• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.321-331
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• 2015

The K-means clustering algorithm is a popular and widely used method for clustering. For covariance matrices, we consider a geodesic clustering algorithm based on the K-means clustering framework in consideration of symmetric positive definite matrices as a Riemannian (non-Euclidean) manifold. This paper considers a geodesic clustering algorithm for data consisting of symmetric positive definite (SPD) matrices, utilizing the Riemannian geometric structure for SPD matrices and the idea of a K-means clustering algorithm. A K-means clustering algorithm is divided into two main steps for which we need a dissimilarity measure between two matrix data points and a way of computing centroids for observations in clusters. In order to use the Riemannian structure, we adopt the geodesic distance and the intrinsic mean for symmetric positive definite matrices. We demonstrate our proposed method through simulations as well as application to real financial data.

• Korean Journal of Applied Biomechanics
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• v.32 no.3
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• pp.87-93
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• 2022

Objective: The purpose of this research was to investigate the age-related changes in whole-body motor variability during sit-to-stand (STS) task. It has been reported that children perform motor tasks less accurately with greater variability as compared to adults. However, it is still unknown how they utilize the abundant degrees of freedom and accomplish voluntary actions. Uncontrolled manifold (UCM) analysis has been used to partition motor variabilities into two independent variability components, task-relevant variability (V_ORT) and task-irrelevant variability (V_UCM). We investigated what differences exist between children and adults with respect to these two motor variability components in relation to motor development stages. Method: Ten 6-year-old children (height: 116.2 ± 4.3 cm, weight: 23.1 ± 3.9 kg, motor development assessment percentile score: 77.5 ± 18.6%), ten 10-year-old children (height: 138.7 ± 7.2 cm, weight: 35.8 ± 10.3 kg, motor development assessment percentile score: 73.9 ± 12.7%), and ten young adults (age: 23 ± 1.6 year-old, height: 164.3 ± 11.4 cm, weight: 60.8 ± 12.0 kg) participated in this study. Each participant performed STS ten times, and a motion capture system was used to capture the whole-body kinematics. Each segment centers of mass and the whole-body center of mass were calculated, and UCM analysis was used to quantify motor variabilities, V_ORT and V_UCM. One-way ANOVA was used for statistical analysis. Results: We found that children produced more motor variabilities in V_ORT and V_UCM in all three dimensions, anterior-posterior, medial-lateral, and vertical. As age increased, both, V_ORT and V_UCM significantly decreased (p<.05). Conclusion: The greater V_ORT found in children compared to adults indicates that the repeatability over repetitions improves through development, while the greater V_UCM found in children suggests that children better utilize the abundant degrees of freedom during STS compared to adults.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.6
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• pp.719-731
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• 2003

In order to maintain and manage ambient air quality, it is necessary to identify sources and to apportion its sources for ambient particulate matters. The receptor methods were one of the statistical methods to achieve reasonable air pollution strategies. Also, receptor methods, a field of chemometrics, is based on manifold applied statistics and is a statistical methodology that analyzes the physicochemical properties of gaseous and particulate pollutant on various atmospheric receptors, identifies the sources of air pollutants, and quantifies the apportionment of the sources to the receptors. The objective of this study was 1) after obtaining results from the PMF modeling, the existing sources of air at the study area were qualitatively identified and the contributions of each source were quantitatively estimated as well. 2) finally efficient air pollution management and control strategies of each source were suggested. The PMF model was intensively applied to estimate the quantitative contribution of air pollution sources based on the chemical information (128 samples and 25 chemical species). Through a case study of the PMF modeling for the PM-10 aerosols, the total of 11 factors were determined. The multiple linear regression analysis between the observed PM-10 mass concentration and the estimated G matrix had been performed following the FPEAK test. Finally the regression analysis provided quantitative source contributions (scaled G matrix) and source profiles (scaled F matrix). The results of the PMF modeling showed that the sources were apportioned by secondary aerosol related source 28.8 ％, soil related source 16.8％, waste incineration source 11.5%, field burning source 11.0%, fossil fuel combustion source 10%, industry related source 8.3％, motor vehicle source 7.9%, oil/coal combustion source 4.4％, non-ferrous metal source 0.3％. and aged sea- salt source 0.2％, respectively.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.167-173
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• 2023

This paper investigates several methods of visualizing high-dimensional data in a low-dimensional space. At first, principal component analysis and multidimensional scaling are briefly introduced as linear approaches, and then kernel principal component analysis, self-organizing map, locally linear embedding, Isomap, Laplacian Eigenmaps, and local multidimensional scaling are introduced as nonlinear approaches. In particular, t-SNE, which is widely used but relatively unfamiliar in the field of statistics, is described in more detail. We also present a simple example for several methods, including t-SNE. Finally, we provide a review of several recent studies pointing out the limitations of t-SNE and discuss the future research problems presented.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.415-424
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• 2009

