• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.411-421
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• 2016

Large frequency limiting distributions of two errors in realized covariance are investigated under noisy and non-synchronous high frequency sampling situations. The first distribution characterizes increased variance of the realized covariance due to noise for large frequency and the second distribution characterizes decreased variance of the realized covariance due to discretization for large frequency. The distribution of the combined error enables us to determine the sampling frequency which depends on a nuisance parameter. A consistent estimator of the nuisance parameter is proposed.

• Korean Journal of Hydrosciences
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• v.4
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• pp.51-63
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• 1993

This study is to verify the applicability of statistical models in predicting flood frequency at the stage gaging stations of which the flow is under natural condition in the Han River basin. The results of the study show that the statistical flood frequency models were proven to be fairly reasonable to apply in practice, and also were compared with sampling variance to calibrate the statistical efficiency of the estimators of the T year floods Q(T) by two different flood frequency models. As a result, it was showed that for return periods greater than about T = 10 years the annual exceedance series estimators of Q(T) has smaller sampling variance than the annual maximum series estimators. It was showed that for the range of return periods the partial duration series estimators of !(T) has smaller sampling variance than the annual maximum series estimate only if the POT model contains at least 2N(N : record length) items or more in order to estimate Q(T) more efficiently than the ANNMAX model.

• The Journal of Korean Physical Therapy
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• v.17 no.2
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• pp.88-106
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• 2005

AMF(amplitude modulated frequency) is defined as currents in the frequency range 1 to 100Hz. The aim of this study was to determine the effects of blood flow and skin temperature according to different stimulating frequency($1{\sim}30Hz,\;30{\sim}50Hz,\;50{\sim}100Hz$) of interferential currents. The results were as follow; 1. There were statistical significance on the blood flow with IFC 1, IFC 2, and IFC 3 group, and inter-groups(p<0.05). 2. There were statistical significance on the skin temperature with IFC 1 and IFC 3 group, and inter-groups(p<0.05). 3. IFC 1 was more statistical significance than IFC 3 group on blood flow(pP<0.05) 4. There was no statistical significance between IFC 1 and IFC 3 group on skin temperature(p>0.05).

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.581-585
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• 2010

This study introduced a Bayesian based frequency analysis in which the statistical trend seasonal analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel and GEV extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both trend and seasonal analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. In addition, full annual cycle of the design rainfall through seasonal model could be applied to annual control such as dam operation, flood control, irrigation water management, and so on. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.547-559
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• 2022

For a chi-squared test, which is a statistical method used to test the independence of a contingency table of two factors, the expected frequency of each cell must be greater than 5. The percentage of cells with an expected frequency below 5 must be less than 20% of all cells. However, there are many cases in which the regional expected frequency is below 5 in general small area studies. Even in large-scale surveys, it is difficult to forecast the expected frequency to be greater than 5 when there is small area estimation with subgroup analysis. Another statistical method to test independence is to use the Bayes factor, but since there is a high ratio of data dependency due to the nature of the Bayesian approach, the low expected frequency tends to decrease the precision of the test results. To overcome these limitations, we will borrow information from areas with similar characteristics and pool the data statistically to propose a pooled Bayes test of independence in target areas. Jo et al. (2021) suggested hierarchical Bayesian pooling models for small area estimation of categorical data, and we will introduce the pooled Bayes factors calculated by expanding their restricted pooling model. We applied the pooled Bayes factors using bone mineral density and body mass index data from the Third National Health and Nutrition Examination Survey conducted in the United States and compared them with chi-squared tests often used in tests of independence.

• Korean Journal of Pharmacognosy
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• v.3 no.2
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• pp.57-64
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• 1972

For the purpose of scientific evaluation of oriental medicine, statistical analyses of oriental medicine formularies have been attempted. Four hundred and sixty seven prescriptions in 'Bang-Yak-Hap-Pyon', the most popular formulary of oriental medicine in Korea, were analysed to obtain statistical characteristics on the prescription frequency and origin distribution of two hundred and ninety three herb drugs.

• Water for future
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• v.25 no.2
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• pp.89-97
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• 1992

This study is to verify the applicability of statistical models for predicting flood frequency at the stage gaging stations selected by considering whether the flow is natural condition in the Han River basin. From the result of verification, this statistical flood frequency models showed that is fairly reasonable to apply in practice, and also were compared with sampling variance to calibrate the statistical dfficiency of the estimate of the T year flood Q(T) by two different flood frequency models. As a result, it was showed that for return periods greater than about T=10 years the annual exceedence series estimate of Q(T) has smaller sampling variance than the annual maximum series estimate. It was showed that for the range of return periods the partial duration series estimate of Q(T) has smaller sampling varianed than the annual maximum series estimate only if the POT model contains at least 2N(N:record length)items or more in order to estimate Q(T) more efficiently than the ANNMAX model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1610-1629
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• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.977-994
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• 1999

Five equating methos for elective subjects of College Scholastic Ability Test were analyzed under a common-items nonequivalent groups design using a real data set of 110 thousand examinees. Five methods were (a)two-stage linear equating (b) two-stage equi-percentile equating (c) Tucker equating (d) Frequency estimation equating and (e)Braun-Holland equating. The results indicated that Frequency estimation equating fits well and two-stage linear equating produces most different equating results from the Frequency estimation equating.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.491-499
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• 2014

This paper studied the statistics such as the total number of syllables: the kinds of syllables: the frequency of syllables, the total number of eojeols, the kinds of eojeols(word phrases unique in Korean language), average length of eojeols and the frequency of eojeols in four different Korean textbooks for 7th-grade students. The results of the statistical survey are as follows: the number of syllables was 286,801; the kinds of Korean syllables were 1,350; the average frequency of syllables was 212.4; the number of eoieol was 109,393; the kinds of eoieol were 29,356; the average frequency of eojeol was 3.7; the average length of eojeols was 2.7 syllables, the longest one consist of 8 syllables.