• Journal of Korean Port Research
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• v.12 no.2
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• pp.349-362
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• 1998

Seascape means the scenery which is composed around the sea., Seascape has it's own characteristics compared with landscape and has many important roles in our urban life. Nowadays seascape is being destructed by the development in waterfront area and ocean space. Especially the various kind of buildings which are built in coastal area give great visual impact on seascape. But we have rare research on seascape and no guideline for seascape planning. Before any action against destroying seascape the assessment of seascape has to be preceded. The purpose of this study is to evaluate the representative seascapes which are selected from over 300 slides of various seascapes according to the types of seascapes. We used S.D (Semantic Differential) method with 35 adjective pairs in seven scale to evaluate each seascape. The results can be summarized as follows. 1) Seascapes can be classified as natural type and urban type. The natural type can be divided into beach type and rock-island type. 2) Natural type of seascape is more prefered than urban type. 3)Beach type is the most prefered among seascape types. 4) Natural elements of seascape such as sky, water, sand, trees, forest, mountain, open space, waterfront line, are evaluated as 'good' to see but artificial elements, such as buildings, persons, roads, structures, are evaluated 'bad' to see. 5)As a result of factor analysis five factors(axes) are found out. They are 'wildness', 'vividness', 'preference', 'interest', and 'openness'. These factors can be used for evaluting any seascape.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1530-1537
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• 2016

Recently, solar power generation shows the significant growth in the renewable energy field. Using the short-term prediction, it is possible to control the electric power demand and the power generation plan of the auxiliary device. However, a short-term prediction can be used when you know the weather forecast. If it is not possible to use the weather forecast information because of disconnection of network at the island and the mountains or for security reasons, the accuracy of prediction is not good. Therefore, in this paper, we proposed a system capable of short-term prediction of solar power generation amount by using only the weather information that has been collected by oneself. We used temperature, humidity and insolation as weather information. We have applied a moving average to each information because they had a characteristic of time series. It was composed of min, max and average of each information, differences of mutual information and gradient of it. An artificial neural network, SVM and RBF Network model was used for the prediction algorithm and they were combined by Ensemble method. The results of this suggest that using a moving average during pre-processing and ensemble prediction models will maximize prediction accuracy.

• The Plant Pathology Journal
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• v.35 no.5
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• pp.417-424
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• 2019

Melanose, caused by Diaporthe citri, is one of severe diseases in citrus, a major economic resource in Jeju island. To reduce the usage amount of organic synthetic fungicide, bio-sulfur was tested as an alternative chemical to control citrus melanose in the present study. Direct antifungal activity of bio-sulfur against D. citri was determined through in vitro experiment using artificial nutrient media. Disease severity of melanose on bio-sulfur pretreated citrus leaves was lower than that on untreated ones. To illustrate the mechanism of disease suppression by bio-sulfur, infection structures were observed with a fluorescent microscope and a scanning electron microscope. In fluorescent microscopic observation, most conidia rarely germinated. In addition, hyphal growth on leaves pretreated with bio-sulfur was inhibited compared to that on untreated ones. In scanning electron microscope images of bio-sulfur pretreated leaves, surfaces of most conidia were shrunk while hyphae were morphologically changed and frequently branched. Such microscopic observations were also found for leaves pretreated with a commercial fungicide Dithianon. These results suggest that bio-sulfur may be used to control citrus melanose as an environment friendly alternative to organic synthetic fungicides

• Journal of Environmental Science International
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• v.31 no.6
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• pp.525-533
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• 2022

Baengnyeongdo, located within the Asian dust stream, is an ideal place to analyze Asian dust moving into the West Sea due to its low emission of artificial pollutants. Baengnyeongdo is being used to analyze the vertical distribution of dust from the lower atmosphere to the upper layer through remote observation. This study compared the ground concentration of dust between Baengnyeongdo and the metropolitan area, estimated the lag time of transport of Asian dust from Baengnyeongdo to the metropolitan area, and examined the homogeneity of upper winds using the rawinsonde method. The results showed that the cross correlation coefficient was higher and the lag time was shorter for each observation station when the distance from Baengnyeongdo was shorter. The upper wind at Baengnyeongdo is dominated by the west/northwest wind. It is the basis for the correlation of dust concentration between Baengnyeongdo and the metropolitan area located to the east. In the future, upper wind data and Asian dust concentration data over the West Sea and Baengnyeongdo are expected to contribute to research related to the movement and prediction of Asian dust and preparation for Asian dust in the metropolitan area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.159-160
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• 2021

We are facing major changes such as an aging population along with the 4th industrial revolution based on ICT technologies such as artificial intelligence, the Internet of Things, autonomous driving, and factory automation. For the local governments that are indexed in high population extinction risk, it is essential to consider market expansion and re-education policies suitable for regional characteristics in order to respond to changes such as advanced industrial automation and population aging. For the reemployment of the elderly, we will analyze previous public strategies for elderly-friendly jobs, expand investment in age-friendly industries. In this study, we suggest to improvement direction of the elderly labor market in Cheonan-Si.

