• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.677-692
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• 2018

The total fertility rate of Korea was 1.05 in 2017, showing a return to the 1.08 level in the year 2005. 1.05 is a very low fertility level that is far from replacement level fertility or safety zone 1.5. The number may indicate a low fertility trap. It is therefore important to predict fertility than at any other time. In the meantime, we have predicted the age-specific fertility rate and total fertility rate by various statistical methods. When the data trend is disconnected or fluctuating, it applied a nonparametric method applying the smoothness and weight. In addition, the Bayesian method of using the pre-distribution of fertility rates in advanced countries with reference to the three-stage transition phenomenon have been applied. This paper examines which method is reasonable in terms of precision and feasibility by applying estimation, forecasting, and comparing the results of the recent variability of the Korean fertility rate with parametric, non-parametric and Bayesian methods. The results of the analysis showed that the total fertility rate was in the order of KOSTAT's total fertility rate, Bayesian, parametric and non-parametric method outcomes. Given the level of TFR 1.05 in 2017, the predicted total fertility rate derived from the parametric and nonparametric models is most reasonable. In addition, if a fertility rate data is highly complete and a quality is good, the parametric model approach is superior to other methods in terms of parameter estimation, calculation efficiency and goodness-of-fit.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.323-345
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• 2019

It is essential to predict ground conditions ahead of a tunnel face in order to successfully excavate tunnels using a shield TBM. This study proposes a forward prediction method for a mixed soil ground and/or a ground containing core stones by using electrical resistivity and induced polarization exploration. Soil conditioning in EPB shield TBM is dependent upon the composition of mixed soils; a special care need to be taken when excavating the core-stoned soil ground using TBM. The resistivity and chargeability are assumed to be measured with four electrodes at the tunnel face, whenever the excavation is stopped to assemble one ring of a segment lining. Firstly, the mixed ground consisting of weathered granite soil, sand, and clay was modeled in laboratory-scale experiments. Experimental results show that the measured electrical resistivity considerably coincides with the analytical solution. On the other hand, the induced polarization has either same or opposite trend with the measured resistivity depending on the mixed ground conditions. Based on these experimental results, a method to predict the mixed soil ground that can be used during TBM tunnel driving is suggested. Secondly, tunnel excavation from a homogeneous ground to a ground containing core stones was modeled in laboratory scale; the irregularity of the core stones contained in the soil layer was modeled through random number generation scheme. Experimental results show that as the TBM approaches the ground that contains core stones, the electrical resistivity increases and the induced polarization fluctuates.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.104-114
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• 2019

In the global market competition, countries and businesses are actively engaged in technology prediction activities to maximize their profits by attempting to enter and preempting the core technology of the future. In this paper, we propose a growth model based on patent application trends to predict the time to replace a product with a promising new technology to dominate the market. Although the Fisher-Pry model that Bhargava generalized to predict the emergence of promising alternative technologies was relatively satisfactory compared to the original Fisher-Pry model, it was difficult to predict the replacement rate behavior properly due to a parameter problem. The application of the Fisher-Pry Modification Model in the form of a quadratic equation through the patent trend analysis of the optical storage system for the purpose of verifying the time alternative to the light storage technology has resulted in satisfactory verification results. It is expected that small and medium-sized companies and individual researchers will apply this model and use it more easily to predict the time to replace the market for promising replacement technologies.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2873-2881
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• 2018

It is very important to obtain objective and credible information through election polls in order to contribute to the correct voting behavior of the voters or to establish appropriate election strategies for candidates or political parties. Therefore, many related organizations such as political parties, media organizations, and research institutions have been making efforts to improve the accuracy of the results of the polls and the election prediction. Kim et al. (2017) analyzed whether the non-response group responded that there is no support candidate in the election survey to increase the accuracy of the estimation of the vote rate. As a result, it has been confirmed that the accuracy of the estimation of the vote rate can be significantly improved by performing an appropriate classification on the non-response layer. In this study, we propose a method to estimate the turnout by each strata (sex, age group) under the condition that the total turnout rate is given for a specific district (region) and propose a procedure to predict the vote rate by reflecting the turnout. In addition, case studies were conducted using data gathered through telephone interviews for the 20th National Assembly elections in 2016.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.3
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• pp.183-198
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• 2021

