• Smart Media Journal
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• v.9 no.4
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• pp.26-35
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• 2020

Attempts to predict future stock prices have been studied steadily since the past. However, unlike general time-series data, financial time-series data has various obstacles to making predictions such as non-stationarity, long-term dependence, and non-linearity. In addition, variables of a wide range of data have limitations in the selection by humans, and the model should be able to automatically extract variables well. In this paper, we propose a 'sliding time step normalization' method that can normalize non-stationary data and LSTM autoencoder to compress variables from all variables. and 'moving transfer learning', which divides periods and performs transfer learning. In addition, the experiment shows that the performance is superior when using as many variables as possible through the neural network rather than using only 100 major financial variables and by using 'sliding time step normalization' to normalize the non-stationarity of data in all sections, it is shown to be effective in improving performance. 'moving transfer learning' shows that it is effective in improving the performance in long test intervals by evaluating the performance of the model and performing transfer learning in the test interval for each step.

• Atmosphere
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• v.30 no.4
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• pp.377-390
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• 2020

Not only emissions, but also atmospheric circulation is a key factor that affects local particulate matters (PM) concentrations in Korea through ventilation effects and transboundary transports. As part of the atmospheric circulation, air stagnation especially adversely affects local air quality due to weak ventilation. This study investigates the large-scale circulation related to air stagnation over Korea during winter and projects the climate change impacts on atmospheric patterns, using observed PM data, reanalysis and regional climate projections from HadGEM3-RA with Modified Korea Particulate matter Index. Results show that the stagnation affects the PM concentration, accompanied by pressure ridge at upper troposphere and weaken zonal pressure gradient at lower troposphere. Downscaling using HadGEM3-RA is found to yield Added-Value in the simulated low tropospheric winds. For projection of future stagnation, SSP5-8.5 and SSP1-2.6 (high and low emission) scenarios are used here. It has been found that the stagnation condition occurs more frequently by 11% under SSP5-8.5 and by 5% under SSP1-2.6 than in present-day climate and is most affected by changes in surface wind speed. The increase in the stagnation conditions is related to anticyclonic circulation anomaly at upper troposphere and weaken meridional pressure gradient at lower troposphere. Considering that the present East Asian winter monsoon is mainly affected by change in zonal pressure gradient, it is worth paying attention to this change in the meridional gradient. Our results suggest that future warming condition increase the frequency of air stagnation over Korea during winter with response of atmospheric circulation and its nonlinearity.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.77-90
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• 2022

Despite the decreasing trend of anthropogenic emissions in East Asia in recent years, haze days still frequently occur in spring. Atmospheric blocking, which occurs frequently in the northeastern Pacific, leads to persistent changes in large-scale circulation and blocks westerly flow in the East Asian region. During March 2019, frequent warm and stagnant synoptic meteorological conditions over East Asia were accompanied 6-7 days later by the Alaskan atmospheric blocking. The Alaskan atmospheric blocking over the period of March 18-24, 2019 led to high particulate matter (PM₁₀) severe haze days exceeding a daily average of 50 ㎍ m^-3 over the period of March 25-28, 2019 in South Korea. Although the high-PM₁₀ severe haze days were caused by warm and stagnant meteorological conditions, the regional contribution of anthropogenic emissions in eastern China was calculated to be 30-40% using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The major regional contributions of PM₁₀ aerosols in the period of high-PM₁₀ severe haze days were as follows: nitrates, 20-25%; sulphates, 10-15%; ammonium, 5-10%; and other inorganics, 15-20%. Ammonium nitrate generated via gas-to-aerosol conversion in a warm and stagnant atmosphere largely contributed to the regional transport of PM₁₀ aerosols in the high-PM₁₀ severe haze days in South Korea.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.610-622
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• 2021

The DECOVALEX project is one of the representative international cooperative projects to enhance the understanding of the complex Thermo-Hydro-Mechanical-Chemical(THMC) coupled behavior in the high-level radioactive waste disposal system based on the numerical simulation. DECOVALEX-2023 is the current phase consisting of 7 tasks, and Task C aims to model the THM coupled behavior in the disposal system based on the Full-scale Emplacement (FE) experiment at the Mont-Terri underground rock laboratory. This study performs the numerical simulation based on the OGS-FLAC developed for the current study. In the numerical model, we emplaced the heater with constant power horizontally based on the FE experiment and monitored the pressure development, temperature increase, and mechanical deformation at the specific monitoring points. We monitored the capillary pressure as the primary effect inducing the flow in the buffer system, and thermal stress and pressurization were dominant in the surrounding rocks' area. The results will also be compared and validated with the other participating groups and the experimental data further.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.369-381
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• 2021

Artificial Intelligence(AI) technology can be used in arts exhibitions ranging from planning exhibitions, filed progress, and evaluation. AI has been expanded its scope from planning exhibition and guidance services to tools for creating arts. This paper focuses on chatbots that utilize exhibition and AI technology convergence to provide information and services. To study more specifically, I developed a chatbot for exhibition services using the Naver Clova chatbot tool and information from the National Museum of Modern and Contemporary Art(MMCA), Korea. In this study, information was limited to viewing and exhibition rather than all information of the MMCA, and the chatbot was developed which provides a scenario type to get an answering user want to gain through a button and a text question and answer(Q&A) type to directly input a question. As a result of evaluating the chatbot with six items according to ELIZA's chatbot evaluation scale, a score of 4.2 out of 5 was derived by completing the development of a chatbot to be used to deliver viewing and exhibition information. The future research task is to create a perfect chatbot model that can be used in an actual arts exhibition space by connecting the developed chatbot with continuous scenario answers, resolving text Q&A-type answer failures and errors, and expanding additional services.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.553-568
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• 2022

