• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.27-45
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• 2021

The purpose of this study is to trace the path of policy for urban parks and greenbelts (PUPG) pursued by Seoul Mayor Kim Hyeon-ok, who was a protagonist of Seoul's modernization and to reveal the policy's characteristics. A high modernism perspective was projected to advance his PUPG discussion. High modernism was an unavoidable phenomenon that appeared in post-war urban reconstruction projects and emerged in the form of a belief that the national elite creates the ideal social order and rational planning. Its characteristics were to build with legibility, immediacy, and convenience by power, with private participation and profit creation, while realizing the spectacle of "the city being built". As a high-modernist, Seoul Mayor Kim Hyun-ok's urban planning aimed to deal with the booming population and the expansion of Seoul's territory. Although his PUPG extended the parks to the outskirts of Seoul, he showed a dualistic attitude, diverting parks away from the city center. On the other hand, he induced the participation of the private sector to create parks. However, he showed the other side of modernization, eliminating the placeness and excluding related systems. The path taken by Mayor Kim Hyun-ok's PUPG was started to respond to population growth and resolve the encroachment of parks. The ultimate goal was to accept the realization of urban planning and experiment with non-financial methods. The characteristics of his PUPG reflecting high modernism were: First, elites were represented in the National Land Planning Association, HURPI, and Jang Moon-gi participated; second, legibility was ensured by using east-west and north-south axes, elevation standards, and rational planning. Third, parks were quickly released to respond to the rapid urban change. Fourth, it showed off events and spectacles to attract private capital.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.49-62
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• 2022

Realized volatility is well known to have long memory, strong association with other global financial markets and interdependences among macroeconomic indices such as exchange rate, oil price and interest rates. This paper proposes autoencoder factor-augmented heterogeneous autoregressive (AE-FAHAR) model for realized volatility forecasting. AE-FAHAR incorporates long memory using HAR structure, and exogenous variables into few factors summarized by autoencoder. Autoencoder requires intensive calculation due to its nonlinear structure, however, it is more suitable to summarize complex, possibly nonstationary high-dimensional time series. Our AE-FAHAR model is shown to have smaller out-of-sample forecasting error in empirical analysis. We also discuss pre-training, ensemble in autoencoder to reduce computational cost and estimation errors.

• Korean System Dynamics Review
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• v.7 no.2
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• pp.35-56
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• 2006

Korea is implementing strong regulatory derives such as Feed in Tariff to provide incentives for renewable energy developers. But if the government is planning to increase the renewable capacity with only "Price policy" not considering the investors behavior in the competitive electricity market, the policy would be failed. It is necessary system thinking and simulation model analysis to decide government's incentive goal. This study is focusing on the assesment of the competitiveness of renewable energy with the current Feed in Tariff incentives compared to the traditional energy source, specially coal and gas. The simulation results show that the market penetration of renewable energy with the current Feed-in-Tariff level is about 60-70% of the government goal under condition that the solar energy and fuel cell are assumed to provide the whole capacity set in the governmental goal. If the contribution from solar and fuel cell is lower than planned, the total penetration of renewable energy will be dropped more. Notably, Wind power turned out to be proved only 10% of government goal because of its low availability.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.87-95
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• 2007

On this study, we researched differences between 2D and 3D with principle of GUI with the estimate that the user interface will be changed to 3D and we figured out the special feature of 3d-GUI through 3 ways, Autonomy, Interaction and Presence. Based on this theory research, we also had a survey with difference of 3d and 2d GUI to forecast the possibility of 3d-GUI for the main user interface of the future media contents and finally found out its marketability as an ideal interface.

