• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3185-3199
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• 1997

This paper suggests techniques to reduce coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, we choose new approximation coefficients using a non-linear approximation of luminance term. This boosts the fidelity. Our experiment employing the above methods shows enhancement in the coding time more than two times over traditional coding methods and shows improvement in PSNR value by about 1-3dB at the same com- pression rate.

• Journal of IKEEE
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• v.5 no.2 s.9
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• pp.190-200
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• 2001

This paper is addressed to welding defect feature vector selection and implementation method of welding defect classifier using fuzzy techniques. We compare IAV, zero-crossing number as time domain analysis, power spectrum coefficient as frequency domain, histogram as both domain for welding defect feature selection. We choose histogram as feature vector by graph analysis and find out that maximum frequent occurrence number and section of corresponding signal scale in relative histogram show obvious difference between normal welding and voiding with penetration depth defect. We implement a fuzzy welding defect classifier using these feature vector, test it to verify its effectiveness for 695 welding data frame which consist of 4000 sampled data. As result of test, correct classification rate is 92.96%. Lab experimental results show a effectiveness of fuzzy welding defect classifier using relative histogram for practical Laser welding monitoring system in industry.

• Journal of the Korean Society of Food Culture
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• v.13 no.1
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• pp.37-46
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• 1998

Distribution structure is the link between a society's needs and its industrial responses. A change in distribution structure brings about a consumption structure which may results in considerable changes in lifestyle including food habits. The purpose of this study was to evaluate a effect of change of distribution structure on the food purchase. The survey was carried from May to June, 1997 by way of questionnaire of 407 housewives, aged 23-64 years, in Seoul and the capital area. The questionaire consists of sociodemographic characteristics of the subjects and distribution channel, information route of food selection, acknowledgement and coefficient of utilization of new distribution channel, mainly used distribution channel in food purchase, important factors in food selection, and food purchasing behavior. Their data were statistically analyzed based on frequency, mean, and $X^2-test$. The major findings of this study were as follows; 1) Most frequently used distribution channels in food purchase were supermarket(38.53%), department store(15.23%), discount store(14.05%), a conventional retail market(13.87%), membership wholesale club(8.07%), and a conventional wholesale market(6.53%). 2) The new distribution channels that subjects have ever used were discount store(75.4% of the subject), membership wholesale club(63%), mail order house(32%), outlet store(29.4%), home shopping(10.3%). 3) Compared to the subject living far from the new distribution channel, the subject living close to the new distribution channel was higher in frequency of new distribution channel utilization. These observations suggest that change of the distribution structure promotes the change of the food purchasing behavior.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1291-1300
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• 2017

In the high-dimensional data, the number of variables is very larger than the number of observations. In this case, the impact of influential observations on regression coefficient estimates can be very large. Jang and Anderson-Cook (2017) suggested the LASSO influence plot. In this paper, we propose the LASSO influence plot, LASSO variable selection ranking plot, and three-dimensional LASSO influence plot as graphical methods for evaluating the impact of influential observations in high-dimensional data. With real two high-dimensional data examples, we apply these graphical methods as the regression diagnostics tools for finding influential observations. It has been found that we can obtain influential observations with by these graphical methods.

• Korean Journal of Adult Nursing
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• v.26 no.2
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• pp.149-158
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• 2014

Purpose: The purpose of this study was to determine whether Selection, Optimization and Compensation (SOC) Strategy mediated the relationship between job stress and health promoting behaviors among nurses. Methods: A descriptive causal relationship research design was used. 245 subjects recruited from the five general hospitals, which have over 500 beds in Seoul and Kyunggi-do, participated in the study by completing a survey which included questions about SOC strategy, job stress and health promoting behaviors. t-test, ANOVA, Pearson's correlation coefficient and multiple regression were used to analyze the data. SPSS/WIN 20.0 was used for all analysis. Results: The mean job stress score was 47.89; mean SOC strategy score was .71. 'Spiritual development' was the highest reported health promoting behavior with a mean of 3.57. Job stress was significantly and negatively related to health promoting behaviors. The result showed that all the mediating paths of SOC strategy were significant. The partial mediating model showed high goodness of fit demonstrating that the model was outstanding. Conclusion: SOC strategy mediated the relationship between job stress and health promoting behaviors. Applying better SOC strategies among nurses will increase flexibility in responding to job stress and will also better perform health promoting behaviors.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.5
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• pp.401-406
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• 2001

