• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.121-131
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• 2009

This study will estimate the fair return on private participants' investments on BTO type PPI (Private Public Infrastructure) projects using the data from past BTO projects in Korea. In the past, the real returns of $6%\sim9%$ were provided to private participants. The results of this study show that those returns were too high compared with the estimated fair returns, especially for projects with the minimum revenue guarantee (MRG) by the government. Moreover, the excess portion of the return over the fair return becomes even larger when there is a demand forecast bias. In reality, most of the BTO projects have far lower actual revenues than the initial forecasted revenue in concession agreements. This phenomenon implies that BTO projects have a tendency of overly forecasting revenues. If so, the value of the minimum revenue guarantee becomes larger, and therefore, the fair return to private participants should decrease. It is hoped that this study helps future BTO projects' concession agreements between the government and private participants to become more fair from the perspectives of risk and return profiles.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.5
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• pp.361-371
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• 2015

To understand the impact of 2015 spring drought on crop production of DPRK (Democratic People's Republic of Korea), we analyzed satellite and weather data to produce 2015 spring outlook of rice paddy field and rice growth in relation to weather anomaly. We defined anomaly of 2015 for weather and NDVI in comparison to past 5 year-average data. Weather anomaly layers for rainfall and mean temperature were calculated based on 27 weather station data. Rainfall in late April, early May, and late May in 2015 was much lower than those in average years. NDVI values as an indicator of rice growth in early June of 2015 was much lower than in 2014 and the average years. RapidEye and Radarsat-2 images were used to monitor status of rice paddy irrigation and transplanting. Due to rainfall shortage from late April to May, rice paddy irrigation was not favorable and rice planting was not progressed in large portion of paddy fields until early June near Pyongyang. Satellite images taken in late June showed rice paddy fields which were not irrigated until early June were flooded, assuming that rice was transplanted after rainfall in June. Weather and NDVI anomaly data in regular basis and timely acquired satellite data can be useful for grasping the crop and land status of DPRK, which is in high demand.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.137-146
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• 2016

In recent years, business environment is faced with multi uncertainty that have not been suffered in the past. As supply chain is getting expanded and longer, the flow of information, material and production is also being complicated. It is well known that development service industry using application software has various uncertainty in random events such as supply and demand fluctuation of developer's capcity, project effective date after winning a contract, manpower cost (or revenue), subcontract cost (or purchase), and overrun due to developer's skill-level. This study intends to social contribution through attempts to optimize enterprise's goal by supply chain management platform to balance demand and supply and stochastic programming which is basically applied in order to solve uncertainty considering economical and operational risk at solution supplier. In Particular, this study emphasizes to determine allocation of internal and external manpower of developers using S&OP (Sales & Operations Planning) as monthly resource input has constraint on resource's capability that shared in industry or task. This study is to verify how Stochastic Programming such as Markowitz's MV (Mean Variance) model or 2-Stage Recourse Model is flexible and efficient than Deterministic Programming in software enterprise field by experiment with process and data from service industry which is manufacturing software and performing projects. In addition, this study is also to analysis how profit and labor input plan according to scope of uncertainty is changed based on Pareto Optimal, then lastly it is to enumerate limitation of the study extracted drawback which can be happened in real business environment and to contribute direction in future research considering another applicable methodology.

• KIEAE Journal
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• v.13 no.4
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• pp.43-48
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• 2013

The effect of climate change has influenced humanity and ecosystem with tremendous changes in temperature. For the past 150 years, the national annual average temperature is 0.6 degree increased and the heating degree day reduced from April to November. However, December to January, the climate change was generated and the heating degree day increased. The blackout occured in 2011 and 2012 by increasing electricity consumption of heating and cooling equipment to the effects of climate change. That is because heating load accounted for 20% of building electric use. In this study, strengthening measures to reduce heating energy consumption is presented due to climate change in winter since 1980 to prevent blackout and reliable power supply for the building energy-saving design standards by Meteorological data provided by the National Weather Service were calculated using the heating degree days in order to present eighteen cities from 1980 to 2012. Insulation standards are presented to prevent black-out by the heating degree days. the heating energy demand was reduced almost 6% including 10% in Central, 5% in South and Jeju area based on strengthening of the insulation. It is applied to the entire country an annual economic effect of 250 billion won, and black-out can be prevented.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.410-418
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• 2021

In a program that runs an engineering education certification, program outcomes refer to the knowledge, skills, and attitudes a student must have until graduation. In general, capstone design is used as a tool for evaluating program outcomes. This paper applies the intraclass correlation coefficient (ICC) to measure the raters' reliability in assessing program outcomes. Several raters evaluate program outcomes, and the result is used to obtain the raters' ICC. ICC measures the reliability of ratings or measurements for clusters - data that has been collected as groups or sorted into groups. If the ICC is close to 1, it means that the reliability among the raters is high. We evaluated the proposed method's usefulness through case analysis. As a method for assessing an evaluation tool's objectivity, multiple raters measure the same evaluation tool. As a result, we measured the ICC values for all POs, and analyzed the cause for the low measured POs. We applied this method to evaluate program outcomes of the Department of Computer Engineering in the past two years. As a result, we derived guidelines for improvement and program outcomes.

