• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.47 no.4
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• pp.239-248
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• 2021

The paper reviews various classifications and surgical techniques for the treatment of temporomandibular joint ankylosis. PubMed, EBSCO, Web of Science, and Google Scholar were searched using a combination of keywords. Articles related to classification, resection-reconstruction of the temporomandibular joint, and management of airway obstruction were considered and categorized based on the objectives. Seventy-nine articles were selected, which included randomized clinical trials, non-randomized controlled cohort studies, and case series. Though several classifications exist, most classifications are centered on the radiographic extent of the ankylotic mass and do not include the clinical and functional parameters. Hence there is a need for a comprehensive staging system that takes into consideration the age of the patient, severity of the disease, clinical, functional, and radiographic findings. Staging the disease will help the clinician to adopt a holistic approach in treating these patients. Interpositional arthroplasty (IA) results in better maximal incisal opening compared with gap arthroplasty, with no significant difference in recurrent rates. Distraction osteogenesis (DO) is emerging as a popular technique for the restoration of symmetry and function as well as for relieving airway obstruction. IA, with a costochondral graft, is recommended in growing patients and may be combined with or preceded by DO in cases of severe airway obstruction. Alloplastic total joint replacement combined with fat grafts and simultaneous osteotomy procedures are gaining popularity. A custom-made total joint prosthesis using CAD/CAM can efficiently overcome the shortcomings of stock prostheses.

• Health Policy and Management
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• v.32 no.1
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• pp.73-93
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• 2022

Background: Appropriate physician workforce projection through reasonable discussions and decisions with a broad view on supply and demand of the workforce, thus, is very important for high-quality healthcare services. The study expects to provide preliminary research data on the workforce diagnosis standard model for Korean physician workforce policy decision through more flexible and objective physician workforce projection in reflection of diverse changes in healthcare policy and sociodemographic environments. Methods: A low flow rate through the causal map was developed, and an objective workforce demand projection from 2019 to 2040 was conducted. In addition, projections by scenarios under various situations were conducted with the low flow rate developed in the study. Lastly, the demand projection of the physician workforce by region of 17 cities and provinces was conducted. Results: First, demand of physicians in 2019 was 110,665, 113,450 in 2020, 129,496 in 2025, 146,837 in 2030, 163,719 in 2035, and 179,288 in 2040. Second, the scenario for the retirement of baby boomers led to a decrease in the growth rate due to time delay. Third, Seoul and Gyeonggi-do account for a high percentage of demand, a very high upward trend was identified in Gyeonggi-do, and as a result, the projection showed that the demand of the physician workforce in Gyeonggi-do would worsen over time. Conclusion: This study is meaningful in that rational and collective physician workforce supply and demand and its imbalance in workforce distribution were verified through various projections by scenarios and regions of Korea with System Dynamics.

• The Journal of Economics, Marketing and Management
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• v.11 no.4
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• pp.19-30
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• 2023

Purpose: This study examines the factors that the Millennials and Gen Z prefers to invest in assets. We look at the asset structure they want now and in the future and the idea of designing the future. This can be expected that the center of Korea's asset market will change to the structure they want in the future. Research design, data and methodology: The spatial extent of the study is all over Korea including Seoul, the metropolitan area, and local cities. The survey was conducted for about 16 days from May 7 to May 22, 2023. The survey was conducted by the surveyor visiting the subject in person, distributing the questionnaire, explaining it, and filling it out in person. For the analysis, descriptive statistics and logistic regression analysis were conducted using the SPSS 25.0 statistical package. Results: It was confirmed that the preferred assets of the Millennials and Gen Z were different by period. There was also a difference in the influencing factors between Millennial Generation and Generation Z in asset preference. Conclusions: The Millennials and Gen Z's preferred assets were different by period. The reason is interpreted as the current process of collecting assets during the asset formation period. In the future, they intend to purchase real estate assets by using financial assets as a lump sum of money. We learned the characteristics of the entire Millennials and Gen Z, in addition, the difference between income and assets is believed to have affected the difference in preference factors of Millennial Generation and Generation Z, respectively.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.153-167
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• 2022

Purpose: The purpose of this study is to guide the operation managers who plan daily production of large mass-processing facility that services multi-customers with multi-product, small-batch item characteristics by providing the practical best production quantity and the inventory allowed to build. Methods: Close observation of a subcontract paint-shop operator captured the daily decision process which was reflected in the subcontractor-unique mathematical model and the system dynamics simulation model. Multiple simulations were run to find the practical best production quantity and the maximum allowable stock level of inventory that did not undermine the profit from practical best daily production. Actual data and a few constant values were obtained from the firm under study. Results: While the inventory holding cost for the customer-owned material harms the total profit of the subcontractor, the running cost of the processing facility hinders production in small batches. This balances the maximum possible productions and results in practical best daily production which can be found through simulation runs with actual data. The maximum level of stocked inventory is deduced from the practical best daily production. Conclusion: To build a large volume that enables economy-of-scale production, operators should deal with multi-product small-batch items from multiple customers. When the planned schedule of the time and amount of material in-flow tend not to be reliable, operators can find it practical to execute level production across the planning horizon instead of adjusting to day-to-day in-flow fluctuations.