The applicability of non-destructive near infrared reflectance spectroscopic (NIRS) method was tested to determine the protein and oil contents of intact soybean [Glycine max (L.) Merr.] seeds. A total of 198 soybean calibration samples and 101 validation samples were used for NIRS equation development and validation, respectively. In the developed non-destructive NIRS equation for analysis of protein and oil contents, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing, and 1 point second smoothing) and 2, 1, 20, 10 math treatment conditions with Standard Normal Variate and Detrend (SNVD) scatter correction method and entire spectrum (400-2500 nm) by using Modified Partial Least Squares (MPLS) regression, respectively. Validation of these non-destructive NIRS equations showed very low bias (protein: 0.060%, oil: -0.017%) and standard error of prediction (SEP, protein: 0.568 %, oil : 0.451 %) as well as high coefficient of determination ($R^2$, protein: 0.927, oil: 0.906). Therefore, these non-destructive NIRS equations can be applicable and reliable for determination of protein and oil content of intact soybean seeds, and non-destructive NIRS method could be used as a mass screening technique for selection of high protein and oil soybean in breeding programs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.1013-1022
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• 2014

Correlation Power Analysis (CPA) is a type of Side-Channel Analysis (SCA) that extracts the secret key using the correlation coefficient both side-channel information leakage by cryptography device and intermediate value of algorithms. Attack performance of the CPA is affected by noise and temporal synchronization of power consumption leaked. In the recent years, various researches about the signal processing have been presented to improve the performance of power analysis. Among these signal processing techniques, compression techniques of the signal based on Principal Component Analysis (PCA) has been presented. Selection of the principal components is an important issue in signal compression based on PCA. Because selection of the principal component will affect the performance of the analysis. In this paper, we present a method of selecting the principal component by using the correlation of the principal components and the power consumption is high and a CPA technique based on the principal component that utilizes the feature that the principal component has different. Also, we prove the performance of our method by carrying out the experiment.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.203-212
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• 2022

In this paper, we propose to identify the factors and satisfaction of the selection of University and departments of One university freshmen. Research subjects were 499 freshmen in 2021 at K University located in G city. The data were analyzed by descriptive statistics, t-test, ANOVA, Scheffe' test and pearson's correlation coefficient using SPSS WIN 18.0. The results of this study showed that the internet/SNS was the highest in university information media, the school teacher was the highest in information provider, and the employment rate had the most impact on university registration decision. The University satisfaction score was 3.43, and there was a significant difference in gender(t=5.527, p=.019) and admission type(F=5.527, p<.001). The department satisfaction was 3.86 and there was a significant difference in the admissions type(F=3.004, p=.018). Univdrsity satisfaction and Department satisfaction showed a significant positive correlation(r=5.527, p<.001). Universities should improve their competitiveness through systematic admission information system.

• Animal Bioscience
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• v.37 no.5
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• pp.817-825
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• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.8
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• pp.924-934
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• 2003

The aim of the present study was to measure intra-individual consistency in clothing style evaluation and to examine its relation to the ratings. For this study, a pilot test was conducted to 50 clothing majored university students to explore the stimulus of‘cute’,‘casual’,‘sexy’,‘elegant’,‘intelligent’,‘formal’,‘romantic’,‘individual’,‘refined’for the 9 each image styles from the 32 spring wears in fashion magazine$\boxDr$FARBE$\boxUl$(March, 2000). On the basis of the preliminary survey, the question items explored the 15 pairs of bipolar adjectives as seven-point Likert type. The main survey was preceded 94 female and 111 men of university students from March 13 to 24 in 2000, twice for 7-days interval. As a result of analyzing of correlation coefficients between the two ratings for each subjects, intra-individual consistency in the evaluation, ranged from -.11 to .87 and mean coefficient was .64 of female and .20 to .76 and mean coefficient was .57 of male. Female had higher intra-individual consistency in the evaluation than male. Based on the coefficients, the subjects were classified into three groups: high, medium, and low intra-individual consistency. Analysis of variance of mean ratings by the three groups revealed that significant difference existed in 42% of female and 25% of male in 135 combinations of 9 clothing and 15 semantic differential scales. There was an apparent tendency that subjects of female with high intra-individual consistency were mostly definitely to evaluate clothing, whereas the ones with low were least. But male shows opposit trend compare to each groups of female. The result of this study, it was found that female rated higher intra-individual consistency and definition in the two times evaluations than male and among the semantic differential scales'consistency differ depending on style and gender. It is believed that the result of this study is helpful clothing image evaluation, and clothing image selection tendency.