• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Korean Journal of Ecology and Environment
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• v.35 no.4 s.100
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• pp.285-294
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• 2002

The purpose of this study was to evaluate the relationships between purification characteristics and hydraulic conditions, and to clarify the basic and essential factors required to be considered in the construction and management of artificial wetland system for the improvement of reservoir water quality. The artificial wetland system was composed of a pumping station and six sequential plants beds with five species of macrophytes: Oenanthe javanica, Acorus calamus, Zizania latifolia, Typha angustifolia, and Phragmites australis. The system was operated on free surface-flow system, and operation conditions were $3,444-4,156\; m^3/d$ of inflow rate, 0.5-2.0 hr of HRT, 0.1-0.2 m of water depth, 6.0-9.4 m/d of hydraulic loading, and relatively low nutrients concentration (0.224-2.462 mgN/L, 0.145-0.164 mgP/L) of inflow water. The mean purification efficiencies of TN ranged from 12.1% to 14.3% by showing the highest efficiency at the Phragmites australis bed, and these of TP were 6.3-9.5% by showing the similar ranges of efficiencies among all species. The mean purification efficiencies of SS and Chl-A ranged from 17.4% to 38.5% and from 12.0% to 20.2%, respectively, and the Oenanthe javanica bed showed the highest efficiency with higher concentration of influent than others. The mean purification amount per day of each pollutant were $9.8-4.1\;g{\cdot}m^{-2}{\cdot}d^{-1}$ in BOD, $1.299-2.343\;g{\cdot}m^{-2}{\cdot}d^{-1}$ in TN, $0.085-1.821\;g{\cdot}m^{-2}{\cdot}d^{-1}$ in TP, $17.9-111.6\;g{\cdot}m^{-2}{\cdot}d^{-1}$ in SS and $0.011-0.094\;g{\cdot}m^{-2}{\cdot}d^{-1}$ in Chl-a. The purification amount per day of TN revealed the hi링hest level at the Zizania latifolia bed, and TP showed at the Acrous calamus bed. SS and Chl-a, as particulate materials, revealed the highest purification amount per day at the Oenanthe javanica bed that was high on the whole parameters. It was estimated that the purification amount per day was increased with the high concentration of influent and shoot density of macrophytes, as was shown in the purification efficiency. Correlation coefficients between purification efficiencies and hydraulic conditions (HRT and inflow rate) were 0.016-0.731 of $R^2$ in terms of HRT, and 0.015-0.868 of $R^2$ daily inflow rate. Correlation coefficients of purification amounts per day with hydraulic conditions were 0.173-0.763 of Ra in terms of HRT, and 0.209-0.770 daily inflow rate. Among the correlation coefficients between purification efficiency and hydraulic condition, the percentages of over 0.5 range of $R^2$ were 20% in HRT and in daily inflow rate. However, the percentages of over 0.5 range of correlation coefficients ($R^2$) between purification amount per day and hydraulic conditions were 53% in HRT and 73% in daily inflow rate. The relationships between purificationamount per day and hydraulic condition were more significant than those of purifi-cation efficiency. In this study, high hydraulic conditions (HRT and inflow rate) are not likely to affect significantly the purification efficiency of nutrient. Therefore, the emphasis should be on the purification amounts per day with high hydraulicloadings (HRT and inflow rate) for the improvement of eutrophic reservoir withrelatively low nutrients concentration and large quantity to be treated.

• Korean Journal of Heritage: History & Science
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• v.53 no.4
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• pp.234-249
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• 2020

The dispute involving the construction of the Tomb of Queen Sindeok (hereinafter "Jeongreung"), King Taejo's wife in Seoul, and the moving of that tomb, represents the most clearly demonstrated case for the collision of new and old ideologies between political powers in the early period of Joseon. Jeongreung, the tomb of Queen Sindeok from the Kang Clan, was built inside the capital fortress, but in 1409, King Taejong forced the tomb to be moved outside the capital, and the stone relics remaining at the original location were used to build the stone bridge, Gwangtong-gyo. In an unofficial story, King Taejong moved the tomb outside the capital and used the stone items there to make the Cheonggyecheon Gwang-gyo so that the people would step upon the area in order to curse Lady Kang. In the final year of King Taejo, Lady Kang and King Taejong were in a politically conflictual relationship, but they were close to being political partners until King Taejo became the king. Sillok records pertaining to the establishment of Jeongreung or Gwangtong-gyo in fact state things more plainly, indicating that the moving of Jeongreung was a result of following the sangeon (a written statement to the king) of Uijeongbu (the highest administrative agency in Joseon), which stated that having the tomb of a king or queen in the capital was inappropriate, and since it was close to the official quarter of envoys, it had to be moved. The assertion that it was aimed at degrading Jeongreung in order to repair Gwangtong-gyo thus does not reflect the factual relationship. This article presents the possibility that the use of stone items from Jeongreung to repair Gwangtong-gyo reflected an emerging need for efficient material procurement that accompanied a drastic increase in demand for materials required in civil works both in- and outside the capital. The cause for constructing Jeongreung within the capital and the cause of moving the tomb outside the capital would therefore be attributable to the heterogeneity of the ideological backgrounds of King Taejo and King Taejong. King Taejo was the ruler of the Confucius state, as he reigned through the Yeokseong Revolution, but he constructed the tomb and Hongcheon-sa, the temple in the capital for his wife Queen Sindeok. In this respect, it is considered that, with the power of Buddhism, there was an attempt to rally supporters and gather the force needed to establish the authority of Queen Sindeok. Yi Seong-gye, who was raised in the Dorugachi clan of Yuan, lived as a military man in the border area, and so he would not have had a high level of understanding in Confucian scholarship. Rather, he was a man of the old system with its 'Buddhist" tendency. On the other hand, King Taejong Yi Bang-won was an elite Confucian student who passed the national examination at the end of the Goryeo era, and he is also known to have held a profound understanding of Neo-Confucianism. To state it differently, it would be reasonable to say that the understanding of symbolic implications for the capital would be more profound in a Confucian state. Since the national system that was ruled by laws had been established following the Three-Kingdom era, the principle of burial outside of the capital that would have seen a grave constructed on the outskirts of the capital was not upheld, without exception. Jeongreung was built inside the capital due to the strong individual desire of King Taejo, but since he was a Confucian scholar prior to becoming king, it would not have been accepted as desirable. After taking the throne, King Taejong took the initiative to begin overhauling the capital in order to reflect his intent to clearly realize Confucian ideology emphasizing 'Yechi' ("ruling with good manners") with the scenic view of the Capital's Hanyang river. It would be reasonable to conclude accordingly that the moving of Jeongreung was undertaken in the context of such a historic background.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.4
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• pp.24-36
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• 2014

