• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Journal of Korean Association for Spatial Structures
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• v.12 no.1
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• pp.109-119
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• 2012

For membrane structure, there are three main steps in design and construction, which are form finding, statistical load analysis, and cutting patterning. Unlike the first two stages, the step of cutting pattern involves the translation of a double-curved surface in 3D space into a 2D plane with minimal error. For economic reasons, the seam lines of generated cutting patterns rely greatly on the geodesic line. Generally, as searching regions of the seam line are plane elements in the step of shape analysis, the seam line is not a smooth curve, but an irregularly divided straight line. So, it is how we make an irregularly divided straight line a smooth curve that defines the quality of the pattern. Accordingly, in this paper, we analyzed interpolation schemes using spline, and apply these methods to cutting pattern generation on the curved surface. To generate the pattern, three types of spline functions were used, i.e., cubic spline function, B-spline, and least-square spline approximation, and simple model and the catenary-shaped membrane was adopted to examine the result of generation. The result of comparing the approximation curves by the number of elements and the number of extracted nodes of simple model revealed that the seam line for less number of extracted nodes with large number of elements were more efficient, and the least-square spline approximation provided smoother seam line than other methods.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.747-754
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• 2021

Purpose: Seismic safety evaluation of a curved bridge must be performed since the curved bridges exhibit the complex behavior rather than the straight bridges, due to geometrical characteristics. In order to conduct the probabilistic seismic assessment of the curved bridge, Seismic fragility evaluation was performed using the uncertainty of the steel material properties of a curved bridge girde, in this study. Method: The finite element (FE) model using ABAQUS platform of the curved bridge girder was constructed, and the statistical parameters of steel materials presented in previous studies were used. 100 steel material models were sampled using the Latin Hypercube Sampling method. As an input ground motion in this study, seismic fragility evaluation was performed by the normalized scale of the Gyeongju earthquake to 0.2g, 0.5g, 0.8g, 1.2g, and 1.5g. Result: As a result of the seismic fragility evaluation of the curved girder, it was found that there was no failure up to 0.03g corresponding to the limit state of allowable stress design, but the failure was started from 0.11g associated with using limit state design. Conclusion: In this study, seismic fragility evaluation was performed considering steel materials uncertainties. Further it must be considered the seismic fragility of the curved bridge using both the uncertainties of input motions and material properties.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.1
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• pp.33-47
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• 2022

In this study, distribution of submarine sand ridges in the coastal waters of Korea was surveyed using multibeam echo sounder data, and the topographic characteristics of each region were identified. For this purpose, the DEM (Digital Elevation Model) data was generated using depth data obtained from the Yellow Sea and the South Sea by Korea Hydrographic and Oceanographic Agency, and then applied the TPI (Topographic Position Index) technique to precisely extract the boundary of the sand ridges. As a result, a total of 200 sand ridges distributed in the coastal waters were identified, and the characteristics of each region of the sedimentary sediments were analyzed by performing statistical analysis on the scale (width, length, perimeter, area, height) and shape (width/length ratio, height/width ratio, linear·branch type, exposure·non-exposure type). The results of this study are expected to be used not only for coastal navigational safety, but also for marine naming support, marine aggregate resource identification, and fisheries resource management.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Journal of Korean Home Economics Education Association
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• v.4 no.1
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• pp.87-95
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• 1992

The purpose of this study is to suggest how we can get over the difficulties of practical drill under experimentation concerning the units of making clothes in the curriculum of home economics. The import of this study was based on the results of the preceding studies the field of the making Korean clothes, from the standpoint of the teaching tools and teaching materials by the use of VTR, is one of the most insufficient. On the one hand, the teaching procedure here a VTR, running 34 minutes or so, was made up with the process of making Korean men’s slacks, and was led by the researcher’s own. The contents of the lesson are as follows： the shape of Korean clothes, the name of each part, the process of drawing, cutting and sewing, and the items of evaluation and arrangement. On the other hand, the two comparative groups were made to compare one with the other： One group was taught by help of VTR media, and the other by the model performance and explanation of the instructor’s own. All of the statistical data were analyzed in terms of SPSS/PC, and t-verification was made, to make difference between the two, after standard deviation was calculated according to the classified domains. The consequences of the test research are shown as below： 1. The difference of understanding was obviously made in considering that the group made a better score than the comparative one in understanding to process of making Korean clothes. 2. The difference of skill was highly made in considering that the group made a better score than the comparative one in the practical drill of making Korean clothes. 3. The difference of interests was evidentally made in considering that the group made a better score than the comparative one in the stage of making Koran clothes. Such means that the motivation and attitude of the learners was made stimulate by the Audio-Visual material than by the traditional cramming method. 4. The difference of frequency was fairly made in considering that the experimeatal group made a better score than the comparative one in the frequency of individual teaching. 5. The difference of the efficiency of time-consumption was clearly made in considering that the experimental group made a better score than the comparative one. As the results of the research above, the medium of VTR proved to more effective to the achievement of schoolwork and the strategies of teaching. Therefore, more use of VTR media will help the instructors with the difficulties of practical drill in the whole process of making Korean clothes； Widely use of VTR media in teaching will be surely more fruitfull to the unit of making Korean clothes than teaching by explanation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.3
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• pp.258-264
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• 2011

