• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3B
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• pp.315-321
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• 2008

Recently, in the light of environments and utilization, countermeasures to preserve beaches in coastal area are required without depending on such as jetties and breakwaters. The necessity of integrated sand management including not only coastal sediment but also sediment discharge from hinterland rivers is increased so as to establish long-term counterplan for sediment transport. In this regard, the following subjects are examined in this study; efficient ways for discharged sand to be transported from a river to the neighboring coast, the river terrace occurrence and its growth at the river delta, measures to improve storage efficiency of the discharged sand and measures to prevent the sand resources from being discharged into the deep sea during flooding. In recent, A jetty of 260 m length was constructed at Namdae River mouth in the year of 2005 as a countermeasure against the occurrence of sand-bar at river mouth and its close. In this study, a series of numerical experiments were carried out to investigate the characteristics of sediment transport and morphological change due to the construction of jetty at the entrance of Namdae River mouth. Firstly, The sand discharge from Namdae River is quantified by one-dimensional numerical analysis assuming the mixed sand of three different particle diameters. Then, in order to understand the transport behavior of the sand discharge from river and river mouth phenomena the numerical experiments were then conducted to examine the flow behaviors of river efflux and wind generated circulations in coastal area. And, after establishing the numerical model system, which predicts the sea bed changes obtained from the flux model combining with the wave propagation, wave-induced currents and sediment transport models, the sediment transport in the vicinity of Namdae River mouth is analyzed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.497-507
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• 2010

Climate changes affect greatly natural ecosystem, human social and economic system acting on constituting the climate system such as air, ocean, life, glacier and land, etc. and estimating the current impact of climate change would be the most important thing to adapt to the climate changes. This study set the target area to Nakdong river watershed and investigated the impact of climate changes through analyzing precipitation tendency, and to understand the impact of climate changes on hydrological elements, analyzed elasticity of precipitation-streamflow. For the analysis of precipitation trend, collecting the precipitation data of the National Weather Service from major points of Nakdong river watershed, resampling them at the units of year, season and month, used as the data of precipitation trend analysis. To analyze precipitation-streamflow elasticity, collecting area average precipitation and long-term streamflow data provided by WAMIS, annual and seasonal time-series were analyzed. In addition, The results of this study and elasticity, and other abroad study compared with the elasticity analysis and the validity of this study was verified. Results of this study will be able to be utilized for study on a plan to increase of flood control ability of flooding constructs caused by the increase of streamflow around Nakdong river watershed due to climate changes and on a plan of adapting to water environment according to climate changes.

• KDI Journal of Economic Policy
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• v.45 no.4
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• pp.57-77
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• 2023

The Chonsei component holds the highest level of weight (5.4%) in the composition of the Korean consumer price index (CPI). The variations in Chonsei prices are directly reflected in the CPI as a representation of cost swings. The Chonsei refers to a deposit that accumulates the costs related to housing services and is mostly affected by variations in rental rates. Nevertheless, it is important to note that Chonsei prices are also susceptible to fluctuations in interest rates, regardless of the rent prices. Therefore, if Chonsei were directly and one-to-one indexed to the CPI, they could include changes other than residential service prices. After analyzing the time series data of the Chonsei index and rent index inside the CPI, it becomes apparent that the Chonsei index displays an average annual growth rate of 2.3%, whilst the rent index reveals a growth rate of 0.9%. The observed disparity in growth rates indicates a divergence in trends between the two indices. It is posited that the Chonsei index, when capitalized, has had a more rapid increase compared to the rental index, owing to the gradual drop in interest rates. To effectively reflect fluctuations in the housing service costs, proxies for the Chonsei index were utilized in the construction of a consumer price index. The findings of our study suggest that, overall, the newly developed CPI demonstrates a comparatively lower rate of inflation when compared to the official CPI. Furthermore, the inclusion of imputed rents for owner-occupied housing in CPI amplifies this effect.

• Health Policy and Management
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• v.33 no.4
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• pp.450-456
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• 2023

