• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1243-1254
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• 2021

For water resources operation or agricultural water management, it is important to accurately predict evapotranspiration for a long-term future over a seasonal or monthly basis. In this study, reference evapotranspiration forecast (up to 12 months in advance) was performed using statistically predicted monthly temperatures and temperature-based Hamon method for the Han River basin. First, the daily maximum and minimum temperature data for 15 meterological stations in the basin were derived by spatial-temporal downscaling the monthly temperature forecasts. The results of goodness-of-fit test for the downscaled temperature data at each site showed that the percent bias (PBIAS) ranged from 1.3 to 6.9%, the ratio of the root mean square error to the standard deviation of the observations (RSR) ranged from 0.22 to 0.27, the Nash-Sutcliffe efficiency (NSE) ranged from 0.93 to 0.95, and the Pearson correlation coefficient (r) ranged from 0.97 to 0.98 for the monthly average daily maximum temperature. And for the monthly average daily minimum temperature, PBIAS was 7.8 to 44.7%, RSR was 0.21 to 0.25, NSE was 0.94 to 0.96, and r was 0.98 to 0.99. The difference by site was not large, and the downscaled results were similar to the observations. In the results of comparing the forecasted reference evapotranspiration calculated using the downscaled data with the observed values for the entire region, PBIAS was 2.2 to 5.4%, RSR was 0.21 to 0.28, NSE was 0.92 to 0.96, and r was 0.96 to 0.98, indicating a very high fit. Due to the characteristics of the statistical models and uncertainty in the downscaling process, the predicted reference evapotranspiration may slightly deviate from the observed value in some periods when temperatures completely different from the past are observed. However, considering that it is a forecast result for the future period, it will be sufficiently useful as information for the evaluation or operation of water resources in the future.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.161-176
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• 2021

In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7-432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.

• Korea Real Estate Review
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• v.28 no.1
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• pp.79-90
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• 2018

The purpose of this study was to estimate the pricing factors of residential lands in new cities by estimating the pricing model of residential lands. For this purpose, hedonic equations for each quantile of the conditional distribution of land prices were estimated using quantile regression methods and the sale price date of Jangyu New Town in Gimhae. In this study, a quantile regression method that models the relation between a set of explanatory variables and each quantile of land price was adopted. As a result, the differences in the effects of the characteristics by price quantile were confirmed. The number of years that elapsed after the completion of land construction is the quadratic effect in the model because its impact may give rise to a non-linear price pattern. Age appears to decrease the price until certain years after the construction, and increases the price afterward. In the estimation of the quantile regression, land age appears to have a statistically significant impact on land price at the traditional level, and the turning point appears to be shorter for the low quantiles than for the higher quantiles. The positive effects of the use of land for commercial and residential purposes were found to be the biggest. Land demand is preferred if there are more than two roads on the ground. In this case, the amount of sunshine will improve. It appears that the shape of a square wave is preferred to a free-looking land. This is because the square land is favorable for development. The variables of the land used for commercial and residential purposes have a greater impact on low-priced residential lands. This is because such lands tend to be mostly used for rental housing and have different characteristics from residential houses. Residential land prices have different characteristics depending on the price level, and it is necessary to consider this in the evaluation of the collateral value and the drafting of real estate policy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.49-62
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• 2018

The purpose of this study is to develop an assessment index for the selection of promising start-ups, which will enhance the efficiency of program that support start-ups. In order to develop assessment models for selecting start-ups, three major research steps were conducted. First, this study attempted to theoretically redefine the assessment index from the perspective of the Balanced Scorecard (BSC) through a literature review. Second, major assessment index were derived using Delphi technique for experts in start-up areas. Third, weights were derived by applying AHP technique to calculate the importance of each index. The results of this study are summarized as follows. First, this study attempted to apply the assessment model for selecting start-ups from the Balanced Scorecard (BSC) view through the previous study review. Second, the final major questions were derived with sufficient opinions collected and structured survey of leading start-up experts in areas related to research subjects and elicited the most representative questions. Third, the results of applying the weights of the main selected assessment index, commercialization viewpoint is the most priority, followed by market view, technology development viewpoint, and organizational capability viewpoint. In the middle section, th ability to make products in the commercialization viewpoint, market competitiveness in the market, product discrimination capacity in the technology development perspective, and the ability of the entrepreneur in the organizational capacity perspective were important. Overall important items were found to be in the order of the capabilities of entrepreneurs, market competitiveness, product fire capability, and product discrimination. The importance of small items was highest priority for comparative excellence of competing products, and the degree of marketability, capacity of entrepreneurship, ability to raise capital, desire for entrepreneurship, and passion were shown. The results of this study presented a conceptual alternative to the preceding study on the development of existing selection assessment indexes. And it provides meaningful and important implications as an attempt to develop more sophisticated indicators by overcoming the limitations of empirical research on only some of the evaluation metrics.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.5
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• pp.78-90
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• 2019

