• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.555-566
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• 2017

For multivariate datasets with large number of variables, classical dimensional reduction methods such as principal component analysis may not be effective for data visualization. The underlying reason is that the dimensionality of the space of variables is often larger than two or three, while the visualization to the human eye is most effective with two or three dimensions. This paper proposes a working procedure which first partitions the variables into several "latent" clusters, explores individual data subsets, and finally integrates findings. We use R pakacage "ClustOfVar" for partitioning variables around latent dimensions and the principal component biplot method to visualize within-cluster patterns. Additionally, we use the technique for embedding supplementary variables to figure out the relationships between within-cluster variables and outside variables.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.363-379
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• 2023

Purpose: The main objective of this research is to construct an AI-based Composite Supplementary Index (ACSI) model to achieve accurate predictions of the Composite Index of Business Indicators. By incorporating various economic indicators as independent variables, the ACSI model enables the prediction and analysis of both the leading index (CLI) and coincident index (CCI). Methods: This study proposes an AI-based Composite Supplementary Index (ACSI) model that leverages diverse economic indicators as independent variables to forecast leading and coincident economic indicators. To evaluate the model's performance, advanced machine learning techniques including MLP, RNN, LSTM, and GRU were employed. Furthermore, the study explores the potential of employing deep learning models to train the weights associated with the independent variables that constitute the composite supplementary index. Results: The experimental results demonstrate the superior accuracy of the proposed composite supple- mentary index model in predicting leading and coincident economic indicators. Consequently, this model proves to be highly effective in forecasting economic cycles. Conclusion: In conclusion, the developed AI-based Composite Supplementary Index (ACSI) model successfully predicts the Composite Index of Business Indicators. Apart from its utility in management, economics, and investment domains, this model serves as a valuable indicator supporting policy-making and decision-making processes related to the economy.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.51-60
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• 1995

Given an $n \times p$ data matrix, if we add the $p_s$ variables somewhat different nature than the p variables to this matrix, we have a new $n \times (p+p_s)$ data matrix. Because of these $p_s$ variables, the traditional principal component analysis can't provide its efficient results. In this study, to improve this problem we review the supplementary principal component analysis putting $p_s$ variables to supplementary variable. This technique is based on the algebraic and geometric aspects of the traditional principal component analysis. So we provide a type of statistical data analysis for the records of eight teams and fourteen fields of the 1982-1992 Korean Pro Baseball Data based on the supplementary principal component analysis and the traditional principal component analysis. And we compare the their results.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.107-114
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• 1990

A queueing system with compound Poisson arrival and server vacation is analyzed by including supplementary variables. We consider a vacation system in which the server leaves for a vacation as soon as the system empties. When he returns, if no customer is waiting for service, he waits until a group of customers arrive and then begins to serve. We obtain the system size distribution and the waiting time distribution. Additional performance measures will be also considered.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.3 no.1
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• pp.42-50
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• 1991

The purpose of this study is an augmentation of heat transfer in the case of upward rectangular impinging water jet system. The variables of this study are nozzle-to-heated surface distance, jet velocity and supplementary water height. Optimum heights of supplementary water which augment the heat transfer rate are S/B=2 for H/B=30 and S/B=I for H/B=40, 50. On the Y-direction of nozzle, there exhibits the secondary peak of heat transfer coefficient when supplementary water is not used, however using the supplementary water, it does not exhibits. In the case of using supplementary water, heat transfer coefficient increases not only in stagnation region but also in wall jet region.

• Journal of Biomedical Engineering Research
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• v.31 no.1
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• pp.27-32
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• 2010

Noninvasive detection of patients with probable Alzheimer's disease (AD) is of great importance for assisting a medical doctor's decision for early treatment of AD patients. In the present study, we have extracted quantitative electroencephalogram (qEEG) variables, which can be potentially used to diagnose AD, from resting eyes-closed continuous EEGs of 22 AD patients and 27 age-matched normal control (NC) subjects. We have extracted qEEG variables from mean phase coherence (MPC) and EEG coherence, evaluated for all possible combinations of electrode pairs. Preliminary trials to discriminate the two groups with the extracted qEEG variables demonstrated that the use of MPC as a supplementary or alternative measure for the EEG coherence may enhance the accuracy of noninvasive diagnosis of AD.