As one of the unsupervised learning neural network methods, self-organizing maps(SOM) are applied to various fields. It reduces the dimension of multidimensional data by representing observations on the low dimensional manifold. On the other hand, the minimal spanning tree(MST) of a graph that achieves the most economic subset of edges connecting all components by a single open loop. In this study, we apply the MST technique to SOM with subnodes. We propose SOM's with embedded MST and a distance measure for optimum choice of the size and shape of the map. We demonstrate the method with Fisher's Iris data and a real gene expression data. Simulated data sets are also analyzed to check the validity of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1633-1649
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• 2017

In remote sensing image processing, the traditional fusion algorithm is based on the Intensity-Hue-Saturation (IHS) transformation. This method does not take into account the texture or spectrum information, spatial resolution and statistical information of the photos adequately, which leads to spectrum distortion of the image. Although traditional solutions in such application combine manifold methods, the fusion procedure is rather complicated and not suitable for practical operation. In this paper, an improved IHS transformation fusion algorithm based on the local variance weighting scheme is proposed for remote sensing images. In our proposal, firstly, the local variance of the SPOT (which comes from French "Systeme Probatoire d'Observation dela Tarre" and means "earth observing system") image is calculated by using different sliding windows. The optimal window size is then selected with the images being normalized with the optimal window local variance. Secondly, the power exponent is chosen as the mapping function, and the local variance is used to obtain the weight of the I component and match SPOT images. Then we obtain the I' component with the weight, the I component and the matched SPOT images. Finally, the final fusion image is obtained by the inverse Intensity-Hue-Saturation transformation of the I', H and S components. The proposed algorithm has been tested and compared with some other image fusion methods well known in the literature. Simulation result indicates that the proposed algorithm could obtain a superior fused image based on quantitative fusion evaluation indices.

• The Korean Journal of Elementary Counseling
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• v.5 no.1
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• pp.205-226
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• 2006

The purpose of this study was to find out the relations between 6th graders' negative cognitive process and anger experience and aggressiveness. To achieve the goal, it conducted a test to examine children's negative cognitive process, anger experience, aggressiveness targeting 100 children of 6th grade in C elementary school, Gyeonggj province. Then it conducted SPSS 12.0 statistical program to get the results of correlation analysis and regression analysis. The outcomes were as follows. First, there was a meaningfully positive relation between a negative cognitive process and anger experience. In other words, children having more negative cognitive process seemed to experience the feelings of anger more often, this presented the important role of cognition while getting into a temper Second, it reported a positive relation between anger experience and aggressiveness. Children who have experienced anger more often showed more violent behaviors, especially there were more significant positive relations between trait-anger and aggressiveness compared to state-anger and aggressiveness. This could explain some possibilities that children with high level of trait-anger might outrage more often than others by recognizing the situations as anger stimulants. Third, when conducting a regression analysis, a negative cognitive process made an effect on anger experience which affected aggressiveness. However, it did not show a negative cognitive process making a direct effect on aggressiveness. This is considered that children could experience an anger while evaluating an event or object in a negative way based on individual belief, and emotional linguistic behavioral aggressiveness would be formalized as they express the sparked fury either internally or externally. In conclusion, this study proved that there were close relations between children's negative cognitive process and anger experience and aggressiveness. A negative cognitive process affects anger experience, and anger experience affects aggressiveness afterwards. A negative cognitive process affects aggressiveness through anger experience indirectly, and especially trait-anger among anger experience is the main factor to influence on aggressiveness. With consideration of these results, it is believed that mediation is important key to moderate the negative cognition and trait-anger in order to diminish children's aggressive behaviors. This study has a meaning to provide searching for manifold mediating methods between negative cognition and trait anger, with a fundamental resource.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.127-139
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• 2023

Compensation and pay dispersion has been rigorously scrutinized to investigate their impacts on productivity and organizational performance. However, it is difficult to find a systematic study on the systematic dynamics of compensation and pay dispersion effects specifically in the context of Korean venture companies. Venture companies should manage their organizational resources efficiently to maximize their organizational performance through pay structure by efficiently managing the inherent resources. However, we acknowledge that empirical studies on how compensation and pay dispersion affect organizational productivity and performance are rare to find in the Korean context. To overcome this supplement limitation, this study hypothesized that (1) pay and members' productivity are positively related, (2) pay dispersion and organizational productivity have U shaped relationship, and (3) organizational productivity mediates the positive relationship between compensation and organizational performance. Venture companies and professional sports teams share manifold common characteristics such as size, financial circumstances, and operational objectives. We collect 9 seasons (2013~2014 - 2021~2022) of 10 teams' data of Korean Basketball League teams to test our hypotheses. Methodologically, the assessment of our analysis is rendered with PROCESS macro model 58. The statistical results showed that all hypotheses are statistically supported. This study explains how compensation and pay dispersion affect organizational productivity and performance of venture companies in Korea.