• Journal of Family Resource Management and Policy Review
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• v.11 no.1
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• pp.53-63
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• 2007

This study analyzes the contents of low birthrate measures by the government and their effectiveness. The discussion on the measures being promoted by the government is conducted by considering the analysis on the cause of low birthrates, introduction of overseas policies and government policy propositions, etc. The evaluation on effectiveness is conducted by considering the recognition of the policies by women who are the subject of childbirth and preceding studies. Low birth rates are not the problem of an individual anymore, but a task that the whole of society has to resolve. The comprehensive measures should be made including the elements that influence birth rate such as reducing the cost of raising a child, creating a favorable environment in society and worksite, and improving the nurturing environment, etc.

• Journal of the Korean Home Economics Association
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• v.20 no.4
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• pp.83-89
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• 1982

The purpose of this study was to analyze the 45 measuring items for the clothing construction in order to observe the factorial structure of items and to extract the common factor and the special unique factor from data. The sample for the study was drawn randomly out of senior high schoolgirls in Seoul urban area. The size of sample was 301 girls between age 16 and 18. The method of analysis was applied by the principal component analysis with orthogonal rotation after extraction of 9 major factors. All of the above data was analyzed by the computer installed at Seoul National University. From these analyses, the major findings can be summerized as follows: 1. The results of factor analysis generally indicated that the first factor was clustered with 15 items, length measures and height measures. The eigenvalue of the first factor was 16.5 and the cumulative percentage of variables 36.6%. 2. The second factor was clustered with width measures, girth measures and weight of 19 items. The eigenvalue of the second factor was 6.5 and the cumulative percentage of variables 51.0%.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.2
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• pp.39-46
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• 2023

Purpose: The small-scale environmental impact assessment system in Korea was introduced and implemented in August 2000, but it has a problem that it cannot guarantee implementation due to the large proportion of qualitative reduction measures for each evaluation item. Therefore, when preparing a small-scale environmental impact assessment, research was conducted on how to improve the existing simple listing-type reduction measures and qualitative evaluation standards to quantitative reduction measures and evaluation standards reflecting regional characteristics. Research design, data and methodology: The small-scale environmental impact assessment system in Korea was introduced and implemented in August 2000, but it has a problem that it cannot guarantee implementation due to the large proportion of qualitative reduction measures for each evaluation item. Therefore, when preparing a small-scale environmental impact assessment, research was conducted on how to improve the existing simple listing-type reduction measures and qualitative evaluation standards to quantitative reduction measures and evaluation standards reflecting regional characteristics. Results: As a result of the analysis of qualitative and quantitative factors, the arithmetic sum of the qualitative factors of the total six projects is 160, accounting for 80% of the total number of reduction measures, and the quantitative factors are 40, accounting for 20%. Among them, the number of qualitative reduction measures reached 97.4% for animal and plant items, and more than 90% for air quality, noise and vibration, and eco-friendly resource circulation items. Conclusions: Therefore, it is necessary to avoid establishing qualitative reduction measures and set quantitative measures as the basis, but to specify the specifications, size, and installation location related to the reduction measures, and to calculate the numerical reduction efficiency.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.41-48
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• 2003

In this paper, we present a new measure to evaluate the interestingness of association rules. Ultimately. to evaluate whether a rule is interesting or not is subjective. However, an interestingness measure is useful in that it shows the cause for pruning uninteresting rules statistically or logically. Some interestingness measures have been developed in association rules mining. We present an overview of interestingness measures and propose a new measure. A comparative study of some interestingness measures is made on an example dataset and a real dataset. Our experiments show that the new measure can avoid the discovery of misleading rules.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2005.11a
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• pp.87-88
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• 2005

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.857-868
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• 2014

Data mining is the representative analysis methodology in the era of big data, and is the process to analyze a massive volume database and summarize it into meaningful information. Association rule technique finds the relationship among several items in huge database using the interestingness measures such as support, confidence, lift, etc. But these interestingness measures cannot be used to establish a causality relationship between antecedent and consequent item sets. Moreover, we can not know association direction by them. This paper propose causally confirmed association thresholds to compensate for these problems, and then check the three conditions of interestingness measures. The comparative studies with basic association thresholds, causal association thresholds, and causally confirmed association thresholds are shown by simulation studies. The results show that causally confirmed association thresholds are better than basic and causal association thresholds.

• Journal of Korea Port Economic Association
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• v.20 no.2
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• pp.73-87
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• 2004

The purpose of this paper is to setup reasonable criterion for underwriters to reimburse the expenses of suing and labouring incurred by assured, using game theory. As for the upper limit for the reimbursement, MIA and ICC do not mention at all but stipulate that proper and reasonable expenses shall be reimbursed, while ITC-Hulls set the amount insured as the upper limit to compensate the sum of expenses and damage loss. And as for failed measures of averting and minimizing loss, MIA and ICC do not mention either, while ITC-Hulls stipulates underwriters shall compensate the expenses and damage loss within the amount insured. The main results of this paper are as follows: First, it is for the benefit of underwriters to reimburse the expenses incurred to take such reasonable measures to avert or minimizing a loss which would be recoverable under the insurance. Second, the expenses of single measure should not be above the amount insured. Third, even if the measures failed, the expense should be reimbursed if it is less than the expected value of the subject-matter insured that could be recovered by the measures. Last, if the measures are taken several times individually, even if the sum of expenses might be above the amount insured, it should be reimbursed.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.979-987
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• 2013

It is becoming increasingly difficult for colleges to recruit new students to their full capacity. The increase of the withdrawal rate drives these colleges into crisis yet little has been done about it, because students with great possibility to withdraw enter colleges and old measures to stop them from dropping out hardly work. This study attempts to grope new measures to prevent dropout from college. To do this, I investigated withdrawal rate by college admission types and suggested measures to reduce withdrawal rate by incorporating the results of the investigation into admission procedures. I also compared the different types of admission in students satisfaction with college life and withdrawal rate, and suggested the measures to alleviated withdrawal rate. I expect the suggestions made in this study would be used effectively to reduce the withdrawal in colleges.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.117-124
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• 2013

Association rule of data mining techniques is the method to quantify the relationship between a set of items in a huge database, andhas been applied in various fields like internet shopping mall, healthcare, insurance, and education. There are three primary interestingness measures for association rule, support and confidence and lift. Confidence is the most important measure of these measures, and we generate some association rules using confidence. But it is an asymmetric measure and has only positive value. So we can face with difficult problems in generation of association rules. In this paper we apply the similarity measures by probabilistic interestingness measure (PIM) with all marginal proportions (AMP) to solve this problem. The comparative studies with support, confidences, lift, chi-square statistics, and some similarity measures by PIM with AMPare shown by numerical example. As the result, we knew that the similarity measures by PIM with AMP could be seen the degree of association same as confidence. And we could confirm the direction of association because they had the sign of their values, and select the best similarity measure by PIM with AMP.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.135-144
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• 2003

This work is concerned with comparison of the recently developed disparity measures for the partial association model in three dimensional categorical data. Data are generated by using simulation on each term in the log-linear model equation based on the partial association model, which is a proposed method in this paper. This alternative Monte Carlo methods are explored to study the behavior of disparity measures such as the power divergence statistic I(λ), the Pearson chi-square statistic X$^2$, the likelihood ratio statistic G$^2$, the blended weight chi-square statistic BWCS(λ), the blended weight Hellinger distance statistic BWHD(λ), and the negative exponential disparity statistic NED(λ) for moderate sample sizes. We find that the power divergence statistic I(2/3) and the blended weight Hellinger distance family BWHD(1/9) are the best tests with respect to size and power.