• Journal of Technologic Dentistry
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• v.32 no.4
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• pp.417-433
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• 2010

Purpose: This study evaluated the manpower planning of dental technicians. Methods: Methods : Survey was conducted regarding subject's general characteristics, characteristics of dental technician's occupational view and working conditions, and reason to enter into branches of the public health enter. The survey sample consisted of 323 dental technicians (221 male/ 102 female). Survey was conducted for one month from August 1 to September 1 in 2010. Following results were obtained. Results: 1. Regarding general characteristics of the subjects, there was a slight male predilection with 68.4%. Subjects in their 40s occupied the highest proportion of 32.2%. Majority of subjects worked in the big cities (71.5%). Favored working places were dental laboratory (57.6%) and dental hospital or dental clinic (19.5%). Although no position is available in the public sector such as public health center or health care civil servant, 9.3% preferred working in the public health center. Public sector is more favored than 2-year technical colleges or dental supply and equipment companies. In respect to education, 57% of the subjects graduated college. 67.8% were married. Subjects who specialize in the porcelain or all-ceramic were 57.9%. With regard to current position, head of the dental laboratory was most common. 2. Following occupation characteristics were found. Economic reason took the highest proportion when deciding their occupation (39.9%) followed by gaining social experience (36.5%). Majority of the subjects (76.5%) wanted to work as dental technicians until their retirement. 71.5% pursuit to become a manager of the dental laboratory. 76.1% agreed on opening a dental technician position in the public health center. Regarding an authority to lead developing the dental technician position in the public sector, majority of the subject chose ministry of health and welfare (35.6%) and Korean dental technologist association (34.7%). Employment (average, 30%) and turnover rate (average, 36.5%) of dental technology college graduates ranged from 40% to 60%. Most important factors for the employment were practical experience (41.2%) and competency (34.4%). With regard to job satisfaction, so-so as 46.7% and satisfactory was 42.7% 3. In respect to the reason for opening a position in the public health center, 'It is needed to continue denture rogram for elderly patients' obtained the highest score (4.14 point). 'Institutional devices are required to open a position for dental technicians as a public healthcare provider' received high score (4.11 point). 4. Concerning the working conditions, 'professional knowledge is required' received the highest score (4.23) followed by 'too short maternity and parental leave' (4.21). 5. Relationship between general characteristics of the subjects and favor of working in the public health center was investigated. Significant differences were found according to the current and favored working area, favored occupation, education level, marital status, and specialty. Working in the public health center was favored by following subjects: working in mid- or small-sized cities (4.16 point, p<0.05); PhD degree-holder (4.59 point, p<0.01). 6. Among general characteristics of the subjects, significant difference of working conditions was found in the following factors: gender; working areas; favored working areas; favored working positions, and education level. Majority of subjects favored working in big cities and currently work in big cities although satisfaction was comparatively low (3.75 score). 7. Future plan to work in public health center was evaluated according to occupational characteristics. Subject's intention to work in the public healthcare center was significantly affected by opening of dental technician position, leading authority, average turnover rate, and factors affecting employment. Working in the public health care center was favored by the following subjects: Dental technicians who actively supported opening of the dental technician position (4.34 point, p<0.001); subjects who thought the Korean dental technologist association is responsible for the opening of positions in the public sector (4.26 point, p<0.001); and subjects who thought that attitude and character are important for the employment (p<0.001). 8. Concerning difference of working conditions according to the occupational characteristics, significant difference was demonstrated by factors such as a reason to choose to be a dental technician, work plan, pursuing position, responsible authority, average employment rate, and job satisfaction. High standard of working conditions was required in subjects who selected to be a dental technician for the leisure time after work (s.05 point, p<0.01), who planted to work until their marriage (4.25 point, p<0.001), and who pursuit to be a manager (3.98, p<0.05). 9. In respect to influence of general characteristics on the advancement to public health centers, the coefficient of determination (R2) was 0.068 and age affected the working condition with significant difference according to the pvalue. 10. Regarding influence of general characteristics on the advancement to public health centers, the coefficient of determination (R2) was 0.335 and work plan, opening of dental technician position in the public sector, and responsible authority had significant influence over the subject's intention to work in the public health center according to the p-value. 11. With regard to the influence of general characteristics on the advancement to public health centers, the coefficient of determination (R2) was 0.091 and reason to choose to be a dental technician, work plan, and responsible authority significantly affected subject's working conditions. Conclusion: Korean society is becoming a super-aged society according to several statistics. As aged population is rapidly increasing, national health insurance plans to cover denture for senior citizen over 75 years old from 2012. Therefore, dental technicians are urgently needed in the public health centers all over the nation. Many subjects in this study planed to work until their retirement and recognized dental technician's expertise. Ministry of health and welfare and Korean dental technologist association should co-operate each other to prepare foundation and institutional devices for dental technicians to advance into the public health center. This will improve oral health of the population. This study showed urgency of medical facilities and services which meets increasing number of aged population and welfare of the population.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.1
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• pp.124-136
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• 2002

