• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.329-352
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• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• Journal of Environmental Policy
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• v.12 no.3
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• pp.97-122
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• 2013

The ARDL(Autoregressive Distributed Lag) method is employed analyzes the long-run equilibrium relationships among environmental pollution($CO_2$ emissions) per capita, income levels per capita, and energy consumption per capita. The error correction model is employed to analyze the short-term effects of income and energy consumption on $CO_2$ emissions. The Toda-Yammamoto method is employed for causal analysis among the three variables. The results show that income levels, energy consumption, and $CO_2$ emissions are cointegrated. We found the N type relationship between income and $CO_2$ emissions. Long-term elasticities of income and energy consumption with respect to $CO_2$ emission were greater than their short-term elasticities. There were a bilateral causality between energy consumption and $CO_2$ emissions. There was a unilateral causality from $CO_2$ emissions to income and from energy consumption to income not vice versa. Energy consumption can be an important variable to contribute to forecasting $CO_2$ emissions.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1555-1559
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• 2010

본 연구는 미래 물 관리를 위한 기후변화 대응방안 도출 연구의 사전연구로서 금강유역의 과거 기상 수문요소의 특성변화 분석을 수행하였다. 기상자료로 금강유역 기상관측소 8개소의 37개년(1973~2009)의 기온, 강수량, 상대습도 자료를 수집하였다. 하천수위자료는 수위자료와 수위-유량관계곡선의 신뢰성 문제, 이후 수행될 장기유출분석을 고려하여 최종적으로 공주, 규암 수위관측소의 36개년(1973~2008)의 자료를 이용하였고, 지하수위자료는 강우관측소와 근접하게 위치해 있으면서 과거 자료를 최대한 많이 보유하고 있는 6개 관측소의 10개년(1999~2008)의 자료를 이용하였다. 수집된 자료의 평균, 표준편차, 왜곡도, 변동계수를 산출하여 연 계절별로 수문기상인자의 경년변화를 파악한 결과 기상인자 중 강수량의 변동성이 가장 크게 나타나 경년별 변화가 큰 것으로 분석되었고 하천수위보다는 지하수위가 경년별 변동이 적은 것으로 분석되었다. 수문학적 지속성 분석을 위해 Run 검정, Turning Point 검정, Anderson Exact검정을 이용하여 시계열자료에 주기성이 있는지 분석한 결과 기온과 강수는 무작위성, 상대습도, 하천수위는 지속성을 가지는 인자로 분석되었고 지하수위는 관측소별, 기간별로 무작위성과 지속성이 혼재되어 있는 것으로 나타났다. 마지막으로 경향성 분석을 위해 단순 선형 회귀분석과 Mann-Kendall 검정을 이용하였다. 그 결과 기온은 연 계절 모두 증가경향이 나타났고, 강수량은 여름에만 증가경향이 나타났으며, 상대습도는 뚜렷한 감소경향을 보였다. 또한 하천수위는 감소경향이 나타났으며 지하수위는 유의수준 범위에서 경향성은 보이지 않았다. 본 연구의 결과는 기후변화로 인해 발생될 수 있는 수자원의 영향을 평가하고 미래 물 관리 적응기술 개발 및 계획 수립을 위한 자료로 활용될 수 있을 것으로 사료된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.25-33
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• 2020

A drought event is characterized by duration, severity and affected area. In general, after calculating a drought index using hydro-meteorological time series at a station, a drought event is defined based on the run theory to identify the beginning and end time. However, this one-dimensional analysis has limitations for analyzing the spatio-temporal occurrence characteristics and movement paths of drought. Therefore, this study is to define a three-dimensional drought event using a simple clustering algorithm and to develop a drought map that can be used to understand the drought severity according to the spatio-temporal expansion of drought. As a result, compared with the two-dimensional monitoring information to show spatial distribution of drought index, a proposed drought map is able to show three-dimensional drought characteristics inclusing drought duration, spatial cumulative severity, and centroid of drought. The analysis of drought map indicated that there was a drought event which had the affected area less than 10 % while on occations while there were 11 drought events (44 %) which had the affected area more a than 90 % of the total area. This means that it is important to understand the relationship between spatial variation of drought affected area and severity corresponding to various drought durations. The development of drought map based on three-dimensional drought analysis is useful to analyze the spatio-temporal occurrence characteristics and propagation patterns of regional drought which can be utilized in developing mitigation measures for future extreme droughts.

