• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.80.1-80.1
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• 2019

Photometric investigations of asteroids allow us to determine their rotation states and shape models (Apostolovska et al. 2014). Our main target, asteroid (2078) Nanking's perihelion distance (q) is 1.480 AU, which belongs to the Mars-crossing asteroid (1.3 < q < 1.66 AU). Mars-crossing asteroids are objects that cross the orbit of Mars and regarded as one of the primary sources of near-Earth asteroids due to the unstable nature of their orbits. We present the analysis of the spin parameters and 3D shape model of (2078) Nanking. We conducted Cousins_R-band time-series photometry of this asteroid from November 26, 2014 to January 17, 2015 at the Sobaeksan Optical Astronomy Observatory (SOAO) and for 25 nights from March to April 2016 using the Korea Microlensing Telescope Network (KMTNet) to reconstruct its physical model with our dense photometric datasets. Using the lightcurve inversion method (Kaasalainen & Torppa 2001; Kaasalainen et al. 2001), we determine the pole orientation and shape model of this object based on our lightcurves along with the archival data obtained from the literatures. We derived rotational period of 6.461 h, the preliminary ecliptic longitude (${\lambda}_p$) and latitude (${\beta}_p$) of its pole as ${\lambda}_p{\sim}8^{\circ}$ and ${\beta}_p{\sim}-52^{\circ}$ which indicates a retrograde rotation of the body. From the apparent W UMa-shaped lightcurve and its location in the rotation frequency-amplitude plot of Sheppard and Jewitt (2004), we suspect the contact binary nature of the body (Choi 2016).

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.135-144
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• 2021

This paper attempted to find implications for water resource management and water quality improvement by analyzing the causal relationship among discharge, water temperature and pollution index, which were expected to have a great effect on water quality with the rise of water temperature and precipitation change as the warming effect in recent years. For this purpose, the unit root test, cointegration test, and Granger causal test were carried out for 10 multi-purpose dams in Korean major water systems using time series data on discharge, water temperature, BOD, COD and DO. It was analyzed that the fluctuation of water temperature affected the pollution index more than the fluctuation of discharge volume. Also, Hapcheon dam and Chungju dam were the best water quality management dams based on the high causal relationship between water quality and discharge. The second rank was Daecheong dam. The third-ranking group were Yongdam and Andong dam, whose causal relationships between water quality and discharge were low. The last group were the remaining five dams.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.523-532
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• 2011

In this study, from 2004 to 2008 influents and discharging effluents from 241 municipal public sewage treatment plants were surveyed. Statistics including average, Coefficient of Variation (CV) and Coefficient of Reliability (COR) for each season, time series analysis for removal efficiency and water quality of effluents, and a comparison of the effluent standards in Korea and other countries were presented. The average concentrations of TN and TP in influents. during winter season were 32.6 and 3.78 mg/L and during other season were 30.8 and 3.61 mg/L in 2008, respectively. The average TN concentration on the basis of the maximum monthly concentrations in the effluents during winter season ranged from 14.2~17.4 mg/L and during other season ranged from 12.2~14.8 mg/L. The TP concentration in the effluents depending on the each season was no big difference. TN removal efficiency decreased from Jan. to Feb. and TP removal efficiency decreased in Jan., Jun and July. Maximum COR during winter season were 0.61 but the COR for TN and TP during other season ranged from 0.96~1.48 and 1.09~1.81, respectively, due to big difference in the standard for TN and TP in effluents depending on the season. TN and TP standards for effluent of sewage treatment during winter season in Korea was much higher than those in other countries. Therefore the lower effluent standards during winter season is essential for the water quality improvement.

• The Journal of Bigdata
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• v.5 no.2
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• pp.111-120
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• 2020

Despite the recent economic contraction caused by the Corona 19 incident, interest in the residential environment is growing as more people live at home due to the increase in telecommuting, thereby increasing demand for remodeling. In addition, the government's real estate policy is also expected to have a visible impact on the sales of the interior and furniture industries as it shifts from regulatory policy to the expansion of housing supply. Accurate demand forecasting is a problem directly related to inventory management, and a good demand forecast can reduce logistics and inventory costs due to overproduction by eliminating the need to have unnecessary inventory. However, it is a difficult problem to predict accurate demand because external factors such as constantly changing economic trends, market trends, and social issues must be taken into account. In this study, LSTM model and 1D-CNN model were compared and analyzed by artificial intelligence-based time series analysis method to produce reliable results for manufacturers producing furniture components.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.689-696
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• 2020