As an official journal of the Asian-Australasian Association of Animal Production Societies (AAAP), the Asian-Australasian Journal of Animal Sciences (AJAS) was born in February 1987 and the first issue (Volume 1, Number 1) was published in March 1988 under the Editorship of Professor In K. Han (Korea). By the end of 2001, a total of 84 issues in 14 volumes and 1,761 papers in 11,462 pages had been published. In addition to these 14 volumes, a special issue entitled "Recent Advances in Animal Nutrition" (April, 2000) and 3 supplements entitled "Proceedings of the 9th AAAP Animal Science Congress" (July, 2000) were also published. Publication frequency has steadily increased from 4 issues in 1988, to 6 issues in 1997 and to 12 issues in 2000. The total number of pages per volume and the number of original or review papers published also increased. Some significant milestones in the history of the AJAS include that (1) it became a Science Citation Index (SCI) journal in 1997, (2) the impact factor of the journal improved from 0.257 in 1999 to 0.446 in 2000, (3) it became a monthly journal (12 issues per volume) in 2000, (4) it adopted an English editing system in 1999, and (5) it has been covered in "Current Contents/Agriculture, Biology and Environmental Science since 2000. The AJAS is subscribed by 842 individuals or institutions. Annual subscription fees of US$ 50 (Category B) or US$ 70 (Category A) for individuals and US$ 70 (Category B) or US$ 120 (Category A) for institutions are much less than the actual production costs of US$ 130. A list of the 1,761 papers published in AJAS, listed according to subject area, may be found in the AJAS homepage (http://www.ajas.snu.ac.kr) and a very well prepared "Editorial Policy with Guide for Authors" is available in the Appendix of this paper. With regard to the submission status of manuscripts from AAAP member countries, India (235), Korea (235) and Japan (198) have submitted the most manuscripts. On the other hand, Mongolia, Nepal, and Papua New Guinea have never submitted any articles. The average time required from submission of a manuscript to printing in the AJAS has been reduced from 11 months in 1997-2000 to 7.8 months in 2001. The average rejection rate of manuscripts was 35.3%, a percentage slightly higher than most leading animal science journals. The total number of scientific papers published in the AJAS by AAAP member countries during a 14-year period (1988-2001) was 1,333 papers (75.7%) and that by non- AAAP member countries was 428 papers (24.3%). Japanese animal scientists have published the largest number of papers (397), followed by Korea (275), India (160), Bangladesh (111), Pakistan (85), Australia (71), Malaysia (59), China (53), Thailand (53), and Indonesia (34). It is regrettable that the Philippines (15), Vietnam (10), New Zealand (8), Nepal (2), Mongolia (0) and Papua New Guinea (0) have not actively participated in publishing papers in the AJAS. It is also interesting to note that the top 5 countries (Bangladesh, India, Japan, Korea and Pakistan) have published 1,028 papers in total indicating 77% of the total papers being published by AAAP animal scientists from Vol. 1 to 14 of the AJAS. The largest number of papers were published in the ruminant nutrition section (591 papers-44.3%), followed by the non-ruminant nutrition section (251 papers-18.8%), the animal reproduction section (153 papers-11.5%) and the animal breeding section (115 papers-8.6%). The largest portion of AJAS manuscripts was reviewed by Korean editors (44.3%), followed by Japanese editors (18.1%), Australian editors (6.0%) and Chinese editors (5.6%). Editors from the rest of the AAAP member countries have reviewed slightly less than 5% of the total AJAS manuscripts. It was regrettably noticed that editorial members representing Nepal (66.7%), Mongolia (50.0%), India (35.7%), Pakistan (25.0%), Papua New Guinea (25.0%), Malaysia (22.8%) and New Zealand (21.5%) have failed to return many of the manuscripts requested to be reviewed by the Editor-in-Chief. Financial records show that Korea has contributed the largest portion of production costs (68.5%), followed by Japan (17.3%), China (8.3%), and Australia (3.5%). It was found that 6 AAAP member countries have contributed less than 1% of the total production costs (Bangladesh, India, Indonesia, Malaysia, Papua New Guinea and Thailand), and another 6 AAAP member countries (Mongolia, Nepal and Pakistan, Philippine and Vietnam) have never provided any financial contribution in the form of subscriptions, page charges or reprints. It should be pointed out that most AAAP member countries have published more papers than their financial input with the exception of Korea and China. For example, Japan has published 29.8% of the total papers published in AJAS by AAAP member countries. However, Japan has contributed only 17.3% of total income. Similar trends could also be found in the case of Australia, Bangladesh, India, Indonesia, Malaysia and Thailand. A total of 12 Asian young animal scientists (under 40 years of age) have been awarded the AJAS-Purina Outstanding Research Award which was initiated in 1990 with a donation of US$ 2,000-3,000 by Mr. K. Y. Kim, President of Agribrands Purina Korea Inc. In order to improve the impact factor (citation frequency) and the financial structure of the AJAS, (1) submission of more manuscripts of good quality should be encouraged, (2) subscription rate of all AAAP member countries, especially Category B member countries should be dramatically increased, (3) a page charge policy and reprint ordering system should be applied to all AAAP member countries, and (4) all AAAP countries, especially Category A member countries should share more of the financial burden (advertisement revenue or support from public or private sector).

