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經皮電氣刺戟을 위한 强度,周波數,듀티비 效果에 관한 硏究
함광근,허 웅,이호재,민홍기 明知大學校 産業技術硏究所 1992 産業技術硏究所論文集 Vol.11 No.-
In this paper, we have searched for the optimal electro-stimulation condition which for the electrotactile matrix device. The required parameters of electro-stimulus condition for the experiments are waveforms, frequency stimulation intensity, duty ratio. As a result, when we gave a stimulation to finger's skin with monophasic, biphasic and differential phasic waveform, the most appropriate stimulation condition was 200 to 250[Hz] in frequency, 10 to 25[%] in duty ratio. A Burst type pulse was more sensitive than that of the continuous pulse.
柳濟福,咸炯範,洪基學 淸州大學校 産業經營硏究所 1988 産業經營硏究 Vol.11 No.1
Suppose that n items are put on test simultaneously and that the test is censored ( without or with replacement ) at r ( ≤n ). Then the failure times occur in order and it may be required on the basis of the first k ( k<r≤n ) failure times, X₁≤X₂≤ ... ≤X_(k), to predict the rth failure time. This paper deals with obtaining a prediction interval on X_(R) when failure time follows one parameter exponential distribution.
Two Stage Sampling on Successive Occasions in Superpopulation Elliptic Process
Ryu, Jea-Bok,Park, Jung-Skb,Ham, Hyung-Bum 청주대학교 경상대학 1987 經商論叢 Vol.28 No.-
To estimate the mean of the population with a relation between units, a repeated sample survey on successive occasions has been studied. In this paper, the theory of single stage sampling on successive occasions in two dimensional finite population is extended to two stage sampling and also the optimal estimator and it's PEV are computed by applying the stationary elliptic model to successive occasions sampling.
柳濟福,咸炯範 청주대학교 산업과학연구소 1987 産業科學硏究 Vol.5 No.-
Consider an ordered sample of size n X_(1)≤X_(2)≤…≤X_(n) from a Weibull distribution. Now we discuss the problem that a future observation X_(r) is preditced based on first k observations X_(1), X_(2), …, X_(k)(k<r≤n). It is shown how to find an interval estimate for a future observation Y_(r) when life distribution is an exponential distribution. By using the above result we predict an interval estimate for a future observation X _(γ) when life distribution is a Weibull.