It is known through prior research that the crust of the Korean Peninsula moves southeast at an annual average of 3 cm/year. The 2011 Great East Japan Earthquake caused a great change in the crust of the Korean Peninsula. Since then, the frequency of earthquakes has increased on the Korean Peninsula. Therefore, by using NGII and IGS GNSS observation data of the recent 15 years, to analyze the trends of changes in the deformation of the Korean Peninsula before and after the outbreak of the Great East Japan Earthquake. Data processing utilized Bernese Software V5.2, a widely used scientific and technical software around the world. As a result, the global movement of the Korean peninsula differed by about 4mm and the direction of movement by about 10° compared to before the Great East Japan Earthquake. As for the internal distortion of the Korean Peninsula, the East-West expansion of the Korean peninsula's crust was observed during the Great East Japan Earthquake, but it is believed that it has not fully returned to the level before the Great East Japan Earthquake.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.131-144
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• 2020

As the blockchain technology attracts attention, interest in cryptocurrency that is received as a reward is also increasing. Currently, investments and transactions are continuing with the expectation and increasing value of cryptocurrency. Accordingly, prediction for cryptocurrency price has been attempted through artificial intelligence technology and social sentiment analysis. The purpose of this paper is to develop a deep learning ensemble model for predicting the price fluctuations and one-day lag price of cryptocurrency based on the design science research method. This paper intends to perform predictive modeling on Ethereum among cryptocurrencies to make predictions more efficiently and accurately than existing models. Therefore, it collects data for five years related to Ethereum price and performs pre-processing through customized functions. In the model development stage, four LSTM models, which are efficient for time series data processing, are utilized to build an ensemble model with the optimal combination of hyperparameters found in the experimental process. Then, based on the performance evaluation scale, the superiority of the model is evaluated through comparison with other deep learning models. The results of this paper have a practical contribution that can be used as a model that shows high performance and predictive rate for cryptocurrency price prediction and price fluctuations. Besides, it shows academic contribution in that it improves the quality of research by following scientific design research procedures that solve scientific problems and create and evaluate new and innovative products in the field of information systems.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.67-87
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• 2021

Provisioning service, which is one of the ecosystem service functions, means goods and services such as food and fuel that people get from ecosystem. Provisioning functions are closely related to the primary industry, a sector of economy. Excessive demand and use of human society can cause trade-offs among regulation, cultural, and supporting services. Therefore, it is important to perform evaluation ecosystem services periodically and to monitor the time series fluctuations to identify the impact of provisioning services on other ecosystem services (trade-off) and to maintain sustainable provisioning service. When it comes to the precise assessment of provisioning service, it is necessary to get the statistical data and standardize indicators and methods. In this study, indicators and methods, which are applicable to the spatial level of national-local-protected areas, were derived through literature analysis and expert survey. The result of this study implies that provisioning services measurement by spatial level improve the efficiency of the establishment of environmental conservation plans by whose purpose.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.1-14
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• 2022

This study aims to identify topics in newspaper articles related to fine particle matter and to investigate the characteristics and time series trend of each topic. Related national newspaper articles during 1990 and 2021 were collected from Bigkinds. A total of 18 topics have been discovered using LDA, and 11 clusters deduced from clustering. Hot topics include related products/residence, overseas cause(China), power plant as a domestic cause, nationwide emergency reduction measures, international cooperation, political issues, current situation & countermeasure in other countries, and consumption patterns. Cold topics include the concentration standard and indoor air quality improvement. These findings would be useful in inferring the political direction and strategies. In particular, the consumer protection policy should be expanded as the related market is growing. It will also be necessary to pursue policies that will promote public safety and health, and that will enhance public consensus and international cooperation.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.495-504
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• 2022

With the recent development of artificial intelligence, a Long Short-Term Memory (LSTM) model that is efficient with time-series analysis is being used to increase the accuracy of predicting the inflow of dams. In this study, we predict the inflow of the Soyang River dam, using the LSTM model with the Sequence-to-Sequence (LSTM-s2s) and attention mechanism (LSTM-s2s with attention) that can further improve the LSTM performance. Hourly inflow, temperature, and precipitation data from 2013 to 2020 were used to train the model, and validate and test for evaluating the performance of the models. As a result, the LSTM-s2s with attention showed better performance than the LSTM-s2s in general as well as in predicting a peak value. Both models captured the inflow pattern during the peaks but detailed hourly variability is limitedly simulated. We conclude that the proposed LSTM-s2s with attention can improve inflow forecasting despite its limits in hourly prediction.

• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.631-644
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• 2022

This paper considers robust estimation of the sparse vector autoregressive model (sVAR) useful in high-dimensional time series analysis. First, we generalize the result of Xu et al. (2008) that the adaptive lasso indeed has robustness in sVAR as well. However, adaptive lasso method in sVAR performs poorly as the number and sizes of outliers increases. Therefore, we propose new robust estimation methods for sVAR based on least absolute deviation (LAD) and Huber estimation. Our simulation results show that our proposed methods provide more accurate estimation in turn showed better forecasting performance when outliers exist. In addition, we applied our proposed methods to power usage data and confirmed that there are unignorable outliers and robust estimation taking such outliers into account improves forecasting.