• The Journal of Information Technology
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• v.2 no.2
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• pp.107-125
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• 1999

The growing popularity of Internet and the technology revolution of information communication has affected our financial system, and electronic banking has increased its scale and range since '90. Now this changes, deeply and fast, invade the our economical-social environments. Without having to go to a bank, customer and merchants will be able to perform freely complicated financial transactions by accessing online banking network and CD/ATM etc. Customer can use the various payment method - cash, credit card, smart cards, electronic money in real world and cyberspace, and manager the assets more efficiently. They increased their money liquidity yet. Banks need to expand the various baskets of transaction services and methods to satisfy their customer needs and create new participator, Government had to evaluate and forecast the trend of electronic banking, and establish a new rules and standards in the new electronic payment system.

• Journal of Energy Engineering
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• v.22 no.3
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• pp.283-286
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• 2013

The existing nuclear power plants have been often redesigned by increasing or decreasing electrical power without changing design concept by the request of utility, economic factors or other factors. When the cost of power plant equipment redesigned by changing reactor power and electrical power is estimated, if its quotation is not available in the market place, cost scaling factor(CSF) applies to the cost of existing plant equipment and then the new-designed equipment cost can be calculated. In this paper, we review CSFs according to plant capacity change cases in United State DOE, EPRI, ABB, SWEC and introduce the results applied to Korean PWR 1000MWe and 1400MWe.

• Journal of Information Technology Services
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• v.14 no.4
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• pp.185-197
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• 2015

As the uncertainty of demand in B2B electronics market has increased, firms need a strong method to estimate the market demand. An accurate prediction on the market demand is crucial for a firm not to overproduce or underproduce its goods, which would influence the performance of the firm. However, it is complicated to estimate the demand in a B2B market, particularly for the private sector, because firms are very diverse in terms of size, industry, and types of business. This study proposes both qualitative and quantitative demand forecasting approaches for B2B PC products. Four different measures for predicting PC products in B2B market with consideration of the different PC uses-personal work, common work, promotion, and welfare-are developed as the qualitative model's input variables. These measures are verified by survey data collected from experts in 139 firms, and can be applied when individual firms estimate the demand of PC goods in a B2B market. As the quantitative approach, the multiple regression model is proposed and it includes variables of region, type of industry, and size of the firm. The regression model can be applied when the aggregated demand for overall domestic PC market needs to be estimated.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.45-57
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• 2020

Among the fintech businesses that are actively developing around the world, payment and settlement are the most prominent. Korea has a well-developed IT industry and a good existing card payment environment, however, its innovative movement is overwhelmingly slower than that of other countries in the fintech. In this study, we try to assess the regulations on fintech and their impacts on the startup ecosystem by comparing the cases of U.S., China, and Korea. We have found that both the United States and China have lowered barriers to entry for the newly launched fintech industry, allowing startups and IT companies to start fintech businesses at the existing financial sector. Particularly the implementation of predictable regulations in U.S., and the failure to apply the financial regulations in China, help start-up companies' growth in the fintech industry. This finding provides us with a lesson that current positive regulations in Korea should gradually change into negative regulations, and predictable regulations that strictly enforce post-management except major items rather than pre-approval. The policy implications are discussed with the perspective of start-ups in fintech industry.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.4881-4894
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• 2014

This study selected 83 manufacturing firms that had been delisted from the KOSDAQ market from 2009 to 2012 and the sample firms for the two-paired sampling method were compared with 83 normal firms running businesses with same items or in same industry. The 75 financial ratios for five years immediately before delisting were used for Mean Difference Analysis with those of normal firms. Fifteen variables assumed to be significant variables for five consecutive years out of the analysis were used to in the Dichotomous Classification Technique, Logistic Regression Analysis and Discriminant Analysis. As a result of those three analyses, the Logistic Regression Analysis model was found to show the greatest discrimination. This study is differentiated from previous studies as it assumed that the firm's failure proceeded slowly over long period of time and it tried to predict the firm's failure earlier using the five years' historical data immediately before failure, whereas previous studies predicted it using three years' data only. This study is also differentiated from the proceeding comparative studies by its statistically complex Multi-Variate Analysis and Dichotomous Classification Analysis, which general stakeholders can easily approach.