• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.274-276
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• 2002

최근에 지리 정보를 검색, 관리, 분석할 수 있는 지리 정보 시스템(Geographic information System)의 사용이 확대됨에 따라 단순한 수치지도 정보 이외에 좀 더 현실적이고. 사실적인 정보를 제공해 줄 수 있는 시스템에 대한 요구가 커지고 있다 이러한 요구에 부응하는 한 방향으로써 차량에 부착된 카메라 등등 사용하여 획득한 비디오 데이터와 수치지도 정보를 연계하여 특정 수치지도 객체의 영상을 제공함으로써 수치지도 객체에 대한 자세한 현장의 정보를 쉽게 파악할 수 있도록 하는 비디오 지리 정보 시스템이 등장하였다. 하지만 기존의 비디오 지리 정보 시스템은 획득한 비디오 데이터를 수치지도의 한 속성으로서 표현하거나, 수치지도에서 비디오 데이터로의 단순한 링크를 사용하여 수치지도와 연계함으로써 수치지도의 검색을 통한 영상 정보의 출력이라는 단방향 검색만을 지원한다. 즉, 비디오 데이터에 존재하는 수치지도 객체의 검색을 통한 수치지도의 검색 및 관리, 분석은 지원해 주지 못하고 있다. 본 논문에서는 비디오 데이터와 수치지도의 양방향 검색 및 관리를 지원하는 비디오 지리 정보 시스템을 설계하고 구현한다. 이를 위해 1) 비디오 데이터와 수치지도 정보를 효율적으로 연계하기 위한 데이터 모델을 제안하고, 2) 비디오 데이터와 수치지도 정보의 연계 정보를 추출 및 구축하는 과정을 제안하며, 3) 비디오 데이터의 출력 및 검색, 수치지도의 출력 및 검색, 연계 정보를 통한 비디오 데이터와 수치지도 정보의 연동 등을 효율적으로 지원하기 위한 시스템을 컴포넌트(Component) 구조를 사용하여 설계한다. 이해성 및 이를 기반으로 하는 교육용 애플리케이션 개발의 용이성의 증대를 기대할 수 있으며, 모델의 재사용성을 보장할 수 있다. 제안한다.수행하였다. 분석에서는 제품의 효율성뿐만 아니라 보안성을 중요하게 생각하였으며, 앞으로 보안 관련 소프트웨어 개발에 사용될 수 있는 도구들이 가이드 라인에 대한 정보를 제공한다.용할 수 있는지 세부 설계를 제시한다.다.으로서 hemicellulose구조가 polyuronic acid의 형태인 것으로 사료된다. 추출획분의 구성단당은 여러 곡물연구의 보고와 유사하게 glucose, arabinose, xylose 함량이 대체로 높게 나타났다. 점미가 수가용성분에서 goucose대비 용출함량이 고르게 나타나는 경향을 보였고 흑미는 알칼리가용분에서 glucose가 상당량(0.68%) 포함되고 있음을 보여주었고 arabinose(0.68%), xylose(0.05%)도 다른 종류에 비해서 다량 함유한 것으로 나타났다. 흑미는 총식이섬유 함량이 높고 pectic substances, hemicellulose, uronic acid 함량이 높아서 콜레스테롤 저하 등의 효과가 기대되며 고섬유식품으로서 조리 특성 연구가 필요한 것으로 사료된다.리하였다. 얻어진 소견(所見)은 다음과 같았다. 1. 모년령(母年齡), 임신회수(姙娠回數), 임신기간(姙娠其間), 출산시체중등(出産時體重等)의 제요인(諸要因)은 주산기사망(周産基死亡)에 대(對)하여 통계적(統計的)으로 유의(有意)한 영향을 미치고 있어 $25{\sim}29$세(歲)의 연령군에서, 2번째 임신과 2번째의 출산에서 그리고 만삭의

• Korean Journal of Construction Engineering and Management
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• v.21 no.5
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• pp.11-19
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• 2020

A daily progress monitoring and further schedule management of a construction project have a significant impact on the construction manager's decision making in schedule change and controlling field operation. However, a current site monitoring method highly relies on the manually recorded daily-log book by the person in charge of the work. For this reason, it is difficult to take a detached view and sometimes human error such as omission of contents may occur. In order to resolve these problems, previous researches have developed automated site monitoring method with the object recognition-based visualization or BIM data creation. Despite of the research results along with the related technology development, there are limitations in application targeting the practical construction projects due to the constraints in the experimental methods that assume the fixed equipment at a specific location. To overcome these limitations, some smart devices carried by the field workers can be employed as a medium for data creation. Specifically, the extracted information from the site picture by object recognition technology of CNN model, and positional information by GIPS are applied to update 4D BIM data. A standard CNN model is developed and BIM data modification experiments are conducted with the collected data to validate the research suggestion. Based on the experimental results, it is confirmed that the methods and performance are applicable to the construction site management and further it is expected to contribute speedy and precise data creation with the application of automated progress monitoring methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.100-109
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• 2019

Maintainability indicates the extent to which maintenance can be done easily and quickly. The consideration of maintainability is crucial to reduce the operation and support costs of weapon systems, but if the maintainability is evaluated after the prototype production is done and necessitates design changes, it may increase the cost and delay the schedule. The evaluation should verify whether maintenance work can be performed, and support the designers in developing a design to improve maintainability. In previous studies, the maintainability index was calculated using the graph theory at the early design phase, but evaluation accuracy appeared to be limited. Analyzing the methods of evaluating the maintainability using fuzzy logic and 3D modeling indicate that the design of a system with good maintainability should be done in an integrated manner during the whole system life cycle. This paper proposes a method to evaluate maintainability using SysML-based modeling and simulation technique and fuzzy logic. The physical design structure with maintainability attributes was modeled using SysML 'bdd' diagram, and the maintainability was represented by an AHP matrix for maintainability attributes. We then calculated the maintainability using AHP-based weighting calculation and fuzzy logic through the use of SysML 'par' diagram that incorporated MATLAB. The proposed maintainability model can be managed efficiently and consistently, and the state of system design and maintainability can be analyzed quantitatively, thereby improving design by early identifying the items with low maintainability.