A MCS technique is represented to stochastically analyze the uncertainties of wave forces exerted on the upright sections of composite breakwaters. A stochastical models for horizontal and uplift wave forces can be straightforwardly formulated as a function of the probabilistic characteristics of maximum wave height. Under the assumption of wave forces followed by extreme distribution, the behaviors of relative wave forces to Goda's wave forces are studied by the MCS technique. Double-truncated normal distribution is applied to take the effects of uncertainties of scale and shape parameters of extreme distribution into account properly. Averages and variances of relative wave forces are quantitatively calculated with respect to the exceedance probabilities of maximum design wave height. It is found that the averages of relative wave forces may be decreased consistently with the increases of the exceedance probabilities. In particular, the averages on uplift wave force are evaluated slightly larger than those on horizontal wave force, but the variations of coefficient of the former are adversely smaller than those of the latter. It means that the uncertainties of uplift wave forces are smaller than those of horizontal wave forces in the same condition of the exceedance probabilities. Therefore, the present results could be useful to the reliability based-design method that require the statistical properties about the uncertainties of wave forces.

• Bulletin of the Korean Chemical Society
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• v.7 no.5
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• pp.367-371
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• 1986

Dynamic and equilibrium properties of n-alkane chains immersed in solvent molecules have been investigated by a molecular dynamics method. The n-alkane chain is assumed to be a chain of elements (CH$_2$) interconnected by bonds having a fixed bond length and bond angle, but each bond of the chain is allowed to execute hindered internal rotation. We studied the effect of the number of the chain elements (N$_c$ = 10, 15 and 20) on the equilibrium properties of the system, e.g., the pair correlation functions between a chain element and solvent molecules, g$_{cs}$(r), and between the chain elements, g$_{cc}$(r), and the configurational properties such as the mean-square end-to-end distance < R$^2$ >, the mean-square radius of gyration < S$^2$ >, and the eigenvalues of the moment-of-inertia tensor < S$_i^2$ > / < S$^2$ > (i = 1, 2 and 3). We also studied the dynamic properties of the system, e.g., the autocorrelation function C(A;t) where A = R$^2$(t), = S$^2$(t), or = ${\vec{V}}(t)({\vec{V}}$ = velocity of the center of mass), and the diffusion coefficient D. The g$_{cs}$(r)'s are almost equal irrespective of the change of Nc while g$_{cc}$(r) becomes larger as N$_c$ increases; The MD computed configurational properties < R$^2$2 > and < S$^2$ > were found to be a little different from the values calculated from the statistical equations of < R$^2$ > and < S$^2$ >, it may be due to the fact that our model for the MD simulations includes a long-range volume effect. From the < S$_i^2$ > / < S$^2$ >, it is found that the chain molecule has a nearly spherical shape irrespective of the variation of N$_c$. For the dynamic properties we found that the C(R$^2$;t) and C(S$^2$;t) of lower N$_c$ decay faster than those of higher N$_c$, while the C($\vec V$;t) of the center of mass in the chain is weakly dependent on the N$_c$. The center of mass diffusion coefficient D$_c$ decreases as N$_c$ increases while the end point diffusion coefficient D$_e$ is nearly equal irrespective of the change of N$_c$.

• Journal of the Mineralogical Society of Korea
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• v.22 no.4
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• pp.313-324
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• 2009

We explore the effect of particle shape and size on 3-dimensional (3D) network and pore structure of porous earth materials composed of glass beads and silica gel using NMR micro-imaging in order to gain better insights into relationship between structure and the corresponding hydrologic and seismological properties. The 3D micro-imaging data for the model porous networks show that the specific surface area, porosity, and permeability range from 2.5 to $9.6\;mm^2/mm^3$, from 0.21 to 0.38, and from 11.6 to 892.3 D (Darcy), respectively, which are typical values for unconsolidated sands. The relationships among specific surface area, porosity, and permeability of the porous media are relatively well explained with the Kozeny equation. Cube counting fractal dimension analysis shows that fractal dimension increases from ~2.5－2.6 to 3.0 with increasing specific surface area from 2.5 to $9.6\;mm^2/mm^3$, with the data also suggesting the effect of porosity. Specific surface area, porosity, permeability, and cube counting fractal dimension for the natural mongolian sandstone are $0.33\;mm^2/mm^3$, 0.017, 30.9 mD, and 1.59, respectively. The current results highlight that NMR micro-imaging, together with detailed statistical analyses can be useful to characterize 3D pore structures of various porous earth materials and be potentially effective in accounting for transport properties and seismic wave velocity and attenuation of diverse porous media in earth crust and interiors.