• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.455-458
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• 2008

기업의 전사적 비즈니스와 IT 환경의 통합 청사진을 보여주는 엔터프라이즈 아키텍처의 효율적인 시스템 적용을 위하여는 조직의 비즈니스, 정보, 응용시스템, 기술 기반구조의 연관관계와 미래모델을 시각적으로 사용자에게 보여주어야 한다. 기존 ITAMS 혹은 EAMS 라고 불리는 시스템에 아키텍처 툴을 이용하여 EA 의 모델정보를 퍼블리싱하여 시각화하였는데 시스템과 아키텍처 툴간의 플랫폼의 이질성으로 인하여 아키텍처정보를 그래픽화하여 변환하고 해당정보를 시스템에서 보여주는데 실시간 적용이 불가능 했을 뿐 아니라 사용자의 편의성이 원활하지 않았다. 이에 본 연구는 XML 기반의 SVG 그래픽 도구를 이용하여 아키텍처 작업을 가능하게 하고 SVG 정보의 자동 생성 및 웹기반 모델링 툴을 구현하여 시스템과 모델링 툴의 단일 레파지토리화를 통하여 데이터의 이원화를 해소하고 사용자 편의성을 증대하는 패턴을 구현한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.191-197
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• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• Communications of Mathematical Education
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• v.30 no.4
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• pp.515-530
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• 2016

Recently an extensive study of the mathematicians who have overcome the visually impaired and contribute to the academic in math was published. In the case of Korea, we can find there are mathematicians who have overcome physical disabilities such as cerebral palsy and polio. However there is no example of blind person who majored mathematics to become a mathematic's teacher or professor and have entered any mathematics related professions. This let us to study the reasons that caused difficulties to visually impaired students majoring in mathematics. We also suggest ways that may help blind students to have access to mathematics intuitively. In this study, we propose a tactile mathematics textbooks and teaching manuals utilizing 3D printing which the visually impaired students can touch and feel. We can supply such materials to visually impaired youth, special education teachers and parents in Korea. As a result, visually impaired students will be able to access mathematics easily and can build their confidence in mathematics. We hope that some blind students with mathematical talent do not hesitate to major mathematics and choose career in mathematical professions.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.85-92
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• 2023

Recently, interest in artificial intelligence has increased due to the development of artificial intelligence fields such as ChatGPT and self-driving cars. However, there are still many unknown elements in training process of artificial intelligence, so that optimizing the model requires more time and effort than it needs. Therefore, there is a need for a tool or methodology that can analyze the weight changes during the training process of artificial intelligence and help out understatnding those changes. In this research, I propose a visualization system which helps people to understand the accumulated weight changes. The system calculates the weights for each training period to accumulates weight changes and stores accumulated weight changes to plot them in 3D space. This research will allow us to explore different aspect of artificial intelligence learning process, such as understanding how the model get trained and providing us an indicator on which hyperparameters should be changed for better performance. These attempts are expected to explore better in artificial intelligence learning process that is still considered as unknown and contribute to the development and application of artificial intelligence models.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.493-495
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• 2004

본 논문은 도시계획과정에서 도시설계안을 행정가, 설계자, 지주, 인근거주자 등에게 제시하고 이들의 요구사항을 실시간으로 반영할 수 있는 도시설계를 위한 가상현실 협업시스템인 AR-Station을 소개한다. 본 시스템은 다양한 참여자들 간의 원활한 의사소통과 협업을 위하여 가상 도시 모델을 시각화하기 위한 Hybrid Scene Graph와 직관적인 인터랙션을 제공하기 위한 탠저블 인터페이스를 사용한다. 참여자들의 작업공간은 시스템과 참여자들 사에의 상호작용이 효율적으로 이루어지도록 반영공간과 인터랙션공간으로 구분하여 설계하고 구현하였다.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.31-38
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• 2023

In this paper, a basic machine learning model learning and utilization education curriculum for non-majors is proposed, and an education method using Orange machine learning model learning and analysis tools is proposed. Orange is an open-source machine learning and data visualization tool that can create machine learning models by learning data using visual widgets without complex programming. Orange is a platform that is widely used by non-major undergraduates to expert groups. In this paper, a basic machine learning model learning and utilization education curriculum and weekly practice contents for one semester are proposed. In addition, in order to demonstrate the reality of practice contents for machine learning model learning and utilization, we used the Orange tool to learn machine learning models from categorical data samples and numerical data samples, and utilized the models. Thus, use cases for predicting the outcome of the population were proposed. Finally, the educational satisfaction of this curriculum is surveyed and analyzed for non-majors.

