• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Atmosphere
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• v.24 no.3
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• pp.303-315
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• 2014

Terrestrial ecosystem plays the important role as carbon sink in the global carbon cycle. Understanding of interactions of terrestrial carbon cycle with climate is important for better prediction of future climate change. In this paper, terrestrial carbon cycle is investigated by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (HadGEM2-CC) that considers vegetation dynamics and an interactive carbon cycle with climate. The simulation for future projection is based on the three (8.5/4.5/2.6) representative concentration pathways (RCPs) from 2006 to 2100 and compared with historical land carbon uptake from 1979 to 2005. Projected changes in ecological features such as production, respiration, net ecosystem exchange and climate condition show similar pattern in three RCPs, while the response amplitude in each RCPs are different. For all RCP scenarios, temperature and precipitation increase with rising of the atmospheric $CO_2$. Such climate conditions are favorable for vegetation growth and extension, causing future increase of terrestrial carbon uptakes in all RCPs. At the end of 21st century, the global average of gross and net primary productions and respiration increase in all RCPs and terrestrial ecosystem remains as carbon sink. This enhancement of land $CO_2$ uptake is attributed by the vegetated area expansion, increasing LAI, and early onset of growing season. After mid-21st century, temperature rising leads to excessive increase of soil respiration than net primary production and thus the terrestrial carbon uptake begins to fall since that time. Regionally the NEE average value of East-Asia ($90^{\circ}E-140^{\circ}E$, $20^{\circ}N{\sim}60^{\circ}N$) area is bigger than that of the same latitude band. In the end-$21^{st}$ the NEE mean values in East-Asia area are $-2.09PgC\;yr^{-1}$, $-1.12PgC\;yr^{-1}$, $-0.47PgC\;yr^{-1}$ and zonal mean NEEs of the same latitude region are $-1.12PgC\;yr^{-1}$, $-0.55PgC\;yr^{-1}$, $-0.17PgC\;yr^{-1}$ for RCP 8.5, 4.5, 2.6.

• Economic and Environmental Geology
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• v.45 no.6
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• pp.643-659
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• 2012

The Chungju Fe-REE deposit is located in the Kyemyeongsan Formation of the Ogcheon Group. The Kyemyeongsan Formation includes meta-volcanic rocks and pegmatite hosted REE deposit which show different kind of REE-containing minerals. The meta-volcanic rocks hosted REE deposits' main REE minerals are allanite, zircon, apatite, and sphene, whereas the pegmatite hosted REE deposits is mainly composed of fergusonite, and karnasurtite, zircon, thorite. The meta-volcanic rock hosted major REE mineral is allanite as the form of aggregation and contains 23.89-29.19 wt% TREO (Total Rare Earth Oxide), 4.71-9.92 wt% $La_2O_3$, 11.30-14.33 wt% $Ce_2O_3$, 0.11-0.29 wt% $Y_2O_3$, 0.15-0.94 wt% $ThO_2$, as a formula of (Ca, Y, REE, Th)$_{2.095}$(Mg, Al, Ti, Mn, $Fe^{3+})_{2.770}(SiO_4)_{2.975}(OH)$. Accompanying REE in a coupled substitution for $Ca^{2+}$ (M1 site) and $Al^{3+}-Fe^{2+}$ (M2 site) leads to a large chemical variety. Due to the allanite's high contents of Fe, it belongs to Ferrialanite. The pegmatite hosted deposit's domi-nant REE mineral is fergusonite as prismatic or subhedral grains associated with zircon, fluorite and karnasurtite. Geochemical composition of the fergusonite($YNbO_4$) suggests substitution of Y-REE and Y-Th in A-site, and Nb-Ta-Ti in B-site, furthermore the proportion of $Y_2O_3$ and $Nb_2O_5$ is oddly 1:1.5 comparing to the ideal ratio 1:1 and Nb is higher than Y, also A-site Y actively substitutes with REE. Karnasurtite in pegmatite variously ranges 9.16-22.88 wt% $Ce_2O_3$, 2.15-9.16 wt% and $La_2O_3$, 0.44-10.8 wt% $ThO_2$, as a calculated formula (Y, REE, Th, K, Na, Ca)$_{1.478}(Ti, Nb)_{1.304}$(Mg, Al, Mn, $Fe^{3+})_{0.988}$(Si, P)$_{1.431}O_7(OH)_4{\cdot}3H_2O$. Firstly the 870-860 Ma is the initial age of the supercontinent Rhodinia dispersal and subsequent A-1 type volcanism, which contains Fe, REE, and HFS(High Field Strength elements; Nb, Zr, Y etc.) elements in Fe-rich meta-volcanic rocks dominant Kyemyeongsan Formation, might mineralized allanite. Another synthesis is that regional metamorphism at late Paleozoic 300-280 Ma(Cho et al., 2002) might cause allanite mineralization. Also pegmatite REE mineralization highly related to the granite intrusion over the Chungju area in Jurassic(190 Ma; Koh et al., 2012). Otherwise above all, A-1 type volcanism at the same time of the Kyemyeongsan Formation development, regional metamorphism and pegmatite, might have caused REE mineralization. Although REE ore bodies display a close spatial association, each ore bodies display temporal distinction, different mineral assemblage and environment of ore formation.