• KEPCO Journal on Electric Power and Energy
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• v.3 no.1
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• pp.65-72
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• 2017

This study analyzed causal relationship between electricity consumption and economic output (GDP) for Korea from 2001 to 2014 employing the vector error-correction model estimation by manufacturing sector. The results of unit-roots tests show that all sectoral GDP and electricity consumptions were not stationary. And cointegration tests show that processed foods, Wood Pulp Paper, electricity apparatus, Precision Medical sectors had a linear combinations in the long run between electricity consumptions and economic growth. With respect to the direction of causality, manufacturing sector has a uni-directional running from economic output (GDP) to electricity consumption in short term. The results of study show that sectoral causal relation were different each other in short term and long term. These findings imply that electricity demand management policy focusing on efficiency improvement is necessary to minimize negative impacts on economic growth and to adopt suitable structural policies can induce energy conservation.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.78-98
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• 2018

On the 855 pure Korean commercial fictional movies, excluding diversity films, released in Korea from 2004 to August 2017, I conducted deciles distribution analysis of box office performance of those movies and average box office performance of directors, producers and lead actors who involved in making them. Deciles distribution analysis of average box office performance might be helpful to predict their next box office performance of newly produced Korean movies and to evaluate their contribution to box office performance. In baseball, the various index such as winning rate, on-base percentage, slugging percentage, stolen base percentage, battling average, earned run average is used for predicting and reviewing of professional players. In this study, I evaluate the script's narrative quality by the indirect method of insight and judgment of creative manpower involved in making the movies. For the more productive prediction, direct statistical analysis method on the narrative of the script needs to develop. Time series analysis is required to evaluate the rise and fall of creative manpower and network analysis is also necessary to see the interaction among creative people.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1229-1235
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• 2018

We have examined dynamic relationships among water-efficiency, economic growth, electricity generation, and $CO_2$ emissions in Korea using various time-series analysis methods for 1990-2014. While previous studies have been limited to economic growth, $CO_2$ emissions, and electricity generation, this study contributed to explain the relationship between existing variables and water-efficiency. We find that the four variables reach a balanced state in the long run through short-term adjustment, $CO_2$ emissions and economic growth are responsible for water efficiency, and that $CO_2$ emissions, economic growth and water efficiency are the causes of electricity generation. The long-term impact coefficient estimates on water-efficiency show that the increase in electricity generation and the decrease in $CO_2$ emissions increase water-efficiency. Although economic growth has increased water-efficiency, moreover, we have identified an inverted U-shaped relationship between economic growth and water-efficiency, which suggests that economic growth above a certain level reduces the rate of increase in water-efficiency.

• Health Policy and Management
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• v.34 no.2
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• pp.196-210
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• 2024

Background: In January 2018, revised elderly fixed outpatient copayment for the elderly were implemented. When people ages 65 years and older receive outpatient treatment at clinic-level medical institutions (clinic, dental clinic, Korean medicine clinic), with medical expenses exceeding 15,000 won but not exceeding 25,000 won, their copayment rates have decreased differentially from 30%. This study aimed to examine the changes of health utilization of elderly after revised elderly fixed outpatient copayment. Methods: We used Korea health panel data from 2016 to 2018. The time period is divided into before and after the revised elderly fixed outpatient copayment. We conducted Poisson segmented regression to estimate the changes in outpatient utilization and inpatient utilization and conducted segmented regression to estimate the changes in medical expenses. Results: Immediately after the revised policy, the number of clinic and Korean medicine outpatient visits of medical expenses under 15,000 won decreased. But the number of clinic outpatient visits in the range of 15,000 to 20,000 won and Korean medicine clinic in the range of 20,000 to 25,000 won increased. Copayment in outpatient temporarily decreased. The inpatient admission rates and total medical expenses temporarily decreased but increased again. Conclusion: We confirmed the temporary increase in outpatient utilization in the medical expense segment with reduced copayment rates. And a temporary decrease in medical expenses followed by an increase again. To reduce the burden of medical expense among elderly in the long run, efforts to establish chronic disease management policies aimed at preventing disease occurrence and deterioration in advance need to continue.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.1-48
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• 2009

Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.