• 한국정보교육학회:학술대회논문집
• /
• 2005.08a
• /
• pp.107-115
• /
• 2005

통계 학습에서 자바 애플릿의 활용은 통계간을 직관적으로 이해할 수 있어 학습의 효과를 높일 수 있다. 통계 영역의 그래프를 공부하는데 통계값의 의미를 눈으로 보면서 이해하고 직접 조작하며 학습을 하면 보다 능률적일 것이다. 이에 본 연구에서는 통계 영역의 교육과정을 분석하여 그래프 객체를 정의하고, 객체의 속성과 메소드를 분석하여 클래스를 구성한 후 클래스 사이의 관계를 파악하여 클래스 계층구조를 설계하였다.

• Proceedings of the KAIS Fall Conference
• /
• 2010.05b
• /
• pp.1189-1192
• /
• 2010

컴퓨터 과학 교육 분야의 알고리즘을 학습할 수 있는 교육용 콘텐츠를 제안한다. 제안하는 콘텐츠는 컴퓨터 과학 교육을 학습 하고자 할 때에 학습 효과를 더욱 증대시키기 위한 것 이다. 본 논문은 그래프 알고리즘을 기반으로 하는 학습 콘텐츠 플래시를 만들고자 한다. 학습 콘텐츠의 기반은 플래시 형식으로 하고, 학습자가 스스로 학습할 수 있는 콘텐츠를 플래시 기반으로 하여 설계하여 동적으로 학습 하도록 구현하였다.

• The KIPS Transactions:PartD
• /
• v.13D no.7 s.110
• /
• pp.1017-1026
• /
• 2006

Recently, distributed collaborative development environment has been recognized an alternative environment for product development in which multidisciplinary participants are naturally involving. Reuse of Product design information has long been recognized as one of core requirements for efficient product development. This paper addresses an image-based retrieval system to support product design information reuse. In the system, product images obtained from multi-modal devices are utilized to reuse design information. The proposed system conducts the segmentation of a product image by using a labeling method and generates an attributed relational graph (ARG) that represents properties of segmented regions and their relationships. The generated ARG is extended by integrating corresponding part/assembly information. In this manner, the reuse of assembly design information using a product image has been realized. The main advantages of the presented system are following. First, the system is not dependent to specific design tools, because it utilizes multimedia images that can be obtained easily from peripheral devices. Second ratio-based features extracted from images enable image retrievals that contain various sizes of parts. Third, the system has shown outstanding search performance, because we applied various information of segmented part regions and their relationships between parts.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.31 no.5
• /
• pp.411-419
• /
• 2013

Research on developing algorithms for building modeling such as extracting outlines of the buildings and segmenting patches of the roofs using aerial images or LiDAR data are active. However, utilizing information from the building model is not well implemented yet. This study aims to propose a scheme for search identical or similar shape of buildings by utilizing graph topology pattern matching under the assumptions: (1) Buildings were modeled beforehand using imagery or LiDAR data, or (2) 3D building data from digital maps are available. Side walls, segmented roofs and footprints were represented as nodes, and relationships among the nodes were defined using graph topology. Topology graph database was generated and pattern matching was performed with buildings of various shapes. The results show that efficiency of the proposed method in terms of reliability of matching and database structure. In addition, flexibility in the search was achieved by altering conditions for the pattern matching. Furthermore, topology graph representation could be used as scale and rotation invariant shape descriptor.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.1
• /
• pp.649-654
• /
• 2023

This paper proposes the design of a neural network structure search model using graph convolutional neural networks. Deep learning has a problem of not being able to verify whether the designed model has a structure with optimized performance due to the nature of learning as a black box. The neural network structure search model is composed of a recurrent neural network that creates a model and a convolutional neural network that is the generated network. Conventional neural network structure search models use recurrent neural networks, but in this paper, we propose GC-NAS, which uses graph convolutional neural networks instead of recurrent neural networks to create convolutional neural network models. The proposed GC-NAS uses the Layer Extraction Block to explore depth, and the Hyper Parameter Prediction Block to explore spatial and temporal information (hyper parameters) based on depth information in parallel. Therefore, since the depth information is reflected, the search area is wider, and the purpose of the search area of the model is clear by conducting a parallel search with depth information, so it is judged to be superior in theoretical structure compared to GC-NAS. GC-NAS is expected to solve the problem of the high-dimensional time axis and the range of spatial search of recurrent neural networks in the existing neural network structure search model through the graph convolutional neural network block and graph generation algorithm. In addition, we hope that the GC-NAS proposed in this paper will serve as an opportunity for active research on the application of graph convolutional neural networks to neural network structure search.