• Journal of the Korean Society of Food Culture
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• v.6 no.4
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• pp.421-432
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• 1991

This study was conducted to investigate the intake of a kind of Gom-Tang (Beef soup made with internal organs and bone), which is the Korean traditional food, and factors affecting the eating behavior of customers. Two hundred male customers of a H Korean Restaurant specialized in Gom-Tang, which is a well-known restaurant in Seoul, were surveyed from June 26 to 29, 1990. The results were shown as follows. (1) ${\ulcorner}$Frequency of intake${\lrcorner}$ and ${\ulcorner}$preference${\lrcorner}$ were very high. Those who took a kind of Gom-Tang ${\ulcorner}$more than once a week${\lrcorner}$ were 66.5% of the subjects. Those who evaluated ${\ulcorner}$good${\lrcorner}$ for the taste and flavor were 86.5% and 59.0% of the subjects, respectively. (2) The reasons why they chose a kind of Gom-Tang from among many Korean traditional foods were ${\ulcorner}$preference${\lrcorner}$ and ${\ulcorner}$phygiological condition${\lrcorner}$ in ${\ulcorner}$high frequency of intake${\lrcorner}$ group. ${\ulcorner}$Phygiological condition${\lrcorner}$ was more critical factor than ${\ulcorner}$preference${\lrcorner}$ in ${\ulcorner}$low frequency of intake${\lrcorner}$ group. (3) The effect of the intake of a kind of Gom-Tang on health was evaluated as ${\ulcorner}$healthy${\lrcorner}$ (80.5%). ${\ulcorner}$No effect${\lrcorner}$ and ${\ulcorner}$harmful${\lrcorner}$ were 30.5% and 6.5%, respectively. (4) ${\ulcorner}$High frequency of intake${\lrcorner}$ group, mainly more than 50 years of age, had a high ${\ulcorner}$preference${\lrcorner}$ and ${\ulcorner}$food knowledge${\lrcorner}$ as well as positive ${\ulcorner}$eating behavior${\lrcorner}$ and ${\ulcorner}$healthy state${\lrcorner}$, ${\ulcorner}$Middle frequency of intake${\lrcorner}$ group, mainly the forties, had a high ${\ulcorner}$preference${\lrcorner}$, but had less positive ${\ulcorner}$eating behavior${\lrcorner}$ than ${\ulcorner}$high frequency of intake${\lrcorner}$ group. ${\ulcorner}$Low frequency of intake${\lrcorner}$ group, mainly the twenties and thirties, had a medial ${\ulcorner}$preference${\lrcorner}$. They took a kind of Gom-Tang for reasons of ${\ulcorner}$on the recommendation of friends${\lrcorner}$ better than ${\ulcorner}$preference${\lrcorner}$. Foregoing results showed that ${\ulcorner}$a kind of Gom-Tang${\lrcorner}$ was a typical food recognized as ${\ulcorner}$healthy${\lrcorner}$ as well as ${\ulcorner}$delicious${\lrcorner}$. This may suggest that ${\ulcorner}$a kind of Gom-Tang${\lrcorner}$ is a candidate for the effective food on nutritional education.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.3
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• pp.41-66
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• 2017

