• Korean Journal of Agricultural and Forest Meteorology
• /
• v.9 no.2
• /
• pp.149-160
• /
• 2007

KoFlux Gwangneung Supersite comprises complex topography and diverse vegetation types (and structures), which necessitate complementary multi-disciplinary measurements to understand energy and matter exchange. Here, we report the results of this ongoing research with special focuses on carbon/water budgets in Gwangneung forest, implications of inter-dependency between water and carbon cycles, and the importance of hydrology in carbon cycling under monsoon climate. Comprehensive biometric and chamber measurements indicated the mean annual net ecosystem productivity (NEP) of this forest to be ${\sim}2.6\;t\;C\;ha^{-1}y^{-1}$. In conjunction with the tower flux measurement, the preliminary carbon budget suggests the Gwangneung forest to be an important sink for atmospheric $CO_2$. The catchment scale water budget indicated that $30\sim40%$ of annual precipitation was apportioned to evapotranspiration (ET). The growing season average of the water use efficiency (WUE), determined from leaf carbon isotope ratios of representative tree species, was about $12{\mu}mol\;CO_2/mmol\;H_2O$ with noticeable seasonal variations. Such information on ET and WUE can be used to constrain the catchment scale carbon uptake. Inter-annual variations in tree ring growth and soil respiration rates correlated with the magnitude and the pattern of precipitation during the growing season, which requires further investigation of the effect of a monsoon climate on the catchment carbon cycle. Additionally, we examine whether structural and functional units exist in this catchment by characterizing the spatial heterogeneity of the study site, which will provide the linkage between different spatial and temporal scale measurements.

• Progress in Medical Physics
• /
• v.25 no.4
• /
• pp.298-303
• /
• 2014

In this study, we examine the trends and types of incidents frequently occur during radiation therapy by using the data from the radiation oncology safety information system (ROSIS), according to discovery method explores the development direction of future research accident cause factor control method. This study was carried out analysis of incident data in ROSIS nearly 1163 cases in last 11 years from 2003 to 2013. We categorized into treatment methods, found the time, discoverer of occupations and finding ways to analyze the data. Then, we calculate the percentage and the classification for each item. About 1163 cases of incident cases including the near miss cases, external radiation therapy, brachytherapy and other were 97%, 2% and 1%. In the case was improperly planned dose delivery was 44% (497 cases) which 429 cases (86%) was found before 3 fractions and 13 cases were found after 11 fractions. The investigation was found to be distributed in various a found times. Approximately 42% of found time was during treatment and 29% of patients were found the problem during inspection chart. Occupation to discover the most radiation accidents was the radiation therapist (53%) who works in treatment room. Among 1163 incidence cases, 24% cases were found the accident before the treatment, therefore most of accident were found after of during the treatment (70%, 813 cases). This trend is acquired through ROSIS analysis, is expected to be not significantly different in the case of Korea, so it is necessary more diverse and systematic research for the prevention and early detection by using the ROSIS data.

• Journal of Life Science
• /
• v.15 no.6 s.73
• /
• pp.972-978
• /
• 2005

The present study was carried out to investigate the blood markers of Jeju horses. The redcell cypes (blood groups) and blood protein types (biochemical polymorphisms) were tested from 102 Jeju horses by serological and electrophoretc procedure, and their phenotypes and gene frequencies were estimated. The blood group and biochemical polymorphism phenotypes observed with high frequency were $A^{af}\;(27.45\%$), $C^{a}\;(99.02\%$), $K^{-}\;(97.06\%$), $U^{a}\;(62.75\%$), $P^{b}\;(36.27\%$), $Q^{c}\;(47.06\%$), $D^{cgm/dghm}\;(13.73\%$), $D^{adn/cgm}\;(9.80\%$), $D^{ad/cgm}$\;(8.82\%$), $D^{dghm/dghm}(7.84\%$), $D^{cgm/cgm}(7.84\%$), $AL^{B}\;(48.04\%$), $GC^{F}\;(99.02\%$), $AlB^{K}\;(97.06\%$), $ES^{FI}\;(36.27\%$), $TF^{F2}\;(25.49\%$), $HB^{B1}\;(45.10\%$), and $PGD^{F}\;(86.27\%$) in Jeju horses, respectively. Alleles observed with high gene frequency were $A^{af}$ (0.3726), $A^{C}$ (0.2647), $C^{-}$ (0.5050), $K^{-}$ (0.9853), $U^{-}$ (0.6863), $P^{b}$ (0.4657), $Q^{c}$ (0.5294), $D^{cgm}$ (0.3039), $HB^{B1}$(0.6863), $PGD^{F}$ (0.9265), $AL^{B}$ (0.6912), $ALB^{K}$ (0.9852), $GC^{F}$ (0.9950), $ES^{I}$ (0.5000) and $TF^{F2}$ (0.4950) in Jeju horses, and sfecific alleles, $D^{cgm(f)}$ (0.0196), $HB^{A}$ (0.0147), $HB^{A2}$ (0.0196), $ES^{G}$ (0.0441), $ES^{H}$ (0.0098), $TF^{E}$TF'(0.0246), $TF^{H2}$ (0.0049) and $PGD^{D}$ (0.0098) were detected in Jeju horses. These preliminary results present basic information for detecting the genetic markers in Jeju horse. and developing a system for parentage verification and individuals identification in jeju horses.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.4
• /
• pp.195-209
• /
• 2021

