• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.93-104
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• 2022

In forecasting realized volatility of the major US stock price indexes (S&P 500, Russell 2000, DJIA, Nasdaq 100), internet search volume reflecting investor's interests and implied volatility are used to improve forecast via a deep learning method of the LSTM. The LSTM method combined with search volume index produces better forecasts than existing standard methods of the vector autoregressive (VAR) and the vector error correction (VEC) models. It also beats the recently proposed vector error correction heterogeneous autoregressive (VECHAR) model which takes advantage of the cointegration relation between realized volatility and implied volatility.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.607-615
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• 2020

The purpose of this study was to analyze the research status and trends related to the industrial mathematics based on text mining techniques with a sample of 4910 papers collected in the SIAM Journal on Applied Mathematics from 1970 to 2019. The R program was used to collect titles, abstracts, and key words from the papers and to analyze topic modeling techniques based on LDA algorithm. As a result of the coherence score on the collected papers, 20 topics were determined optimally using the Gibbs sampling methods. The main results were as follows. First, studies on industrial mathematics were conducted in a variety of mathematics fields, including computational mathematics, geometry, mathematical modeling, topology, discrete mathematics, probability and statistics, with a focus on analysis and algebra. Second, 5 hot topics (mathematical biology, nonlinear partial differential equation, discrete mathematics, statistics, topology) and 1 cold topic (probability theory) were found based on time series regression analysis. Third, among the fields that were not reflected in the 2015 revised mathematics curriculum, numeral system, matrix, vector in space, and complex numbers were extracted as the contents to be covered in the high school mathematical curriculum. Finally, this study suggested strategies to activate industrial mathematics in Korea, described the study limitations, and proposed directions for future research.

• Journal of the Korean GEO-environmental Society
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• v.4 no.3
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• pp.79-88
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• 2003

This paper presents a numerical study of the spatial behavior of a linear absorbing solute in a heterogeneous porous medium. The spatially correlated log-normal hydraulic conductivity field is generated in a given two-dimensional domain by using the geostatistical method (Turning Bands algorithm). The velocity vector field is calculated by applying the two-dimensional saturated groundwater flow equation to the Galerkin finite element method. The simulation of solute transport is carried out by using the random walk particle tracking model with CD(constant displacement) scheme in which the time interval is automatically adjusted. In this study, the spatial behavior of a solute is analyzed by the longitudinal center-of-mass displacement, longitudinal spatial spread moment and longitudinal plume skewness.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.293-299
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• 2018

The weather has a lot of influence on the cultivation of crops. Weather information on agricultural crop cultivation areas is indispensable for efficient cultivation and management of agricultural crops. Despite the high demand for agricultural weather, research on this is in short supply. In this research, we deal with the production method of agricultural weather in Jeollanam-do, which is the main production area of onions through GloSea5 and deep learning. A deep neural network model using the sliding window method was used and utilized to train daily weather prediction for predicting the agricultural weather. RMSE and MAE are used for evaluating the accuracy of the model. The accuracy improves as the learning period increases, so we compare the prediction performance according to the learning period and the prediction period. As a result of the analysis, although the learning period and the prediction period are similar, there was a limit to reflect the trend according to the seasonal change. a modified deep layer neural network model was presented, that applying the difference between the predicted value and the observed value to the next day predicted value.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.34 no.2
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• pp.21-37
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• 2021

Objectives : Allergic rhinitis(AR) is a common chronic disease that accounts for 10-40% of the world's population. This study aims to analyze the status of claims, prevalence, and medical utilization of allergic rhinitis patients using representative patients sample data. Methods : This study used the National Patients Sample(HIRA-NPS) of the Health Insurance Review and Assessment Service for 7 years(2010-2016). And we defined AR patients as all statements including J30 or a subcategory of J30 as the main disease, using the Korean Standard Classification of Diseases(KCD-7). The trend of AR patients by year was divided into Western medicine(WM) and Korean medicine(KM), and analyzed by subgroup analysis such as inpatient/outpatient, gender, age, insurance type, and care institution. Results : Patients with AR were mainly claimed for first sub diagnosis in WM and major diagnosis in KM, and the number of claims increased about 1.3 times and 1.4 times compared to 2010 in WM and KM, respectively. In addition, the total annual medical expenses in 2016 increased 1.3 times and 1.7 times compared to 2010, respectively. Conclusions : Both WM and KM are showing a steadily increasing trend in medical use due to allergic rhinitis. Further research is needed by considering genetic and environmental factors and individual characteristics, and linking with additional data.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.129-139
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• 2023

Forecasting volatility is essential to avoiding the risk caused by the uncertainties of an financial asset. Complicated financial volatility features such as ambiguity between non-stationarity and stationarity, asymmetry, long-memory, sudden fairly large values like outliers bring great challenges to volatility forecasts. In order to address such complicated features implicity, we consider machine leaning models such as LSTM (1997) and GRU (2014), which are known to be suitable for existing time series forecasting. However, there are the problems of vanishing gradients, of enormous amount of computation, and of a huge memory. To solve these problems, a causal temporal convolutional network (TCN) model, an advanced form of 1D CNN, is also applied. It is confirmed that the overall forecasting power of TCN model is higher than that of the RNN models in forecasting VIX, VXD, and VXN, the daily volatility indices of S&P 500, DJIA, Nasdaq, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.337-347
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• 2018