Background: This study aims to develop a "Predictive Model for the Possibility of Collection Delinquent Health Insurance Contributions" for the National Health Insurance Service to enhance administrative efficiency in protecting and collecting contributions from livelihood-type defaulters. Additionally, it aims to establish customized collection management strategies based on individuals' ability to pay health insurance contributions. Methods: Firstly, to develop the "Predictive Model for the Possibility of Collection Delinquent Health Insurance Contributions," a series of processes including (1) analysis of defaulter characteristics, (2) model estimation and performance evaluation, and (3) model derivation will be conducted. Secondly, using the predictions from the model, individuals will be categorized into four types based on their payment ability and livelihood status, and collection strategies will be provided for each type. Results: Firstly, the regression equation of the prediction model is as follows: phat = exp (0.4729 + 0.0392 × gender + 0.00894 × age + 0.000563 × total income - 0.2849 × low-income type enrollee - 0.2271 × delinquency frequency + 0.9714 × delinquency action + 0.0851 × reduction) / [1 + exp (0.4729 + 0.0392 × gender + 0.00894 × age + 0.000563 × total income - 0.2849 × low-income type enrollee - 0.2271 × delinquency frequency + 0.9714 × delinquency action + 0.0851 × reduction)]. The prediction performance is an accuracy of 86.0%, sensitivity of 87.0%, and specificity of 84.8%. Secondly, individuals were categorized into four types based on livelihood status and payment ability. Particularly, the "support needed group," which comprises those with low payment ability and low-income type enrollee, suggests enhancing contribution relief and support policies. On the other hand, the "high-risk group," which comprises those without livelihood type and low payment ability, suggests implementing stricter default handling to improve collection rates. Conclusion: Upon examining the regression equation of the prediction model, it is evident that individuals with lower income levels and a history of past defaults have a lower probability of payment. This implies that defaults occur among those without the ability to bear the burden of health insurance contributions, leading to long-term defaults. Social insurance operates on the principles of mandatory participation and burden based on the ability to pay. Therefore, it is necessary to develop policies that consider individuals' ability to pay, such as transitioning livelihood-type defaulters to medical assistance or reducing insurance contribution burdens.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.2
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• pp.27-36
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• 2018

This study suggests the necessity of behavior analysis as changes to a park environment to reflect user desires can be implemented only by grasping the needs of park users. Online data (blog) were defined as the basic data of the study. After collecting data by 5 - year units, data mining was used to derive the characteristics of the time series behavior while the significance of the online data was verified through social network analysis. The results of the text mining analysis are as follows. First, primary results included 'walking', 'photography', 'riding bicycles'(inline, kickboard, etc.), and 'eating'. Second, in the early days of the collected data, active physical activity such as exercise was the main factor, but recent passive behavior such as eating, using a mobile phone, games, food and drinking coffee also appeared as a new behavior characteristic in parks. Third, the factors affecting the behavior of park users are the changes of various conditions of society such as internet development and a culture of expressing unique personalities and styles. Fourth, the special behaviors appearing at Olympic Park were derived from educational activities such as cultural activities including watching performances and history lessons. In conclusion, it has been shown that people's lifestyle changes and the behavior of a park are influenced by the changes of the various times rather than the original purpose that was intended during park planning and design. Therefore, it is necessary to create an environment tailored to users by considering the main behaviors and influencing factors of Olympic Park. Text mining used as an analytical method has the merit that past data can be collected. Therefore, it is possible to form analysis from a long-term viewpoint of behavior analysis as well as to measure new behavior and value with derived keywords. In addition, the validity of online data was verified through social network analysis to increase the legitimacy of research results. Research on more comprehensive behavior analysis should be carried out by diversifying the types of data collected later, and various methods for verifying the accuracy and reliability of large-volume data will be needed.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.6 no.4
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• pp.357-368
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• 2008

On July 31, 2008, the Government issued the construction and operation permit for the first low and intermediate level radioactive waste disposal facility in the Republic of Korea. In this paper, the fundamental regulatory framework, regulatory requirements and technical standards of the disposal facility are introduced, and the phased review process adopted for evaluation of the safety of the facility is briefly described. The Atomic Energy Act sets forth a stepwise regulatory framework for the whole life-cycle of the disposal facility such as siting, design, construction, operation, closure and institutional control. More detailed regulatory requirements and technical standards are stipulated in the subsequent regulations of the Atomic Energy Act and a series of Notices issued by the Ministry of Eduction, Science and Technology. The Korea Institute of Nuclear Safety, as entrusted by the Ministry under the Atomic Energy Act, conducted safety review on the disposal facility, and evaluated the compliance with relevant criteria in all technical elements(i.e. siting and structural safety, radiological environmental impact, operational safety, systems and components, quality assurance, and total systematic performance assessment, etc.). The overall safety review process can be phased into inception phase, initial review phase, main review phase and completion phase. The review results were reported to and deliberated by the five Sub-committees of the Special Committee on Nuclear Safety, and then reported to the Ministry. The Ministry issued the construction and operation permit of the disposal facility through the deliberation of the review results by the Nuclear Safety Commission. Hereafter, the safety of the repository will be reassured by a series of subsequent regulatory inspections and reviews under the Atomic Energy Act. In addition, the licensee's continuous implementation of the "Safety Promotion Plan" may also enhance the long-term safety of the repository and contribute to build-up the confidence of the safety case.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.665-679
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• 2019