• Proceedings of the Korean Information Science Society Conference
• /
• 2000.04a
• /
• pp.489-491
• /
• 2000

본 논문은 ATM(Abstract Timed Machine)으로 명세된 실시간 시스템을 검증하기 위한 방법을 기술한다. ATM은 임무 위급 시스템인 실시간 시스템을 명세, 분석, 검증하기 위한 정형기법이다. ATM은 모드와 전이, 포트로 구성된다. 다른 정형기법과 비교하여 ATM은 소프트웨어의 순환공학 과정에서 사용하기 위해 설계되었다. 역공학 과정에서 ATM은 계산 논리 뿐만 아니라 실시간 시스템의 실제 소스코드에 있는 설계나 환경정보를 표현할 수 있다. 이러한 목적을 위해 ATM은 다양한 모드를 사용한다. ATM을 사용한 실시간 시스템의 검증은 도달성 그래프를 생성함으로써 수행한다. 도달성 그래프는 상태와 시간을 추상화되고 압축된 형태로 표현할 수 있으며 그 결과 시간 속성을 지닌 상태 공간을 감소시킬 수 있다. 또한 시스템의 교착상태를 쉽게 발견할 수 있다. 본 논문은 ATM과 실행 모델, 도달성 그래프, 검증을 위한 속성 등을 기술하며 이들을 다른 정형 기법들과 예제를 통하여 비교한다.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.8
• /
• pp.2430-2441
• /
• 2000

A visual concurrent programming environment, called ESTGVP is designed and implemented, which is easy to understand, highly portable, and can represent parallel behaviors. For our purpose, a conventional state transition graph is extended so as to enable both of synchronous and asynchronous parallel operations. We call it extended state transition graph (ESTG). ESTGVP uses the ESTG and texts for programming, and makes it easy programming sequential and parallel behaviors. Also, it is easy to understand the control structure of a program because ESTGVP is a visual programming environment based on the graph. ESTGVP is written in Tel language and thus it is highly portable on various operating systems. It consists of three major components; edition, transformation and execution. If necessary, ESTG can be transformed into C or Tel language, and its execution is based on Tel.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.34-34
• /
• 2022

우리나라의 하천은 그 중요도와 규모에 따라 국가·지방·소하천 및 세천 등으로 분류하고 있다. 우리나라 하천 관리는 주로 국가 지방하천을 중심으로 이루어지고 있다. 특히 수리량 계측에 있어서 대부분의 수위 유량 관측시설이 국가 지방하천에 위치해 있으며, 소하천에 대한 관측은 거의 이루어 지지 않고 있다. 이로 인해 소하천 설계기준의 홍수량 산정 공식은 국내 중규모 이상 하천의 경험식이나 외국의 소하천 경험식에 기반한 매개변수를 따르고 있어, 국내 소하천의 특성을 반영하지 못하고 있다. 국립재난안전연구원에서는 국내 소하천 특성에 적합한 설계기준 개발 및 홍수량 산정을 위해 소하천 자동유량계측기술을 개발하고, 전국 소하천의 10%(2,230개소)에 설치·운영하는 것을 목표로 행정안전부 및 지자체와 협력하여 확대 구축을 추진 중이다. 소하천은 유로연장이 짧고 유역면적이 크지 않아 도달시간이 짧은 것이 특징으로, 강우-유량 노모그래프를 사용하여 소하천 홍수 예·경보를 위한 홍수량 산정이 가능하다. 강우-유량 관계는 선행강우에 따른 토양의 포화상태와 강우 발생 시점의 기저유량 등에 영향을 많이 받는다. 본 연구에서는 자동유량계측기술 설치 시범소하천 5개소의 계측데이터를 사용하여 선행강우를 고려한 강우-유량 노모그래프를 개발하였다. 또한, 뉴로-퍼지 기법과 회귀분석을 사용한 홍수량 예측결과와 비교 연구를 수행하였다.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.9
• /
• pp.167-176
• /
• 2023

In this paper, we designed and implemented a graph assessment module that can evaluate graphs in an programming assessment system based on text and numbers. The assessment method of the graph assessment module is self-evaluation that outputs two graphs generated by codes submitted by learners and by answers, automatic-evaluation that converts each graph image into an array, and gives feedback if it is wrong. The data used to generate the graph can be inputted directly or used from external data, and the method of generatng graph that can be evaluated is MATLAB style in matplotlib, and the graph shape that can be evaluated is presented in mathematics and curriculum. Through expert review, it was confirmed that the content elements of the assessment module, the possibility of learning, and the validity of the learner's needs were met. The graph assessment module developed in this study has expanded the evaluation area of the programming automatic asssessment system and is expected to help students learn data visualization.

• Journal of KIISE:Software and Applications
• /
• v.32 no.1
• /
• pp.10-21
• /
• 2005

Software architecture is increasingly being viewed as a key design in developing complex software systems, which largely affects the achievement of quality attributes. During the architecture-based software development, therefore, architectural transformation is needed to achieve quality attributes. Due to the variety of design alternatives and the poor predictability of the effects of the transformation, however, it is not easy to apply architectural transformation. Therefore, the method is needed to support architectural transformation through systematically analyzing the effects of applying various design alternatives to the architecture. This paper proposes an approach to support software architecture transformation. Based on architectural design decisions and the constraints on them included in the architecture, our approach defines a decision constraint graph representing the dependencies among architectural design decisions. Through using the decision constraint graph, architectural transformation can be systematically performed by understanding the effects of applying a transformation. While this work supports more understanding of applying architectural transformation, it also helps reconstruct a software architecture to improve the quality of the software.