http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Using R Software for Reliability Data Analysis
Shaffer, Leslie B.,Young, Timothy M.,Guess, Frank M.,Bensmail, Halima,Leon, Ramon V. The Korean Reliability Society 2008 International Journal of Reliability and Applicati Vol.9 No.1
In this paper, we discuss the plethora of uses for the software package R, and focus specifically on its helpful applications in reliability data analyses. Examples are presented; including the R coding protocol, R code, and plots for various statistical as well as reliability analyses. We explore Kaplan-Meier estimates and maximum likelihood estimation for distributions including the Weibull. Finally, we discuss future applications of R, and usages of quantile regression in reliability.
DESIGN AND VALIDATION OF ROBUST AND AUTONOMOUS CONTROL FOR NUCLEAR REACTORS
SHAFFER ROMAN A.,EDWARDS ROBERT M.,LEE KWANG Y. Korean Nuclear Society 2005 Nuclear Engineering and Technology Vol.37 No.2
A robust control design procedure for a nuclear reactor has been developed and experimentally validated on the Penn State TRIGA research reactor. The utilization of the robust controller as a component of an autonomous control system is also demonstrated. Two methods of specifying a low order (fourth-order) nominal-plant model for a robust control design were evaluated: 1) by approximation based on the 'physics' of the process and 2) by an optimal Hankel approximation of a higher order plant model. The uncertainty between the nominal plant models and the higher order plant model is supplied as a specification to the ,u-synthesis robust control design procedure. Two methods of quantifying uncertainty were evaluated: 1) a combination of additive and multiplicative uncertainty and 2) multiplicative uncertainty alone. The conclusions are that the optimal Hankel approximation and a combination of additive and multiplicative uncertainty are the best approach to design robust control for this application. The results from nonlinear simulation testing and the physical experiments are consistent and thus help to confirm the correctness of the robust control design procedures and conclusions.
The “Great Myanmar Poverty Debate”
Paul SHAFFER 연세대학교 빈곤문제국제개발연구원 2014 Journal of Poverty Alleviation and International D Vol.5 No.2
There is a “micro-macro paradox” in poverty measurement. In a number of countries, declines in income or consumption poverty found in nationally representative household survey data are at odds with people’s perceptions of worsening poverty or deprivation more broadly. The objective of this article is to offer a number of potential explanations for this paradox and to present the case of Myanmar where many of these same issues have recently played out. It is argued that there are plausible explanations which reconcile, in part, apparently conflicting positions in Myanmar’s “Great Poverty Debate.”