The purpose of this study is to explore the direction of developing policies for parks and green spaces for inclusive urban planning and regeneration. By reviewing the status, budget, and laws pertaining to urban parks in Korea, as well as assessing the inclusivity of urban parks, this study revealed the problems and limitations in Korea as follows. First, the urban park system, which takes into account indicators such as park area per capita and green space ratio, is focused only on quantitative expansion. Second, the distribution of urban parks is unequal; hence, the higher the number of vulnerable residents, the lower the quality of urban parks and green spaces. Moreover, this study focused on the UK central government, along with the five local governments, including London, Edinburgh, Cardiff, Belfast, and Liverpool. Through an analysis of the contexts and contents establishing UK park and green space policies that can reduce socioeconomic inequalities while at the same time increase inclusiveness. This study discovered the following. The government's awareness of the necessity of tackling socioeconomic inequalities to make an inclusive society, the change in the urban regeneration policies from physical redevelopment to neighborhood renewal, and the survey and research on the correlation of parks and green spaces, inequality, health, and well-being provided the background for policy establishment. As a result, the creation of an inclusive society has been reflected in the stated goals of the UK's national plan and the strategies for park and green space supply and qualitative improvement. Deprived areas and vulnerable groups have been included in many local governments' park and green space policies. Also, tools for analyzing deficiencies in parks and methods for examining the qualitative evaluation of parks were developed. Besides, for the sustainability of each project, various funding programs have been set up, such as raising funds and fund-matching schemes. Different ways of supporting partnerships have been arranged, such as the establishment of collaborative bodies for government organizations, allowing for the participation of private organizations. The study results suggested five policy schemes, including conducting research on inequality and inclusiveness for parks and green spaces, developing strategies for improving the quality of park services, identifying tools for analyzing policy areas, developing park project models for urban regeneration, and building partnerships and establishing support systems.

• The Korean Journal of Archival Studies
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• no.35
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• pp.161-206
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• 2013

'Maeul' is a concept connoting a community. As a place where ordinary people's lives are planned and realized, Maeul is the foundation of their daily lives as well as a place where they work, rest and enjoy pastime activities. In Korea, however, most Maeul communities are dismantled while going though the modern period representing colonization and developmental dictatorship. Growth-oriented industrialization and urbanization turned into such adverse effects as individualization, a sense of loss and a sense of alienation. Recently, through innovations from below, Maeuls are restored, and through Maeul communities restored this way, every Maeul and many researchers carry out activities to build a healthy civil society. This study was conducted on such a background. For a healthy restoration of Maeul communities and a sustainable operation of those communities, it is necessary to establish archives where record the trace of Maeul members' daily lives and relations between those members. The archive of Maeul communities is a place that contains each Maeul's local characteristics as well as human relations as well. It is because this place can be space where Maeul members can record their history, communicate with each other and make a better future. The archive of Maeul communities can be made into various different models, which can be operated by reflecting the identity of a community such as main agents and characteristics, objectives and orientation of objects recorded. Rather than when Maeul communities exist as individuals, they can display more important functions and better effect when they form a network. Therefore, it is needed to provide various and creative methodologies different from the existing government-led record management. Not only on the form of archives, but also all over their functions, such as collection, arrangement, classification, evaluation, management and utilization, Maeul and Maeul residents' norms, orientation and realistic conditions should be thoroughly reflected. Starting from a chance to look back at individuals' lives, the archive of Maeul communities will be a new chapter to restore and build a healthy community in our society and overcome social contradictions from below. Moreover, the archive of Maeul communities has a great significance that it will broaden its prospect creatively with a new paradigm, not only mechanically turning the existing public sector-centered record management into a non-governmental sector.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.4
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• pp.41-54
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• 2021