• Asia-Pacific Journal of Business
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• v.14 no.2
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• pp.51-61
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• 2023

Purpose - Since COVID-19, the government's expansion of liquidity to stimulate the economy has resulted in an increase in private debt and an increase in asset prices of such as real estate and stocks. The recent sharp rise of the US Federal fund rate and tapering by the Fed have led to a fast rise in domestic interest rates, putting a heavy burden on the Korean economy, where the level of household debt is very high. Excessive household debt might have negative effects on the economy, such as shrinking consumption, economic recession, and deepening economic inequality. Therefore, now more than ever, it is necessary to identify the causes of the increase in household debt. Design/methodology/approach - Main methodology is regression analysis. Dependent variable is household loans from depository institutions. Independent variables are consumer price index, unemployment rate, household loan interest rate, housing sales price index, and composite stock price index. The sample periods are from 2017 to May 2022, comprising 72 months of data. The comparative analysis period before and after COVID-19 is from January 2017 to December 2019 for the pre-COVID-19 period, and from Jan 2020 to December 2022 for the post-COVID-19 period. Findings - Looking at the results of the regression analysis for the entire period, it was found that increases in the consumer price index, unemployment rate, and household loan interest rates decrease household loans, while increases in the housing sales price index increase household loans. Research implications or Originality - Household loans of depository institutions are mainly made up of high-credit and high-income borrowers with good repayment ability, so the risk of the financial system is low. As household loans are closely linked to the real estate market, the risk of household loan defaults may increase if real estate prices fall sharply.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.99-106
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• 2024

In the event of an emergency such as facility shutdown during process operation, the by-product gas must be urgently discharged to the vent stack to prevent leakage, fire, and explosion. At this time, the explosion drop value of the released by-product gas is calculated using ISO 10156 formula, which is 27.7 vol%. Therefore, it does not correspond to flammable gas because it is less than 13% of the explosion drop value, which is the standard for flammable gas defined by the Occupational Safety and Health Act, and since the explosion drop value is high, it can be seen that the risk of fire explosion is low even if it is discharged urgently with the vent stock. As a result of calculating the range of explosion hazard sites for hydrogen gas discharged to the Bent Stack according to KS C IEC 60079-10-1, 23 meters were calculated. Since hydrogen is lighter than air, electromechanical devices should not be installed within 23 meters of the upper portion of the Bent Stack, and if it is not possible, an explosion-proof electromechanical device suitable for type 1 of dangerous place should be installed. In addition, the height of the stack should be at least 5 meters so that the diffusion of by-product gas is facilitated in case of emergency discharge, and it should be installed so that there are no obstacles around it.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.11-20
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• 2024

This study presents TabNet, a novel deep learning method, to enhance corporate credit rating accuracy amidst growing financial market uncertainties due to technological advancements. By analyzing data from major Korean stock markets, the research constructs a credit rating prediction model using TabNet. Comparing it with traditional machine learning, TabNet proves superior, achieving a Precision of 0.884 and an F1 score of 0.895. It notably reduces misclassification of high-risk companies as low-risk, emphasizing its potential as a vital tool for financial institutions in credit risk management and decision-making.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Management & Information Systems Review
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• v.29 no.4
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• pp.23-44
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• 2010

This study examines the value-relevance of accruals and discretionary accruals. Also, by examining the effects of the corporate life-cycle on these relationship, this study is able to provide evidence of the value-relevance of accruals and discretionary accruals measures in the economic context of life-cycle theory. This study uses results based on life-cycle classification methods developed by Anthony and Ramesh(1992), adjust Jones model and Dechow Dechev(2002) model. We classify firms using individuals variables(sales growth, capital expenditure growth, employee growth) and then use a composite score obtained from all variables for classification. Our sample consists of 272 firms listed in the Korean Stock Exchange during 14 years(1996-2009). Our final sample for regression variables consists of 2,448 firm-year observations. This evidence implies that the value-relevance of accruals and discretionary accruals in the growth and mature stage can have positive impact on the price but in the decline the value-relevance of accruals and discretionary accruals can have negative impact on the price. The results mean that discretionary accruals communicate managements' private information in the growth stage, but. earnings management in the decline stage. The results of this study suggest that corporate life cycle stages influence the value-relevance of accruals and discretionary accruals measures.

• The Korean Journal of Quaternary Research
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• v.18 no.2 s.23
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• pp.107-107
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• 2004

In this paper we have introduced some results of study on stand growth pattern and stand structure of larch forest which are located in selected forest sites of Khangai and Gobi-Altai mountain ranges of Mongolia. Our investigations showed that growth intensity and stand structure in western Mongolia are very specific from the other forest vegetation zones of Mongolia. Studies on the stand structure and growth trend indicate that tree types of stand structure and different types of growth of Larix sibrica are very common in Western Mongolia. These peculiarities of stand structure and growth of larch stands in Western Monolia could be used for inventory work and an improvement of the forest management in Western Mongolian region. The larch tree is the dominant tree species in Western Mogolia. Forest cover of the region is about 15%, which is two times higher than the country's average. In this region forest area is divided into 4 forest sub-regions: the Central Khangai, Western Khangai, North Eastern Khangai and South Easterun Khangai sub-regions including taiga, pseudo taiga, sub taiga, sub-alpine and forest steppe belts. Silviculture practices and forest research management request to study forest growth trends in local and general conditions, which means to indicate a change of taxonomic characteristics of stand from time to time including diameter, height, basal area, growth stock etc. The forest management practice mostly uses tables of forest growth and yield based on the results of long term research on forest growth. Forest yield tables and other relevant forest standards of Russia are used for the forest inventory and forest management. They are not able to determine forest structure and growth peculiatities of Mongolian forests. Studies on forest resource assessment in Mongolia indicate that after logging operations and forest fires the natural regeneration of desired species such as pine and larch often does not succeed. This situation forces to take a different approach of forest management and silviculture practice depending on the stand structure and growth rate of the forest stands. According to our investigation in last years, forest growth pattern of larch forest depends mostly on stand structure, stand age and growth condition including forest soil, climate and location in different slopes. Due to improve environmental function of forest ecosystem in the region, it is needed to conduct very comprehensive study of high mountain forest ecosystem in selected sub-regions.