The EPB (Earth Pressure Balanced) shield TBM method restrains the ground deformation through continuous excavation and support. Still, the significant surface settlement occurs due to the ground conditions, tunnel dimensions, and construction conditions. Therefore, it is necessary to clarify the settlement behavior with its influence factors and evaluate the possible settlement during construction. In this study, the analytical model of surface settlement based on the influence factors and their mechanisms were proposed. Then, the parametric study for controllable factors during excavation was conducted by numerical method. Through the numerical analysis, the settlement behavior according to the construction conditions was quantitatively derived. Then, the qualitative trend according to the ground conditions was visualized by coupling the numerical results with the analytical model of settlement. Based on the results of this study, it is expected to contribute to the derivation of the settlement prediction algorithm for EPB shield TBM excavation.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.87-95
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• 2020

The Incheon airport is a gateway to and from the Republic of Korea and has a great influence on the image of the country. Therefore, it is necessary to predict the number of airport passengers in the long term in order to maintain the quality of service at the airport. In this study, we compared the predictive performance of various time series models to predict the air passenger demand at Incheon Airport. From 2002 to 2019, passenger data include trend and seasonality. We considered the naive method, decomposition method, exponential smoothing method, SARIMA, PROPHET. In order to compare the capacity and number of passengers at Incheon Airport in the future, the short-term, mid-term, and long-term was forecasted by time series models. For the short-term forecast, the exponential smoothing model, which weighted the recent data, was excellent, and the number of annual users in 2020 will be about 73.5 million. For the medium-term forecast, the SARIMA model considering stationarity was excellent, and the annual number of air passengers in 2022 will be around 79.8 million. The PROPHET model was excellent for long-term prediction and the annual number of passengers is expected to be about 99.0 million in 2024.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.165-175
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• 2022

Earthquakes have occurred owing to movements on a fault since several billion years ago. Research on the relationship between earthquakes and groundwater began in the 1960s in the United States, but related works, including hydrogeochemistry research, only began in the 2010s in South Korea. In this study, domestic studies on the relationship between earthquakes and groundwater until 2021 were collected from the Web of Science and characterized by subject area (groundwater level, hydrogeochemistry, combination of the two, and others). The results showed that the number of published articles per year was positively correlated with the 2011 Tohoku earthquake, 2016 Gyeongju earthquake, and 2017 Pohang earthquake, with the maximum numbers observed in 2011, 2018, 2019, and 2020. Most studies on the relationship between earthquakes and groundwater level addressed groundwater level fluctuations in the duration of the subject earthquake, with little consideration of the precursors. Groundwater level monitoring data, as well as hydrogeochemical information and microbial communities, may contribute to a more detailed understanding of groundwater flow and chemical reactions in bedrock caused by earthquakes. Therefore, the establishment of a national groundwater monitoring network for seismic monitoring and prediction is required.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.81-93
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• 2022

The stock investing is one of the most popular investment techniques. However, since it is not easy to obtain a return through actual investment, various strategies have been devised and tried in the past to obtain an effective and stable return. Among them, the volatility breakout strategy identifies a strong uptrend that exceeds a certain level on a daily basis as a breakout signal, follows the uptrend, and quickly earns daily returns. It is one of the popular investment strategies that are widely used to realize profits. However, it is difficult to predict stock prices by understanding the price trend pattern of stocks. In this paper, we propose a method of buying and selling stocks by predicting the return in trading based on the volatility breakout strategy using a bi-directional long short-term memory deep neural network that can realize a return in a short period of time. As a result of the experiment assuming actual trading on the test data with the learned model, it can be seen that the results outperform both the return and stability compared to the existing closing price prediction model using the long-short-term memory deep neural network model.

• Journal of Space Technology and Applications
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• v.1 no.2
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• pp.178-198
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• 2021

The Solar Space Environment Division of the Korean Society of Space Science (KSSS) has recently conducted a survey among the domestic researchers affiliated with academia, national research institutes, and for-profit institutes of how the data and models in their professional research field are produced, maintained, and utilized. The primary purpose of this survey is to increase the awareness and utilization of the space environment data and models as well as to promote constructive collaborations among the domestic and international researchers. The models and data surveyed are categorized into three sub-fields: the solar and interplanetary space, the (terrestrial) magnetosphere, and the ionosphere and upper atmosphere. The present paper reports the survey results in the "Magnetosphere" category. The survey shows that the domestically produced data in this category are far less than the data produced in other categories. This can be understood in part as follows: Magnetospheric research relies heavily on the in-situ observations but the development and operation of space-hardened satellites require a significant investment. Nevertheless, the recent publications show an increasing trend of research using the data from the ground stations and the recently launched domestic space missions. In the modeling front, there are first-principles physics models covering from the magnetospheric scale to the sub-ion scale and the models geared towards the space weather prediction. The detailed survey results can be accessed from the KSSS website (http://ksss.or.kr/).

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.