• Geomechanics and Engineering
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• 제15권2호
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• pp.783-791
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• 2018

In consideration of the mesoscopic structure of soil-rock mixtures in which the rock aggregates are wrapped by soil at normal temperatures, a two-layer embedded model of single-inclusion composite material was built to calculate the shear modulus of soil-rock mixtures. At a freezing temperature, an interface ice interlayer was placed between the soil and rock interface in the mesoscopic structure of the soil-rock mixtures. Considering that, a three-layer embedded model of double-inclusion composite materials and a multi-step multiphase micromechanics model were then built to calculate the shear modulus of the frozen soil-rock mixtures. Given the effect of pore structure of soil-rock mixtures at normal temperatures, its shear modulus was also calculated by using of the three-layer embedded model. Experimental comparison showed that compared with the two-layer embedded model, the effect predicted by the three-layer embedded model of the soil-rock mixtures was better. The shear modulus of the soil-rock mixtures gradually increased with the increase in rock regardless of temperature, and the increment rate of the shear modulus increased rapidly particularly when the rock content ranged from 50% to 70%. The shear modulus of the frozen soil-rock mixtures was nearly 3.7 times higher than that of the soil-rock mixtures at a normal temperature.

• Communications for Statistical Applications and Methods
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• 제18권3호
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• pp.357-365
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• 2011

This paper investigates a penalized likelihood method for estimating the parameter of normal mixtures in multivariate settings with full covariance matrices. The proposed model estimates the number of components through the addition of a penalty term to the usual likelihood function and the construction of a penalized likelihood function. We prove the consistency of the estimator and present the simulation results on the multi-dimensional nor-mal mixtures up to the 8-dimension.

• Communications for Statistical Applications and Methods
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• 제18권6호
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• pp.837-849
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• 2011

본 연구에서는 자기조직화 신경망이 필요한 노드만을 가지고 최적화하여 정규혼합분포를 추정하는 모형을 제안한다. 제안한 모형은 SOMN모형과 벌점가능도를 사용한 모형을 결합한 것이다. SOMN의 장점은 수렴속도가 빠르고 표본의 크기가 작아도 발산하는 가능성이 낮다는 것이며, 벌점가능도를 사용한 모형은 필요없는 성분의 수를 줄일 수 있다는 것이다. 모의실험을 통하여 제안한 모형이 기대한 결과를 얻음을 확인하였다.

• 대한한의학회지
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• 제26권4호
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• pp.62-73
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• 2005

Objectives: This study was designed to identify the ergogenic effects of Red ginseng and Paeonia radix mixtures and optimal ratios. Materials and Methods: This study was conducted by administering treatments of Red ginseng and Paeonia radix mixtures to rats and by measuring the time to exhaustion by treadmill running. Results: The treatment of Red ginseng and Paeonia radix mixtures to the rats increased the time to exhaustion by treadmill running. The most potent inhibition of Red ginseng and Paeonia radix mixtures on the 5-HT synthesis and the TPH expression in the dorsal raphe was observed at the dose of 200 mg/kg and the optimal ratio of Red ginseng and Paeonia radix for the maximum efficacy was 50:50. Under normal conditions (not exercise), long-term treatment of Red ginseng and Paeonia radix mixtures did not affect the 5-HT synthesis and the TPH expression in the dorsal raphe, suggesting that Red ginseng and Paeonia radix mixtures does not alter serotonin level in the normal rats. The suppressive effect of Red ginseng and Paeonia radix mixtures on the 5-HT synthesis and the TPH expression during exercise is a possible ergogenic mechanism of these mixtures. Conclusions : Red ginseng and Paeonia radix mixtures reduce exercise-induced fatigue, and have the effect of acting as ergogenic aids on the time to exhaustion by treadmill exercise and on 5-HT synthesis and TPH expression.

• Geomechanics and Engineering
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• 제15권1호
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• pp.659-668
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• 2018