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.103-122
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• 2011

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.

• Magazine of the Korean Society of Agricultural Engineers
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• v.11 no.1
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• pp.1561-1579
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• 1969

In Korea, the duty of water in paddy fields was measured at the Agricultural Experimental Station in Suwon about 60 years ago. After that time some testing has been made in several places, but the key points in its experiment were the water depth of evapo-transpiration. Improved breeds, progress in cultivation and management techniques as well as development of measuring apparatus in recent years have necessitated the review of the duty of water in paddy fields. The necessity of reviewing the conventional methods has become even more important, as no source of information has been made available through survey of water utilization on a soil use basis which requires data on peculiar features of the water depth of evapo-transpiration. For example, the duty of water in paddy field is largely affected by the water depth of evapo-transpiration in connection with the wetted paddy field, whereas in connection with the normal paddy fields without this characteristic the vertical percolation become the predominant factor in measuring the decreasing depth of water. Therefore, it becomes important. that not only the water depth of evapotranspiration but also the vertical percolation process should also be observed in order to arrive at a realistic conclusion. As the vertical percolation has aclose relationship to the height of the underground water, the change of the latter can be measured. As the conclusion of this experiment, the following subjects are indicated. 1. In order to determine the economic duty of water in paddy fields on a basis of varying soil features, the varying soil features in the benifited area should be investigated thoroughly. The water depths of evapo-transpiration(ET) ratio to evaporation in the evaporator(V) on a basis of the varying soil features are as follows: clay loam ET/V = 1.11, loam ET/V = 1.64, sandy loam ET.V = 1.63 2. The decreasing depth of water consists of the water depth of evapotranspiration, the vertical per colation and the percolation of foot path. Among these three, the percolation of foot path can be utilized again. 3. As the result of this experiment, it shows the decreasing depth of water as follows. clay loam 9.3 mm/day, loam 13.5mm/daty, sandy loam 15.3mm/day 4. On a basis of the varying soil features and the height of the underground water, the vertical percolation varies. 5. The change of the vertical percolation on a basis of the varying soil features shows as follows: clay loam $1{\sim}2$ mm/day, loam $2{\sim}3$mm/day, sandy loam $3{\sim}4$mm/day 6. The level of the underground water changes sensibly by priority of clay loam, loam, sandy loam. When it rains, the level of the underground water rises fast and falls down slowly. 7. The level of the underground water changes within the scope of 25cm 8. The transpiration ratio is given in table 8 and their value are as follows: clay loam 168.8, loam 255.6, sandy loam 272.5

• Journal of Chest Surgery
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• v.41 no.1
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• pp.12-24
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• 2008