Weather causes much of the risk of agricultural activity. For efficient farming, we need to use weather information. Modern agriculture has been developed to create high added value through convergence with state-of-the-art Information and Communication Technology (ICT). This study deals with the quality control algorithms of weather monitoring equipment through Ubiquitous Sensor Network (USN) observational equipment for efficient cultivation of cabbage. Accurate weather observations are important. To achieve this goal, the Korea Meteorological Administration, for example, developed various quality control algorithms to determine regularity of the observation. The research data of this study were obtained from five USN stations, which were installed in Anbandegi and Gwinemi from 2015 to 2017. Quality control algorithms were developed for flat line check, temporal outliers check, time series consistency check and spatial outliers check. Finally, the quality control algorithms proposed in this study can also identify potential abnormal observations taking into account the temporal and spatial characteristics of weather data. It is expected to be useful for efficient management of highland cabbage production by providing quality-controlled weather data.

• Korean Journal of Comparative Education
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• v.28 no.3
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• pp.291-307
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• 2018

As the value of lifelong learning becomes important, states are making efforts to build a system of lifelong learning. According to this tendency, this paper intends to compare the participation rate of lifelong learning, learning outcomes, learning support infrastructure, support of learning expenses, and recognition of lifelong learning. For the comparative pedagogical approach, Bray and Thomas' cubes such as geographical / regional level, non - geographical demographic statistics, social and educational aspects were utilized. The participation rate of lifelong learning in Korea is 34.4% in 2017, which is lower than the OECD average of 46%. The competency scores of Korean adults were lower than the OECD national averages of the PIAAC survey which measured adult competence, language ability, numeracy, and computer-based problem solving ability. In order to recognize prior learning, EU countries have developed EQFs to evaluate all non-formal and informal learning outcomes, while Korea recognizes qualification as a credit banking credit under the academic credit banking system. International comparisons of lifelong learning can be used as an important tool for diagnosing the actual conditions of lifelong learning in a country and establishing future lifelong learning policies. Therefore, it is necessary to maintain that the comparative pedagogical approach of lifelong learning differs according to the historical context, socioeconomic characteristics, and population dynamics, including the formation process and characteristics of modern countries.

• International Area Studies Review
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• v.14 no.1
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• pp.55-76
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• 2010

This paper analyses interaction between yen/dollar exchange rates and NIKKEI index using bivariate GJR-GARCH(1,1) model. The data employed for the study is daily data series for the period of Jan. 4, 1995 through Aug. 30, 2009. One of main findings is that market inefficiency appears in the periods of financial crisis. Second, the volatility of exchange rates and stock returns has more increased in the wake of the volatility shock of the previous period during financial crisis than during non-financial crisis. Third, interestingly, the asymmetric volatility shock by bad news in those markets is bigger in financial crisis period than in non financial crisis. Fourth, in the period of current global financial crisis triggered by subprime mortgage crisis in U.S, volatility shock at the previous period is bigger than that of Asian financial crisis that happened in 1997. Lastly, the correlation between both returns of exchange rates and stock prices turns up positive according to the empirical estimation. This result may come from the fact that Japanese stock market does not have much attraction for international financial investment compared to stock markets of neighbouring countries like China, Korea and so on, while real sector's contribution to the economy is considered more importantly.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.34 no.2
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• pp.38-52
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• 2021

Objectives : The purpose of this study is to analyze the use of insured herbal extracts and Korean medicinal treatments, which are mainly used to treat allergic rhinitis in Korean medicine. Methods : Among all HIRA(Health Insurance Review and Assessment Service) claims data in 2016, we included all statements that included J30(vasomotor and allergic rhinitis) or a subcategory of J30(J30.0, J30.1, J30.2, J30.3, or J30.4) as the main disease, using the Korean Standard Classification of Diseases(KCD-7). This study analyzed the most frequently used insured herbal extracts and Korean medicinal treatments for allergic rhinitis in Korean medicine. We performed a frequency analysis on subgroups based on treatment type(inpatient or outpatient), sex, age, insurance type, and medical institution type. Results : The result shows the 10 most frequently used insured herbal extracts and Korean medicinal treatments for allergic rhinitis. The total number of insured herbal extracts prescriptions was 82,533, and the most commonly prescribed insured herbal extracts was socheongryong-tang(35,131 prescriptions), followed by hyeonggaeyeongyo-tang(18,157 prescriptions), samsoeum(6,257 prescriptions), and galgeun-tang(4,465 prescriptions). The total number of Korean medicinal treatments prescriptions was 1,878,541, of which the most common Korean medicinal treatments was acupuncture(922,977 prescriptions), followed by moxibustion(372,120 prescriptions), cupping(242,094 prescriptions), and segmental acupuncture(161,553 prescriptions). Conclusions : It is expected that the results of this study can be used as a basis for establishing the priorities of evidence-based clinical research topics in the field of Korean medicine and making health care policy decisions to strengthen coverage in the future.