• The Journal of Korean Medicine
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• v.33 no.4
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• pp.60-68
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• 2012

Objectives: By grasping trends in research, technology, and general characteristics of learning support tools, this study was conducted to present a model for research on Korean Medicine (KM) to make use of information technology to support teaching and learning. The purpose is to improve the future clinical competence of medical personnel, which is directly linked to national health. Methods: With papers and patents published up to 2011 as the objects, 438 papers were extracted from "Web of Science" and 313 patents were extracted from the WIPS database (DB). Descriptive analysis and network analysis were conducted on the annual developments, academic journals, and research fields of the papers, patents searched were subjected to quantitative analysis per application year, nation, and technology, and an activity index (AI) was calculated. Results: First, research on medical learning support tools has continued to increase and is active in the fields of computer engineering, education research, and surgery. Second, the largest number of patent applications on medical learning support tools were made in the United States, South Korea, and Japan in this order, and the securement of remediation technology-centered patents, rather than basic/essential patents, seemed possible. Third, when the results of the analysis of research trends were comprehensively analyzed, international research on e-PBL- and medical simulation-centered medical learning support tools was seen to expand continuously to improve the clinical competence of medical personnel, which is directly linked to national health. Conclusions: The KM learning support tool model proposed in the present study is expected to be applicable to computer-based tests at KM schools and to be able to replace certain functions of national KM doctor license examinations once its problem DB, e-PBL, and TKM simulator have been constructed. This learning support tool will undergo a standardization process in the future.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.249-255
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• 2019

Type 2 diabetes mellitus(T2DM) is included in metabolic disorders characterized by hyperglycemia, which causes many complications, and requires long-term treatment resulting in massive medical expenses each year. There have been many studies to solve this problem, but the existing studies have not been accurate by learning and predicting the data at specific time point. Thus, this study proposed a model using RNN to increase the accuracy of prediction of T2DM. This work propose a T2DM prediction model based on Korean Genome and Epidemiology study(Ansan, Anseong Korea). We trained all of the data over time to create prediction model of diabetes. To verify the results of the prediction model, we compared the accuracy with the existing machine learning methods, LR, k-NN, and SVM. Proposed prediction model accuracy was 0.92 and the AUC was 0.92, which were higher than the other. Therefore predicting the onset of T2DM by using the proposed diabetes prediction model in this study, it could lead to healthier lifestyle and hyperglycemic control resulting in lower risk of diabetes by alerted diabetes occurrence.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.2
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• pp.133-155
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• 2022

The purpose of this study was to develop the indicatives for the analysis of the effects of Gyeonggi-do Book Sharing Project on pre-schoolers of supporter' reading care and thereby, suggest some data useful to the establishment of a reading culture promotion policy in Gyeonggi-do. Preceding studies and cases were reviewed to analyze the effects of the book-sharing project on pre-schoolers of supporter' reading care and thereby, develop some measurement indicatives, and thus, the indicatives were verified by professionals using the Delphi technique. Then, supporter of 3~5 year-old pre-schoolers were sampled from 7 cities and counties in Gyeonggi-do (Pocheon-si, Yangpyeong-gun, Yeoju-si, Dongducheon-si, Gapyeong-gun, Yeoncheon-gun and Yangju-si) to be divided into control and test groups and thereby, their reading care effect indicatives were compared before and after the test. The theoretical background is theory of family literacy, emergent literacy and parenting efficacy. As a result of developing the indicatives for analysis of pre-schoolers of supporter's reading care effects and comparing them for the sample pre-schoolers of supporter, before and after the test, the book-sharing project was found effective in improving reading care. The most difficult problem in pre-schoolers' earlier reading education involves acquisition of reading habit. So, it is deemed necessary to operate a regular book sharing project involving public organization and homes. As a result of developing the indicatives and analyzing the effects of the book-sharing project, it was confirmed that the project would serve to improve pre-schoolers of support's reading care and therefore, this study seems to provide some ground for the operation of a sustainable book-sharing project to narrow the education divide and promote a book reading culture in Gyeonggi-do.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.421-428
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• 2022