Background: It is currently thought that tissue valve degeneration is related to an animal's immune response, which is mainly due to cell surface ${\alpha}$-Gal epitopes. Cell surface ${\alpha}$-Gal epitopes are known to be degraded by the enzyme called green coffee bean ${\alpha}$-Galactosidase. It is also well known that ${\alpha}$-Gal epitopes are immunologically stained by Griffonia Simplicifolia isolectin type B4. We know that many commercially available tissue valves are made of aortic valves and pericardial tissue of pig. So, we investigated whether ${\alpha}$-Gal epitopes of the aortic valve and pericardial tissue of a pig can be removed by green coffee bean ${\alpha}$-Galactosidase, and we did so by comparing immunologic staining of the tissues before and after the enzyme treatment. Material and method: After treating fresh porcine aortic valve and pericardial tissue with green coffee bean ${\alpha}$-Galactosidase at concentrations of 0.5 unit/mL, 1.0 unit/mL, 2.0 unit/mL, respectively, under the condition of pH 6.5, temperature. $4^{\circ}C$ and 24 hours of incubation, each sample was stained with Griffonia Simplicifolia isolectin type B4 immunpfluorescent labeling. We then examined whether the ${\alpha}$-Gal epitopes were reduced or abolished in each consecutive. concentration of green coffee bean ${\alpha}$-Galactosidase by comparing the degree of the Griffonia Simplicifolia isolectin B4 staining in each sample. Result: In the pig aortic valve tissue, a 1.0 unit/mL concentration of green coffee bean ${\alpha}$-Galactosidase at pH 6.5, $4^{\circ}C$ and reaction for 24 hours was enough for complete removal of ${\alpha}$-Gal epitopes from the cell sur face on the immunostaining with Griffonia Simplicifolia isolectin B4. On the other hand, more ${\alpha}$-Gal epitopes were present in the pig pericardial tissue on Griffonia Simplicifolia isolectin B4 staining before the enzyme treatment, and 1.0 unit/mL of galactosidase was not sufficient for complete removal of ${\alpha}$-Gal from the tissue. 2.0 units/mL of green coffee bean ${\alpha}$-Galactosidase was needed to completely remove the ${\alpha}$-Gal epitopes from the pericardial tissue on immunostaining. Conclusion: The ${\alpha}$-Gal epitopes of the pig's aortic valve and pericardial tissue were successfully stained with Griffonia Simplicifolia isolectin B4. We could remove nearly all the ${\alpha}$-Gal epitopes using green coffee bean ${\alpha}$-Galactosidase at the concentration of 1.0 unit/mL in the aortic valve. Of pig, and 2.0 unit/mL was need to nearly completely remove all the ${\alpha}$-Gal epitopes in the pericardial tissue of pig under the condition of pH 6.5, $4^{\circ}C$ and 24 hours of reaction time. In the near future, removal of ${\alpha}$-Gal epitapes in the pig's aortic valve and pericardial tissue will become a powerful tool for the improvement of the tissue valve durability. It needs to be determined if ${\alpha}$-galactosidase treated pig tissue is immune to human anti-Gal antibody or anit-Gal mooclonal antibodies.

• Tuberculosis and Respiratory Diseases
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• v.47 no.6
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• pp.775-785
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• 1999