According to the 2019-2020 social media usage survey conducted by the Seoul e-commerce center, 5 out of 10 consumers have experienced shopping through social media. The cost of traditional advertising media has been reduced and advertising spending on social media has risen by 74%, indicating that social media is becoming a more important marketing element. While the number of users of social media has increased and corporate marketing activities have increased accordingly, research has been conducted in various aspects of marketing such as user motivation for social media, satisfaction, and purchase intention. There was no subdivided study on the differences in the social media usage frequency of consumers in actual purchasing behavior. This study attempted to identify differences in consumer characteristics by cluster in the agrifood purchase situation by grouping them by type according to the frequency of use of social media for consumers who purchase agri-food online. Product involvement, product need, and online purchase channel Consumer characteristics such as demographic distribution, perceived risk, and eating and lifestyle in each cluster were checked for the three agrifood purchase situations including choice, and types for each cluster were presented. To this end, questionnaire data on the frequency of social media use and online agrifood purchase behavior were collected from 245 consumers, and the validity of the measurement variables was secured through factor analysis and reliability analysis. As a result of cluster analysis according to the frequency of social media use, it was divided into three clusters. The first cluster was a group that mainly used open social media, and the second cluster was a group that used both open and closed social media and online shopping malls; The third cluster was a group with low online media usage overall, and the characteristics of each cluster appeared. Through regression analysis, the effect on product involvement, product need, and purchase channel selection when purchasing agri-food online through each of the three clusters was confirmed through regression analysis. As a result of the regression analysis, the characteristic of cluster 1 in the situation of purchasing agri-food online is a male in his 30s living in a rural area who has no reluctance to purchase agri-food on social media or online shopping malls. The characteristics of cluster 2 are mainly consumers who are interested in purchasing health food, and the consumer characteristics are represented. In the case of cluster 3, when purchasing products online, they purchase after considering quality and price a lot, and the consumer characteristics are represented as people who are more confident in purchasing offline than online. Through this study, it is judged that by identifying the differences in consumer characteristics that appear in the agri-food purchase situation according to the frequency of social media use, it can be helpful in strategic judgments in marketing practice on social media customer targeting and customer segmentation.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.2
• /
• pp.89-100
• /
• 2021

This study evaluated the degree of interaction between the people and the environment using perceived naturalness measure. The seventh-grade index of Hemeroby was divided into subclasses of land cover according to degrees of human influence. The grade was standardized for each indicator to evaluate the current state of urban parks in Seoul by applying probability density function and weight. User evaluation was conducted on six distinctive parks selected. In the results, three implications were found between spatial evaluation according to the perceived naturalness. First, park users evaluated highly for the spaces such as broad-leaved forest, coniferous forest and mixed forest evaluated highly in the Hemeroby grade index. Park users generally recognized that various types of trees in the area had high naturalness. The density of trees is one of the factors in perceived naturalness. Second, water spaces were highly evaluated for naturalness in the Hemeroby grade index. However, the perceived naturalness of water spaces such as inland wetlands, pond and reservoir evaluated in various ways depending on environmental conditions around the park. Third, perceived naturalness is easily evaluated through vertical landscape elements such as trees rather than horizontal landscapes such as grassland. The perceived naturalness is similar to the naturalness evaluation using land cover. However the study found the perceived naturalness for a specific space was different from the Hemeroby index. Perceived naturalness by the user includes the content that the individual sees, hears, and experiences. Park users are usually structuring naturalness through evaluating the value of urban green spaces based on personal perception. Therefore there is no absolute standard criterion for evaluating the naturalness of urban green spaces. A deeper study is needed that considers user bundles or user groups with conflicting interests on the perceived naturalness in urban parks. These studies will be essential data on the direction of naturalness urban park service should provide.