This study analyzes emerging earthquake and space use technologies from the latest Korean and Japanese scientific and technological foresights in 2022 and 2019, respectively. Unlike the earthquake prediction and early warning technologies presented in the 2017 study, the emerging earthquake technologies in 2022 in Korea was described as an earthquake/complex disaster information technology and public data platform. Many detailed future technologies were presented in Japan's 2019 survey, which includes largescale earthquake prediction, induced earthquake, national liquefaction risk, wide-scale stress measurement; and monitoring by Internet of Things (IoT) or artificial intelligence (AI) observation & analysis. The latest emerging space use technology in Korea and Japan were presented in more detail as robotic mining technology for water/ice, Helium-3, and rare earth metals, and manned station technology that utilizes local resources on the moon and Mars. The technological realization year forecasting in 2019 was delayed by 4-10 years from the prediction in 2015, which could be greater due to the Corona 19 epidemic, the declaration of carbon neutrality in Korea and Japan in 2020 and the Russo-Ukrainian War in 2022. However, it is required to more active research on earthquake and space technologies linked to information technology.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.22-28
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• 2023

In this study, we conducted research on the automated trading of U.S. stocks through a volatility strategy using the Fear and Greed index. Volatility in the stock market is a common phenomenon that can lead to fluctuations in stock prices. Investors can capitalize on this volatility by implementing a strategy based on it, involving the buying and selling of stocks based on their expected level of volatility. The goal of this thesis is to investigate the effectiveness of the volatility strategy in generating profits in the stock market.This study employs a quantitative research methodology using secondary data from the stock market. The dataset comprises daily stock prices and daily volatility measures for the S&P 500 index stocks. Over a five-year period spanning from 2016 to 2020, the stocks were listed on the New York Stock Exchange (NYSE). The strategy involves purchasing stocks from the low volatility group and selling stocks from the high volatility group. The results indicate that the volatility strategy yields positive returns, with an average annual return of 9.2%, compared to the benchmark return of 7.5% for the sample period. Furthermore, the findings demonstrate that the strategy outperforms the benchmark return in four out of the five years within the sample period. Particularly noteworthy is the strategy's performance during periods of high market volatility, such as the COVID-19 pandemic in 2020, where it generated a return of 14.6%, as opposed to the benchmark return of 5.5%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.526-532
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• 2023

Falls are fatal accidents that occur more than 420,000 times a year worldwide. Therefore, to study patients with falls, we found the association between extrinsic injury codes and principal diagnosis S-codes of patients with falls, and developed a prediction model to predict extrinsic injury codes based on the data of principal diagnosis S-codes of patients with falls. In this study, we received two years of data from 2020 and 2021 from Institution A, located in Gangneung City, Gangwon Special Self-Governing Province, and extracted only the data from W00 to W19 of the extrinsic injury codes related to falls, and developed a prediction model using W01, W10, W13, and W18 of the extrinsic injury codes of falls, which had enough principal diagnosis S-codes to develop a prediction model. 80% of the data were categorized as training data and 20% as testing data. The model was developed using MLP (Multi-Layer Perceptron) with 6 variables (gender, age, principal diagnosis S-code, surgery, hospitalization, and alcohol consumption) in the input layer, 2 hidden layers with 64 nodes, and an output layer with 4 nodes for W01, W10, W13, and W18 exogenous damage codes using the softmax activation function. As a result of the training, the first training had an accuracy of 31.2%, but the 30th training had an accuracy of 87.5%, which confirmed the association between the fall extrinsic code and the main diagnosis S code of the fall patient.

• The Mathematical Education
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• v.63 no.2
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• pp.165-186
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• 2024

Despite the growing attention on artificial intelligence-based automated scoring technology as a support method for the introduction of descriptive items in school environments and large-scale assessments, there is a noticeable lack of foundational research in mathematics compared to other subjects. This study developed an automated scoring model for two descriptive items in first-year middle school mathematics using the Random Forest algorithm, evaluated its performance, and explored ways to enhance this performance. The accuracy of the final models for the two items was found to be between 0.95 to 1.00 and 0.73 to 0.89, respectively, which is relatively high compared to automated scoring models in other subjects. We discovered that the strategic selection of the number of evaluation categories, taking into account the amount of data, is crucial for the effective development and performance of automated scoring models. Additionally, text preprocessing by mathematics education experts proved effective in improving both the performance and interpretability of the automated scoring model. Selecting a vectorization method that matches the characteristics of the items and data was identified as one way to enhance model performance. Furthermore, we confirmed that oversampling is a useful method to supplement performance in situations where practical limitations hinder balanced data collection. To enhance educational utility, further research is needed on how to utilize feature importance derived from the Random Forest-based automated scoring model to generate useful information for teaching and learning, such as feedback. This study is significant as foundational research in the field of mathematics descriptive automatic scoring, and there is a need for various subsequent studies through close collaboration between AI experts and math education experts.

