• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.955-968
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• 2021

A water resource plan is routinely based on a natural flow and can be estimated using observed streamflow data or a long-term continuous rainfall-runoff model. However, the watershed with the natural flow is very limited to the upstream area of the dam. In particular, for the ungauged watershed, a rainfall-runoff model is established for the gauged watershed, and the model is then applied to the ungauged watershed by transferring the associated parameters. In this study, the GR4J rainfall-runoff model is mainly used to regionalize the parameters that are estimated from the 14 dam watershed via an optimization process. In terms of optimizing the parameters, the Bayesian approach was applied to consider the uncertainty of parameters quantitatively, and a number of parameter samples obtained from the posterior distribution were used for the regionalization. Here, the relationship between the estimated parameters and the topographical factors was first identified, and the dependencies between them are effectively modeled by a Copula function approach to obtain the regionalized parameters. The predicted streamflow with the use of regionalized parameters showed a good agreement with that of the observed with a correlation of about 0.8. It was found that the proposed regionalized framework is able to effectively simulate streamflow for the ungauged watersheds by the use of the regionalized parameters, along with the associated uncertainty, informed by the basin characteristics.

• Korean Journal of Plant Resources
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• v.35 no.2
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• pp.289-316
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• 2022

This study was investigated to elucidate the distribution of vascular plants and their usefulness of Seondalsan Mountain (1,236 m) in Bonghwa-gun, Gyeongsangbuk-do. The surveys were carried out 20 times from April in 2014 to October in 2020. The vascular plants of Seondalsan Mountain was consisted a total of 638 taxa based on the voucher specimens; 96 families, 341 genera, 562 species, 18 subspecies, 53 varieties, 5 forms. 20 taxa of the Korean endemic plants were recorded and 1 taxa of Critically Endangered (CR), 3 taxa of Vulnerable (VU) and 9 taxa of Least Concern (LC), designated by Korean Forest Service as rare plants, were investigated in this region. Furthermore, V, IV and III degrees of floristic regional indicator plants, designated by the National Institute of Ecology, were included 1 taxa, 11 taxa and 28 taxa, respectively. Among them, edible, medicinal, fragrant, industrial, ornamental, ecological restoration, forage/compost plants were included 440 taxa, 505 taxa, 19 taxa, 234 taxa, 335 taxa, 214 taxa and 269 taxa respectively. In addition, 30 taxa of naturalized plants were observed.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1037-1051
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• 2021

Biochemical oxygen demand (BOD) concentration, one of important water quality indicators, is treated as the measuring item for the ecological chapter in lakes and rivers. This investigation employed novel two-stage hybrid paradigm (i.e., wavelet-based gated recurrent unit, wavelet-based generalized regression neural networks, and wavelet-based random forests) to predict BOD concentration in the Dosan and Hwangji stations, South Korea. These models were assessed with the corresponding independent models (i.e., gated recurrent unit, generalized regression neural networks, and random forests). Diverse water quality and quantity indicators were implemented for developing independent and two-stage hybrid models based on several input combinations (i.e., Divisions 1-5). The addressed models were evaluated using three statistical indices including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (CC). It can be found from results that the two-stage hybrid models cannot always enhance the predictive precision of independent models confidently. Results showed that the DWT-RF5 (RMSE = 0.108 mg/L) model provided more accurate prediction of BOD concentration compared to other optimal models in Dosan station, and the DWT-GRNN4 (RMSE = 0.132 mg/L) model was the best for predicting BOD concentration in Hwangji station, South Korea.

• Korean Journal of Plant Resources
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• v.35 no.5
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• pp.614-640
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• 2022

We investigated vascular plants of Bigeumdo and Dochodo Island in Shinan-gun, Jeollanam-do, Korea. By referring to 4 field surveys between June and September in 2021, a total of 490 taxa were identified and grouped into 113 families, 332 genera, 452 species, 6 subspecies, 27 varieties, and 3 forms. Among those observed, 232 taxa comprising 84 families, 189 genera, 220 species, 4 subspecies, 8 varieties, 4 forms were observed in Bigeumdo, 428 taxa comprising 107 families, 305 genera, 397 species, 5 subspecies, 23 varieties and 3 forms were observed in Dochodo. Among them, 7 taxa were Korean endemic plants. Protected species designated by the Ministry of Environment were 2 taxa of level II. In terms of threated plants according to the IUCN Red List Categoty, there were 5 taxa, consisting of 1 endangered species (EN), 3 vulnerable species (VU), 1 Near Threatened (NT). In total, there are 36 taxa of floristic regional indicator plants, including 1 level V taxa, 5 level IV taxa, 28 level III taxa. In Korea, 3 taxa were the northern distributional limit to Bigeumdo and Dochodo. Alien plants were 58 taxa.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1013-1024
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• 2022

