• Proceedings of The Korean Society of Health Promotion Conference
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• 2004.10a
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• pp.59-88
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• 2004

' Healthy Japan 21 ' is a new health policy that has been proposed for the 21st century: it embodies a totally new concept for its viewpoints and methods. To start with, for its goal, the focus is placed on the ' quality of life ' or a life that is tree of diseases, rather than mere prolongation of life. For its doctrine, the emphasis has shifted dramatically from improving the health of the entire population (the traditional approach for health improvement) to ' achieving an ideal health status for each individual. The ultimate aged society that arrives first in Japan is a society in its ultimate form for human being. Why did Japan become westernized, giving up her traditional culture? Why did she go through industrialization, sacrificing her nature? And why does she try so hard to industrialize the developing countries? These efforts are all preparation for the arrival of a ultimate aged society. During the 20th century, we believed in unlimited possibilities and expanded our social frontier. 1n the 21st century, on the other hand, a super-aged society (the ultimate society), a glimpse of which we have witnessed from time to time, will descend on us sooner or later. It is expected to arrive first in Japan. ' Healthy Japan 21 ' is intended to prepare for the arrival of the hitherto unheard of super-aged society by building the physiological basis of people. This policy is social experimentation on an immense social scale, in which questions are posed on the understanding of health, the relationship between individuals and society, the relationship between administration and citizens, the manner by which central and local governments operate, and the new relationship between prevention and therapy. ' Healthy Japan 21 ' may be summarized as an experiment on a huge scale directed to the ultimate form of human society, in which Japan and each of her citizens playa role and set an example for the rest of the world. Even just by considering various approaches newly suggested for this venture, one may be convinced that it is a policy with features suitable for a country that has already achieved the world's highest longevity.

• Korean Journal of Agricultural Science
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• v.19 no.1
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• pp.1-8
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• 1992

This experiment was conducted to improve the germination when we sowed Chinese milk vetch (Astragalus sinicus L. Local vas. Jinjoo) in the up-land.. The results are summerized as follows 1. There is no difference on the germination of Chinese milk vetch from $15^{\circ}C$ to $35^{\circ}C$. Germination ratio is 7l%, speed is 60% and mean of germinating day. is about 4. But at $10^{\circ}C$ germination ratio and speed are decreased as 65%, 8% but mean of germinating day is increased as 8. 2. Chemicals used for improve of germination $KNO_3$, $H_2SO_4$, HCl, NaOCl, NaOH and GA were increased about 6~8% of germination ratio. 3. Germination in response to soil covering up depth, surface sowing showed 68% of germination and not more than 4cm the seed is germinated 60% but not less than 6cm, germination ratio is not more than 50%. 4. Soil water content needed in the germination is proper about 70~80% of field water capacity and the ratio is 65% but not. more than 40% germination ratio is not more than 31%. 5. Germination in response to seed treatment (1 day sbsorption /1 day dry) germination ratio is not decreased when it treated 2 times but not less than 3 times it decreased seriously and not less that: 5 times it decreased not more than 31%. 6. Germination in response to seed largement, small seed is not good for germination, so seeds harvested after the majority of the seed is ripened.

• Journal of the Korean Geophysical Society
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• v.3 no.4
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• pp.269-280
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• 2000

Rail vibration in city zone is becoming a serious environmental problem. In order to make a reduction plan for rail vibration, the research was conducted in which many experiments to measure actual rail vibration along the railroad through the central Deajeon area. A digital vibration level meter was used to measure rail vibration. Vibration levels of Z-axis were measured at every second for the duration of the train passing. The measuring station was placed at every 5m for the distance of 55m. A total of 353 different sets of vibration level were obtained. The signals were processed to get $L_{10}$ value and analyzed in terms of distance, train velocity, and number of trains. As a result, it has been found that rail vibration exceed the allowable vibraton limit of 60 dB, at the point of 25 m far from the railroad center, which is regulated by the las of vibration and noise. Train velocity was found to affect a little for vibration level within the zone. It was also found that a trench installed along a railroad could reduce vibration level up to approximately 10 percent. A model test was conducted to investigate the influence of the location and size of trench, on the transfer of vibration. A heavy steel ball was used to generate vibrations. On the basis obtained from this study, it could be concluded that the application of distance-attenuation and the installment of a trench along railroad could be applied as a reduction plan for rail vibration. Because limitions might exist to depend on the effect of distance attenuation, trenchs excavated along a railroad might be suggested as the most efficient solution to reduce railroad vibration.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.2
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• pp.69-79
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• 2020

In this study, the anti-inflammatory and cytotoxic effects of hot-water extracts from 10 kinds of macroalgae in Korea were investigated. It was selected materials in consideration of biological activity and industrial potential as follows: Caulerpa okamurae; Codium fragile; Ulva australis; Ishige foliacea; Saccharina japonica; Sargassum horneri; Undaria pinnatifida; Gloiopeltis tenax; Gracilaria verrucosa; Porphyra tenera. Results showed that S. japonica and G. tenax significantly decreased NO productionn in LPS-stimulated Raw 264.7 cells at concentrations of 100, 1000 ㎍/mL and 1000 ㎍/mL, respectively. However, most of the other macroalgae used in the experiment did not affect NO production. It was observed that all macroalgae extracts except for the highest concentration (1000 ㎍/mL) treatment group of P. tenera did not affect the viability in Raw 264.7 cells. In addition, there was not significant decrease in cell viability by macroalgae extracts treatment in HINAE cells. These results suggest that S. japonica and G. tenax could be used as potential safe natural anti-inflammatory agents for food and feed additives. Also, the results of this study are expected to be used as basic data for the development of functional materials for 10 kinds of macroalgae resources in Korea.

