Climate change is known to affect both natural and managed ecosystems, and will likely impact on the terrestrail carbon balance. This paper reports the effects of climate change on spatial-temporal changes in carbon reductions in South Korea's during 2000-2100. Future carbon (C) stock distributions are simulated for the same period using various spatial data sets including land cover, net primary production(NPP) and leaf area index (LAI) obtained from MODIS(Moderate Resolution Imaging Spectroradiometer), and climate data from Data Assimilation Office(DAO) and Korea Meteorological Administration(KMA). This study attempts to predict future NPP using multiple linear regression and to model dependence of soil respiration on soil temperature. Plants store large amounts of carbon during the growing periods. During 2030-2100, Carbon accumulation in vegetation was increased to $566{\sim}610gC/m^2$/year owing to climate change. On the other hand, soil respiration is a key ecosystem process that releases carbon from the soil in the form of carbon dioxide. The estimated soil respiration spatially ranged from $49gC/m^2$/year to $231gC/m^2$/year in the year of 2010, and correlating well with the reference value. This results include Spatial-Temporal C reduction variation caused by climate change. Therefore this results is more comprehensive than previous results. The uncertainty in this study is still large, but it can be reduced if a detailed map becomes available.
Journal of the Korea Society of Computer and Information
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v.26
no.12
/
pp.85-97
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2021
In this paper, in order to support rapid and effective decision-making and response in disaster situations, we identified the author's organization of academic research papers and conducted a collaborative relationship analysis study based on this. For this purpose, 2,308 papers in 69 Korean academic journals classified by disaster and safety type were selected for analysis and experimental data were constructed based on the Korea Science Citation Database (KSCD) and institutional identification data provided by KISTI. Collaborative relationship analysis was conducted for each of the four units (Institution, Institution type, Institution region and University department type). First, statistical status such as frequency of appearance was compared, and basic properties and main centrality index of each co-occurrence network were calculated and analyzed using Social Network Analysis Method. In addition, a visualization map was created and presented for each network so that the collaborative relationship could be viewed and understood as a whole. The results of this study are expected to contribute to the search activities of institutions and cooperative groups that support effective disaster response and to lay the foundation for the information service system.
Hwang, Jaehong;Chi, KwangHoon;Han, JongGyu;Yeon, Young Kwang;Ryu, Keun Ho
Journal of the Korean Association of Geographic Information Studies
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v.10
no.2
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pp.23-35
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2007
With the development of semantic web technologies in information retrieval area, the necessity for thesaurus is recently increasing along with internet lexicons. A thesaurus is the combination of classification and a lexicon, and is the topic map of knowledge structure expressing relations among concepts(terms) subject to human knowledge activities such as learning and research using formally organized and controlled index terms for clarifying the context of superordinate and subordinate concepts. However, although thesaurus are regarded as essential tools for controlling and standardizing terms and searching and processing information efficiently, we do not have a Korean thesaurus for geology. To build a thesaurus, we need standardized and well-defined guidelines. The standardized guidelines enable efficient information management and help information users use correct information easily and conveniently. The present study purposed to build a thesaurus system with terms used in geology. For this, First, we surveyed related works for standardizing geological terms in Korea and other countries. Second, we defined geological topics in 15 areas and prepared a classification system(draft) for each topic. Third, based on the geological thesaurus classification system, we created the specification of geological thesaurus. Lastly, we designed and implemented an internet-based geological thesaurus system using the specification.
The liquefaction phenomenon that occurred during the Pohang earthquake (ML=5.4) brought new awareness to the people about the risk of liquefaction caused by the earthquake. Liquefaction hazard maps with 2 km grid made in 2014 used more than 100,000 borehole data for the whole country, and regions without soil investigation data were produced using interpolation. In the mapping of macro liquefaction hazard for the whole country, the site amplification effect and the ground water level 0 m were considered. Recently, the Ministry of Public Administration and Security (2018) published a new site classification method and amplification coefficient of the common standard for seismic design. Therefore, it is necessary to rewrite the liquefaction hazard map reflecting the revised amplification coefficient. In this study, the results of site classification according to the average shear wave velocity in soils before and after revision were compared in the whole country. Also, liquefaction assessment results were compared in Gangseo-gu, Busan. At this time, two ground accelerations corresponding to the 500 and 1,000 years of return period and two ground water table, 5 m for the average condition and 0 m the extreme condition were applied. In the drawing of liquefaction hazard map, a 500 m grid was applied to secure a resolution higher than the previous 2 km grid. As a result, the ground conditions that were classified as SC and SD grounds based on the existing site classification standard were reclassified as S2, S3, and S4 through the revised site classification standard. Also, the result of the Liquefaction assessments with a return period of 500 years and 1,000 years resulted in a relatively overestimation of the LPI applied with the ground amplification factor before revision. And the results of this study have a great influence on the liquefaction assessment, which is the basis of the creation of the regional liquefaction hazard map using the amplification factor.
