• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1151-1160
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• 2014

In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1143-1152
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• 2009

A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.29-37
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• 1995

In many metal forming processes, it is common to use stress rings for reducing elastic deformation and failures of forming dies. But, shrink fit of dies inner diameter of die insert, machining is reuqired after shrink fit processes. The reduction of inner diameter can be predicted by the analysis of elastic-plastic finite element method. The dimension of dies before shrink fit can be determined to minimize or remove machining after shrink fit processes by deformation analysis of die. The computation of contacting stresses along die surface was analyzied by rigid plasitic finite element method, and data were interpolated by the contact search algorithm. In this paper, we propose the analysis method of forging dies after shrink fit and forming to improve dimensional accuracy of final products.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.147-152
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• 2000

The ASF(Automatic Sheets Feeders) part of the printer has many bosses supporting gear-trains. Steel-pin bosses are substituted for plastic mold bosses because of advantages such as cost reduction, convenience of manufacturing and accuracy in dimension, but they have a weak point such as fatigue fracture due to low material strength, which causes a serious problem in the reliability of product. To prevent the fatigue fracture of bosses, we should exactly estimate the life to failure of the various shapes of bosses. We take the linear FEM analysis and the statistical method in this paper to figure out the life to failure of bosses. The maximum stress and life to failure of bosses can be easily estimated by this method. This paper specifies how to figure out the life to failure of bosses.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1081-1088
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• 2013

Hyperspectral cameras acquire reflectance values at many different wavelength bands. Dimensions tend to increase because spectral information is stored in each pixel. Several attempts have been made to reduce dimensional problems such as the feature selection using Adaboost and dimension reduction using the Simulated Annealing technique. We propose a novel material detection method that consists of four steps: feature band selection, feature extraction, SVM (Support Vector Machine) learning, and target and specific region detection. It is a combination of the band ratio method and Simulated Annealing algorithm based on detection rate. The experimental results validate the effectiveness of the proposed feature selection and band ratio method.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.411-425
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• 2021

In this paper, a vehicle recognition algorithm based on deep convolutional neural network and compression dictionary is proposed. Firstly, the network structure of fine vehicle recognition based on convolutional neural network is introduced. Then, a vehicle recognition system based on multi-scale pyramid convolutional neural network is constructed. The contribution of different networks to the recognition results is adjusted by the adaptive fusion method that adjusts the network according to the recognition accuracy of a single network. The proportion of output in the network output of the entire multiscale network. Then, the compressed dictionary learning and the data dimension reduction are carried out using the effective block structure method combined with very sparse random projection matrix, which solves the computational complexity caused by high-dimensional features and shortens the dictionary learning time. Finally, the sparse representation classification method is used to realize vehicle type recognition. The experimental results show that the detection effect of the proposed algorithm is stable in sunny, cloudy and rainy weather, and it has strong adaptability to typical application scenarios such as occlusion and blurring, with an average recognition rate of more than 95%.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.3
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• pp.280-285
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• 2015

We consider a linear transceiver design method for multi-user multiple-input multiple-output (MIMO) downlink channels where a base station (BS) equipped with a finitely large number of antennas. Although a matched-filter precoder is a capacity-achieving method in massive MIMO downlink systems, it cannot guarantee to achieve the multi-user MIMO capacity in a finitely large number of antennas due to inter-user interferences. In this paper, we propose a two-stage precoder design method that maximizes the sum-rate of cell-edge users when the BS equipped with a finitely large number of antennas. At the first stage, a matched-filter precoder is adopted to exploit both beamforming gain and the reduction of the dimension of effective channels. Then, we derive the second stage precoder that maximizes the sum-rate by minimizing the weighted mean square error (WMSE). From simulation and analysis, we verify the effectiveness of the proposed method.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.11a
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• pp.14-14
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• 2009

