• Communications for Statistical Applications and Methods
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• 제13권1호
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• pp.113-123
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• 2006

Normal mixture model(NMM) frequently used to cluster genes on microarray gene expression data. In this paper some of component means of NMM are modelled by a linear regression model so that its design matrix presents the pattern between sample classes in microarray matrix. This modelling for the component means by given design matrices certainly has an advantage that we can lead the clusters that are previously designed. However, it suffers from 'overfitting' problem because in practice genes often are highly dimensional. This problem also arises when the NMM restricted by the linear model for component-means is fitted. To cope with this problem, in this paper, the use of the factor analyzer NMM restricted by linear model is proposed to cluster genes. Also several design matrices which are useful for clustering genes are provided.

• 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.

• 한국시스템다이내믹스연구
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• 제9권1호
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• pp.155-170
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• 2008

The purpose of this study was to develop a system dynamics model for management of glucose metabolism disorders that demonstrated dynamic relationships between insulin and plasma glucose levels over the time. The model was developed to 1) represent the physiology of glucose metabolism for an normal adult subject, 2) to draw causal loop diagram that demonstrate feedback systems of glucose regulation in normal condition and pathologic condition of the type 2 diabetes, 3) to develop an interactive computer simulation model for management of glucose metabolism disorders. The simulation results showed the plasma glucose level for normal persons varied from 75 to 140 which was consistent with clinical findings. As an example for patients we selected a case which varied from 110 to 310. Two types of interventions were chosen to review the model; meal control and insulin administration. The simulation results for those cases also matched well with clinical findings. The developed model can be used as an effective educational tool for patients to develop healthy lifestyle choices. The results also provide a blueprint for health providers to maintain normal blood glucose levels in diabetes patients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3668-3684
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• 2021

Video action recognition is widely used in video surveillance, behavior detection, human-computer interaction, medically assisted diagnosis and motion analysis. However, video action recognition can be disturbed by many factors, such as background, illumination and so on. Two-stream convolutional neural network uses the video spatial and temporal models to train separately, and performs fusion at the output end. The multi segment Two-Stream convolutional neural network model trains temporal and spatial information from the video to extract their feature and fuse them, then determine the category of video action. Google Xception model and the transfer learning is adopted in this paper, and the Xception model which trained on ImageNet is used as the initial weight. It greatly overcomes the problem of model underfitting caused by insufficient video behavior dataset, and it can effectively reduce the influence of various factors in the video. This way also greatly improves the accuracy and reduces the training time. What's more, to make up for the shortage of dataset, the kinetics400 dataset was used for pre-training, which greatly improved the accuracy of the model. In this applied research, through continuous efforts, the expected goal is basically achieved, and according to the study and research, the design of the original dual-flow model is improved.

• Water Engineering Research
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• 제6권2호
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• pp.49-61
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• 2005

This paper presents the numerical study to examine characteristics of fluid flow and solute transport in a rough fracture subject to effective normal stresses. The aperture distribution is generated by using the self-affine fractal model. In order to represent a nonlinear relationship between the supported normal stress and the fracture aperture, we combine a simple mechanical model with the local flow model. The solute transport is simulated using the random walk particle following algorithm. Results of numerical simulations show that the flow is significantly affected by the geometry of aperture distribution varying with the effective normal stress level while it is slightly affected by the fractal dimension that determines the degree of the fracture surface roughness. However, solute transport is influenced by the effective normal stress as well as the fracture surface roughness.

• 한국수산과학회지
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• 제40권4호
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• pp.201-209
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• 2007

Line transect sampling in a sighting survey is one of most widely used methods for assessing animal abundance. This study applied distance data, collected from three sighting surveys using line transects for finless porpoise that were conducted in 2004 and 2005 off the west coast of Korea, to four models (hazard-rate, uniform, half-normal and exponential) that can use a variety of detection functions, g (x). The hazard-rate model, a derived model for the detection function, should have a shoulder condition chosen using the AIC (Akaike Information Criterion), as the most suitable model. However, it did not describe a shoulder shape for the value of g(x) near the track tine and underestimated g (x), just as the exponential model did. The hazard-rate model showed a bias toward overestimating the densities of finless porpoises with a higher coefficient of variation (CV) than the other models did. The uniform model underestimated the densities of finless porpoise but had the lowest CV. The half-normal model described a detection function with a shape similar to that of the uniform model. The half-normal model was robust for finless porpoise data and should be able to avoid density underestimation. The estimated abundance of finless porpoise was 3,602 individuals (95% CI=1,251-10,371) inshore in 2005 and 33,045 individuals (95% CI=24,274-44,985) offshore in 2004.

• Journal of the Korean Data and Information Science Society
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• 제17권3호
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• pp.1009-1019
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• 2006

In this paper, we consider the simultaneous estimation problem for the normal means. We set up the model structure using the several different distributions of the errors for observing their effects of model perturbation for the error terms in obtaining the empirical Bayes and hierarchical Bayes estimators. We compare the performance of those estimators under model perturbation based on a simulation study.

• 소음진동
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• 제9권5호
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• pp.975-983
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• 1999

This paper describes the dynamic characteristics of the joint structures in case of using the simplified beam model in the F. E. analysis. The modeling errors, when replace the shell with the beam, are investigated through F. E. normal modes analysis. Normal mode analysis were performed to obtain the natural frequencies of the L and T shaped joints with various type of channels. The results were analyzed to access the effects of the models on the accuracy of F.E. analysis by identifying the geometric factors which cause the error. The geometric factors considered are joint angle, channel length, thickness and area ratio of the hollow section to the filled one. The joint stiffness evaluation technique is developed in this study using normal modes analysis with Lumped Mass. With this method, the progressively improved results of F. E. analysis are obtained using the simplified beam model. The static and normal modes analysis are performed with the joint stiffness values obtained by the Kazunori Shimonkakis' virtual stiffness method and the proposed method and these simplified modeling errors are compared.

• Kyungpook Mathematical Journal
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• 제57권3호
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• pp.457-471
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• 2017

A necessary and sufficient condition for the product AB of a selfadjoint operator A and a bounded selfadjoint operator B to be normal is given. Various properties of the factors of the unitary polar decompositions of A and B are obtained in the case when the product AB is normal. A block operator model for pairs (A, B) of selfadjoint operators such that B is bounded and AB is normal is established. The case when both operators A and B are bounded is discussed. In addition, the example due to Rehder is reexamined from this point of view.

• 응용통계연구
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• 제26권5호
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• pp.821-834
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• 2013

Law 등 (2004)은 군집분석에서 변수선택을 위해 정규분포기반 "두각 혼합모형(salient mixture model)"의 사용을 제안하였다. 본 논문에서는 이 모형의 적합 상의 문제점과 변수선택의 결함을 지적하고 그 대안을 제시한다. 모의자료와 실자료를 바탕으로 제안된 방법이 기존의 방법보다 유용함을 보였다.