• The Journal of Dong Guk Oriental Medicine
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• v.8 no.2
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• pp.1-24
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• 2000

The comparison of climate's character of Yunqi(運氣) with the data of meterological observation were made in the research of climate. 1. The comparison of the average velocity of wind, temperature, rainfall, humidity of Seoul, by late 1954 to 1983, with Yunqi(運氣) was made. Fire-Chi(火氣) and moisture-qi(濕氣) were matched with the attribute of Taiyun(大運). Cold-qi(寒氣) was had some relationship. Dry-qi(燥 氣) and Wind-qi(風氣) were not matched. About the relationship of Spirit-of-official-sky(司天之氣) with climate, when the Moisture-soil(濕土) was added, they were matched and when the King-fire(君火) was added, they have some relationship. But Wind-tree(風木), Dry-metal(燥金), Buble-fire(相火), Cold-water(寒水) was added they were not matched. 2. According to the observation data of rainfall by late 180 years of Seoul; about Taiyun(大運), when the Water-Yun(水運) was greatly exceeded and Fire-Yun(火運) was shorted, in the case of Official-sky(司天), when Wind-Tree(風木) was added, the frequency was highly. So when the Soil-Yun(土運) was greatly exceeded and when Official-sky(司天)was added to the Moisture-soil(濕土), the rainfall was not matched. 3. The relationship of the frequency of the abnormal climate occurrences between Yunqi-promotion-weak(運氣盛衰)and Yunqi-Harmony(運氣同化) and Yunqi-soft-attacking(運氣順逆) in the weather of Korean Peninsula was compared by 1564 to 1863. They were not matched except the case of Yunqi-Harmony(運氣同化). 4. There were some cases which were not matched exactly between the climate predicted by the theory and real climate in 1984, the year of Kap-ga(甲子年). But many correspondence between the observation by the office of meteorology and the prediction by the analysis from Yun-qi-sang-hab(運氣相合) theory. 5. Because meterological phenomena of real world and analysis from the hypothesis of Yunqi(運氣) have no relationship with each other, some of Doctor denied Yunqi(運氣) in the way of matching mechanically. But the thought of Doctor who denied Fortune-spirit(運氣) made promotion for the theory of divination by bringing deeper insight. And it was not only the negative side. 6. In the point of geographical difference, the climate of China, the origination Yunqi theory, is different from the Korea's. Thus some observation errors should be considered. From the basis of this thesis, I hope that the deeper advance would be made into the Korean Yunqi theory.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Clinical and Experimental Pediatrics
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• v.48 no.9
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• pp.986-990
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• 2005

Purpose : Certain strains of lactobacilli are known to accelerate recovery from acute diarrhea. Lactobacillus reuteri is isolated from human breast milk and a commonly occurring Lactobacillus species with therapeutic potential in acute diarrhea. The purpose of the present study was to investigate the therapeutic effect of L. reuteri in acute diarrhea in young children. Methods : Fifty patients between 6 and 36 months of age hospitalized with acute diarrhea (rotavirus in 40 percent) were randomized into two groups to receive either $10^8$ colony-forming units of L. reuteri or a matching placebo, twice a day for their length of hospitalization, or for up to 5 days. Antidiarrheal drugs were not prescribed to either group. The clinical outcome of diarrhea was evaluated. Results : The mean duration of watery diarrhea after initiation of treatment was 2.3 days for the L. leuteri group(n=25) vs. 2.9 days for the placebo group(n=25)(P=0.072). By the second day of treatment, watery diarrhea persisted in 64 percent of patients receiving L. reuteri, compared to 84 percent of those receiving placebo(P=0.006). On the second day, the mean frequency of watery diarrhea was 1.9 in the L. leuteri group and 3.4 in the placebo(P=0.046). Also, vomiting continued to the second day in 16 percent of patients receiving L. reuteri and 40 percent of those recieving placebo(P=0.031). Conclusion : L. reuteri is effective as a therapeutic agent in acute diarrhea in children.

• Korean Journal of Poultry Science
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• v.51 no.2
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• pp.65-71
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• 2024

The feather-sexing method is widely used commercially for chick sex identification. However, for feather-sexing to be industrially practical, the early-feathering (EF) and late-feathering (LF) genes must existed within the foundation stock, a suitable feather-sexing lines must be established, and the accuracy of sex identification by feather-sexing must be ensured. Therefore, this study introduces the method of constructing the Korean native chickens (KNC) feather-sexing lines using EF and LF genes and evaluates the effectiveness of feather sex determination on commercial chicks produced from the constructed KNC lines. The results showed that both EF and LF chickens existed within the foundation stock, with the frequency of LF genes ranging from 0 to 0.205. In feather-sexing line establishment, the paternal strain of the grandparent stock (GPS) was fixed as EF (kk) for both sexes, while the maternal strain was composed of males with LF homozygotes (Z^KZ^K) and females with EF (Z^kW). Thus, in the parent stock (PS), male breeder had EF (Z^kZ^k) and female breeder had LF (Z^KW), resulting in chicks produced from their crosses having LF (Z^KZ^k) for males and EF (Z^kW) for females, allowing sex determination based on feather development. Additionally, to evaluate the effectiveness of feather-sexing for the produced commercial chicks, a study was conducted on 1,000 samples of the produced chicks to investigate the concordance between vent-sexing and feather-sexing, showing a matching rate of 93.1%.