In addition to the assessment measure of electric quality levels, load loss are also a factor in hindering the financial profits of electrical sales companies. Therefore, accurate analysis of load losses generated from distributed power networks is very important. The accurate calculation of load losses in the distribution line has been carried out for a long time in many research institutes as well as power utilities around the world. But it is increasingly difficult to calculate the exact amount of loss due to the increase in the congestion of distribution power network due to the linkage of distributed energy resources(DER). In this paper, we develop smart grid big data infrastructure in order to accurately analyze the load loss of the distribution power network due to the connection of DERs. Through the preprocess of data selected from the smart grid big data, we develop a load loss analysis model that eliminated 'veracity' which is one of the characteristics of smart grid big data. Our analysis results can be used for facility investment plans or network operation plans to maintain stable supply reliability and power quality.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.925-932
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• 2021

A drought-flood abrupt alternation event is an overlapping extreme event that is harder to cope with than a single event of drought and flood. It is also expected to have a significant adverse impact on ecosystems as well as industries and agriculture. However, there has not yet been a comprehensive study that characterizes the drought-flood abrupt alternation events in Korea. Therefore, this study employed a standard weighted average precipitation (SWAP) index, which is efficient to analyze not only individual events of drought and flood but also the drought-flood abrupt alternation events considering various time scales. The SWAP standardized the weighted average precipitation (WAP) by adding temporal weights to the precipitation. The SWAP indices were calculated for middle-sized watersheds of the Han River basin using the area average precipitation during 1966 and 2018. The severity K was calculated to represent the relative regional severity considering normal rainfalls, and used to characterize the drought-flood abrupt alternation in the study areas. The results indicated that 20 of the 30 middle-sized watersheds in the Han River basin were confirmed to increase the severity of drought-flood abrupt alternation over time. Considering the frequency and severity of drought-flood abrupt alternation events in each watershed, vulnerable areas and dangerous areas due to drought-flood abrupt alternation were identified, for example, the Upstream Namhan River (#1001).

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.221-244
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• 2023

Focusing on Gyeonggi Library, which is preparing Metaverse services using resident participatory budgets, we deduced the role of Metaverse suitable for metropolitan representative libraries, conducting a preliminary study and analyzing various informational resources. Subsequently, we presented a collaborative content construction and service model primarily centered around the metropolitan representative library. We conducted a survey targeting on-site librarians from metropolitan representative libraries, as well as various libraries across Gyeonggi Province and the entire nation. Through this survey, we extracted insights into the Metaverse role, content possibilities, and considerations for seamless cooperation within the scope of the metropolitan representative library. Based on the opinions of surveyed librarians, it was evident that the role of the metropolitan representative library's Metaverse should function as a tool for continuous utilization of library resources and serve as a space for the entire local community. Approximately three-fourths of the respondents expressed willingness to participate in collaborative content development. However, concerns were raised about human resource limitations, budget constraints, and excessive workloads as potential obstacles to participation. This highlighted the need for systematic support from the metropolitan representative library to address these concerns.

• Journal of International Area Studies (JIAS)
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• v.13 no.1
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• pp.107-133
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• 2009

International relations in the 21st century is featured by boundless competition among nations to secure sufficient energy resources for achieving economic development. Resource diplomacy, therefore, is competitive in its nature, which is derived from the fact that resources of the globe are limited. Chinese recent economic growth has been possible mainly due to its success in resource diplomacy. The Chinese resource diplomacy has shown two different patterns according to target regions. On the one hand, China has pursued multilateral approach to Central Asia region, by which China aimed to secure energy with joint exploration method in the region. Chinese resource diplomacy toward Africa, on the other hand, has been based on bilateral approach combined with unit-centered economic aid to African nations. This difference in Chinese foreign policy pattern seems to be derived from three factors: namely, Chinese strategic considerations on geopolitical condition, regional security sensitivity, and legacies of Chinese long-time non-alignment diplomacy since the 1950s. Whether China is able to maintain the current pattern of resource diplomacy will be depended on how wisely China pursue its relations with two other global powers: Russia in the Central Asia and the U.S. in Africa. In this regard, the Chinese resource diplomacy is expected to work as determining factor of shaping a pattern of tri-lateral strategic relations among the U.S., Russia, and China. Chinese resource diplomacy thus will determine the future direction of the global politics in terms of strategic arrangement.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.245-259
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• 2023

The agricultural reservoir is a critical water supply system in South Korea, providing approximately 60% of the agricultural water demand. However, the reservoir faces several issues that jeopardize its efficient operation and management. To address this issues, we propose a novel deep-learning-based water level recognition model that uses CCTV image data to accurately estimate water levels in agricultural reservoirs. The model consists of three main parts: (1) dataset construction, (2) image segmentation using the U-Net algorithm, and (3) CCTV-based water level recognition using either CNN or ResNet. The model has been applied to two reservoirs G-reservoir and M-reservoir with observed CCTV image and water level time series data. The results show that the performance of the image segmentation model is superior, while the performance of the water level recognition model varies from 50 to 80% depending on water level classification criteria (i.e., classification guideline) and complexity of image data (i.e., variability of the image pixels). The performance of the model can be improved if more numbers of data can be collected.