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무인수상정의 기뢰 탐지 임무 수행을 위한 통합 시뮬레이션 방법 연구
이혜원(Hye-Won Lee),노명일(Myung-Il Roh),함승호(Seung-Ho Ham),조로만(Luman Zhao),김낙완(Nak-Wan Kim),하솔(Sol Ha),우주현(Joo-Hyun Woo),정우현(Woo-Hyun Jung),유찬우(Chan-Woo Yu) (사)한국CDE학회 2017 한국CDE학회 논문집 Vol.22 No.3
The USV performs various missions including mine detection and marine reconnaissance and survey unmanned. As the autonomic software for USV takes charge of detection, decision, and command instead of human, the verification and validation (V&V) of the software is highly required at the early design stage. Due to the difficulty of such V&V before the real USV is made, the virtual prototype of USV and ocean space are adopted in this study. For mine detection mission, which is one of the most important mission of USV, four modules are developed and implemented here; scenario management and display module, USV motion analysis module, submarine topography synthesis module, and mine detection module. The mine detection module represents the control algorithm in autonomic software, and the rest of the modules are virtual prototype which represents the ocean space and hardware in USV such as GPS (Global Positioning System) and SSS (Side Scan Sonar). With the virtual prototype modules, the control algorithm in mine detection module is verified. Meanwhile, for the data communication between the modules, the ROS (Robot Operating System) is used. The ROS provides message communication function between the modules, so that each module can transmit and receive data during the simulation. To check the applicability of the proposed method, the mine detection scenario is performed using the virtual prototype of USV and ocean space. The result shows that the proposed method can be effectively used to test and develop the mine detection algorithm of autonomic software in USV.
자동차 차체용 AHSS 소재에 대한 AC 펄스 GMA 용접성 평가
소우주(Wooju So),유지영(Jiyoung Yu),김동철(Dong Cheol Kim),강문진(Moon Jin Kang),박영환(Young Whan Park),이세헌(Sehun Rhee) 대한기계학회 2010 대한기계학회 춘추학술대회 Vol.2010 No.4
본 연구에서는 극성 가변 효과와 펄스 전류 특성을 이용한 AC 펄스 GMA 용접을 자동차 차체용 AHSS 소재의 용접 공정에 적용하였다 먼저 AC 펄스 GMA 용접에서 EN ratio 변화에 의한 아크 용융현상과 비드 형상의 변화에 대해 분석하였다. EN ratio가 증가함에 따라 아크 루트가 전극 와이어에 형성되는 시간이 증가하여 와이어 용융속도가 증가하고 모재쪽의 입열이 감소하는 것을 확인하였으며, EN ratio 변화에 따른 비드 형상 변화를 분석하였다. 또한 자동차 차체용 AHSS 소재에 대한 AC 펄스 GMA 용접의 갭 접합성 평가를 통해 생산 현장에서 겹치기 용접 이음부의 0~1㎜ 갭 발생에 대해 적정 용접조건을 제시하였다. Because of the recent increase in oil prices and people's growing interest in environmental issues through the world, automobile makers have conducted various studies on improving fuel efficiency through weight reduction in vehicles. One of the most widely known car weight-reduction methods is to use high strength steel. However, because of poor weldability and gap occurrence in assembly process caused by spring back, it is difficult to obtain good weld quality when working with the AHSS. In this paper, pulse GMA welding which uses changes in the polarity and the characteristics of pulse current, has been applied to the arc welding of AHSS for automobile body.
유지웅 ( Jiwoong Yu ),이우주 ( Woojoo Lee ) 한국보건정보통계학회 2022 보건정보통계학회지 Vol.47 No.5
Propensity score matching (PSM) is one of the most widely-used causal inference methods to estimate the causal estimands such as average treatment effect or average treatment effect on the treated from observational studies. To implement PSM, a researcher first selects an appropriate set of confounders, estimates the propensity score, and matches the treated group with the control group using a matching algorithm such as nearest neighborhood or optimal matching. In this paper, we highlight the importance of investigating the assumptions employed in the PSM procedure thoroughly because they strongly affect the analysis result, but are not testable using observational data. We explain how to exploit the domain knowledge to avoid the potential risks from the violation of the untestable assumptions, and show how the research purpose is linked to selecting the matching algorithm and downstream analysis after PSM. In addition, to examine the vulnerability of the causal result, we highlight the use of sensitivity analysis for the analysis after PSM. These points are demonstrated in detail using National Supported Work data.
유지웅 ( Jiwoong Yu ),이우주 ( Woojoo Lee ) 한국보건정보통계학회 2022 보건정보통계학회지 Vol.47 No.2
Propensity score matching (PSM) is one of the most widely-used causal inference methods to estimate the causal estimands such as average treatment effect or average treatment effect on the treated from observational studies. To implement PSM, a researcher first selects an appropriate set of confounders, estimates the propensity score, and matches the treated group with the control group using a matching algorithm such as nearest neighborhood or optimal matching. In this paper, we highlight the importance of investigating the assumptions employed in the PSM procedure thoroughly because they strongly affect the analysis result, but are not testable using observational data. We explain how to exploit the domain knowledge to avoid the potential risks from the violation of the untestable assumptions, and show how the research purpose is linked to selecting the matching algorithm and downstream analysis after PSM. In addition, to examine the vulnerability of the causal result, we highlight the use of sensitivity analysis for the analysis after PSM. These points are demonstrated in detail using National Supported Work data.