• The Korea Journal of Herbology
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• v.27 no.2
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• pp.1-16
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• 2012

Objective : To investigate the current status of prescription drugs in Oriental medical institutes and to draw up a future plan for the revitalization of Oriental medical health insurance, this survey has been performed. Method : The survey has been made with 321 doctors working at Oriental medical institutes in Daegu and Kyungbuk areas for a period of 3 month from June 1, 2010 until September 1, 2010. Result : 1. When it comes to the current status of the use of herbal drugs in Oriental Health insurance, most of doctors surveyed prescribe insurance drugs, and they prescribe insurance drugs to patients, who are less than 20% of total patients visiting their clinics. 2. The awareness of Herbal Health Care Drugs is investigated. When it comes to the understanding of the difference between insurance drugs(powder type drugs) and granular type drugs, doctors admit that they differ only in one aspect, whether or not their being covered by health insurance. Based on the survey results on the understanding of insurance coverage of granular type drugs, doctors, even though they long for granular type drugs to be accepted as insurance drugs, are worrying whether the number of outpatients might dwindle due to increased insurance co-payments. They also point out that the biggest obstacles in the expansion of the granular type drugs as insurance drugs are the lack of understanding of the government and the objection of the Health Insurance Review and Assesment service (HIRA) for fear of increased insurance claims. 3. Upon investigation on Oriental medicine doctors' understandings of herbal pharmaceutical industry, it is found that doctors' responses on pharmaceutical industry are not all positive ones('new product development and neglect of R&D infrastructure' and 'smallness of industry'). When it is investigated what area needs the greatest improvement in herbal pharmaceutical industry, 'securing sufficient capital, good manufacturing, and strengthening quality control', is the highest. 4. When it is asked what are the most needed in order to improve herbal health insurance medicine, responses such as 'the increase in the accessibility to and the utilization of Oriental medical clinics through the diversification of the means of prescriptions', 'the improvement of insurance benefits(cap adjustments)', 'increase the proportion of high quality medicinal plants', 'the ceiling of co-payments(deductible) at 20,000 won or more', 'expansion of the choices of formulations', 'formulational expansions of tablets and pills', and finally 'admittance and expansion of granular type drug as insurance drug' are the highest. 5. Upon investigating the general characteristics of the current status of the usage of Oriental health care herbal drugs, the followings are observed. First, the frequency of use of health insurance drugs by the doctors who use health insurance with general characteristics shows similar differences in case of total monthly sales amount (p<0.001), average number of daily patients (p<0.05). Secondly, as to the willingness of the expanded usage of insurance drugs, similar differences are observed in case of total monthly sales amount (p<0.05). 6. Upon investigating the general characteristics of the perception of Herbal health care drugs, the followings are observed. First, inspecting general characteristics and insurance claims due to increased co-payments(deductible amount) reveals similar differences in case of working period (p<0.01) and in case of total monthly sales amount (p <0.01). Secondly, inspecting general characteristics and the obstacles that hinder granular type drugs from being accepted as health care insurance drugs shows similar differences in case of working period (p<0.05). 7. Upon investigating the general characteristics of the understanding of Oriental Herbal pharmaceutical companies, the followings are observed. First, opinions on the general characteristics of pharmaceutical companies, when examined with variance analysis, shows similar differences in case of total monthly sales amount (p<0.05). Secondly, when opinions are examined on general characteristics and the problems of herbal pharmaceutical companies, similar differences are found in case of working period (p<0.01) and in case of total monthly sales amount (p<0.001). Lastly, opinions on the general characteristics and reforms of pharmaceutical companies, similar differences are observed in case of working period (p<0.001). 8. Upon investigating the general characteristics of the improvement of insurance Herbal drugs, the followings are observed. First, regarding general characteristics and insurance benefits, similar differences are observed in case of working period (p<0.05), in case of total monthly sales amount (p<0.05), and in case of average number of daily patients (p<0.01). Secondly, opinions on the general characteristics and the needs for the improvement of Herbal insurance drugs are examined in 5 different aspects, which are the approval of granular type drugs as insurance drugs, the expanded practices of the number of prescription insurance drugs, the needs of a variety of formulations, the needs of TFT of which numbers of Oriental medical doctors are members for the revision of the existing system, and the needs of adjusting the current ceiling of the fixed amount and the fixed rate. When processed by the analysis of variance, the results show similar differences in case of average number of daily patients (p<0.01). Conclusion : From the results of this study the first measures to take are, to reform overall insurance benefit system, including insurance co-payment system(fixed rate cap adjustment), to expand the number of the herbal drugs to be prescribed matching with insurance benefit accordingly, and to revitalize herbal medicine insurance system through the change of various formulations. In addition, it is recommended to improve the effectiveness of herbal medicine by making plans to enhance the efficacy of herbal medicine and by enabling small pharmaceutical companies to outgrow themselves.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.