• The Korea Journal of Herbology
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• v.24 no.1
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• pp.59-71
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• 2009

Objectives：The present study has been undertaken to investigate the effects of Mantidis $O\ddot{O}theca$ and Mori Fructus on treatment of osteoporosis in ovariectomized rats. Methods： In this experiment, the rats were ovariectomized. Rats were administered by Mantidis $O\ddot{O}theca$ and Mori Fructus. The levels of bone mineral density, osteocalcin.ALP.calcium.phosphorus in serum, calcium. phosphorus.deoxypyridinoline in urine and calcium.phosphorus.ash weight in bone were measured. Results： 1. The levels of femoral and fibula-tibial bone mineral density were significantly increased in comparison with OVX group at 4, 8 weeks in Mantidis $O\ddot{O}theca$ group. And the levels of femoral and fibula-tibial bone mineral density were significantly increased in comparison with OVX group at 8 weeks in Mori Fructus group. 2. The levels of serum osteoclacin and ALP showed significant decrease in comparison with OVX group at 4, 8 weeks in Mantidis $O\ddot{O}theca$ and Mori Fructus group. The levels of serum calcium showed significant decrease in comparison with OVX group at 4 weeks in Mantidis $O\ddot{O}theca$ and Mori Fructus group. The levels of serum phosphorus showed significant decrease in comparison with OVX group at 4, 8 weeks in Mantidis $O\ddot{O}theca$ and Mori Fructus group. 3. The levels of urine calcium, phosphorus and deoxypyridinoline showed significant decrease in comparison with OVX group in Mantidis $O\ddot{O}theca$ and Mori Fructus group. 4. The levels of fibula-tibial calcium and phosphorus showed significant increase in comparison with OVX group in Mantidis $O\ddot{O}theca$ group and Mori Fructus group. The levels of femoral calcium and phosphorus showed significant increase in comparison with OVX group in Mori Fructus group. The levels of femoral and fibula-tibial ash weight showed significant increase in comparison with OVX group in Mantidis $O\ddot{O}theca$ group and Mori Fructus group. Conclusions： Reviewing these experimetal results, it appeared that Mantidis $O\ddot{O}theca$ and Mori Fructus had efficacy on treatment of osteoporosis.

• Journal of Music and Human Behavior
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• v.4 no.2
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• pp.66-83
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• 2007

The purpose of this study is to learn both effects of the vocal psychotherapy on the self-consciousness and the variety of the self-consciousness on the vocal psychotherapy in return. The research for this study was performed to three subjects who were students of E university, Seoul, ten times for sixty minutes. The subjects were all volunteers for the advertisement on a music-therapy program searching for them on the web site of E university. The vocal psychotherapy program consists of four steps and each of them consists of two to four short terms again. Both before and after the experiment, examinations on self-consciousness were done to recognize the change of the subjects' self-consciousness which would be caused by the vocal psychotherapy activity. After every short term, the subjects were asked to write reports to closely analyze the change of self-consciousness according to the terms and the variety of the subjects. The effect of the vocal psychotherapy activity on the changes of scores in the self-consciousness examination is the first thing to point out on this study. There appeared some personal varieties on the total scores of the examination and scores of some sub-categories. Especially, there were different scores on the private self-consciousness, the public self-consciousness, and the social anxiety between before and after performing the vocal psychotherapy program. Subject A, who had got the best score of all on the scope of the private self-consciousness, showed the steepest decrease on the very scope. On the contrary, the subject showed decrease of scores of the public self-consciousness and the social anxiety in the relatively little rate. Subject B, who had got the highest score of the three on the public self-consciousness, showed the steepest decrease on that of all scopes and showed no difference on the social anxiety scope. In the case of the last one, subject C, who had relatively low scores on the private and public self-consciousness than the others, the private self-consciousness score increased but the public self-consciousness and the social anxiety scores decreased. The changes of the scores of each questions were examined in order to see possible other changes that had not been exposed on the changes of the total and sub-categories scores. As a result of that, of all twenty-eight questions, there were changes about one to two points. Subject A showed the difference with thirteen questions, subject B with sixteen and subject C with nineteen questions. The rate of change of subject C was relatively small but more questions changed and the change of score was wider than the others. Considering all those results, It can be possibly said that the vocal psychotherapy affects the changes of the scores of sub-categories in self-consciousness examination. The next thing to point out on this study is the change of recognition that was exposed on the subjects' report after every short term of the program. As a result of the close analyzing, according to the short terms and variety of self-consciousness, recognizing the way express subjects themselves by voice and recognizing their own voices appeared to be different. How much they cared about others and why they did so were also different. According to the self reports, subject A cared much about her inner thought and emotion and tended to concentrate herself as a social object. There appeared some positive emotional experiments such as emotional abundance and art curiosities on her reports but at the same time some negative emotions such as state-trait anxiety and neuroticism also appeared. Subject B, who showed high scores on the private and public self-consciousness like subject A, had a similar tendency that concentrates on herself as a social object but she showed more social anxiety than subject A. Subject C got relatively lower points in self-consciousness examination, tended to care about herself, and had less negative emotions such as state-trait anxiety than other subjects. Also, with terms going on, she showed changes in the way of caring about her own voice and others. This study has some unique significances in helping people who have problems caused by self-estimation activated with self-consciousness, using voices closely related to one's own self, performing the vocal skills discipline to solve the technical problems. Also, this study has a potentiality that the vocal psychotherapy activity can be effectively used as a way affects the mental health and developing personality.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.