• Journal of Family Resource Management and Policy Review
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• v.4 no.1
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• pp.1-13
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• 2000

This study examined patterns and determinants of families’supplementary educational investment on children. By supplementary educational investment, it meant the amounts of money spent on children’s education other than regular formal schooling expenses. The data used were from the 「1996 Household Expenditure Survey」conducted by the National Statistical Office. The statistical methods employed were descriptive statistics, cluster analysis and logistic multiple regression analysis. Results of cluster analysis revealed five different patterns of family supplementary education expense with relatively even proportion of families allocated to each pattern. The five education expenditure patterns were arts education dominant; other education dominant; gymnastics·clerical·computer education dominant; college entrance exam preparation dominant; and private tutoring dominant. Results of logistic regression analysis showed that the possibility of being in a pattern affected by various family socioeconomic variables. Important factors affecting there patterns were children’s schooling stage, residence, and mother’s education.

• International Journal of Human Ecology
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• v.12 no.1
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• pp.1-14
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• 2011

This study examined the features of maternal involvement in Korean children's early education and their relation to contextual variables and three forms of parental cognition. For this study 333 Korean mothers with 5 to 7 year-old children completed questionnaires that covered aspects such as demographical characteristics, three forms of involvement in their children's education, and three forms of parental cognition. Descriptive analysis indicated that mothers who were more involved in monitoring homework paid more monthly activity fees for supplementary classes and engaged more in cognitively stimulating activities at home. Financial investment in supplementary classes for children was not associated with engagement in cognitively stimulating activities at home. Stepwise regression analysis found that mothers who were more involved in monitoring their young childrens homework expressed higher aspirations for their childrens future occupation. Korean mothers who paid more for their child's supplementary classes had higher family incomes. Korean mothers who engaged more often in cognitively stimulating activities at home expressed higher parental self-efficacy, had a higher educational level, had a younger child, and had an earlier birth order or only child.

• International Journal of Concrete Structures and Materials
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• v.18 no.3E
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• pp.151-159
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• 2006

A total of 32 pullout tests were performed for the multiple headed bars relatively deeply embedded in reinforced concrete column-like members. The objective was to determine the minimum embedment depth that was necessary to safely design exterior beam-column joints using headed bars. The variables for the experiment were embedment depth of headed bar, center-to-center distance between adjacent heads, and amount of supplementary reinforcement. Regular strength concrete and grade SD420 reinforcing steel were used. The results of the test the indicated that a headed bar embedment depth of $10d_b$ was not sufficient to have relatively closely installed headed bars develop the pullout strength corresponding to the yield strength. All the experimental variables, influenced the pullout strength. The pullout strength increased with increasing embedment depth and head-to-head distance. It also increased with increasing amount of supplementary reinforcement. For a group of closely-spaced headed bars installed in a beam-column joint, it is recommended to use column ties at least 0.6% by volume, 1% or greater amount of column main bars, and an embedment depth of $13d_b$ or greater simultaneously, to guarantee the pullout strength of individual headed bars over 125% of $f_y$ and ductile load-displacement behavior.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.14 no.2
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• pp.87-97
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• 1985

Experimental measurements of the heat flux to a upward impinging water jet on high heated test surface were obtained in the transition and film boiling regimes. Test variables were nozzle outlet velocity, subcooled water temperature and height of supplementary water. Boiling curve of this investigation is similar to a pool boiling curve, but it has one or two cap-shaped peaks in the transition regime. In the film boiling regime, the heat transfer rates are increased along with the increment of nozzle outlet velocity and subcooled temperature. There is optimum height of supplementary water for the augmentation of heat transfer Generalized correlations of boiling heat transfer are presented for maximum heat flux, minimum heat flux and $q_c$ at each supplementary height.