The purpose of this research is to empirically trace the junctures of Yigye-gugok managed by Gwan-am Hong Gyeong-mo, a grandson of Yigye Hong Yang-ho who originally designed Yigye-gugok, while reviewing the features of the forms and patterns of gugok. The results of the research are as follows. 1. Ui-dong was part of the domain of the capital during the Chosun dynasty, which also is located in the city of Seoul as a matter of administrative zone. Likewisely, Yigye-gugok is taken as a special meaning for it was one and only gugok. Starting with Mangyeong Waterfall as the $1^{st}$ gok, Yigye follows through the $2^{nd}$ gok of Jeokchwibyeong Rock, the $3^{rd}$ gok of Chanunbong Peak, the $4^{th}$ gok of Jinuigang Rock, the $5^{th}$ gok of Okkyeongdae Rock, the $6^{th}$ gok of Wolyeongdam Pond, the $7^{th}$ gok of Tagyeongam Rock, the $8^{th}$ gok of Myeongoktan Stream, and the $9^{th}$ gok of Jaeganjeong Pavilion. Of these, Mangyeong Waterfall, Chanunbong Peak, and Okkyeongdae Rock are distinct for their locations in as much as their features, while estimated locations for Jinuigang Rock, Wolyeongdam Pond, Myeongoktan Stream, and Jaeganjeong Pavilion were discovered. However, Jeokchwibyeong Rock and Tagyeongam Rock demonstrated multiple locations in close resemblance to documentary literatures within secretive proximity, whereas geography, scenery, and sighted objects were considered to evaluate the 1st estimated location. Through these endeavored, it was possible to identify the shipping routes and structures for the total distance of 2.1km running from the $1^{st}$ gok to the $9^{th}$ gok, which nears Gwanam's description of 5ri(里), or approximately 1.96km for gugok. 2. Set towards the end of the $18^{th}$ century, Yigye-gugok originated from a series of work shaping the space of Hong Yang-ho's tomb into a space for the family. Comparing Yigye-gugok to other gugoks, numerous differences are apparent from beyond the rather more general format such as adjoining the $8^{th}$ gok while paving through the lower directions from the upper directions of the water. This gives rises to the interpretation such that Yigye-gugok was positioned to separate the doman of the family from those of the other families in power, thereby taking over Ui-dong. Yet, the aspect of the possession of the space lends itself to the determination that the location positioned at the $8^{th}$ gok above Mangyeongpok Waterfall representing Wooyi-dong was a consequence of the centrifugal space creation efforts. 3. While writings and poetic works were manufactured in such large quantities in Yigye-gugok whose products of setters and managers seemed intended towards gugok-do and letters carved on the rocks among others, there is yet a tremendous lack of visual media in the same respect. 'Yigye-gugok Daejacheop' Specimens of Handwriting offers the traces of Gwanam's attempts to engrave gakja at the food of Yigye-gugok. This research was able to ascertain that 'Yigye-gugok Daejacheop' Specimens of Handwriting was a product of Hong Yang-ho's collections maintained under the auspices of the National Central Museum, which are renowned for Song Shi-yeol's penmanship.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Korean Security Journal
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• no.9
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• pp.69-98
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• 2005