• Journal of Wind Energy
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• v.14 no.1
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• pp.37-43
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• 2023

In this study, synthetic time series wind data was generated numerically using a second-order Markov chain. One year of wind data in 2020 measured by the AWS on Wido Island was used to investigate the statistics for measured wind data. Both the transition probability matrix and the cumulative transition probability matrix for annual hourly mean wind speed were obtained through statistical analysis. Probability density distribution along the wind speed and autocorrelation according to time were compared with the first- and the second-order Markov chains with various lengths of time series wind data. Probability density distributions for measured wind data and synthetic wind data using the first- and the second-order Markov chains were also compared to each other. For the case of the second-order Markov chain, some improvement of the autocorrelation was verified. It turns out that the autocorrelation converges to zero according to increasing the wind speed when the data size is sufficiently large. The generation of artificial wind data is expected to be useful as input data for virtual digital twin wind turbines.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1447-1460
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• 2021

Urbanization increases the amount of impervious surface and artificial heat emission, resulting in urban heat island (UHI) effect. Local climate zones (LCZ) are a classification scheme for urban areas considering urban land cover characteristics and the geometry and structure of buildings, which can be used for analyzing urban heat island effect in detail. This study aimed to examine the UHI effect by urban structure in Suwon and Daegu using the LCZ scheme. First, the LCZ maps were generated using Landsat 8 images and convolutional neural network (CNN) deep learning over the two cities. Then, Surface UHI (SUHI), which indicates the land surface temperature (LST) difference between urban and rural areas, was analyzed by LCZ class. The results showed that the overall accuracies of the CNN models for LCZ classification were relatively high 87.9% and 81.7% for Suwon and Daegu, respectively. In general, Daegu had higher LST for all LCZ classes than Suwon. For both cities, LST tended to increase with increasing building density with relatively low building height. For both cities, the intensity of SUHI was very high in summer regardless of LCZ classes and was also relatively high except for a few classes in spring and fall. In winter the SUHI intensity was low, resulting in negative values for many LCZ classes. This implies that UHI is very strong in summer, and some urban areas often are colder than rural areas in winter. The research findings demonstrated the applicability of the LCZ data for SUHI analysis and can provide a basis for establishing timely strategies to respond urban on-going climate change over urban areas.

• Korean Journal of Environment and Ecology
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• v.25 no.1
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• pp.91-101
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• 2011

The purpose of this study is to demonstrate the positive effects of artificial ground greening on the reduction of carbon dioxide ($CO_2$) which can help improve ecological functions in cities and mitigation of climate change, through quantifying $CO_2$ uptake and evapotranspiration by the process of photosynthesis of some plants. Experiment of $CO_2$ uptake and evapotranspiration was conducted by measurement of $CO_2$ exchange rate using the infrared gas analyzer, for 7 month, growing season from May to November 2009, 2 times a month. The result was as follows; The $CO_2$ uptake quantity per $cm^2$ of Chrysanthemum zawadskii was the highest rate at $21.47{\times}10^{-6}g/cm^2/s$ and Poa pratensis was $16.20g{\times}10^{-6}g/cm^2/s$. The stronger was light of intensity, the higher were $CO_2$ uptake rate of most plants. In quantity of evapotranspiration, Poa pratensis was the highest rate at $8.75{\times}10^{-5}g/cm^2/s$ and Aquilegia buergariana was $8.66{\times}10^{-5}g/cm^2/s$. From this study, it is confirmed that artificial ground greening has capacity of absorption $CO_2$ and effects on improving urban microclimate.

• The Korean Journal of Malacology
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• v.27 no.2
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• pp.99-105
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• 2011

This study was conducted to compare the species composition of sessile organisms on the artificial substrates of PVC submerged at different time intervals and duration in Jangmok Bay, Geoje Island, southern coast of Korea. Three PVC plates were submerged at one month interval from March to October and retrieved in November, 2007. A mussel, Mytilus galloprovincialis exclusively occupied the artificial substrates submerged from March to April and occurred as a dominant species to July. An ascidian, Styela plicata occurred as a dominant sessile species from May to August. Balanus amphtrite, Bugula sp., and hydrozoans occurred as dominant species on the plates submerged from July to September. There was a mis-match between the peak time of settlement and dominance of sessile organisms due to the interspecies competitions when the PVC plates were retrieved in November. There was no clear relationship between submerged duration and the abundance of sessile organisms due to the different settlement period. M. galloprovincialis seemed to be a strong competitor which could exclude the previous recruiters of macroalgae by overgrowth and occupy the substrate surface and maintain its high population density by preventing the settlement of other species until late autumn. These results suggested that the composition of sessile organisms in vacant hard substrates could be determined by the combined effects of supply-timing of larvae and post-settlement competitions.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.485-493
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• 2021

Groundwater is an important water resource that can be used along with surface water. In particular, in the case of island regions, research on groundwater level variability is essential for stable groundwater use because the ratio of groundwater use is relatively high. Researches using artificial intelligence models (AIs) for the prediction and analysis of groundwater level variability are continuously increasing. However, there are insufficient studies presenting evaluation criteria to judge the appropriateness of groundwater level prediction. This study comprehensively analyzed the research results that predicted the groundwater level using AIs for various regions around the world over the past 20 years to present the range of allowable groundwater level prediction errors. As a result, the groundwater level prediction error increased as the observed groundwater level variability increased. Therefore, the criteria for evaluating the adequacy of the groundwater level prediction by an AI is presented as follows: less than or equal to the root mean square error or maximum error calculated using the linear regression equations presented in this study, or NSE ≥ 0.849 or R² ≥ 0.880. This allowable prediction error range can be used as a reference for determining the appropriateness of the groundwater level prediction using an AI.