• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1173-1181
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• 2012

In order to suggest the basic resources of mathematics education to the specialized high school, we investigate the attitude of students about mathematics education. Questionnaires survey was carried on 654 students and we use the statistical analysis such as chi-square test, gamma, generalized linear model, Anova, regression. Several result can be derived from the questionnaire analysis. There are differences between the general and specialized high school students in the interest, pre-learning ability etc. The specialized school students think the usefulness of mathematics more importantly, while the general school students think more closely related to their course.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.205-212
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• 2018

The purpose of this study is to examine an influence of university students' openness to diversity on career preparation behavior, unlearning, and the mediating effect of unlearning. The survey questionnaire was distributed to 258 university students and SPSS 22.O program was used for statistical analysis of the data. The results of this study are as follows: First, openness to diversity has a positive effect on career preparation behavior and unlearning. Second, unlearning also has a positive effect on career preparation behavior. Third, unlearning has a partial mediating effect between openness to diversity and career preparation behavior. These results show that the more students enhance their openness to diversity and unlearning, the more students develop their career preparation behavior.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.71-77
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• 2006

Support Vector Machine (SVM) which has roots in a statistical learning theory is a training algorithm based on structural risk minimization. Generally, SVM algorithm uses the kernel for determining a linearly non-separable boundary and classifying the data. But, classical kernels can not apply to effectively the hyperspectral image classification because it measures similarity using vector's dot-product or euclidian distance. So, This paper proposes the spectral similarity kernel to solve this problem. The spectral similariy kernel that calculate both vector's euclidian and angle distance is a local kernel, it can effectively consider a reflectance property of hyperspectral image. For validating our algorithm, SVM which used polynomial kernel, RBF kernel and proposed kernel was applied to land cover classification in Hyperion image. It appears that SVM classifier using spectral similarity kernel has the most outstanding result in qualitative and spatial estimation.

• The Korean Journal of Food And Nutrition
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• v.29 no.6
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• pp.1058-1069
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• 2016

This study is intended to research workers' health, diet and the demand of nutrition education service in Seoul and Gyeonggi-do province. We implemented the survey from September 2012 through August 2013, and analyzed the data from 589 workers' questionnaires out of 890. For the analysis of the compiled data, we utilized the SPSS version 18.0 statistical package program. The study showed that majority of the workers participated in the survey consisted of 447 male (75.9%) and 142 female (24.1%). BMI showed that these men were overweight ($24.5{\pm}2.72$) and women were normal weight ($22.2{\pm}2.70$). Participants often diagnosed with hypertension or hyperlipidemia. In terms of health status, 34.5% answered satisfactory, the most concerned illness was high blood pressure, and the bad eating habits were often associated with general overeating and excessive intake of salt. 65.5% of participants had a meal three times per day. 49.4% of male participants had a meal less than 15 minutes and 66.2% of female participants had a meal between 15 and 30 minutes. The average of workers who needed to nutrition education is 3.74+0.85. The most desired way of learning was through counseling (36.7%), with overweight and weight management identified as the most interested topics. A relatively high portion (80%) passed the nutrition knowledge assessment test. According to the survey the highest rate of full-time employment is 85.2% which showed in small work places (the number of people on meal plan was 100~300), however the lowest rate of full-time employment showed 70.0% in large workplaces (the number of people on meal plan was within 1,000).

• Bulletin of the Korean Chemical Society
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• v.35 no.12
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• pp.3637-3641
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• 2014

In this study, we analyzed the toxicity of mixtures of dimethylformamide (DMF) and methyl ethyl ketone (MEK) or DMF and toluene (TOL) and predicted their toxicity using quantitative structure-activity relationships (QSAR). A QSAR model for single substances and mixtures was analyzed using multiple linear regression (MLR) by taking into account the statistical parameters between the observed and predicted $EC_{50}$. After preprocessing, the best subsets of descriptors in the learning methods were determined using a 5-fold cross-validation method. Significant differences in physico-chemical properties such as boiling point (BP), specific gravity (SG), Reid vapor pressure (rVP), flash point (FP), low explosion limit (LEL), and octanol/water partition coefficient (Pow) were observed between the single substances and the mixtures. The $EC_{50}$ of the mixture of DMF and TOL was significantly lower than that of DMF. The mixture toxicity was directly related to the mixing ratio of TOL and MEK (MLR $EC_{50}$ equation = $1.76997-1.12249{\times}TOL+1.21045{\times}MEK$), as well as to SG, VP, and LEL (MLR equation $EC_{50}=15.44388-19.84549{\times}SG+0.05091{\times}VP+1.85846{\times}LEL$). These results show that QSAR-based models can be used to quantitatively predict the toxicity of mixtures used in manufacturing industries.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.671-681
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• 2019