Background : Though surgery plays an important role in the management of patients with Mycobacterium tuberculosis infection, there is little information regarding the timing of resection. We tried to find out the ideal timing of operation. Method: A retrospective review was performed in 69 patients underwent pulmonary resection for pulmonary tuberculosis between January 1993 and December 1997. They were categorized into various groups according to the length of preoperative specific drug therapy. The rates of treatment failure, realpse and complication in each group were compared statistically by $x^2$-test. Results: Eighty one point two percent were men and 18.8 % women with a median age of 33 years(range, 16 to 63 years). The mean number of resistant drugs was 3.l(range, 0 to 9). Patients were treated preoperatively with multidrug regimens, which mean number of preoperative specific drugs was 4.6, in an effort to reduce the mycobacterial burden with the mean length of preoperative drug therapy, 5.0 months. Postoperative treatment was conducted for a mean period of 13.0 months with a mean number of postoperative specific drugs, 4.4. Postoperative treatment failures were confirmed in 8 among 69 patients(11.6%). 2 of these 8 patients were showed up in the preoperative 3 to 4 months medication group and each of the rest was occurred in the preoperative 2 to 3, 5 to 6, 6 to 7, 12 to 13, 17 to 18 months, less than one month medication group, respectively. 59 of 69 patients were available for evaluation of the relapse rate with the mean duration of the postoperative follow-up, 19.8 months. In 4 patients bacterial relapse was confirmed(6.8%). Each of these 4 was in the preoperative 1 to 2, 2 to 3, 3 to 4, 5 to 6 months medication group. Categorized into various groups according to the length of preoperative specific therapy, there were no statistical significances of the treatment failure rate, relapse rate and complication rate in the groups. There were seven treatment failures of 28 who were AFB culture positive until the time of operation(25%, p<0.01). Categorized the preoperative AFB culture positive group into various groups according to the length of preoperative drug therapy, there were no statistical significances, either. Conclusion: We believe that operation plays an important ancillary role in the treatment of pulmonary tuberculosis. Our results indicate that the timing of resection according to the length of preoperative drug therapy may not cause trouble.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of Ginseng Research
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• v.26 no.3
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• pp.111-131
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• 2002

Korean ginseng (Panax ginseng C.A. Meyer) received a great deal of attention from the Orient and West as a tonic agent, health food and/or alternative herbal therapeutic agent. However, controversy with respect to scientific evidence on pharmacological effects especially, evaluation of clinical efficacy and the methodological approach still remains to be solved. Author reviewed those articles published since 1980 when pharmacodynamic studies on ginseng have intensively started. Special concern was paid on metabolic disorders including diabetes mellitus, circulatory disorders, malignant tumor, sexual dysfunction, and physical and mental performance to give clear information to those who are interested in pharmacological study of ginseng and to promote its clinical use. With respect to chronic diseases such as diabetes mellitus, atherosclerosis, high blood pressure, malignant disorders, and sexual disorders, it seems that ginseng plays preventive and restorative role rather than therapeutics. Particularly, ginseng plays a significant role in ameliorating subjective symptoms and preventing quality of life from deteriorating by long term exposure of chemical therapeutic agents. Also it seems that the potency of ginseng is mild, therefore it could be more effective when used concomitantly with conventional therapy. Clinical studies on the tonic effect of ginseng on work performance demonstrated that physical and mental dysfunction induced by various stresses are improved by increasing adaptability of physical condition. However, the results obtained from clinical studies cannot be mentioned in the indication, which are variable upon the scientist who performed those studies. In this respect, standardized ginseng product and providing planning of the systematic clinical research in double-blind randomized controlled trials are needed to assess the real efficacy for proposing ginseng indication. Pharmacological mode of action of ginseng has not yet been fully elucidated. Pharmacodynamic and pharmacokinetic researches reveal that the role of ginseng not seem to be confined to a given single organ. It has been known that ginseng plays a beneficial role in such general organs as central nervous, endocrine, metabolic, immune systems, which means ginseng improves general physical and mental conditons. Such multivalent effect of ginseng can be attributed to the main active component of ginseng,ginsenosides or non-saponin compounds which are also recently suggested to be another active ingredients. As is generally the similar case with other herbal medicines, effects of ginseng cannot be attributed as a given single compound or group of components. Diversified ingredients play synergistic or antagonistic role each other and act in harmonized manner. A few cases of adverse effect in clinical uses are reported, however, it is not observed when standardized ginseng products are used and recommended dose was administered. Unfavorable interaction with other drugs has also been suggested, which the information on the products and administered dosage are not available. However, efficacy, safety, interaction or contraindication with other medicines has to be more intensively investigated in order to promote clinical application of ginseng. For example, daily recommended doses per day are not agreement as 1-2g in the West and 3-6 g in the Orient. Duration of administration also seems variable according to the purpose. Two to three months are generally recommended to feel the benefit but time- and dose-dependent effects of ginseng still need to be solved from now on. Furthermore, the effect of ginsenosides transformed by the intestinal microflora, and differential effect associated with ginsenosides content and its composition also should be clinically evaluated in the future. In conclusion, the more wide-spread use of ginseng as a herbal medicine or nutraceutical supplement warrants the more rigorous investigations to assess its effacy and safety. In addition, a careful quality control of ginseng preparations should be done to ensure an acceptable standardization of commercial products.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.