The security industry for civilians (Private Security), was first introduced to Korea via the US army's security system in the early 1960's. Shortly after then, official police laws were enforced in 1973, and private security finally started to develop with the passing of the 'service security industry' law in 1976. Korea's Private Security industry grew rapidly in the 1980's with the support of foreign funds and products, and now there are thought to be approximately 2000 private security enterprises currently running in Korea. However, nowadays the majority of these enterprises are experiencing difficulties such as lack of funds, insufficient management, and lack of control over employees, as a result, it seems difficult for some enterprises to avoid the low production output and bankruptcy. As a result of this these enterprises often settle these matters illegally, such as excessive dumping or avoiding problems by hiring inappropriate employees who don't have the right skills or qualifications for the jobs. The main problem with the establishment of this kind of security service is that it is so easy to make inroads into this private service market. All these hindering factors inhibit the market growth and impede qualitative development. Based on these main reasons, I researched this area, and will analyze and criticize the present condition of Korea's private security. I will present a possible development plan for the private security of Korea by referring to cases from the US and Japan. My method of researching was to investigate any related documentary records and articles and to interview people for necessary evidence. The theoretical study, involves investigation books and dissertations which are published from inside and outside of the country, and studying the complete collection of laws and regulations, internet data, various study reports, and the documentary records and the statistical data of many institutions such as the National Police Office, judicial training institute, and the enterprises of private security. Also, in addition, the contents of professionals who are in charge of practical affairs on the spot in order to overcomes the critical points of documentary records when investigating dissertation. I tried to get a firm grasp of the problems and difficulties which people in these work enterprises experience, this I thought would be most effective by interviewing the workers, for example: how they feel in the work places and what are the elements which inpede development? And I also interviewed policemen who are in charge of supervising the private escort enterprises, in an effort to figure out the problems and differences in opinion between domestic private security service and the police. From this investigation and research I will try to pin point the major problems of the private security and present a developmental plan. Firstly-Companies should unify the private police law and private security service law. Secondly-It is essential to introduce the 'specialty certificate' system for the quality improvement of private security service. Thirdly-must open up a new private security market by improving old system. Fourth-must build up the competitive power of the security service enterprises which is based on an efficient management. Fifth-needs special marketing strategy to hold customers Sixth-needs positive research based on theoretical studies. Seventh-needs the consistent and even training according to effective market demand. Eighth-Must maintain interrelationship with the police department. Ninth-must reinforce the system of Korean private security service association. Tenth-must establish private security laboratory. Based on these suggestions there should be improvement of private security service.

• Tuberculosis and Respiratory Diseases
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• v.55 no.2
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• pp.140-153
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• 2003

Background : The cell-mediated immune reaction to tuberculosis infection involves a complex network of cytokines. The extent of inflammation, tissue damage and severity of the disease suggested to be determined by the balance between extent and duration of the proinflammatory cytokine response versus those of the suppressive cytokines. The systemic cytokine response in pathogenesis of tuberculosis can be assessed by measuring serum cytokine levels. Method : Serum interleukin-1 beta(IL-$1{\beta}$), IL-2, IL-4, IL-6, IL-10, IL-12(p40), tumor necrosis factor-alpha(TNF-${\alpha}$), interferon-gamma(IFN-${\gamma}$) and transforming growth factor-beta(TGF-${\beta}$) levels were measured in 83 patients with pulmonary tuberculosis, 10 patients with endobronchial tuberculosis before treatment and 20 healthy subjects by using a sandwich ELISA. In patients with pulmonary tuberculosis, they were divided into mild, moderate and far advanced group according to the severity by ATS guidelines. To compare with those of pretreatment levels, we measured serum IL-$1{\beta}$, IL-2, IL-4, IL-6, IL-10, IL-12(p40), TNF-${\alpha}$, IFN-${\gamma}$ and TGF-${\beta}$ levels in 45 of 83 patients with pulmonary tuberculosis after 2 and 6 months of treatment. Results : 1) In sera of patients with active pulmonary tuberculosis(n=83), IL-$1{\beta}$, IL-6(p<0.05), TNF-${\alpha}$, and IFN-${\gamma}$ were elevated and TGF-${\beta}$ was decreased comparing to control. IL-2, Il-12(p40), IL-4 and IL-10 were similar between the patients with tuberculosis and control. 2) In endobronchial tuberculosis, IL-6 and TNF-${\alpha}$ were elevated and TGF-${\beta}$ was decreased comparing to control. IL-12(p40) seemed to be elevated comparing to pulmonary tuberculosis. 3) Far advanced tuberculosis showed markedly elevated IL-6 and IFN-${\gamma}$ level(p<0.05). 4) The significant correlations were noted between IL-1, IL-6 AND TNF-${\alpha}$ and between IL-12, Il-2 and IL-4(p<0.01). 5) After 2 and 6 months of standard treatment, the level of IL-6 and IFN-${\gamma}$ was significantly decreased(p<0.05). Conclusion : These results showed that an altered balance between cytokines is likely to be involved in the extent of inflammation, tissue damage and severity of the disease tuberculosis. But, it should be considered diversities of cytokine response according to type of tuberculosis and immunity in clinical application and interpreting future studies.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.