• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.203-210
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• 2006

A procedure for determining the lateral load pattern for pushover analysis which includes higher mode effects is presented in this study. It is well-known that the details of future earthquakes at particular site is almost impossible to predict accurately and that the code-design spectra try to represent at least the average nature of probable future earthquakes. Thus the code-design spectrum is directly used as the input earthquakes in this paper when incorporating higher mode effects in the pushover analysis so that the efforts for selecting input motions and constructing response spectrum needed in some existing method could be avoided. A case study based on the time history analysis of a irregular steel moment frame showed that the procedure proposed in this study generally outperforms various pushover analysis procedures of ATC-40 and FEMA 273. However, the proposed procedure tended to be conservative as compared with the time history analysis method.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.476-476
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• 2017

최근 갑작스런 폭우로 인한 제방 붕괴, 침수 및 지진 등과 같은 재해 발생 시 추가 피해를 방지하고 주민들의 긴급대피를 도운 건 SNS를 통한 현장 정보와 경보 메시지의 지속적인 전파이다. 최근의 SNS는 재난정보에서도 활용할 수 있을 정도로 진화하였다. 국가재난정보 중 수재해 관련 정보를 추출하여 다양한 주제도위에 중첩으로 공간정보를 제공할 수 있는 재난정보 제공을 위한 웹서비스를 개발하고자 하였다. 수재해 정보를 필터링하기 위하여 우선 관련된 키워드 선정이 필요하며, 기본적인 키워드는 하천일람표를 참고하여 6개 권역 및 하천이름을 선정하였다. 또한, 한강 홍수 통제소의 수자원 용어사전과 (사)한국물학술단체연합회에서 발간한 물용어집을 참고하여 수재해 관련 용어들 약 300여개를 추가하였다. 선정된 용어들은 1차적으로 적재된 데이터베이스에서 수재해 정보 관련 필터링을 하는데 사용되며, 비정형 데이터들을 필터링하고 주소 정보 검색 및 추출을 통하여 정형화 하게 된다. 추출된 주소정보에 대하여 개발한 지오코딩 모듈을 적용하여 수재해 항목에 대해 좌표정보를 업데이트 하게 된다. 가뭄, 집중호우, 홍수 등의 수재해 정보별, 또한 일자별 그룹화 및 구조화를 진행하고 해당되는 정보를 공간정보 오픈플랫폼 API를 활용하여 지도상에 가시화할 수 있다. 개발한 지오코딩 모듈을 이용하여 실제 테이블 정보를 구성하여 데이터베이스에 수재해 정보 지오코딩 테이블을 구성하여 테스트 모의하였다. 재난정보 중 홍수, 가뭄에 대한 선택정보와 시간정보를 매개변수로 받는 XML 웹서비스 테스트로 검증을 하였다. 본 연구를 통하여 재난정보 가시화에 있어서 사용자가 조회하고자 하는 유형별, 날짜별 선택이 가능한 공간적 정보를 검색 및 확인할 수 있게 되었다. 개발한 수재해 정보 지오코딩 모듈 프로토 타입은 수재해 정보 플랫폼 융합기술 연구단에서 개발하는 핵심 목표시스템 내 재난정보 제공시스템에 적용 가능하며, 수재해 정보에 대하여 대국민 서비스가 가능할 것으로 사료된다.

• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.149-158
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• 2019

This paper introduces an integrated Modeling & Simulation framework for the efficient development of the rescue robot which rescues a wounded patients or soldiers and disposes a dangerous objects or explosive materials in the battlefields and disastrous environments. An integrated M&S(Modeling & Simulation) framework would have enabled us to perform the dynamic simulation program GAZEBO based Software-in-the-Loop Simulation(SILS) which is to replacing the robot platform hardware with a simulation software. An integrated M&S framework would help us to perform designing robot and performance validation of robot control results more efficiently. Furthermore, Tele-operation performance in the unstructured environments could be improved. We review a case study of applying an integrated M&S framework tool in validating performance of mobility stabilization control, one of the most important control strategy in the rescue robot.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.67-76
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• 2019

In this paper, we propose an efficient object classification method based on semantic segmentation for multi-labeled image data. In addition to various pixel unit information and processing techniques such as color information, contour, contrast, and saturation included in image data, a detailed region in which each object is located is extracted as a meaningful unit and the experiment is conducted to reflect the result in the inference. We use a neural network that has been proven to perform well in image classification to understand which object is located where image data containing various class objects are located. Based on these researches, we aim to provide artificial intelligence services that can classify real-time detailed areas of complex images containing various objects in the future.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.509-514
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• 2021

The pandemic of COVID-19 is driving the demand for non-face-to-face diagnosis, observation, and treatment in the healthcare environment, which has led to increased interest in helathcare robots. The authors intend to predict the direction in which the quarantine healthcare robots should be utilized in the post-corona era through analysis of national agency reports, on-offline press reports, and domestic and foreign robot company press releases. The COVID-19 pandemic has raised interest in medical robots. And there is a need to apply healthcare robots that can perform tasks such as disinfection, logistics transfer, screening tests, monitoring of patients, remote medical treatment support for isolated patients, and video calls with family members. Therefore, it is considered that future correct development and application of healthcare robots and empirical research to verify them should be continued based on sufficient consideration for various problems associated with the practical application of robots.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.113-117
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• 2022

