• 한국자동차공학회논문집
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• 제25권3호
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• pp.317-325
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• 2017

The EDR(Event Data Recorder) is a part of the ACU(Airbag Control Unit) functions mounted on a vehicle. EDR data have pre-crash data and post-crash data. Pre-crash data are recorded within 5 sec from time zero(AE) with 0.5 sec resolution, and reveal vehicle speed, engine rotation speed, throttle opening, brake pedal operation, acceleration pedal position and steering angle, etc. Using this EDR data, the investigation of a traffic accident can become more objective and scientific. Crash tests of three vehicles equipped with EDR function had been performed successfully. Evaluation of EDR data reliability had also been performed using Vbox and PC-Crash's sequence table function. Based on the results, we could confirm EDR data's reliability and availability for Traffic Accident Analysis by the series of this process.

• 전기학회논문지P
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• 제54권2호
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• pp.94-100
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• 2005

Abnormal symptoms on operating conditions of power transformer are monitored by a preventive diagnostic system which prevents the sudden power failure in case of quick progress of abnormal situation. The preventive diagnostic system helps plan the proper maintenance method according to the transformer conditions via accumulated data. KEPCO has adopted the preventive diagnostic system at nine of 345kV substations since 1997. Application techniques of the diagnostic sensors were settled, but diagnostic algorithm and practical use of accumulated data are not yet established. To build up the diagnostic algorithm and effective use of the preventive diagnostic system, the reliability of the data which were accumulated in a server computer is very important. This paper describes the data analysis in the server in order to advance the reliability of the accumulated data of the preventive diagnostic system. The principles and data flows of the diagnostic sensors were analyzed, and the data discrepancy between sensors and server were calibrated.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2004년도 신뢰성해외전문가초청세미나
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• pp.55-66
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• 2004

Businesses collect lots of data. The data is not always converted into information or used in decision making. Need to critically evaluate the data collection process. Challenge: How to collect good data in a cost effective manner\ulcorner(omitted)

• 산업경영시스템학회지
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• 제36권4호
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• pp.100-108
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• 2013

In aerospace industry, MTBF (Mean Time Between Failure) and MFTBF (Mean Flight Time Between Failure) are generally used for reliability analysis. So far, especially to Korean military aircraft, MFTBF of avionic equipments is predicted by MIL-HDBK-217 and MIL-HDBK-338, however, the predicted MFTBF by military standard has a wide discrepancy to that of real-world operation, which leads to overstock and increase operation cost. This study analyzes operational data of avionic equipments. Operational MFTBF, which is calculated from operational data, is compared with predicted MFTBF calculated conventionally by military standard. In addition, failure rate trend is investigated to verify reliability growth in operational data, the investigation shows that failure rate curve from operational data has somewhat pattern with decreased failure rate and constant failure rate.

• International Journal of Advanced Culture Technology
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• 제5권2호
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• pp.82-89
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• 2017

The range of problems that can be handled by the activation of big data and the development of hardware has been rapidly expanded and machine learning such as deep learning has become a very versatile technology. In this paper, mnist data set is used as experimental data, and the Cross Entropy function is used as a loss model for evaluating the efficiency of machine learning, and the value of the loss function in the steepest descent method is We applied the GradientDescentOptimize algorithm to minimize and updated weight and bias via backpropagation. In this way we analyze optimal reliability value corresponding to the number of exercises and optimal reliability value without overfitting. And comparing the overfitting time according to the number of data changes based on the number of training times, when the training frequency was 1110 times, we obtained the result of 92%, which is the optimal reliability value without overfitting.

• 대한교통학회지
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• 제27권1호
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• pp.63-71
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• 2009

본 연구의 목적은 이용자 입장에서 정시성이 열악한 노선들을 파악하는 것이다. 이를 위해 서울시의 도심으로 향하는 간선노선을 대상으로 BMS자료를 이용하여 노선별 배차간격의 오차율과 운행시간의 오차율을 계산한 후, 자료 포락분석기법을 이용하여 두 지표를 통합한 노선별 정시성을 분석하였다. 그 결과를 통하여 노선들과 교통권역들의 정시성을 비교하고, 정시성이 열악한 노선들을 개선할 필요성과 이용자들에게 현실을 감안한 운행스케줄을 제시할 필요성이 있음을 제안하였다. 향후 연구로는 BMS와 교통카드 시계열 자료를 이용함으로써 각 노선의 다른 운행환경을 반영한 정시성 범위를 파악하여 노선별 정시성 평가틀을 개발하고, 정시성이 열악한 노선들에 대한 개선방안을 제시할 필요가 있음을 제안하였다.

• 대한인간공학회지
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• 제32권1호
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• pp.87-96
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• 2013

Objective: The aim of this study is to describe several issues which should be considered in the human reliability analysis of soft control operations in nuclear power plants. Background: The operational environment of advanced main control rooms is totally different from that of conventional control rooms. The soft control is one of the major distinguishable features of the advanced main control rooms. The soft control operations should be analyzed to estimate the effects on human reliability. Method: The literatures, about task analysis, simulation data analysis, and a human reliability analysis method for the soft control, were reviewed. From the review, important issues for the human reliability analysis of the soft control were raised. Results: The results of task and simulation data analysis showed that the soft control characteristics could have large effect on human reliability and they should be considered in the human reliability analysis of the soft control operations. Conclusion: The soft control may affect human error and performance of operators. The issues described in this paper should be considered in the human reliability method for the advanced main control rooms. Application: The results of the soft control operation analysis might help to design more efficient interface and education/training program for preventing human errors. The described issues might help to develop a human reliability analysis method for soft control operations.

• International Journal of Contents
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• 제17권3호
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• pp.74-83
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• 2021

A location-aware algorithm is proposed in this study to optimize the system performance of distributed systems for processing big data with low data reliability and application performance. Compared with previous algorithms, the location-aware data block placement algorithm uses data block placement and node data recovery strategies to improve data application performance and reliability. Simulation and actual cluster tests showed that the location-aware placement algorithm proposed in this study could greatly improve data reliability and shorten the application processing time of I/O interfaces in real-time.

• International Journal of Reliability and Applications
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• 제1권2호
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• pp.115-121
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• 2000

The trend change in aging properties, such as failure rate and mean residual life, of a life distribution is important to engineers and reliability analysts. In this paper we develop a test statistic for testing whether or not the failure rate changes its trend using censored data. The asymptotic normality of the test statistics is established. We discuss the efficiency values of loss due to censoring.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1998년도 봄 학술발표회논문집(II)
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• pp.447-454
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• 1998

The main object of the study is that axial force-moment relationships for high strength concrete structures using reliability theory(Linear statstical method, Monte Carlo Simulation) including probability conception. And mean stress factors and centroid factors proposed to high strength concrete structures using reliability theory(Linear statstical method, Monte Carlo Simulation). Finally, The established experimental data for axial force-moment relationships are compared to the analytical data(data for Linear statstical method and Monte Carlo Simulation) for axial force-moment relationships in this analytical method.