• Neonatal Medicine
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• v.16 no.2
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• pp.154-162
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• 2009

Purpose: Death is an important problem for physicians and parents in neonatal intensive care unit. This study was intended to evaluate the mortality rate, causes of death, and the change of mortality rate by year for infants admitted to the neonatal intensive care unit. Methods: We retrospectively surveyed the medical records of the infants who were admitted to the neonatal intensive care unit at Asan Medical Center and who died before discharge between 1998 and 2007. Gestational age, birth weight, gender, time to death and the underlying diseases related to the causes of infant deaths and obtained from the medical records and analyzed according to year. Results: A total of 6,289 infants were admitted and 264 infants died during the study period. The overall mortality rate was 4.2%. For very low and extremely low birth weight infants, the mortality rate was 10.6% and 21.4%, respectively. There was no significant change in the mortality rate during the study period. Prematurity related complications and congenital anomalies were the conditions most frequently associated with death in the neonatal intensive care unit. of the infant deaths 37.1% occurred within the first week of life. Conclusion: Even though a remarkable improvement in neonatal intensive care has been achieved in recent years, the overall mortality rate has not changed. To reduce the mortality rate, it is important to control sepsis and prevent premature births. The first postnatal week is a critical period for deaths in the neonatal intensive care unit.

• Neonatal Medicine
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• v.16 no.2
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• pp.172-181
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• 2009

Purpose: To identify trends in causative bacterial organisms for neonatal sepsis and antimicrobial susceptibilities over 10 years in one neonatal intensive care unit. Methods: We retrospectively reviewed the cases of culture-proven neonatal sepsis between January 1998 and December 2007. The 10-year period was divided into two phases (phase I, 1998-2002; phase II, 2003-2007) to distinguish the differences during the entire period. Results: Total 350 episodes of neonatal sepsis were identified in 315 neonates. The common pathogens of early-onset sepsis were S. epidermidis, S. aureus, P. aeruginosa, and E. cloacae in phase I, and S. epidermidis and E. cloacae in phase II. In cases of late-onset sepsis, coagulase negative Staphylococcus, S. aureus, and K. pneumoniae were isolated frequently in both phases. The incidence of sepsis caused by multi-drug resistant organisms decreased with strict infection control. Gram positive organisms showed 0-20% susceptibility to penicillin, ampicillin, and cefotaxime in both phases. Sensitivity to amikacin for Enterobacter spp. increased, whereas P. aeruginosa showed decreased sensitivity in phase II. Between 50% and 60% of other gram negative bacteria, except P. aeruginosa, were susceptible to cefotaxime in phase II in contrast to phase I. Greater than 80% of gram negative bacteria were sensitive to imipenem except P. aeruginosa and ciprofloxacin in both phases. Conclusion: The trend in causative microorganisms and antimicrobial susceptibilities can be used as a guideline for selection of appropriate antibiotics. A particular attention should be paid to infection control, especially to reduce sepsis caused by multi-drug resistant organisms.

• Journal of Aquaculture
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• v.11 no.4
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• pp.573-580
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• 1998

Red spotted grouper, Epinephelus akaara is distributed in the south and west coasts of Korea. The natural stocks of the fish are decreasing sharply year by uear because of reckless overfishing. This research was carried out to understand general informations on maturation, sex composition and sex-reversals of the fish. Annual fishing uields of red spotted grouper in the castal area of Byonsan Peninsular of Kora decreased over 10% from 1992 to 1994. The main fishing season was from May to July with fishing gear of Hand-lines. Gonadosomatic index (GSI) and condition factor were highest on early and late July, respectively, thus main spawning reriod was assumed from late July to early August. The relationship between total length (X) and body weight (Y) for wild adults was represented as a regression, Y=$0.0169X^{2.9705}$, ($r^2$=0.96). Frequency of sex of wild red spotted gouper showed that the number of female below 38cm in total length was more than that of male, and hermaphrodite mainly occurred from 28cm to 32cm in total length the frequency of male and female were almost same. Also hermaphrodite occurred mainly between 25~29cm. Sex reversal ration of the adults reared in a tank for a year with different sexual compositions revealted that the frequency of female reversed from male was more than that of male reversed from female at 1:1 and 1:2 stocking densities of female and male, respectively. Also, about 20% of female was reversed to male when all females were reared. And the size of the fish reversed to male was larger than that of non-reversed female.