• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.2
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• pp.62-72
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• 2019

Due to the difficulties in forecasting the intensity and the source location of tsunami the countermeasures prepared based on the deterministic approach fail to work properly. Thus, there is an increasing demand of the tsunami hazard analyses that consider the uncertainties of tsunami behavior in probabilistic approach. In this paper a fundamental study is conducted to perform the probabilistic tsunami hazard analysis (PTHA) for the tsunamis that caused the disaster to the east coast of Korea. A logic tree approach is employed to consider the uncertainties of the initial free surface displacement and the tsunami height distribution along the coast. The branches of the logic tree are constructed by reflecting characteristics of tsunamis that have attacked the east coast of Korea. The computational time is nonlinearly increasing if the number of branches increases in the process of extracting the fractile curves. Thus, an improved method valid even for the case of a huge number of branches is proposed to save the computational time. The performance of the discrete weight distribution method proposed first in this study is compared with those of the conventional sorting method and the Monte Carlo method. The present method is comparable to the conventional methods in its accuracy, and is efficient in the sense of computational time when compared with the conventional sorting method. The Monte Carlo method, however, is more efficient than the other two methods if the number of branches and the number of fault segments increase significantly.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.763-776
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• 2020

Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.35-44
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• 2022

In this study, we analyze and forecast quantum computer technology trends. Previous research has been mainly focused on application fields centered on technology for quantum computer technology trends analysis. Therefore, this paper analyzes important quantum computer technologies and performs future signal detection and prediction, for a more market driven technical analysis and prediction. As analyzing words used in news articles to identify rapidly changing market changes and public interest. This paper extends conference presentation of Cha & Chang (2022). The research is conducted by collecting domestic news articles from 2019 to 2021. First, we organize the main keywords through text mining. Next, we explore future quantum computer technologies through analysis of Term Frequency - Inverse Document Frequency(TF-IDF), Key Issue Map(KIM), and Key Emergence Map (KEM). Finally, the relationship between future technologies and supply and demand is identified through random forests, decision trees, and correlation analysis. As results of the study, the interest in artificial intelligence was the highest in frequency analysis, keyword diffusion and visibility analysis. In terms of cyber-security, the rate of mention in news articles is getting overwhelmingly higher than that of other technologies. Quantum communication, resistant cryptography, and augmented reality also showed a high rate of increase in interest. These results show that the expectation is high for applying trend technology in the market. The results of this study can be applied to identifying areas of interest in the quantum computer market and establishing a response system related to technology investment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.83-94
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• 2022

The number of public rental housing has increased according to the government's 「Housing Welfare Roadmap (2017)」, and facility maintenance costs for the demand of improvement of performance and residential standards due to the aging of long-term public housing are significantly increasing. Consequently, the financial burden of public housing rental business for maintaining stocked housing is aggravated. However, there is a lack of objective data to analyze the size of the maintenance costs that are executed by the type of repair work, and the elapsed years of the aged long-term public rental housing. This study analyzes the execution status of 33 long-term public rental housing complexes located in Seoul for 14 to 28 years of elapsed years based on the data of maintenance costs. In addition, this study proposes a model to predict the maintenance costs by elapsed years by dividing 'Long-term Repair Plan Work and Government-Funded Project [Y₁]', 'Planned Repair Work and General & Unplanned Repair Work [Y₂]', and 'Total maintenance costs [Y₃]'. It is intended to be used as basic data for the establishment of the maintenance plan at the stage of setting up the budget and the establishment of the sustainable operation plan for public rental housing

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.146-164
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• 2022

Recently, the Korean government promoted the construction of metropolitan express subway to connect major transportation hub in the metropolitan area within 30 minutes. Most stations of the metropolitan express subway are connected to existing subway stations, so the importance of transfer increased. Although many studies have been conducted on the effect of transfer penalty on route choice, there are few studies on the transfer behavior of the metropolitan express subway. Therefore, in this study, a transfer behavior analysis was conducted on the Shinbundang Line, a representative metropolitan express subway. To analyze the transfer behavior according to the degree of traffic congestion and the presence of fare payment, route choice models were made using transport card data divided according to week, time, and user characteristics. As a result of the analysis, users of the metropolitan express subway had greater disutility to the transfer waiting time compared to the transfer moving time. Furthermore, especially during the peak time, EIVM(Equivalent in-vehicle minutes) of the transfer waiting time was 3.51. In this study, EIVM for metropolitan express subway users were analyzed to be 2.6 minutes, which is significantly lower than the results of previous studies on subways. This suggests that there is a difference in the transfer penalty between subways and metropolitan express subway, and that it is necessary to apply the transfer penalty between subways and express subway differently when forecasting subway traffic demand.