The result of the research conducted for the purpose of investigating the semantic value and the layout of the Cheongryu Gugok of Dorimsa Valley, which exhibits a high level of completeness and scenic preservation value among the three gugoks distributed in the area around Mt. Dongak of Gogseong is as follows.4) The area around Cheongryu Gugok shows a case where the gugok culture, which has been enjoyed as a model of the Neo-Confucianism culture and bedrock scenery, such as waterfall, riverside, pond, and flatland, following the beautiful valley, has been actually substituted, and is an outstanding scenery site as stated in a local map of Gokseong-hyeon in 1872 as "Samnam Jeil Amban Gyeryu Cheongryu-dong(三南第一巖盤溪流 淸流洞: Cheongryu-dong, the best rock mooring in the Samnam area)." Cheongryu Gugok, which is differentiated through the seasonal scenery and epigrams established on both land route and waterway, was probably established by the lead of Sun-tae Jeong(丁舜泰, ?~1916) and Byeong-sun Cho(曺秉順, 1876~1921) before 1916 during the Japanese colonization period. However, based on the fact that a number of Janggugiso of ancient sages, such as political activists, Buddhist leaders, and Neo-Confucian scholars, have been established, it is presumed to have been utilized as a hermit site and scenery site visited by masters from long ago. Cheongryu Gugok, which is formed on the rock floor of the bed rock of Dorimsa Valley, is formed in a total length of 1.2km and average gok(曲) length of 149m on a mountain type stream, which appears to be shorter compared to other gugoks in Korea. The rock writings of the three gugoks in Mt. Dongak, such as Cheongryu Gugok, which was the only one verified in the Jeonnam area, total 165 in number, which is determined to be the assembly place for the highest number of rock writings in the nation. In particular, a result of analyzing the rock writings in Cheongryu Gugok totaling 112 places showed 49pieces(43.8%) with the meaning of 'moral training' in epigram, 21pieces (18.8%) of human life, 16pieces(14.2%) of seasonal scenery, and 12pieces(10.6%) of Janggugiso such as Jangguchur, and the ratio occupied by poem verses appeared to be six cases(3.6%). Sweyeonmun(鎖烟門), which was the first gok of land route, and Jesiinganbyeolyucheon(除是人間別有天) which was the ninth gok of the waterway, corresponds to the Hongdanyeonse(虹斷烟鎖) of the first gok and Jesiinganbyeolyucheon of the ninth gok established in Jaecheon, Chungbuk by Se-hwa Park(朴世和, 1834~1910), which is inferred to be the name of Gugok having the same origin. In addition, the Daeeunbyeong(大隱屛) of the sixth gok. of land route corresponds to the Chu Hsi's Wuyi-Gugok of the seventh gok, which is acknowledged as the basis for Gugok Wollim, and the rock writings and stonework of 'Amseojae(巖棲齋)' and 'Pogyeongjae(抱經齋)' between the seventh gok and eighth gok is a trace comparable with Wuyi Jeongsa(武夷精舍) placed below Wuyi Gugok Eunbyeon-bong, which is understood to be the activity base of Cheongryu-dong of the Giho Sarim(畿湖士林). The rock writings in the Mt. Dongak area, including famous sayings by masters such as Sunsaeuhje(鮮史御帝, Emperor Gojong), Bogahyowoo(保家孝友, Emperor Gojong), Manchunmungywol(萬川明月, King Joengjo), Biryeobudong(非禮不動, Chongzhen Emperor of the Ming Dynasty)', Samusa(思無邪, Euijong of the Ming Dynasty), Baksechungpwoong(百世淸風, Chu Hsi), and Chungryususuk-Dongakpungkyung(淸流水石 動樂風景, Heungseon Daewongun) can be said to be a repository of semantic symbolic cultural scenery, instead of only expressing Confucian aesthetics. In addition, Cheongryu Gugok is noticeable with its feature as a cluster of cultural scenery of the three religions of Confucian-Buddhism-Taoism, where the Confucianism value system, Buddhist concept, and Taoist concept co-exists for mind training and cultivation. Cheongryu Gugok has a semantic feature and spatial character as a basis for history and cultural struggle for the Anti-Japan spirit that has been conceived during the process of establishing and utilizing the spirit of the learning, loyalty for the Emperor and expulsion of barbarians, and inspiration of Anti-Japan force, by inheriting the sense of Dotong(道統) of Neo-Confucianism by the Confucian scholar class at the end of the Joseon era that is represented by Ik-hyun Choi(崔益鉉, 1833~1906), Woo Jeon(田愚, 1841~1922), Woo-man Gi(奇宇萬, 1846~1916), Byung-sun Song(宋秉璿, 1836~1905), and Hyeon Hwang(黃玹, 1855~1910).

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.