This study targets the urban park corresponding to the core areas (Hubs) of Green Infrastructure and estimates their value utilizing the Contingent Valuation Method (CVM) and determines the planning factors which affect them. The research aims to provide basic data for supporting the value improvement in the planning stage for urban parks representing green infrastructure. The primary purpose of this research is to derive variables that affect economic value and planning factors to improve the use-value of urban parks, one of the Hubs of the green infrastructure. In this study, Sejong Lake Park, located in Sejong City, is the target site. This study collected the responses of 105 people by conducting a survey on the intention to pay for the use-value and the planning factors that affect it, targeting visitors to Sejong Lake Park. The study conducts Contingent Valuation Method (CVM) on this survey responses. The results are as follows: first, as a result of analyzing the variables which affect willingness to pay for use-value, residence and age influence the willingness to pay significantly among socioeconomic characteristics. Next, the survey responses of Double-bounded dichotomous choices (DB-DC) CVM are converted into variables through statistic techniques. Furthermore, the variables are used for a Logit model to draw coefficients. The average willingness to pay per person for the use-value of Sejong Lake Park using the derived coefficients was approximately found to be 8,597 won. Therefore, as of 2019, Sejong Lake Park, with a total of 430,000 visitors, is estimated to have an annual economic value of 3.7 billion won. Third, the average Likert scale of the planning factor affecting the decision to pay for the economic value of Sejong Lake Park was the highest along the waterfront landscape, and the convenience facilities and waterfront landscape showed the highest willingness to pay, 10,000 won. In the range between 2,500 won and 5,000 won, the waterfront area ranks highest. Therefore, it can be said that visitors to Sejong Lake Park take account of the economic value of using the waterfront landscape the most. This study is meaningful as a thesis on use-value and the planning factors that affected value evaluation results of urban parks, and the analysis of the correlation between the planning factors of urban parks as hubs located in urban areas.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.111-129
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• 2022

Insomnia is a chronic disease in modern society, with the number of new patients increasing by more than 20% in the last 5 years. Insomnia is a serious disease that requires diagnosis and treatment because the individual and social problems that occur when there is a lack of sleep are serious and the triggers of insomnia are complex. This study collected 5,699 data from 'insomnia', a community on 'Reddit', a social media that freely expresses opinions. Based on the International Classification of Sleep Disorders ICSD-3 standard and the guidelines with the help of experts, the insomnia corpus was constructed by tagging them as insomnia tendency documents and non-insomnia tendency documents. Five deep learning language models (BERT, RoBERTa, ALBERT, ELECTRA, XLNet) were trained using the constructed insomnia corpus as training data. As a result of performance evaluation, RoBERTa showed the highest performance with an accuracy of 81.33%. In order to in-depth analysis of insomnia social data, topic modeling was performed using the newly emerged BERTopic method by supplementing the weaknesses of LDA, which is widely used in the past. As a result of the analysis, 8 subject groups ('Negative emotions', 'Advice and help and gratitude', 'Insomnia-related diseases', 'Sleeping pills', 'Exercise and eating habits', 'Physical characteristics', 'Activity characteristics', 'Environmental characteristics') could be confirmed. Users expressed negative emotions and sought help and advice from the Reddit insomnia community. In addition, they mentioned diseases related to insomnia, shared discourse on the use of sleeping pills, and expressed interest in exercise and eating habits. As insomnia-related characteristics, we found physical characteristics such as breathing, pregnancy, and heart, active characteristics such as zombies, hypnic jerk, and groggy, and environmental characteristics such as sunlight, blankets, temperature, and naps.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.517-534
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• 2021

Hydrogen fuel is emerging as an new energy source to replace fossil fuels in that it can solve environmental pollution problems and reduce energy imbalance and cost. Since hydrogen is eco-friendly but highly explosive, there is a high concern about fire and explosion accidents of hydrogen fueled vehicles. In particular, in semi-enclosed spaces such as tunnels, the risk is predicted to increase. Therefore, this study was conducted on the applicability of the equivalent TNT model and the numerical analysis method to evaluate the hydrogen explosion pressure in the tunnel. In comparison and review of the explosion pressure of 6 equivalent TNT models and Weyandt's experimental results, the Henrych equation was found to be the closest with a deviation of 13.6%. As a result of examining the effect of hydrogen tank capacity (52, 72, 156 L) and tunnel cross-section (40.5, 54, 72, 95 m²) on the explosion pressure using numerical analysis, the explosion pressure wave in the tunnel initially it propagates in a hemispherical shape as in open space. Furthermore, when it passes the certain distance it is transformed a plane wave and propagates at a very gradual decay rate. The Henrych equation agrees well with the numerical analysis results in the section where the explosion pressure is rapidly decreasing, but it is significantly underestimated after the explosion pressure wave is transformed into a plane wave. In case of same hydrogen tank capacity, an explosion pressure decreases as the tunnel cross-sectional area increases, and in case of the same cross-sectional area, the explosion pressure increases by about 2.5 times if the hydrogen tank capacity increases from 52 L to 156 L. As a result of the evaluation of the limiting distance affecting the human body, when a 52 L hydrogen tank explodes, the limiting distance to death was estimated to be about 3 m, and the limiting distance to serious injury was estimated to be 28.5~35.8 m.