High frequency electromagnetic(EM) waves are increasingly being applied in industries because of saturationat lower frequency bands as a result of huge demand. However, electromagneticinterference (EMI) has become a serious problem, and as a result, highfrequency EM absorbers are now being extensively studied. Also, recentdevelopments in absorber technology have focused on producing absorbers thatare thin, flexible, and strong. Hence, one-dimension ferrous nano-materials area potential research field, because of their interesting electronic andmagnetic properties. Commercially, EM wave absorbing products are made ofcomposites, which blend the insulating polymer with magnetic fillers. Inparticular, the shape of the magnetic fillers, such flaky, acicular, or fibrousmagnetic metal particles, rather than spherical, is essential for synthesizingthin and lightweight EM wave absorbers with higher permeability. High aspectratio materials exhibit a higher permeability value and therefore betterabsorption of the EM wave, because of electromagnetic anisotropy. Nanowires areusually fabricated by drawing, template synthesis, phase separation, selfassembly, and electrospinning with a thermal treatment and reduction process.Producing nanowires by the electrospinning method involves a conventionalsol-gel process that is simple, unique, and cost-effective. In thispresentation, Magnetic nanowire and dielectric materials coated magneticnanowire with a high aspect ratio were successfully synthesized by theelectrospinning process with heat treatment and reduction. In addition toestimating the EM wave absorption ability of the synthesized magnetic anddielectric materials coated magnetic nanowire with a network analyzer, weinvestigated the possibility of using these nanowires as high-frequency EM waveabsorbers. Furthermore, a wide variety of topics will be discussed such as thetransparent conducting nanowire and semiconducting nanowire/tube with theelectrospinning process.

• Journal of the Korean Solar Energy Society
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• v.36 no.3
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• pp.9-16
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• 2016

This paper discusses a refined model for investigating the micro-mechanical behavior of beam-like structures, which are composed of various elastic moduli and complex geometries varying through the cross-section directions and are also periodically-repeated and heterogeneous along the axial direction. Following the previous work (Lee and Yu, 2011), the original three-dimensional static problem is first formulated in a unified and compact form using the concept of decomposition of the rotation tensor. Taking advantage of the smallness of the cross-sectional dimension-to-length parameter and the micro-to-macro heterogeneity, while also performing homogenization along the dimensional reduction simultaneously, the variational asymptotic method is rigorously used to construct a total energy function, which is asymptotically correct up to the second order. Furthermore, through the transformation procedure based on the pure kinematic relations and the linearized equilibrium equations, a generalized Timoshenko model is systematically established. For the purpose of dealing with realistic and complex geometries and constituent materials at the microscopic level, this present approach is incorporated into a commercial analysis package. A few examples available in literature are used to demonstrate the consistency and efficiency of this proposed model, especially for the structures, in which the effects of transverse shear deformations are significant.

• East Asian Economic Review
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• v.27 no.3
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• pp.243-269
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• 2023

The multidimensional poverty index is an indicator system established for defining and evaluating poverty, to understand poverty in dimensions beyond just monetary scarcity. Based on income, education, health, living standards, and social dimensions, this article measures and analyzes the level of multidimensional poverty in Xinjiang using the AlkireFoster method, with cross-sectional data obtained from a 2022 survey. Probit model is constructed for regression analysis, further considering the impact of education on enhancing feasible capabilities and alleviating multidimensional poverty at the post-poverty alleviation era. The data shows that many people still face significant challenges from the perspective of multidimensional poverty; the decomposition results of each dimension show that education contributes more to the multidimensional poverty; the regression analysis results show that the higher the education level, the lower the multidimensional poverty; heterogeneity analysis revealed that the inhibitory effect of education on multidimensional poverty is greater for females than males, and the poverty reduction effect of education mainly concentrates on middle-aged and older individuals. This article is meaningful for exploring strategies to alleviate multidimensional poverty in ethnic minority regions in frontier areas in the new era, accelerating regional economic development, and achieving shared prosperity.