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김인수,박재홍,이은영,이은덕,신재곤,김대원,Kim, Insu,Park, Jaehong,Lee, Eun-Young,Lee, Eun Dok,Shin, Jaekon,Kim, Daewon 한국자동차안전학회 2017 자동차안전학회지 Vol.9 No.2
In recent days, crash safety system based on vehicle-to-vehicle communication (V2V) has been legislated. This V2V based safety system collects information from nearby vehicles to predict any crash possibility. Thus, it requires accurate and reliable data. Regularly updated features of Basic Safety Message(BSM) will be used to test validity of various elements included in the BSM. Then, the focus was made on whether values of these elements had notable differences compared to previous values. Through this paper, the validation tool was implemented and the result from V2V OBU experiment was used to identify problems in the current model and additional features that need to be implemented in V2V OBU for more accurate BSM.
고속철도 변전설비 유지보수 부품의 교체주기 산정에 관한 연구
김인수(Insu Kim),최승호(Seung Ho Choi) 한국철도학회 2013 한국철도학회 학술발표대회논문집 Vol.2013 No.11
전철변전소는 고장이나 사고 발생 시 여파가 크게 발생하여 설비 및 운용방법 이중화 등 복합적인 안전장치 및 방안을 구축하여 운용 중이다. 그러나, 변전설비의 구성이 단일품이 아닌 복합적인 설비 및 부품으로 구성되는 특징으로 효과적인 점검이 곤란하다. 변전기기에 대해서는 점검 종류 및 주기가 정의되고 유지보수가 시행되고 있으나, 변전기기를 구성하고 있는 주요 장치에 대해서는 부품단위 생애주기를 감안한 세부점검 계획이 수립, 시행되어야 한다. 본 연구에서는 고속철도 개통 이후 고장내역에 대한 통계분석과 평균수명, 영향인자를 토대로 하여 고속철도 변전설비의 장치별 유지보수 부품 교체주기를 제시하고자 한다. Railway substation has composite safety devices and operation strategies such as duplicated equipment and operating methods for the consideration of breakdown or accident. However, effective inspection is difficult because of complex equipment and components. Although check types and cycles are defined and maintenance is performed, detailed inspection plans should be performed considering life-cycle for each components unit of main devices. In this study, we suggest replacement cycles for each component unit of railway substation based on statistical analysis of fault history, average life cycle, and impact factor of high-speed railway.
김인수 ( Insu Kim ),이명수 ( Myungsoo Yie ) 한국금융연구원 2015 금융연구 Vol.29 No.3
This paper studies the role of unemployment as a feedback variable in monetary policy interest rate rules. While labor market variables are perceived to be important ingredients to explain business cycle fluctuations, many New Keynesian dynamic stochastic general equilibrium (DSGE) model literatures based on Korean economy consider output for the real sector variable in the feedback rule. We also investigate the role of growth variables in the monetary policy rules. Orphanides and Williams (2002) argued that a monetary policy rule responding to growth variables, such as unemployment growth, rather than gap variables can reduce policy mistakes from misperceptions of natural rates of output and unemployment. A monetary policy rule responding to output gap or unemployment gap could bring about unexpected or undesirable results, since natural rates of output and unemployment are not directly observed but measured with uncertainty or measurement errors, and policy actions based on such mistakenly perceived variables could cause the economy to move to the unintended directions. On the other hand, monetary policy rules can avoid such mistakes by responding to growth variables because such rules are not based on the uncertain measures. In order to address these issues, we build a DSGE model with sticky prices and wages and unemployment, and estimate the model using Korean data. The monetary rules considered are interest rate rules responding to past interest rate, inflation rate, and a real sector variable. We consider four different Taylor type rules with respect to a real sector variable. For a real sector variable in the feedback rule, output gap, unemployment gap, output growth, and unemployment growth are used in the analysis. Based on estimated model parameters, we search feedback rule coefficients in a way to minimize welfare losses and evaluate the performance of the rules. In order to analyze the optimal policy rules when output gap and/or unemployment gap are measured with errors, we simulate the case where the central bank adjusts interest rate responding to the output gap or unemployment gap which are measured with errors. We find that the rule responding to unemployment growth is more welfare improving than other rules. It is because unemployment growth contains information on not only output gap, but also price inflation and wage inflation which are components of welfare loss function. Therefore, responding to unemployment growth mitigates inefficiencies from sticky prices and wages at the same time. This result holds with and without uncertainty in output gap and unemployment gap. While, in case of certainty, the rule responding to output gap is more welfare improving than the rule responding to output growth, the result is reversed in case of uncertainty because the rule responding to uncertain output gap measure misleadingly increases fluctuations of other variables. These results imply that, when central banks practice monetary policy, unemployment can be used as a useful feedback variable together with inflation and output variables.
김인수(Insu Kim),성명철(Myungchul Sung),김대진(Daijin Kim) 한국정보과학회 2014 정보과학회논문지 : 소프트웨어 및 응용 Vol.41 No.6
최근 모바일 시장이 증대하면서 회전, 크기, 어파인 변환에 대해 강인하면서 동시에 고속 처리가 가능한 기술자에 대한 요구가 증가하고 있다. 본 논문에서는 2차원 영상에서 물체 인식 및 포즈 추정을 위한 영상 표현 기술인 계층적 구조 패턴에 기반한 새로운 이진 기술자(Binary descriptor)를 제안한다. 최근 제안된 이진 기술자 FREAK, BRISK 등의 연구는 기존의 SIFT-like한 기술자의 인식 성능을 유지하면서 속도를 매우 빠르게 개선하였다. 본 논문에서는 기존 연구의 객체 인식의 프레임워크를 기반으로 하는 계층적 구조 패턴 기반의 이진 기술자 생성 방법 및 변화에 강인한 주 방향을 추정하는 방법을 제안한다. 본 논문에서 제안하는 기술자의 성능을 평가하기 위하여 물체의 조명, 크기, 회전, 시점 변환이 포함된 물체 인식 DB(KAIST-DB)를 실험에 사용한다. 실험 결과 제안하는 기술자는 실시간 처리가 가능하면서 물체 인식 성능에 대해 기존 기술들 보다 더 높고 안정된 인식률을 보였다. Due to the recent growth of mobile market, the need for descriptors that are fast and yet robust to rotation, scale and affine transformations is increasing. In this paper we propose a new binary descriptor based on layered structure patterns for object recognition and pose estimation. Recently proposed binary descriptors such as FREAK and BRISK shows similar performance as the SIFT-like descriptors and yet has greatly enhanced the processing speed. In this paper, we propose a new binary descriptor based on layered structure patterns that maintains the existing framework, and also a method to estimate the dominant orientation that is robust to variations. The proposed descriptors were tested on a database(KAIST-DB) that includes illumination, scale, rotation and affine variation. The results showed that it works in real time with better and more stable performance than recently proposed binary descriptors.
김인수(Insu Kim),이복주(Bogju Lee) 한국정보과학회 2005 한국정보과학회 학술발표논문집 Vol.32 No.1
정보 추출은 텍스트로 되어 있는 비 정형화된 데이터로부터 정형화된 정보를 추출하는 분야이다. 기존의 정보 추출이 구문 중심의 방법인데 비해 본 논문에서는 시맨틱 웹과 온톨로지를 이용한 의미 기반의 정보 추출을 시도한다. 또한 본 논문에서는 기존의 정보 추출 모델을 분류해 보고 반자동 정보 추출이라는 새로운 모델을 제시한다. 이 모델에 기반하여 개인 정보를 자동으로 정형화 시켜주는 정보 추출 도구를 개발하고 이를 소개한다.