• Analyses & Alternatives
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• v.1 no.2
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• pp.31-43
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• 2017

The article is devoted to the theoretical and practical analysis of Chinese global leadership. The concept of leadership is applied as a methodology, which involves identifying the main factors, such as strategic power, the attractiveness of political institutions, the ability to provide acceptable ideas and the presence of allies that contribute to a comprehensive analysis of the country's leadership potential. The authors also describe the relevance of Chinese global leadership and analyze its domestic, economic and international causes. Moreover, the ''Belt and Road'' initiative is defined as the main mechanism for providing the influence of China on the global level which is now being changed its quantitative component, namely the increasing attention to the security aspects of this initiative. In addition to that, it is important to note that China maintains its economic and political positions in Africa, Central Asia and South-East Asia. Africa has a special role in the Chinese ''Belt and Road'' initiative as a recipient of Chinese investments and a site for the deployment of China's naval facilities to protect the trade routes. On the regional level, China will strive to become a leader of the trade and economic processes in the Asia-Pacific region, the South China Sea and the North Korea nuclear program issues. The American factor in modern international relations, namely so-called "Trump factor", which means the U.S. withdrawal from the Trans-Pacific Partnership and the Paris Agreement, will cause demand for Chinese leadership in the Asia-Pacific region and in the world as well. However, in this case a number of questions arise: is China prepared for this? Is Beijing able to bear greater responsibility? Does China have the potential for this? The article concludes that China will not become global leaders in the next 20-30 years, because of internal (political reforms) and foreign policy reasons (doctrinal formulation of foreign policy initiatives, military-political and economic power, international posture and relations with other states). The authors believe that the implementation of Chinese leadership is possible not on the condition of confrontation between China and the United States, but on the establishing of constructive relations between these countries. The last meeting between Trump and Xi Jinping showed a trend for creating channels for dialogue between Beijing and Washington, which can become the basis for interaction. An important place in the work is given to the analysis of development and forecasting the evolution of Russian-Chinese and U.S.-China relations. As for Russia, Moscow should conduct a policy that will not allow it to become a ''junior partner'' of China.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.167-175
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• 2024

Due to the Fourth Industrial Revolution, ICT(Information and Communication Technology) industry is becoming more important and sophisticated than ever. In B2B based ICT industry demand forecasting by analyzing the previous customer data is so important. RFM, one of customer relationship management models is a marketing technique that evaluates Recency, Frequency and Monetary value to predict customers behavior. RFM model has been studied focusing on the B2C based industry. On the other hand there is a lack of research on B2B based technology industry. Therefore this study applied it to B2B based high technology industry and considered T(technology collaboration) value, which are identified as important factors in the technology industry. To present an improved model for market performance in B2B technology industry, an empirical study was conducted on comparing the accuracy of the traditional RFM model and the improved RFM-T model. The objective of this study is to contribute to market performance by presenting an improved model in B2B based high technology industry.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.75-84
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• 2023

Many developing countries face challenges in estimating long-term discharge due to the lack of hydrological data for water supply planning, making it difficult to establish a rational water supply plan for decision-making on water distribution. The study area, the Bandung region in Indonesia, is experiencing rapid urbanization and population concentration, leading to a severe shortage of freshwater. The absence of water reservoir prediction methods has resulted in a water supply rate of approximately 20%. In this study, we aimed to propose an approach for predicting water reservoirs in developing countries by analyzing water safety and potential water supply using the MODSIM (Modified SIMYLD) network model. To assess the suitability of the MODSIM model, we applied the unit hydrograph method to calculate long-term discharge based on 19 years of discharge data (2002-2020) from the Pataruman observation station. The analysis confirmed alignment with the existing monthly optimal operation curve. The analysis of power plant capacity revealed a difference of approximately 0.30% to 0.50%, and the water intake safety at the Pataruman point showed 1.64% for Q95% flow and 0.47% for Q355 flow higher. Operational efficiency, compared to the existing reservoir optimal operation curve, was measured at around 1%, confirming the potential of using the MODSIM network model for water supply evaluation and the need for water supply facilities.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.169-206
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• 2009

This study stems from a question, "How should we understand the pattern of the Korean economy after the 1990s?" Among various analytic methods applicable, this study chooses a Structural Vector Autoregression (SVAR) with long-run restrictions, identifies diverse impacts that gave rise to the current status of the Korean economy, and differentiates relative contributions of those impacts. To that end, SVAR is applied to four economic models; Blanchard and Quah (1989)'s 2-variable model, its 3-variable extensions, and the two other New Keynesian type linear models modified from Stock and Watson (2002). Especially, the latter two models are devised to reflect the recent transitions in the determination of foreign exchange rate (from a fixed rate regime to a flexible rate one) as well as the monetary policy rule (from aggregate targeting to inflation targeting). When organizing the assumed results in the form of impulse response and forecasting error variance decomposition, two common denominators are found as follows. First, changes in the rate of economic growth are mainly attributable to the impact on productivity, and such trend has grown strong since the 2000s, which indicates that Korea's economic growth since the 2000s has been closely associated with its potential growth rate. Second, the magnitude or consistency of impact responses tends to have subsided since the 2000s. Given Korea's high dependence on trade, it is possible that low interest rates, low inflation, steady growth, and the economic emergence of China as a world player have helped secure capital and demand for export and import, which therefore might reduced the impact of each sector on overall economic status. Despite the fact that a diverse mixture of models and impacts has been used for analysis, always two common findings are observed in the result. Therefore, it can be concluded that the decreased rate of economic growth of Korea since 2000 appears to be on the same track as the decrease in Korea's potential growth rate. The contents of this paper are constructed as follows: The second section observes the recent trend of the economic development of Korea and related Korean articles, which might help in clearly defining the scope and analytic methodology of this study. The third section provides an analysis model to be used in this study, which is Structural VAR as mentioned above. Variables used, estimation equations, and identification conditions of impacts are explained. The fourth section reports estimation results derived by the previously introduced model, and the fifth section concludes.