• Journal of the Korea Computer Graphics Society
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• v.28 no.1
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• pp.1-9
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• 2022

Non-small cell lung cancer (NSCLC) accounts for a high proportion of 85% among all lung cancer and has a significantly higher mortality rate (22.7%) compared to other cancers. Therefore, it is very important to predict the prognosis after surgery in patients with non-small cell lung cancer. In this study, the types of preoperative chest CT image patches for non-small cell lung cancer patients with tumor as a region of interest are diversified into five types according to tumor-related information, and performance of single classifier model, ensemble classifier model with soft-voting method, and ensemble classifier model using 3 input channels for combination of three different patches using pre-trained ResNet and EfficientNet CNN networks are analyzed through misclassification cases and Grad-CAM visualization. As a result of the experiment, the ResNet152 single model and the EfficientNet-b7 single model trained on the peritumoral patch showed accuracy of 87.93% and 81.03%, respectively. In addition, ResNet152 ensemble model using the image, peritumoral, and shape-focused intratumoral patches which were placed in each input channels showed stable performance with an accuracy of 87.93%. Also, EfficientNet-b7 ensemble classifier model with soft-voting method using the image and peritumoral patches showed accuracy of 84.48%.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.187-191
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• 1998

DEVS(Discrete Event system Specification)형식론은 계층적이고 모듈화 된 형식으로 시스템을 설계함으로써 신뢰성 있는 모델링이 가능하도록 이론적으로 잘 정립된 시뮬레이션 방법론이다. 시뮬레이션의 진행과정 및 결과를 표현하기 위한 애니메이션 개발 환경에 있어서도 DEVS 모델의 구조를 반영하여 계층적 애니메이션 환경을 구현 할 수 있다. 계층적 애니메이션은 시뮬레이션 관찰자가 시스템의 특정 레벨에 맞추어 애니메이션 진행 상황을 볼 수 있도록 한다. 이는 일반적으로 시뮬레이션 애니메이션이 갖는 장점인 시스템 이해 및 모델의 신뢰성 검증의 향상 뿐 아니라, 다양한 관점에서 시스템의 변화를 확인 할 수 있다는데 그 필요성이 요구된다. 본 논문에서는 계층적인 애니메이션과 그래픽 표현이 가능하도록 하기위해 DEVS 모델의 구조를 반영한 계층성을 갖는 애니메이터(시뮬레이션과 애니메이션의 연결 프로세서)를 설계하였다. 이러한 애니메이터는 모델과 같은 구조로 각 모델에 필요한 애니메이션 객체들을 유지·관리함으로써 계층적 애니메이션을 가능하게 하며, 시뮬레이션의 이산적인 시각 경과와 애니메이션의 연속적인 시간 경과와 애니메이션의 연속적인 시간 경과 사이에 동기화를 용이하게 한다.

• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.161-164
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• 2019

본 논문은 BERT 모델을 이용하여 동형이의어의 단어 표현(Word Representation) 차이에 대한 실험을 한다. BERT 모델은 Transformer 모델의 인코더 부분을 사용하여 양방향을 고려한 단어 예측과 문장 수준의 이해를 얻을 수 있는 모델이다. 실험은 동형이의어에 해당되는 단어의 임베딩으로 군집화를 수행하고 이를 Purity와 NMI 점수로 계산하였다. 또한 각 단어 임베딩 사이를 코사인거리(Cosine Distance)로 계산하고 t-SNE를 통해 계층에 따른 변화를 시각화하였다. 군집된 결과는 모델의 중간 계층에서 점수가 가장 높았으며, 코사인거리는 8계층까지는 증가하고 11계층에서 급격히 값이 변하는 것을 확인할 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1207-1212
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• 2015

In this paper, we propose three-dimensional (3D) visualization and recognition techniques of micro-objects under photon-starved conditions using photon counting integral imaging microscopy. To capture high resolution 2D images with different perspectives in the proposed method, we use Synthetic Aperture Integral Imaging (SAII). Poisson distribution which is mathematical model of photon counting imaging system is used to extract photons from the images. To estimate 3D images with 2D photon counting images, the statistical estimation is used. Therefore, 3D images can be obtained and visualized without any damage under photon-starved conditions. In addition, 3D object recognition can be implemented using nonlinear correlation filters. To prove the usefulness of our technique, we implemented the optical experiment.