• Journal of Korean Society of Environmental Engineers
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• v.27 no.8
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• pp.870-876
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• 2005

The multiple regression models which have two factors(population and commercial area) have been used to forecast the water demand in the future. But, the coefficient of population had a negative value because proper regional classification wasn't performed, and it is not reasonable because the population must be a positive factor. So, the regional classification was performed by principal component and cluster analysis to solve the problem. 6 regional characters were transformed into 4 principal components, and the areas were divided into two groups according to cluster analysis which had 4 principal components. The new regression models were made by each group, and the problem was solved. And, the future water demands were estimated by three scenarios(Active, moderate, and passive one). The increase of water demand ore $89.034\;m^3/day$ in active plat $49,077\;m^3/day$ in moderate plan, and $19,996\;m^3/day$ in passive plan. The water supply ability as scenarios is enough in water treatment plant, however, 2 reservoirs among 4 reservoirs don't have enough retention time in all scenarios.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.55-68
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• 2016

Academic research of the social service delivery system is very limited. This paper checked on the status of research on current social service delivery system in order to explore new research and policy directions. Analysis study consisted of 79 pieces and the framework was divided into dimensional analysis, content analysis and analytical standards. Research on the papers of social service delivery systems showed from the initial stage of the policy discussion to the phase of the individual services. Summarizing the study is as follows. First, This studies confirmed that at this time the quality studies on social service delivery system is needed. Second, this indicates that right now, the government budget of social services and the data relating to social service agencies will be opened to the public for the expansion of social services studies. Third, to expand social services delivery systems research, it showed that social services demand forecasting research such as budget allocation, population characteristics, equality of public service and local information is needed. Finally, since the quality of service is reduced by the oversupply, the discussion of the entry regulations of social service providers is required.

• Journal of Korean Society of Transportation
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• v.31 no.5
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• pp.37-47
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• 2013

This Study analyzed the electric car effect on the Korea Expressway System in terms of year 2020 $CO_2$ emission. The analysis was based on the green car dissemination goal by the government and year 2010 emission statistics. Major contents performed in the study area were as follows. First, the greenhouse gases emitted from the highways were found to be approximately 17.3 million tons of $CO_2$ as of 2010. Analysis showed the emission would be 17.4 million tons in 2015 and 16.2 million tons in 2020. The results in the pattern reflect the effect of O/D on the KTBD and the trend of traffic increase from 2015 to 2020 followed by decrease in 2020. Second, in the case of greenhouse gas emission with the anticipated supply of electric cars, the amount of emission in 2015 will be 17.1 million tons, which is about 2.0% reduction compared to the lack of introduction of electric cars. The analysis also showed that in 2020, the amount of emission will be 14.2 million tons, which indicates the effect of reduction is 12.8% compared to non implementation of the program.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.31-40
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• 2014

The Korean government made the 2nd Energy Basic Plan to achieve 11% of new and renewable energies distribution rate until 2035 as a response to cope with international discussion about greenhouse gas emission reduction. Renewable energies include solar thermal, photovoltaic, bioenergy, wind power, small hydropower, geothermal energy, ocean energy, and waste energy. New energies contain fuel cells, coal gasification and liquefaction, and hydrogen. As public and private investment to enhance the distribution of new and renewable energies, it is necessary to clarify the economic effects of the new and renewable energies sector. To the end, this study attempts to apply an input-output analysis and analyze the economic effects of new and renewable energies sector using 2012 input-output table. Three topics are dealt with. First, production-inducing effect, value-added creation effect, and employment-inducing effect are quantified based on demand-driven model. Second, supply shortage effects are analyzed employing supply-driven model. Lastly, price pervasive effects are investigated applying Leontief price model. The results of this analysis are as follows. First, one won of production or investment in new and renewable energies sector induces 2.1776 won of production and 0.7080 won of value-added. Moreover, the employment-inducing effect of one billion won of production or investment in new and renewable energies sector is estimated to be 9.0337 persons. Second, production shortage cost from one won of supply failure in new and renewable energies sector is calculated to be 1.6314 won, which is not small. Third, the impact of the 10% increase in new and renewable energies rate on the general price level is computed to be 0.0123%, which is small. This information can be utilized in forecasting the economic effects of new and renewable energies sector.