Park, Chang-Hee;Kang, Jin-Suk;Sung, Mee-Young;Park, Jong-Song;Kim, Jang-Hyung
Journal of the Korea Institute of Information and Communication Engineering
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v.10
no.11
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pp.1960-1972
/
2006
In this thesis, GPS and the electronic mapping were used to realize such a system by recognizing license plate numbers and identifying the location of objects that move at synchronous times with simulated movement in the electronic map. As well, throughout the study, a camera attached to a PDA, one of the mobile devices, automatically recognized and confirmed acquired license plate numbers from the front and back of each cu. Using this mobile technique in a wireless network searches for specific plate numbers and information about the location of the car is transmitted to a remote sewer. The use of such a GPS-based system allows for the measurement of topography and the effective acquisition of a car's location. The information is then transmitted to a central controlling center and stored as text to be reproduced later in the form of diagrams. Getting positional information through GPS and using image-processing with a PDA makes it possible to estimate the correct information of a car's location and to transmit the specific information of the car to a control center simultaneously, so that the center will get information such as type of the cu, possibility of the defects that a car might have, and possibly to offer help with those functions. Such information can establish a mobile system that can recognize and accurately trace the location of cars.
In this thesis, GPS and the electronic mapping were used to realize such a system by recognizing license plate numbers and identifying the location of objects that move at synchronous times with simulated movement in the electronic map. As well, throughout the study, a camera attached to a PDA, one of the mobile devices, automatically recognized and confirmed acquired license plate numbers from the front and back of each car. Using this mobile technique in a wireless network, searches for specific plate numbers and information about the location of the car is transmitted to a remote server. The use of such a GPS-based system allows for the measurement of topography and the effective acquisition of a car's location. The information is then transmitted to a central controlling center and stored as text to be reproduced later in the form of diagrams. Getting positional information through GPS and using image-processing with a PDA makes it possible to estimate the correct information of a car's location and to transmit the specific information of the car to a control center simultaneously, so that the center will get information such as type of the car, possibility of the defects that a car might have, and possibly to offer help with those functions. Such information can establish a mobile system that can recognize and accurately trace the location of cars.
Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.
This study measured and analyzed the weather characteristics and the air-ion characteristics of walking space by land use type in Chungju, Chungcheongbuk Province during the heat wave. We used the land registration map to classify the type of land use in walking areas in the studied into the production and green area, the residential area, and the commercial area. We then selected 44 measurement points in about 4.1 km. They included 12 walking space points in the green area, 14 in the residential area, and 18 in the commercial area. Moreover, we calculated the ion index by analyzing the impact of weather factors such as temperature, relative humidity, solar radiation, and net radiation in the walking space on the anion generation and cation generation by land use type during the heat wave. Comparison of air ion characteristics in walking space by type of land use during the heat wave showed that the average cation generation was in the order of commercial area ($700.73cations/cm^3$) > residential area ($600.76cations/cm^3$) > green area ($589.73cations/cm^3$). The average anion generation was in the order of green area ($663.95anions/cm^3$) > residential area ($628.48anions/cm^3$) > commercial area ($527.48anions/cm^3$). The average ion index was in the order of green area (1.13) > residential area (1.04) > commercial area (0.75). This study checked the weather characteristics, cation generation, and anion generation in walking space according to the land use type during the heat wave and checked the difference of ion indexes in the walking space according to the land use type. However, there were limitations in the lack of accurate comparison according to the land use due to the moving measurement and the insufficient quantitative comparison according to the change of road width. Therefore, we recommend further studies that consider the road characteristics.
The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.
Kim, Seokkon;Song, Jaegyok;Ji, Sungmi;Kwon, Min A;Nam, Dajeong
Journal of Dental Anesthesia and Pain Medicine
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v.19
no.6
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pp.353-360
/
2019
Background: Controlled hypotension (CH) provides a better surgical environment and reduces operative time. However, there are some risks related to organ hypoperfusion. The EV1000/FloTrac system can provide continuous cardiac output monitoring without the insertion of pulmonary arterial catheter. The present study investigated the efficacy of this device in double jaw surgery under CH. Methods: We retrospectively reviewed the medical records of patients who underwent double jaw surgery between 2010 and 2015. Patients were administered conventional general anesthesia with desflurane; CH was performed with remifentanil infusion and monitored with an invasive radial arterial pressure monitor or the EV1000/FloTrac system. We allocated the patients into two groups, namely an A-line group and an EV1000 group, according to the monitoring methods used, and the study variables were compared. Results: Eighty-five patients were reviewed. The A-line group reported a higher number of failed CH (P = 0.005). A significant correlation was found between preoperative hemoglobin and intraoperative packed red blood cell transfusion (r = 0.525; P < 0.001). In the EV1000 group, the mean arterial pressure (MAP) was significantly lower 2 h after CH (P = 0.014), and the cardiac index significantly decreased 1 h after CH (P = 0.001) and 2 h after CH (P = 0.007). Moreover, venous oxygen saturation (ScVO2) decreased significantly at both 1 h (P = 0.002) and 2 h after CH (P = 0.029); however, these values were within normal limits. Conclusion: The EV1000 group reported a lower failure rate of CH than the A-line group. However, EV1000/FloTrac monitoring did not present with any specific advantage over the conventional arterial line monitoring when CH was performed with the same protocol and same mean blood pressure. Preoperative anemia treatment will be helpful to decrease intraoperative transfusion. Furthermore, ScVO2 monitoring did not present with sufficient benefits over the risk and cost.
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