• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.721-731
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• 2017

In this study, principal component analysis methods using Lasso penalty are introduced. There are two popular methods that apply Lasso penalty to principal component analysis. The first method is to find an optimal vector of linear combination as the regression coefficient vector of regressing for each principal component on the original data matrix with Lasso penalty (elastic net penalty in general). The second method is to find an optimal vector of linear combination by minimizing the residual matrix obtained from approximating the original matrix by the singular value decomposition with Lasso penalty. In this study, we have reviewed two methods of principal components using Lasso penalty in detail, and shown that these methods have an advantage especially in applying to data sets that have more variables than cases. Also, these methods are compared in an application to a real data set using R program. More specifically, these methods are applied to the crime data in Ahamad (1967), which has more variables than cases.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.254-262
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• 2003

In this study, acoustic emission (AE) signals due to surface cracking and moisture movement in the flat-sawn boards of oak (Quercus Variablilis) during drying under the ambient conditions were analyzed and classified using the principal component analysis. The AE signals corresponding to surface cracking showed higher in peak amplitude and peak frequency, and shorter in rise time than those corresponding to moisture movement. To reduce the multicollinearity among AE features and to extract the significant AE parameters, correlation analysis was performed. Over 99% of the variance of AE parameters could be accounted for by the first to the fourth principal components. The classification feasibility and success rate were investigated in terms of two statistical classifiers having six independent variables (AE parameters) and six principal components. As a result, the statistical classifier having AE parameters showed the success rate of 70.0%. The statistical classifier having principal components showed the success rate of 87.5% which was considerably than that of the statistical classifier having AE parameters.

• Geomechanics and Engineering
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• v.14 no.2
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• pp.195-202
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• 2018

Many laboratory experiments on crack propagation under uniaxial loading and biaxial loading have been conducted in the past using transparent materials such as resin, polymethyl methacrylate (PMMA), etc. However, propagation behaviors of three-dimensional (3D) cracks in rock or rock-like materials under tri-axial loading are often considerably different. In this study, a series of true tri-axial loading tests on the rock-like material with two semi-ellipse pre-existing cracks were performed in laboratory to investigate the acoustic emission (AE) characteristics and propagation characteristics of 3D crack groups influenced by intermediate principal stress. Compared with previous experiments under uniaxial loading and biaxial loading, the tests under true tri-axial loading showed that shear cracks, anti-wing cracks and secondary cracks were the main failure mechanisms, and the initiation and propagation of tensile cracks were limited. Shear cracks propagated in the direction parallel to pre-existing crack plane. With the increase of intermediate principal stress, the critical stress of crack initiation increased gradually, and secondary shear cracks may no longer coalesce in the rock bridge. Crack aperture decreased with the increase of intermediate principal stress, and the failure is dominated by shear fracturing. There are two stages of fracture development: stable propagation stage and unstable failure stage. The AE events occurred in a zone parallel to pre-existing crack plane, and the AE zone increased gradually with the increase of intermediate principal stress, eventually forming obvious shear rupture planes. This shows that shear cracks initiated and propagated in the pre-existing crack direction, forming a shear rupture plane inside the specimens. The paths of fracturing inside the specimens were observed using the Computerized Tomography (CT) scanning and reconstruction.

• Journal of Soil and Groundwater Environment
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• v.27 no.6
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• pp.22-36
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• 2022

Water resources in Jeju Island are dependent virtually entirely on groundwater. For groundwater resources, drought damage can cause environmental and economic losses because it progresses slowly and occurs for a long time in a large area. Therefore, this study quantitatively evaluated groundwater level fluctuations using principal component and cluster analyses for 42 monitoring wells in Jeju Island, and further identified the types of groundwater fluctuations caused by drought. As a result of principal component analysis for the monthly average groundwater level during 2005-2019 and the daily average groundwater level during the dry season, it was found that the first three principal components account for most of the variance 74.5-93.5% of the total data. In the cluster analysis using these three principal components, most of wells belong to Cluster 1, and seasonal characteristics have a significant impact on groundwater fluctuations. However, wells belonging to Cluster 2 with high factor loadings of components 2 and 3 affected by groundwater pumping, tide levels, and nearby surface water are mainly distributed on the west coast. Based on these results, it is expected that groundwater in the western area will be more vulnerable to saltwater intrusion and groundwater depletion caused by drought.

• Journal of Animal Science and Technology
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• v.44 no.6
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• pp.643-652
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• 2002

Data were consisted of the ten body measurements (withers height, rump height, body length, chest depth, chest width, rump width, rump length, thurls width, hipbone width and chest girth) of 642 steers (Korean cattle), which was entered in the National Beef Quality Contest hosted by the Korea Animal Improvement Association from 1997 to 2001. A principal components analysis was used to classify the body types of the steers, and estimate the correlations between carcass traits and principal components for the body measurements of the first, second, third and fourth period, respectively. The first principal component of body measurements at the first, second, third and fourth period accounted for 76.0%, 83.0%, 72.7% and 57.4% of the total variance, respectively. The sum of first, second and third principal component at each period accounted for 86.69%, 90.49%, 84.62% and 77.26% of the total variance, respectively. At each period, all the first principal component of the body measurements were positive and it generally showed large framed body shape. The size of body was influenced mostly by chest depth(0.328${\sim}$0.339) and rump length(0.325${\sim}$0.341). The second, third and fourth principal component at the each period were various. There were positive correlations between principal components index of each period and carcass traits such as carcass weight(0.539${\sim}$0.755), average daily gain(0.256${\sim}$0.564), backfat thickness(0.227${\sim}$0.280), and eye muscle area(0.187${\sim}$0.344). The correlation with yield grade index(－0.246${\sim}$－0.110), however, was negative. The correlation with marbling score(0.066${\sim}$0.099) was low or statistically insignificant. According to principal component indexes of the second, third, and fourth components, the correlations with the carcass traits were various. There were no large differences between the correlations of the single body measurement trait with the carcass traits and the correlations of the first principal component indexes with the carcass traits.