• Journal of Wetlands Research
• /
• v.24 no.4
• /
• pp.331-344
• /
• 2022

This study analyzed the characteristics of the soil and hydrological environment of abandoned paddy wetlands examined the changes in land cover type in the ecological affect area, analyzed the environmental factors of abandoned paddy wetlands, and examined the changes in land cover type in the ecological impact area. The ecological environment characteristics of the reference abandoned paddy wetlands were investigated through literature research, environmental spatial information service, and preliminary exploration of the abandoned paddy wetlands, and the basic data for the restoration of abandoned paddy wetlands ware provided by examining the changes in land cover type in the ecological impact area for 40 years. Through this study, it will be possible to manage the rapidly increasing number of abandoned farmland to be converted into wetlands so that it can perform functions equivalent to or greater than that of natural wetlands. In particular, as we checked the clues that abandoned paddy wetlands could spread to surrounding ecological influences through land cover changes, the study sites are highly likely to be reference wetlands, and if the topography, soil, water circulation system, and carbon reduction performance are analyzed carefully, it will be possible to standardize the development process. In addition, through the change in land cover, clues were confirmed that the abandoned paddy wetlands could spread to the surrounding ecological affect areas. The land cover type in the ecological impact area, forests was mainly distributed, but generally decreased rapidly in the last 10-20 years, and forests were changing from coniferous forests to broad-leaved forests, mixed forests, or grassland. It has not yet been fully called to the wetland, and it is found that it has maintained the form of barren or grassland, and as can be seen in the case of natural wetlands after more than 30 years after abandoned, it is expected that the transition will gradually proceed to wetlands that are structurally and functionally similar to natural wetlands.

• The Journal of Engineering Geology
• /
• v.32 no.4
• /
• pp.697-723
• /
• 2022

Data-driven models to predict groundwater levels 30 days in advance were developed for 12 groundwater monitoring stations in the middle-Jeju watershed, Jeju Island. Stacked long short-term memory (stacked-LSTM), a deep learning technique suitable for time series forecasting, was used for model development. Daily time series data from 2001 to 2022 for precipitation, groundwater usage amount, and groundwater level were considered. Various models were proposed that used different combinations of the input data types and varying lengths of previous time series data for each input variable. A general procedure for deep-learning-based model development is suggested based on consideration of the comparative validation results of the tested models. A model using precipitation, groundwater usage amount, and previous groundwater level data as input variables outperformed any model neglecting one or more of these data categories. Using extended sequences of these past data improved the predictions, possibly owing to the long delay time between precipitation and groundwater recharge, which results from the deep groundwater level in Jeju Island. However, limiting the range of considered groundwater usage data that significantly affected the groundwater level fluctuation (rather than using all the groundwater usage data) improved the performance of the predictive model. The developed models can predict the future groundwater level based on the current amount of precipitation and groundwater use. Therefore, the models provide information on the soundness of the aquifer system, which will help to prepare management plans to maintain appropriate groundwater quantities.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.5B
• /
• pp.595-601
• /
• 2008

The purpose of this study is to investigate the trends and patterns of various kind of water uses in a household by metering in Korea. Water use components are classified by toilet, washbowl, bathing, laundry, kitchen, miscellaneous. Flow meters are installed in 140 household selected by sampling in all around Korea. The data are gathered by web-based data collection system from the year 2002 to 2006, considering pre-investigated data such as occupation, revenue, family members, housing types, age, floor area, water saving devices, education, miscellaneous. Reliable data are selected by upper fence method for each observed water use component and statistical characteristics are estimated for each residential type to determine liter per capita per day. Estimated domestic per capita day show an indoor water use with the range from 150 lpcd to 169 lpcd for each housing type as the order of high rise apartment, multi-house, and single house. As the order of consuming amount among water use components, it is investigated that toilet (38.5 lpcd) is the first, and the second is laundry water (30.8 lpcd), the third is kitchen (28.4 lpcd), the fourth is bathtub (24.7 lpcd), the next is washbowl (15.4 lpcd). The results are compared with water uses in U.K. and U.S. As life style has been changed into western style, pattern of water use in Korea is tend to be similar with the U.S. water use pattern. Compared with the surveying results by Bradley, on 1985. Thirty liter of total use increased with the advancement of economic level, and a little change of water use pattern can be found. Especially, toilet water take almost half part of total water use and laundry water shows lowest as 11% in surveying at the year of 1985. But, this study shows that 39 liter, 28% of toilet water, has been decreased by the spread of saving devices and campaign. It is supposed that the spread large sized laundry machine make by-hand laundry has been decreased and water use increased. Unit water amount of each end-use in household can be applied to design factor for water and wastewater facilities, and it play a role as information in establishing water demand forecasting and conservation policy.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2023.04a
• /
• pp.7-7
• /
• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of Intelligence and Information Systems
• /
• v.21 no.4
• /
• pp.111-131
• /
• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.