• Journal of Energy Engineering
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• v.17 no.1
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• pp.31-37
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• 2008

At present, the target amount of demand-side management and investment cost of EE (Energy Efficiency) program, which consists of high-efficiency appliances, has been estimated simply by the diffusion function based on the real historical data in the past or last year. In the internal and external condition, the penetration amount of each appliance has been estimated by Bass diffusion model which is expressed by time and three coefficients. And enough acquisition of real historical data is necessary for reasonable estimation of coefficients. In energy efficiency, to estimate the target amount of demand-side management, the penetration amount of each appliance should be primarily forecasted by Bass diffusion model in Korea. On going programs, however, lightings, inverters, vending machine and motors have a insufficient real historical data which is a essential condition to forecast the penetration amount using a Bass diffusion model due to the short period of program progress. In other words, the forecast of penetration amount may not be exact, so that it is necessary for the method of forecast to apply improvement of method. In this paper, the penetration amount of high-efficiency appliances is forecasted by Bass, virtual Bass, Logistic and Lawrence & Lawton diffusion models to analyze the diffusion progress. And also, by statistic standards, each penetration is compared with historical data for model suitability by characteristic of each appliance. Based on the these result, in the forecast of penetration amount by diffusion model, the reason for error occurrence caused by simple application of diffusion model and preferences of each diffusion model far a characteristic of data are analyzed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.106-118
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• 2020

This study examined the impact of COVID-19 on traffic demand (Average Daily Traffic : ADT) by analyzing the available data on highway traffic volume and the spread of COVID-19 cases in Korea. This study used the data from 228 permanent traffic counts (PTCs) on highways from January to May of 2019 and 2020 to analyze the change in ADT. The first cases of infection in Korea occurred on January 20, 2020, and the maximum daily number of infections was 909 on February 29. On April 30, 2020, the daily number of infections decreased to four. The ADT decreased by 3.3% due to the impact of COVID-19. Considering that the traffic volume has increased 2.3% annually over the past decade, the actual decrease in ADT due to the COVID-19 is estimated to be 5.6% (3.3% + 2.3%). The ADT for weekends decreased significantly, compared to during the week. An analysis of the changes in ADT according to the road type revealed decreases in the following: urban roads -4.6%, rural roads -3.2%, and recreational roads -0.7%. Urban roads decreased the most, and tourist roads decreased the least.

• KDI Journal of Economic Policy
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• v.12 no.1
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• pp.3-29
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• 1990

Korean input-output tables for 1975 and 1985 are first deflated into 1975 constant domestic prices(hypothetical terms), and the constant price I-O data are used to decompose the sources of industrial growth and structural change during the 1975-85 period. Using the same methodology, our results for the 1975-85 period are then linked to the results for the earlier period(1955-75) in order to analyze and evaluate the "demand-side" sources of industrialization over the past three decades. The results from the decomposition of the whole economy indicate that over three decades(1955-85) the relative contribution of domestic demand expansion (DDE) to growth and structural change has continuously declined while the contribution of export expansion(EE) has generally continued to rise. The contribution of import-substitution(IS) which had been significantly higher than that of EE during 1955-63 declined substantially, remaining at an insignificantly low level during the period following 1963. Although it is well known that the government's industrial policy in the 1970s emphasized import-substitution in heavy and chemical industries, no significant changes in the export-oriented growth pattern could be observed even for that period, except for a minor decline in the relative contribution of EE. This may be attributed to the substantially larger, backward-linkage effects of EE than that of IS. The sources-of-growth decompositions for major branches of the manufacturing sector generally support the major conclusions derived from the decomposition for the whole economy. The IS contribution which had been significantly high in almost all manufacturing branches during the 1955-63 period declined to low levels in all but two branches, heavy industry and machinery, during the following period. On the other hand, the relative contribution of EE showed a continuous rise in almost all manufacturing branches(except food processing). Finally, the sources of growth for 1975-85 which were decomposed by detailed sub branches, are analyzed by correlating them with changes in relative prices and industrial protection rates by sub-branches for the same period. A major result is that contrary to general expectations, the EE contributions by sub-branch are not negatively correlated with the nominal rates of protection and/or the effective rates of protection for the same sub-branches. It is also found that no statistically significant, positive correlation exists between IS contributions and nominal protection rates or effective protection rates. These unexpected results may be explained by the peculiar nature of the Korean system of industrial incentives for the past period.

• Land and Housing Review
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• v.12 no.4
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• pp.41-59
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• 2021

This study reviews theoretical considerations and past studies about real estate prices, macroeconomic variables, and real estate policies. Monthly data from January 2003 to June 2021 are used, and a VEC model, the most widely used multivariate time series analysis method, is employed for analysis. Through the model, the effects of macroeconomic variables and real estate regulatory policies on real estate prices in Seoul are analyzed. Findings are summarized as follows. First, macroeconomic variables such as money supply and interest rates do not have a significant impact on Seoul's apartment prices. Due to the high demand for housing and insufficient supply, there is a demand for buying a home regardless of macroeconomic booms or recessions. Second, tax and financial regulatory policies have an initial impact on the rise in apartment prices in Seoul, and their influence diminishes over time. Third, anti-speculation zones are expected to decrease apartment prices through the suppression of demand. However, these zones cause a rise in apartment prices. This could be understood as a lock-in effect due to the strengthening of capital gains tax. Fourth, the price ceiling did not decrease apartment prices. These findings propose that, in Seoul, where demand is high and supply is insufficient, the supply of high-quality and sufficient housing should be prioritized over various regulations such as tax regulations, financial regulations, anti-speculation zones, and price caps. Moreover, the findings provide an implication that city-specific real estate policies should be implemented for Seoul rather than regulation-oriented approaches in public policy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.