• Journal of Distribution Science
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• v.13 no.10
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• pp.123-133
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• 2015

Purpose - The Korean government has devised intermodal transportation policies and granted subsidies to shippers and logistics companies that made a conversion of transportation means through the policies. This provides support by expanding the complex uniform railroad transportation and overhauling the deteriorated railroad facilities. As for 2013, however, the freight transportation percentage of railroad was 4.5% in tons and 8.5% in ton kilometers. Meanwhile, since the 1990s, developed countries such as the U.S. and Europe have been trying to expand intermodal freight transport with a legal and institutional support to build a logistics system corresponding with social and economic environmental changes. In this study, I set out to examine the effects of the intermodal freight transport policies in the EU and the U.S., and to explore the direction of setting up a rail intermodal transport system in South Korea. Research design, data, and methodology - The paper used a qualitative research methodology through the literature review. First, was an overview of Intermodal transportation in the EU, U.S. and UN. Second, it describes the development of transport in Europe and the U.S. with particular emphasis on intermodal freight transport. Third, it explores the direction of setting up a intermodal freight transport in South Korea. The last section contains concluding remarks. Results - As for the EU, it has been promoting integration between transport and intermodal logistics network designs while utilizing ITS or ICT and supports for rail freight intermodal by giving reduction to a facilities fee or subsidizing for rail freight in order to minimize the cost of external due to freight transport. On the other hand, as for the U.S., it has been made up of an industrial-led operating project and has been promoting it to improve accessibility between intermodal hubs and cargo terminals through intermodal corridor program, and an intermodal cargo hub access corridor projects, etc. Moreover, it has tried to construct intermodal transport system using ITS or ICT and to remove Barrier. As a result, in these countries, the proportion of intermodal freight transport is going to be the second significant transport compared with rail and maritime transport. An Effective rail intermodal transport system is needed in South Korea, as seen in the case of these countries. In order to achieve this object, the following points are required to establish radical infrastructure policy; diversify investment financing measures taken under public-private partnerships, legal responsibilities, improvement of utilization of existing facilities to connect the railway terminal and truck terminal, and enhancement service competitiveness through providing cargo tracking and security information that combines the ITS and ICT. Conclusions - This study will be used as a basis for policy and support for intermodal freight transport in South Korea. In the future, it is also necessary to examine from the perspective of the shipper companies using the rail intermodal transport, ie, recognition of shipper, needed institutional supports, and transportation demand forecasting and cost-effective analysis of the railway infrastructure systems improvement.

• 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 Remote Sensing
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• v.33 no.5_2
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• pp.631-640
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• 2017

The estimation of rice yield affects the income of farmers as well as the fields related to agriculture. Moreover, it has an important effect on the government's policy making including the control of supply demand and the price estimation. Thus, it is necessary to build the crop yield estimation model and from the past, many studies utilizing empirical statistical models or artificial neural network algorithms have been conducted through climatic and satellite data. Presently, scientists have achieved successful results with deep learning algorithms in the field of pattern recognition, computer vision, speech recognition, etc. Among deep learning algorithms, the SSAE (Stacked Sparse AutoEncoder) algorithm has been confirmed to be applicable in the field of forecasting through time series data and in this study, SSAE was utilized to estimate the rice yield in South Korea. The climatic and satellite data were used as the input variables and different types of input data were constructed according to the period of rice growth in South Korea. As a result, the combination of the satellite data from May to September and the climatic data using the 16 day average value showed the best performance with showing average annual %RMSE (percent Root Mean Square Error) and region %RMSE of 7.43% and 7.16% that the applicability of the SSAE algorithm could be proved in the field of rice yield estimation.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.353-358
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• 2001

Since the financial crisis broke out, liquidity has become the critical issue in housing construction industry. In order to secure liquidity, it is prerequisite to precisely forecast cash flow. However, construction companies have failed to come up with a systematic process to manage and forecast cash flow. Until now, companies have solely relied on the prediction of profits and losses, which is carried out as they review business feasibility. To obtain more accurate cash flow forecast model, practical pattern of payments should be taken into account. In this theory, basic model that analyzes practical housing payment collection pattern resulting from prepayments and arrears is described. This model is to complement conventional cash flow forecast scheme in the phase of business feasibility review. Analysis result on final losses in cash that occur as a result of prepayment and arrears is considered in this model. Additionally, in the estimation of construction cost in the phase of business feasibility review, real construction prices instead of official prices are applied to enhance accuracy of cash outflow forecast. The proportion of payment made by a bill and changes in payment date caused by rescheduling of a bill are also factored in to estimate cash outflow. This model would contribute to achieving accurate cash flow forecast that better reflect real situation and to enhancing efficiency in capital management by giving a clear picture with regard to the demand and supply timing of capital.

• 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.

• 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.