• Women's Health Nursing
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• v.28 no.4
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• pp.348-357
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• 2022

Purpose: This study aimed to identify maternal, infant, and perinatal mortality using the national population data of South Korea between 2018 and 2020, and to analyze mortality rates according to characteristics such as age, date of death, and cause of death in each group. This study updates the most recent study using 2009 to 2017 data. Methods: Analyses of maternal, infant, and perinatal mortality were done with data identified through the supplementary investigation system for cases of death from the Census of Population Dynamics data provided by Statistics Korea from 2018 to 2020. Results: Between 2018 and 2020, a total of 99 maternal deaths, 2,427 infant deaths, and 2,408 perinatal deaths were identified from 901,835 live births. The maternal mortality ratio was 11.3 deaths per 100,000 live births in 2018; it decreased to 9.9 in 2019 but increased again to 11.8 in 2020. The maternal mortality ratio increased steeply in women over the age of 40 years. An increasing trend in the maternal mortality ratio was found for complications related to the puerperium and hypertensive disorders. Both infant and perinatal mortality continued to decrease, from 2.8 deaths per 1,000 live births in 2018 to 2.5 in 2020 and from 2.8 in 2018 to 2.5 in 2020, respectively. Conclusion: Overall, the maternal, infant, and perinatal mortality statistics showed improvements. However, more attention should be paid to women over 40 years of age and specific causes of maternal deaths, which should be taken into account in Korea's maternal and child health policies.

• Bulletin of the Korean Chemical Society
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• v.25 no.9
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• pp.1408-1410
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• 2004

• The Mathematical Education
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• v.45 no.4 s.115
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• pp.381-406
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• 2006

This work aims to investigate mathematics teachers' knowledge and belief on the high school probability and statistics. For this aim, two research questions are estabilished as follows. (1) How is mathematics teachers' knowledge on the main contents of the high school probability and statistics in the 7th mathematics curriculum? (2) What is mathematics teachers' belief on the high school probability and statistics? Survey and interviews were carried out to answer the above research questions. Subjects of the survey were 2 7mathematics teachers who were answered to questionnaire. Among them, 3 volunteers were chosen by provinces for in-depth interview. Research findings in mathematics teacher's knowledge are as follows. Firstly, mathematics teachers do not have much of mathematical knowledge on the newly added and changed contents of the high school probability and statistics in the 7th mathematics curriculum. Secondly, mathematics teachers do not change their teaching-learning method for probability and statistics. Thirdly, many teachers think that the use of technology and reconstruction of the textbooks are required in teaching and learning of the high school probability and statistics. But, they stick on their own way. Research findings in mathematics teachers' belief are as follows. Firstly, many mathematics teachers view the nature of statistics as a branch of the applied mathematics and put the value of high school probability and statistics on the practical usefulness, Secondly, many mathematics teachers think that understanding concepts and improving problem solving ability are the best method of the teaching and learning. Thirdly, many mathematics teachers think that high school probability and statistics textbooks should cause motivations and interests in order not to give up studying probability and statistics. It is expected that the above findings can be used to change teachers' teaching and learning methods and to improve teachers training program.

• International Journal of Reliability and Applications
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• v.1 no.2
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• pp.145-154
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• 2000

In this paper, tests of statistical hypotheses for the expectation and variance of Gaussian fuzzy population are discussed.

• Journal of Korean Society for Quality Management
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• v.9 no.1
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• pp.12-21
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• 1981

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.42-42
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• 2001

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.453-469
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• 2005

In Korea, mathematics education of 11-12 grade students has been taken according to the 7th national mathematics curriculum, which was renovated by the Ministry of Education and Human Resources Development announcement in 1997. The education of probability and statistics has been carried out as a part of this curriculum. We analyze mathematics textbooks-Practical mathematics and Mathematics I- and compare the 7th national mathematics curriculum with the 6th national mathematics curriculum.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.657-668
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• 2023

It's important to note that air compressors in the industrial sector are major energy consumers, accounting for a significant portion of total energy costs in manufacturing plants, ranging from 12% to 40%. To address this issue, researchers have compared forecasting models that can predict the power consumption of air compressors. The forecasting models were designed to incorporate variables such as flow rate, pressure, temperature, humidity, and dew point, utilizing statistical methods, machine learning, and deep learning techniques. The model performance was compared using measures such as RMSE, MAE and SMAPE. Out of the 21 models tested, the Elastic Net, a statistical method, proved to be the most effective in power comsumption forecasting.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1205-1213
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• 2023

This study delves into methods for enhancing the power efficiency of air compressor systems, with the primary objective of significantly impacting industrial energy consumption and environmental preservation. The paper scrutinizes Shinhan Airro Co., Ltd.'s power efficiency optimization technology and employs machine learning ensemble models to simulate power efficiency optimization. The results indicate that Shinhan Airro's optimization system led to a notable 23.5% increase in power efficiency. Nonetheless, the study's simulations, utilizing machine learning ensemble techniques, reveal the potential for a further 51.3% increase in power efficiency. By continually exploring and advancing these methodologies, this research introduces a practical approach for identifying optimization points through data-driven simulations using machine learning ensembles.

• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.57-66
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• 1998

In the analysis of time series it is an important issue to determine whether a time series under study is stationary. For the test of the stationary of the time series the Dickey-Fuller (DF) type tests have been mainly used. In this paper, we consider the regular unit root tests and seasonal unit root tests based on the generalized Durbin-Watson (DW) statistics when the errors are independent. The limiting distributions of the proposed DW-type test statistics are the functionals of standard Brownian motions. We also obtain the finite distributions and powers of the DW-type test statistics and compare the performances with the DF-type tests. It is observed that the DW-type test statistics have good behaviors against the DF-type test statistics especially in the nonzero (seasonal) mean model.