The Household Income and Expenditure Survey is a representative survey of Statistics Korea, which aims to measure and analyze national income and consumption levels and their changes by understanding the current state of household balances. Recently, the disconnection problem in these time series caused by the large-scale reorganization of the survey methods in 2017 and 2019 has become an issue. In this study, we model the characteristics of the time series in the Household Income and Expenditure Survey up to 2016, and use the modeling to compute forecasts for linking the expenditures in 2017 and 2018. In order to evenly reflect the characteristics across all expenditure item series and to reduce the impact of a specific forecast model, we synthesize a total of 8 models such as regression models, time series models, and machine learning techniques. In particular, the noteworthy aspect of this study is that it improves the forecast by using the optimal combination technique that can exactly reflect the hierarchical structure of the Household Income and Expenditure Survey without loss of information as in the top-down or bottom-up methods. As a result of applying the proposed method to forecast expenditure series from 2017 to 2019, it contributed to the recovery of time series linkage and improved the forecast. In addition, it was confirmed that the hierarchical time series forecasts by the optimal combination method make linkage results closer to the actual survey series.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.95-105
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• 2022

Recently, as the scale of a construction project has become larger and more complicated, there are many cases where construction projects with complex structures are carried out in a fast track method to save construction duration. In the fast track method, the proper division of construction phases is an important issue in determining the overall project period. This study presents a rational phase division method that can be applied when a construction project with complex structures is carried out as a fast track. For this study, a subdivided work breakdown structure (WBS) is developed using the construction of 4 soccer stadiums as application examples, and the schedule is analyzed by dividing the construction process of major phases. To this end, five proposals are applied to analyze the adequacy of the fast track phase division. For the draft with the minimum construction period, the fast track phase division and the schedule model of by each phase were presented. This methodology can have an application in the appropriate phase division and schedule model by construction phase when fast track is applied in large construction project of a similar size.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.639-650
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• 2022

In areas where large-scale sediment transport occurs, it is important to apply appropriate countermeasure method because the phenomenon tends to accelerate by time duration. Among the various countermeasure methods applied so far, beach nourishment needs to be reviewed as an erosion prevention measure because the erosion pattern is mitigated and environmentally friendly depending on the particle size. In the case of beach nourishment. a detailed review is required to determine the size, range, etc., of an appropriate particle diameter. In this study, we investigated the characteristics of the related topographic change using the change in the particle size of nourishment materials, the application of partial area, and the condition under the coexistence of waves and wind as variables because those factors are hard to be analyzed and interpreted within results and limitation of that the existing numerical models are not able to calculate and result out so that it is required that phenomenon or efforts are reviewed at the same time through physical model experiments, field monitoring and etc. So we attempt to reproduce the tendency of beach erosion and deposition and predict possible phenomena in the future using machine learning techniques for phenomena that it is not able to be interpreted by numerical models. we used the hydraulic experiment results for the training data, and the accuracy of the prediction results according to the change in the training method was simultaneously analyzed. As a result of the study it was found that topographic changes using machine learning tended to be similar to those of previous studies in short-term predictions, but we also found differences in the formation of scour and sandbars.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.349-359
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• 2022

At present, with the diversified development of the global economy, the trade of cultural products has become an important factor affecting the competition of comprehensive strength among countries. As a neighboring country to China, South Korea has a similar cultural development environment to China. As an important pillar of South Korea's economy, cultural product trade, its development experience has reference significance for China. This paper adopts literature research method, comparative analysis method and empirical analysis method to conduct research. The article firstly analyzes the export level of China and South Korea from the scale of the import and export of cultural products, and finds the difference between the import and export of cultural products between the two countries. Then, it compares and analyzes the insufficiency of China's cultural product trade structure and the advantage of Korea's cultural product trade structure. Finally, this paper uses the stochastic frontier gravity model to conduct empirical analysis and draws relevant conclusions about the trade potential of cultural products between China and South Korea. The research results show that: (1) the international competitiveness of cultural products trade in China and South Korea is relatively high, but the competitiveness of China's cultural products has been improved slowly; (2) compared with South Korea, China's cultural product exports are affected by trade inefficiency factors larger. (3) The improvement of government efficiency has a great effect on reducing the inefficiency of trade in China.

• Journal of the Korean earth science society
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• v.42 no.2
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• pp.149-163
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• 2021

In this study, the changes in ozone (O3) concentrations due to the removal of power plant emissions were analyzed using a community multi-scale air quality (CMAQ) model. Two different CMAQ model simulations, one considering the emissions from the Hadong power plant and one without considering the emissions, were conducted to investigate the effect of the emissions on the changes in the O3 concentrations in the surrounding areas. Subsequently, the CMAQ simulations exhibited an increase in the O3 concentration (25.24%) despite a decrease in the NOx (-18.87%) and volatile organic carbon (VOC, -11.27%) concentrations, which are major O3 precursors. The changes in the NO and O3 concentrations due to the removal of power plant emissions presented a strong negative correlation (r= -0.72). This indicated that the increase in the O3 concentration was mainly attributed to the significantly decreased NO concentration, thus, mitigating the O3 titration reaction (NO+O3→NO2+O2). Additionally, due to the VOC-limited (i.e., NOx-saturated) conditions in the study region, NO affected the O3 concentration, indicating that the O3 concentrations in a particular region are not only proportional to the increase or decrease in emissions. Therefore, an in-depth understanding of the chemical O3 production and loss in a particular region is necessary to accurately evaluate the effect of emission control on the changes in the O3 concentration.