Mesoscale soil moisture measurement from the promising Cosmic-Ray Neutron Probe (CRNP) is expected to bridge the gap between large scale microwave remote sensing and point-based in-situ soil moisture observations. Traditional calibration based on $N_0$ method is used to convert neutron intensity measured at the CRNP to field scale soil moisture. However, the static calibration parameter $N_0$ used in traditional technique is insufficient to quantify long term soil moisture variation and easily influenced by different time-variant factors, contributing to the high uncertainties in CRNP soil moisture product. Consequently, in this study, we proposed a modified traditional calibration method, so-called Dynamic-$N_0$ method, which take into account the temporal variation of $N_0$ to improve the CRNP based soil moisture estimation. In particular, a nonlinear regression method has been developed to directly estimate the time series of $N_0$ data from the corrected neutron intensity. The $N_0$ time series were then reapplied to generate the soil moisture. We evaluated the performance of Dynamic-$N_0$ method for soil moisture estimation compared with the traditional one by using a weighted in-situ soil moisture product. The results indicated that Dynamic-$N_0$ method outperformed the traditional calibration technique, where correlation coefficient increased from 0.70 to 0.72 and RMSE and bias reduced from 0.036 to 0.026 and -0.006 to $-0.001m^3m^{-3}$. Superior performance of the Dynamic-$N_0$ calibration method revealed that the temporal variability of $N_0$ was caused by hydrogen pools surrounding the CRNP. Although several uncertainty sources contributed to the variation of $N_0$ were not fully identified, this proposed calibration method gave a new insight to improve field scale soil moisture estimation from the CRNP.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.3
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• pp.115-128
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• 2019

In this study, a probabilistic model for the estimation of yearly workable wave condition period for offshore operations is developed. In doing so, we first hindcast the significant wave heights and peak periods off the Ulsan every hour from 2003.1.1 to 2017.12.31 based on the meteorological data by JMA (Japan Meterological Agency) and NOAA (National Oceanic and Atmospheric Administration), and SWAN. Then, we proceed to derive the long term significant wave height distribution from the simulated time series using a least square method. It was shown that the agreements are more remarkable in the distribution in line with the Modified Glukhovskiy Distribution than in the three parameters Weibull distribution which has been preferred in the literature. In an effort to develop a more comprehensive probabilistic model for the estimation of yearly workable wave condition period for offshore operations, wave height distribution over the 15 years with individual waves occurring within the unit simulation period (1 hour) being fully taken into account is also derived based on the Borgman Convolution Integral. It is shown that the coefficients of the Modified Glukhovskiy distribution are $A_p=15.92$, $H_p=4.374m$, ${\kappa}_p=1.824$, and the yearly workable wave condition period for offshore work is estimated to be 319 days when a threshold wave height for offshore work is $H_S=1.5m$. In search of a way to validate the probabilistic model derived in this study, we also carry out the wave by wave analysis of the entire time series of numerically simulated significant wave heights over the 15 years to collect every duration periods of waves the height of which are surpassing the threshold height which has been reported to be $H_S=1.5m$ in the field practice in South Korea. It turns out that the average duration period is 45.5 days from 2003 to 2017, which is very close to 46 days from the probabilistic model derived in this study.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Korean Journal of Environment and Ecology
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• v.38 no.2
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• pp.204-216
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• 2024

Understanding the trade-off effect in ecosystem services and measuring the interrelationships between services are crucial for managing limited environmental resources. Accordingly, in this study, we identified the dominant trends and increases and decreases in ecosystem services derived from changes in land cover over about 30 years and tracked changes in the relationships between ecosystem services that occurred over time. Through it, we determined the relationship between land cover changes and ecosystem service changes, as well as the distinct characteristics of service changes in different areas. The research primarily utilized the InVEST model, an ecosystem service assessment model. After standardizing the evaluation results between 0 and 1, it went through principal component analysis, a dimensionality reduction technique, to observe the time-series changes and understand the relationships between the services. According to the research results, the area of urbanized regions dramatically increased between 1989 and 2019, while forests showed a significant increase between 2009 and 2019. Between 1989 and 2019, the national ecosystem service supply witnessed a 13.9% decrease in water supply, a 10.5% decrease in nitrogen retention, a 2.6% increase in phosphorus retention, a 0.9% decrease in carbon storage, a 1.2% increase in air purification, and a 3.4% decrease in habitat quality. Over the past 30 years, South Korea experienced an increase in urbanized areas, a decrease in agricultural land, and an increase in forests, resulting in a trade-off effect between phosphorus retention and habitat quality. This study concluded that South Korea's environment management policies contribute to improving ecosystem quality, which has declined due to urbanization, and maximizing ecosystem services. These findings can help policymakers establish and implement forestry policies focusing on sustainable environmental conservation and ecosystem service provision.