A series of direct shear tests were implemented on three different types of specimens (i.e., clean Perth sand, sand containing 10, 20 and 30% bentonite, sand containing 1, 3 and 5% slag, and sand containing 10, 20 and 30% bentonite with increasing percentages of added slag (1%, 3% and 5%). This paper focuses on the shear stress characteristics of clean sand and sand mixtures. The samples were tested under different three normal stresses (100, 150 and 200 kPa) and three curing periods of no curing time, 7 and 14 days. It was observed that the shear stresses of clean sand and mixtures were increased with increasing normal stresses. In addition, the use of slag has improved the shear strength of the sand-slag mixtures; the shear stresses rose from 128.642 kPa in the clean sand at normal stress of 200 kPa to 146.89 kPa, 154 kPa and 161.14 kPa when sand was mixed with 1%, 3% and 5% slag respectively and tested at the same normal stress. Internal friction angle increased from $32.74^{\circ}$ in the clean sand to $34.87^{\circ}$, $37.12^{\circ}$ and $39.4^{\circ}$ when sand was mixed with 1%, 3% and 5% slag respectively and tested at 100, 150, and 200 kPa normal stresses. The cohesion of sand-bentonite mixtures increased from 3.34 kPa in 10% bentonite to 22.9 kPa, 70.6 kPa when sand was mixed with 20% and 30% bentonite respectively. All the mixtures of clean sand, different bentonite and slag contents showed different behaviour; some mixtures exhibited shear stress more than clean sand whereas others showed less than clean sand. The internal friction angle increased, and cohesion decreased with increasing curing time.

• Communications for Statistical Applications and Methods
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• 제25권2호
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• pp.109-130
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• 2018

Several measures of multivariate skewness for scale mixtures of skew-normal distributions are derived. As a special case, those of multivariate skew-t distribution are considered in detail. Furthermore, the similarities, differences, and behavior of these measures are explored for cases of some specific members of the multivariate skew-normal and skew-t distributions using a simulation study. Since some measures are vectors, it is better to take all measures in the same scale when comparing them. In order to attain such a set of comparable indices, the sample version is considered for each of the skewness measures that are taken as test statistics for the hypothesis of t distribution against skew-t distribution. An application is reported for the data set consisting of 71 total glycerol and magnesium contents in Grignolino wine.

• International Journal of Concrete Structures and Materials
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• 제8권3호
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• pp.251-258
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• 2014

The use of sustainable technologies such as supplementary cementitious materials, and/or recycled post-consumer environmental wastes is widely used in concrete industry in the last decade. This paper presents the results of a laboratory investigation of normal concrete containing sustainable technologies. Twenty one mixtures (21) were prepared with different combinations of silica fume, fly ash, olive's seed ash, and corncob ash (CCA). Fresh and hardened concrete properties were measured, as expected the inclusion of the sustainable technologies affected both fresh and hardened concrete properties. Based on the results obtained in this study and the analyses conducted, the following observations were drawn: replacing the cement by olive's seed ash or CCA has a significant effect on fresh concrete workability. Olive's seed ash increased the slump by more than 200 % compared to the control mixtures. The compressive strength of mixtures containing olive's seed ash showed by 45 and 75 % decrease compared to the control mixtures. The 28 days compressive strength of mixtures produced by CCA of 10 % replacement decreased by 41 % compared to the control mixture.

• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.459-469
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• 2012

본 연구에서는 자기조직화 신경망이 필요한 노드만을 가지고 최적화하여 정규혼합분포를 추정하는 모형(Ahn과 Kim, 2011)을 Java언어에서 제공하는 스레드(thread)를 기반으로, 멀티코어 컴퓨팅환경에서 병렬처리방식으로 구현하여 순차처리방식에 비해 짧은 연산시간으로 정규혼합모형의 추정이 가능함을 보이려고 한다. 이를 위하여 Ahn과 Kim이 제안한 모형을 바탕으로 두 가지의 병렬처리 방법을 제안하고 그 성능을 평가하였다. 병렬처리 방법은 Java의 멀티스레드를 이용하여 구현되었으며, 모의실험을 통하여 제안한 모형이 순차처리방식과 비교하여 수렴속도가 빠름을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제16권1호
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• pp.143-155
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• 2009

Best subset selection procedure based on mutual information (MI) between a set of explanatory variables and a dependent class variable is suggested. Derivation of multivariate MI is based on normal mixtures. Several types of normal mixtures are proposed. Also a best subset selection algorithm is proposed. Four real data sets are employed to demonstrate the efficiency of the proposals.

• Communications for Statistical Applications and Methods
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• 제15권1호
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• pp.1-11
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• 2008

혼합정규분포로부터 얻은 자료의 크기가 크면 EM 알고리즘으로 모수를 추정하는 경우 추정에 많은 시간이 걸리며 이는 실시간 음성인식 분야등에서는 적용이 어렵게 되는 문제가 발생한다. 대용량 자료를 구간도수로 요약하여 구간도수 EM 알고리즘을 적용하면 표준 EM 알고리즘에 비해 실행속도가 획기적으로 개선되며 더욱이 구간도수 EM 알고리즘에서의 추정치의 효율성이 표준 EM 알고리즘에 근접함을 시뮬레이션 실험을 통하여 보였다.