• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.505-511
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• 2007

In this paper, we examine the Markov chain $\{X_k,\;N_k;\;k=0,\;1,...$. We show that the marginal steady state distribution of Xk is discrete phase type. The implication of this result is that the queue length distribution of phase type for large number of examples where this Markov chain is applicable and shows a queueing application by matrix geometric methods.

• Journal of Magnetics
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• v.8 no.1
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• pp.7-12
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• 2003

The method for evaluation of the particle size distribution of fine particles from hysteresis loop measurements is Presented. The method is illustrated on the SiO$_2$-based Co nanoparticle systems. The influence of technological conditions of sample preparation onto particle size distribution is investigated.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.11-18
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• 1999

To estimate the mean and the variance of a lognormal distribution, Finney (1941) derived the uniformly minimun variance unbiased estimators(UMVUE) in the form of infinite series. However, the conditions ${\sigma}^{2}\;>\;n\;and\;{\sigma}^{2}\;<\;\frac{n}{4}$ for computing $E(\hat{\theta}_{AM})\;and\;E(\hat{\eta}^{2}_{AM})$ are necessary. In this paper, we give an alternative derivation of the UMVUE's.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.137-143
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• 1993

Generally there are three methods to derive an approximation formula: 1) approching standard normal distribution by appropriate changing variable 2) using standardization variable for expansion 3) deriving approximation formula by direct method. This paper present correction terms having the form of $C_{1/v^{n/2}}/{\;}+{\;}C_2{\;}(n=1,2)$ with respect to $x^2_{\alpha}(v)$ distribution (${\nu}{\;}{\leq}{\;}30$), which minimize the error by EDA method and least square method.

• International Journal of Contents
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• v.9 no.4
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• pp.67-71
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• 2013

This study examined the effects of biofeedback postural control training on the weight distribution rate and functional ability of subjects with stroke. A total of 30 stroke patients were enrolled in this study. Subjects were divided into a biofeedback postural training group (experimental group, n=15) and a dynamic balance training group (control group, n=15). Experimental subjects received biofeedback postural training and control subjects received dynamic balance training for 30 minutes per day, 5 times per week over a 6 week period. Weight distribution rate and functional ability were measured to identify the effect of the biofeedback postural training. Significant difference in weight distribution rate was observed in the experimental group, compared with the control group (p=0.05), and a significant difference in functional ability. The results of this study provide evidence in support of incorporating a biofeedback postural training for the improvement of weight distribution rate and functional ability of stroke patients.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.275-283
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• 1999

In order to estimate a parameter $(\alpha,\beta^r), r\epsilonN$, in a distribution belonging to a location-scale family we usually use best invariant estimator (BIE) and best unbiased estimator (BUE). But in some conditions Ryu (1996) showed that BIE is better than BUE. In this paper we calculate risks of BIE and BUE in a normal and an exponential distribution respectively and calculate a percentage risk improvement exponential distribution respectively and calculate a percentage risk improvement (PRI). We find the sample size n which make no significant differences between BIE and BUE in a normal distribution. And we show that BIE is always significantly better than BUE in an exponential distribution. Also simulation in a normal distribution is given to convince us of our result.

• Atmosphere
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• v.22 no.1
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• pp.87-96
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• 2012

Aerosol number concentration ($N_{CN}$), size distribution and cloud condensation nuclei (CCN) concentration ($N_{CCN}$) were measured during 16-21 August 2008 at Daegwallyeong (DG) located in the eastern rural region of the Korean Peninsula. In the very next week (22-29 August 2008) the same aerosol properties were measured at Yeongjong Island (YJ) in the Yellow Sea. $N_{CN}$ for all 3 size cuts (above 3, 6 and 10 nm) was significantly higher at DG than YJ, but $N_{CCN}$ was significantly lower at the former and resulted in the $N_{CCN}/N_{CN}$ ratio more than twice higher at YJ ($0.94{\pm}0.09$ vs. $0.35{\pm}0.15$ at 0.53% supersaturation). The geometric mean diameter at DG, $53{\pm}15nm$, was much smaller than that at YJ, $91{\pm}6nm$, due to the particle formation events that were likely to have occurred continuously at DG. For given mean diameter, aerosols were more likely to act as CCN at YG compared to those at DG.

• Korean Journal of Ecology and Environment
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• v.54 no.4
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• pp.291-302
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• 2021

The phytoplankton community in the estuarine system is affected by changes of physicochemical factors easily. The present study analyzed phytoplankton community distribution and similarity, in addition to exploring factors influencing variations in phytoplankton community structure in three lakes located in the Yeongsan River estuary from March 2014 to November 2017. We carried out non-multidimensional scaling (NMDS) and random forest analysis (RF) for comparing the pattern of phytoplankton distribution and the relationship between phytoplankton distribution and environmental variables. Similarity Percentage (SIMPER) and Analysis of Similarity (ANOSIM) were performed to figure out the similarity of phytoplankton community at each site of three lakes. From NMDS, Phytoplankton community distribution differed between Yeongsan and Gumho lakes, and the factors influencing the distribution of phytoplankton communities across the three lakes were water temperature, dissolved oxygen, total nitrogen (T-N), nitrate-N (NO₃-N), and conductivity. NO₃-N was a key factor influencing phytoplankton community structure in the three lakes based on RF. A total of 24 species were identified as indicator species in the three lakes studied, with the highest species numbers observed in Yeongsan Lake (13) and the lowest observed in Yeongam Lake (2). According to SIMPER and ANOSIM results, the phytoplankton community in Yeongsan and Yeongam lakes were similar, and they differed from those in Gumho Lake. In addition, the phytoplankton community structure varied across the study sites in the three lakes, indicating that water channels across the lakes a minor influence phytoplankton community distribution.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.67-74
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• 2000

This paper presents the analysis of partial discharge signals according to the particle states in GIS, for preventing the insulation failure and recognizing the particle states. In this paper, four states of particle (particle on electrode, particle on enclosure, particle on spacer and crossing particle) were simulated. And $\Phi$-Q-N distribution of partial discharge signals was analyzed and the statistical operator of the $\Phi$-Q distribution was analyzed. As a result, it was found that the states of particle were distinguished by analysis of the $\Phi$-Q-N distribution and the statistical operator of the $\Phi$-Q distribution.

• Journal of The Korean Society of Grassland and Forage Science
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• v.11 no.4
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• pp.215-221
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• 1991

This experiment was carried out to determine the effects of cutting frequency and nitrogen fertilization in the mixed pasture on root production and its depth distribution. The results are summarized as follows: 1. Root distribution studied on botanical composition was not significantly different by the upper 20cm level in all treatments. 2. Root yields were all high irrespectively of dominant species. However, Arrhenatherum elatius dominant pasture showed the lowest. Alopecurus pratensis dominant pasture showed the highest in root yield. 3. With the root yield, there was no significant difference in cutting frequency, but the moderate nitrogen level(N-2) showed the highest root yield among three N levels. 4. The depth distribution of root was 1m depth in all treatments.