Studies on predicting arrhythmia using machine learning have been actively conducted with increasing number of arrhythmia patients. Existing studies have predicted arrhythmia based on multivariate data of feature variables extracted from RR interval data at a specific time point. In this study, we consider that the pattern of the heart state changes with time can be important information for the arrhythmia prediction. Therefore, we investigate the usefulness of predicting the arrhythmia with multivariate time series data obtained by extracting and accumulating the multivariate vectors of the feature variables at various time points. When considering 1-nearest neighbor classification method and its ensemble for comparison, it is confirmed that the multivariate time series data based method can have better classification performance than the multivariate data based method if we select an appropriate time series distance function.

• Human Ecology Research
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• v.58 no.1
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• pp.1-12
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• 2020

This study examined if the effect of family functioning on preschoolers' school readiness can be mediated by mothers' affective parenting and preschoolers' self-regulation in the year before children enter elementary school. This study analyzed the 7^th year data of panel study of Korean children collected by the Korean Institute of Child Care and Education. Statistical analysis included 1,513 pairs of 6-year-old children and mothers. Descriptive statistics analysis, correlation analysis, structural equation modeling, and bootstrapping analysis were conducted using SPSS 22 and Amos 20. The primary findings were as follows. First, the sub-factors of preschoolers' school readiness composed of children's social and emotional development, approach to learning, cognitive development and general knowledge, and communication were positively correlated with family functioning, mothers' affective parenting, and preschoolers' self-regulation. Second, the result of structural equation modeling showed that the indirect paths from family functioning to preschoolers' school readiness through mothers' affective parenting and preschoolers' self-regulation were significant, while the direct path was insignificant. Third, bootstrapping analysis showed that mothers' affective parenting and preschoolers' self-regulation fully mediated the relationship between family functioning and preschoolers' self-regulation. The findings provide the grounds for families and parents with preschool aged children to implement effective support practices to maintain a functional family system that can promote preschoolers' school readiness.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.569-575
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• 2020

The serial arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet, and statistical features have been used, additional steps such as transformation and feature extraction are required. On the contrary, deep learning models directly use the raw data without any feature extraction processes. Therefore, the usage of time-domain data is preferred, but the performance is not satisfactory. To solve this problem, subsequent 1-D signals are transformed into 2-D data that can feed into a convolutional neural network (CNN). Experiments validated that CNN model outperforms deep neural network (DNN) by the classification accuracy of 8.6%. In addition, data augmentation is utilized, resulting in the accuracy improvement by 14%.

• The Korean Journal of Community Living Science
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• v.21 no.3
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• pp.411-425
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• 2010

The purpose of this study is to examine the middle aged social preparation for later life and to explore the effect of social activities and social relationships on social preparation for later life. This research is also focused on gender differences in social activities, social relationships and social preparation for later life. The survey data was gathered from 424 middle aged citizens who live in the Gwangju & Jeonnam area, using a structured questionnaire. The statistical methods used for data analysis were descriptive statistics, cross tables, t-test, correlations, and hierarchical regression with SPSS win 18.0 program. The major findings of this study are as follows: Most of the respondents perceive an importance of social activities and social relationships. Middle aged women enjoy leisure activities such as learning and religious activity more than men. Middle aged men engage in hobby activities more than women. And most of respondents perceive they are making an effort to keep a relationship with spouses, family & friends. The results show that there are no differences in social preparation for later life between gender groups, but the variables which have an effect in social preparation for later life are different between gender groups. Social activities and Social relationships play an important role in social preparation for later life of Middle aged men and women. At the same time, Social activities and Social relationships have more positive effect on the social preparation of women. Implications of the results are discussed.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.83-98
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• 2005

Exploring distributional patterns of multivariate data is very essential in understanding the characteristics of given data set, as well as in building plausible models for the data. For that purpose, low-dimensional visualization methods have been developed by many researchers along various directions. As one of methods, Kohonen's SOM (Self-Organizing Map) is prominent. SOM compresses the volume of the data, yields abstraction from the data and offers visual display on low-dimensional grids. Although it is proven quite effective, it has one undesirable property: SOM's display is discrete. In this study, we propose two techniques for enhancing quality of SOM's display, so that SOM's display becomes continuous. The proposed methods are demonstrated in two numerical examples.