• Korean Journal of Construction Engineering and Management
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• v.20 no.2
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• pp.28-36
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• 2019

The APR1400 (Advanced Power Reactor 1400MW) nuclear power plant is a large-scale national infrastructure facility with a total project cost of 8.6 trillion won and a project period of 10 years or more. The total project area is about 2.17 million square meters and consists of more than 20 buildings and structures. And the total number of drawings required for construction is about 65,000. In order to design such a large facility, it is important to establish a design standard that reflects the design intent and can increase conformity between documents (drawings). To this end, a design bases document (DBD) reflecting the design bases that extracted in regulatory requirements (e.g. 10CFR50, Korean Law, etc.) is created. However, although the design bases are important concepts that are a big framework for the whole design of the nuclear power plant, they are managed in 2-dimensional by the experts in each field fragmentarily. Therefore, in order to improve the usability of building information, we developed BIM(Building Information Model) based 3-dimensional design bases management system. For this purpose, the concept of design bases information layer (DBIL) was introduced. Through the simulation of developed system, design bases attribute and element data extraction for each DBIL was confirmed, and walls, floors, doors, and penetrations with DBIL were successfully extracted.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.121-137
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• 2019

De-identification is a method by which the remaining information can not be referred to a specific individual by removing the personal information from the data set. As a result, de-identification can lower the exposure risk of personal information that may occur in the process of collecting, processing, storing and distributing information. Although there have been many studies in de-identification algorithms, protection models, and etc., most of them are limited to structured data, and there are relatively few considerations on de-identification of unstructured data. Especially, in the medical field where the unstructured text is frequently used, many people simply remove all personally identifiable information in order to lower the exposure risk of personal information, while admitting the fact that the data utility is lowered accordingly. This study proposes a new method to perform de-identification by applying the k-anonymity protection model targeting unstructured text in the medical field in which de-identification is mandatory because privacy protection issues are more critical in comparison to other fields. Also, the goal of this study is to propose a new utility metric so that people can comprehend de-identified data set utility intuitively. Therefore, if the result of this research is applied to various industrial fields where unstructured text is used, we expect that we can increase the utility of the unstructured text which contains personal information.

• Journal of the Korea Computer Graphics Society
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• v.27 no.2
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• pp.1-11
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• 2021

In a virtual environment, a 3D workspace and 3D interaction are possible, but most virtual reality applications use a 2D color picker. This paper implements a 3D color picker based on 3D color space in a virtual environment, and compares color selection performance with the existing 2D color picker. The 3D color picker is intuitive by using the 3D color space as it is, and it can position the 3D pointer at a specific point in the color space using a controller, which is a virtual reality device, so a user can select a color in one step. On the other hand, the 2D color picker has the advantage of being familiar with existing users who work with colors in a computer environment, but has a disadvantage that requires several steps of user interaction since it has to set color properties through 2D interfaces. Based on user experiments, we confirmed the usefulness of a 3D color picker in addition to a 2D color picker in a virtual environment, and it was possible to perform natural 3D work in a virtual environment using the 3D color picker.

• Smart Media Journal
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• v.9 no.4
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• pp.66-72
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• 2020

As the online education market expands, educational contents with various presentation methods are being developed and released. In addition, it is imperative to develop content that reflects the usability and user environment of users who use this educational content. However, for qualitative growth of contents that will support quantitative expansion of markets, existing model analysis methods are urgently needed at a time when development direction of newly developed contents is secured. In this process of content development, a typical model for setting development goals is needed, as the rules of the prototype affect the entire development process and the final development outcome. It can also provide a positive benefit that screens the issue of performance dualization between processes due to the absence of communication between a single entity or between a number of entities. In the case of AR-based educational content which is effective to secure data necessary for development by securing samples of similar categories because there are not enough ready-made samples released. Therefore, a big data statistical analysis service is needed that can easily collect data and make decisions using big data. In this paper, we would like to design analysis services that enable the selection and detection of intuitive multidimensional factors and attributes, and propose big data-based statistical analysis services that can assist cooperative activities within an organization or among many companies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• Korean Journal of Social Welfare Studies
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• v.44 no.2
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• pp.465-497
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• 2013

This paper criticizes the ontological and epistemological dichotomy in social sciences including social welfare and probes into Critical Realism as an alternative paradigm. Many theories for social welfare have adhered to dichotomous ontological standpoint, 'agency' vs. 'social structure', and Eco-system approach have occupied dominant position to integrate this dichotomy. These theoretical standpoint have had great influence on social work practice. On the other hand, dichotomous epistemological standpoint which is constituted of different views of phenomena, 'positivism' and 'constructionism', have had great influence on social work research and practice. These dichotomous ontological and epistemological approach have a limit to reveal qualitative nature of the relationship between agency and social structure, to ponder the deeper reality, the mechanism of stratified reality, and the reality being independent of agency. Replacing these approaches, Critical Realism unfold the theoretical potential as an alternative paradigm for social welfare through the discussion on stratified realty(the empirical, the actual, and the real), intransitive/transitive dimension, double hermeneutics in these dimensions, and the conditions for conceptualization, duality of structure and practice, transformation model of agency and structure.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.