Additive manufacturing (AM, also known as 3D printing) technology is digitalized technology, making it easy to predict and manage quality and also, have design freedom ability. With these advantages, AM technology is applied to various industries. In particular, a method of manufacturing buildings and infrastructure with AM technology is being proposed to the construction industry. However, the application of AM technology is restricted due to problems such as insufficient history and quality of technology, lack of construction management methods, and certification of manufacturing products. Therefore, the manufacture of architectural products is implemented with indirect AM technology. In particular, it manufactures formwork using AM and injecting building materials to implement the architectural product. In this study, hybrid type material extrusion AM is used to manufacture large-sized formwork and implement building products. Moreover, we identify factors that can predict productivity and economic feasibility in the additive manufacturing process. As a result, design optimization results are proposed to reduce the production cost and time of architecture buildings.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.351-357
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• 2021

At the time when interest in the use of big data is rising in the face of the technological paradigm shift of the 4th industrial revolution, interest in the use of patented big data is increasing, especially as the proportion of intangible assets of companies increases. In addition to quantitative information, patent data contains various information such as unstructured text such as title, abstract, claim, citation and citation relations, drawings, and technology classification. It is judged that the use of treatment is important. Therefore, in this study, in order to systematically operate the innovative patent strategy framework and to secure a competitive advantage by strengthening the fundamental technological competitiveness of the company, we propose a method of using patent big data centering on the case of Company A, and verify its validity. I would like to suggest some implications. Through this, it is intended to raise awareness of the use of patent big data, and to suggest ways to use patent big data in connection with the company's company-wide strategy, business strategy, and functional strategy.

• Journal of KIISE
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• v.44 no.9
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• pp.893-907
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• 2017

In safety-critical systems, software defects may have serious consequences. Therefore, defects should be considered during the requirements specification process, which is the first step of a software development lifecycle. Stakeholder requirements that are usually written in natural language are difficult to derived, and there may also be defects due to ambiguity and inaccuracy. To address these issues, we propose a requirement specification method using a standardized Boilerplate and a GSN Model. The Boilerplate is a semi-standard language that follows a predefined format. Due to its ability to provide a consistent representation of the requirements, boilerplate helps stakeholders avoid ambiguities about what they mean and to define the exact meaning of the requirement. Meanwhile, GSN is recognized notation to prepare a Safety Case to prove to authorities that a system is safe. It can be expressed as a functional goal, e.g., Safety Evidence, etc. The proposed study allows an analyst to easily identify a fault from the early stage of the software development lifecycle. The Boilerplate and GSN Model are designed to specify the requirements of safety critical systems and to prove safety conformity through a connection with Safety Evidence. In addition, the proposed approach is also useful to develop secure software by correcting deficiencies in the requirements found during this process.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.151-166
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• 2020

A recommender system is a system that recommends products or services that best meet the preferences of each customer using statistical or machine learning techniques. Collaborative filtering (CF) is the most commonly used algorithm for implementing recommender systems. However, in most cases, it only uses purchase history or customer ratings, even though customers provide numerous other data that are available. E-commerce customers frequently use a search function to find the products in which they are interested among the vast array of products offered. Such search keyword data may be a very useful information source for modeling customer preferences. However, it is rarely used as a source of information for recommendation systems. In this paper, we propose a novel hybrid CF model based on the Doc2Vec algorithm using search keywords and purchase history data of online shopping mall customers. To validate the applicability of the proposed model, we empirically tested its performance using real-world online shopping mall data from Korea. As the number of recommended products increases, the recommendation performance of the proposed CF (or, hybrid CF based on the customer's search keywords) is improved. On the other hand, the performance of a conventional CF gradually decreased as the number of recommended products increased. As a result, we found that using search keyword data effectively represents customer preferences and might contribute to an improvement in conventional CF recommender systems.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.307-316
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• 2015

Although the use of CAD and CAM technologies has been broadly adopted by architecture-engineering- construction-facility management (AEC/FM) industry as the means of producing complex forms, there are still remained issues such as reducing cost, and enhancing quality and manufacturability. In this paper, to resolve given issues, we suggest a process of rationalization in digital architecture design and fabrication as an integrated approach. The rationalization, which is usually used as the term related with the skin panel of free-form architecture, is a process of re-designing a digital model to meet the requirements of manufacturing considering the gap with an original designs. Thus we classified this process and conducted a case study of fabricated models as an exploratory study. As the result, we found that each phase is connected with other phases with the circulation of information and rationalization process can be determined as the circulative process which re-designs digital model by minimally deviating from the original design based on the information deducted from analysis of inter-compatability of software and requirement of hardware.