree centrality, betweenness centrality, and eigenvector centrality) with R 3.5.1. Moreover, I visualized the results as the word cloud and keyword network. Results: As a result of network analysis, 'smoking' and 'smoking cessation' were key words with high frequency, high degree centrality, and betweenness centrality. As a result of looking at trends in keyword, many study had been done on the keyword 'secondhand smoke' and 'adolescent' from 2009 to 2013, and 'cigarette graphic warning' and 'electronic cigarette' from 2014 to 2018. Conclusion: This study contributes to understand trends on smoking cessation study and seek further study with the keyword network analysis.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.461-468
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• 2020

This study examined how national research and development (R&D) in the domain of logistics has changed recently in the Republic of Korea. We conducted basic statistical analysis and social network analysis on 5,327 logistics-related R&D projects undertaken during 2005-2019. Data for performing these analyses were collected from the R&D database of the National Science and Technology Information Service (NTIS). By constructing a co-occurrence matrix with keywords, we conducted degree and betweenness centrality analysis and visualized the network matrix to display a cluster map. This study presents our observations related to the following findings: (1) the chronical trends of logistics R&D, (2) focused fields of logistics R&D, (3) the relations among keywords, and (4) the characteristics of logistics R&D. Finally, we suggest policy implications to boost and diversify logistics R&D.

• Genomics & Informatics
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• v.19 no.3
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• pp.28.1-28.4
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• 2021

Since only a small number of patients have a rare disease, it is difficult to identify all of the features of these diseases. This is especially true for patients uncommonly presenting with rare diseases. It can also be difficult for the patient, their families, and even clinicians to know which one of a number of disease phenotypes the patient is exhibiting. To address this issue, during Biomedical Linked Annotation Hackathon 7 (BLAH7), we tried to extract Alexander disease patient data in Portable Document Format. We then visualized the phenotypic diversity of those Alexander disease patients with uncommon presentations. This led to us identifying several issues that we need to overcome in our future work.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.799-802
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• 2010

HPC에서 시뮬레이션을 수행한 결과로 생성된 데이터는 크기가 방대하고 구조가 복잡해지는 양상을 보이고 있다. 데이터 크기로만 보더라도 기가바이트를 넘어 테라바이트에 이를 정도로 대형화되는 경향을 보이고 있으며, 이렇게 복잡도가 놓은 대형 데이터는 이미 컴퓨터 한 대에서 처리하고 분석할 수 있는 범주는 넘어서고 있다. 본 논문에서는 이런 복잡한 과학 시뮬레이션 데이터 중, 특히 로터 동역학 분야의 데이터를 가시화하고 제어하는데 필요한 통합 가상현실 인터페이스를 소개하기로 한다. 현재 개발중인 GLOVE 프레임워크는 대용량 데이터를 연구자가 필요로 하는 형태로 다양하게 가공해서 가시화해서 분석할 수 있게 하는 프레임워크이며, GIVI는 그 중 사용자와의 인터페이스 부분을 담당하는 프레임워크다. GIVI는 가상현실 환경에서 시뮬레이션 데이터를 실시간으로 상호작용을 통해 분석하는데 필요한 기반환경을 제공하며, 향후에는 실시간 시뮬레이션을 위한 인터페이스로도 확장될 것이다.