• Atmosphere
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• v.22 no.2
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• pp.149-161
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• 2012

Going by the research results of the past, of all the uncertainties resulting from the research on climate change, the uncertainty caused by the climate change scenario has the highest degree of uncertainty. Therefore, depending upon what kind of climate change scenario one adopts, the projection of the water resources in the future will differ significantly. As a matter of principle, it is highly recommended to utilize all the GCM scenarios offered by the IPCC. However, this could be considered to be an impractical alternative if a decision has to be made at an action officer's level. Hence, as an alternative, it is deemed necessary to select several scenarios so as to express the possible number of cases to the maximum extent possible. The objective standards in selecting the climate change scenarios have not been properly established and the scenarios have been selected, either at random or subject to the researcher's discretion. In this research, a new scenario selection process, in which it is possible to have the effect of having utilized all the possible scenarios, with using only a few principal scenarios and maintaining some of the uncertainties, has been suggested. In this research, the use of cluster analysis and the selection of a representative scenario in each cluster have efficiently reduced the number of climate change scenarios. In the cluster analysis method, the K-means clustering method, which takes advantage of the statistical features of scenarios has been employed; in the selection of a representative scenario in each cluster, the selection method was analyzed and reviewed and the PDF method was used to select the best scenarios with the closest simulation accuracy and the principal scenarios that is suggested by this research. In the selection of the best scenarios, it has been shown that the GCM scenario which demonstrated high level of simulation accuracy in the past need not necessarily demonstrate the similarly high level of simulation accuracy in the future and various GCM scenarios were selected for the principal scenarios. Secondly, the "Maximum entropy" which can quantify the uncertainties of the climate change scenario has been used to both quantify and compare the uncertainties associated with all the scenarios, best scenarios and the principal scenarios. Comparison has shown that the principal scenarios do maintain and are able to better explain the uncertainties of all the scenarios than the best scenarios. Therefore, through the scenario selection process, it has been proven that the principal scenarios have the effect of having utilized all the scenarios and retaining the uncertainties associated with the climate change to the maximum extent possible, while reducing the number of scenarios at the same time. Lastly, the climate change scenario most suitable for the climate on the Korean peninsula has been suggested. Through the scenario selection process, of all the scenarios found in the 4th IPCC report, principal climate change scenarios, which are suitable for the Korean peninsula and maintain most of the uncertainties, have been suggested. Therefore, it is assessed that the use of the scenario most suitable for the future projection of water resources on the Korean peninsula will be able to provide the projection of the water resources management that maintains more than 70~80% level of uncertainties of all the scenarios.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.37-44
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• 2006

Specular reflections provide the visual feedback that describes the material type of an object, its local shape, and lighting environment. In photorealistic rendering, there have been a number of research available to render specular reflections effectively based on a local reflection model. In traditional cel animations and cartoons, specular reflections plays important role in representing artistic intentions for an object and its related environment reflections, so the shapes of highlights are quite stylistic. In this paper, we present a method to render and control stylized specular reflections using projective textures based on principal curvature analysis. Specifying a texture as a pattern of a highlight and projecting the texture on the specular region of a given 3D model, we can obtain a stylized representation of specular reflections. For a given polygonal model, a view point, and a light source, we first find the maximum specular intensity point, and then locate the texture projector along the line parallel to the normal vector and passing through the point. The orientation of the projector is determined by the principal directions at the point. Finally, the size of the projection frustum is determined by the principal curvatures corresponding to the principal directions. The proposed method can control the position, orientation, and size of the specular reflection efficiently by translating the projector along the principal directions, rotating the projector about the normal vector, and scaling the principal curvatures, respectively. The method is be applicable to real-time applications such as cartoon style 3D games. We implement the method by Microsoft DirectX 9.0c SDK and programmable vertex/pixel shaders on Nvidia GeForce FX 7800 graphics subsystems. According to our experimental results, we can render and control the stylized specular reflections for a 3D model of several ten thousands of triangles in real-time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.241-242
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• 2012

• Structural Engineering and Mechanics
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• v.20 no.3
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• pp.381-387
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• 2005

• Kyungpook Mathematical Journal
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• v.58 no.2
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• pp.377-388
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• 2018

In this paper, we define new quaternionic associated curves called quaternionic principal-direction curves and quaternionic principal-donor curves. We give some properties and relationships between Frenet vectors and curvatures of these curves. For spatial quaternionic curves, we give characterizations for quaternionic helices and quaternionic slant helices by means of their associated curves.