• The Korean Society of Law and Medicine
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• v.16 no.2
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• pp.263-291
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• 2015

In May, 2015, a 68 years old man, who has been Middle East Saudi Arabia and the United Arab Emirates, had high fever, muscle aches, cough and shortness of breath. he went two local hospital near his house and the S Medical Center emergency center. He was diagnosed MERS(Middle East respiratory syndrome) and the diseases had put South Korea the fear of epidemics for three months. Especially, this disease has firstly reported in Middle East Asia in September 2012 and spreaded to twenty-six countries. In 21, July, 2015, European Center for disease prevention and control reported 533 people were died and in South Korea, 186 people were infected, 36 people were died and 16,693 people were isolated from MERS. South Korea government were faced into epidemic control and blamed from public. Especially, hospital acquired infection, disease control chain, opening of information, ventilation, lack of isolation bed, the problem of function of local health center, the issue of reparation for hospital and insurance cover rate, the classification of disease, the role of Korea Centers for disease control and prevention, the culture of visiting hospital to see sick people, the issue of hospital multiple room and other related social support policy. it is time to study and discuss to solve these problems. South Korea citizens felt fear and fright from MERS. What is wore, they thought the dieses were out of their government control. It was unusual case for word except Middle East Asia. numerous tourists canceled visiting korea. South korea economic were severly damaged especially, tourism industry. South korea government should admit that they had failed initial action against MERS and take full reasonability from any damages. The government have to open information to public in terms of epidemic diseases and try to prevent any other epidemic diseases and try to work with local governments.

• Journal of Hospice and Palliative Care
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• v.4 no.1
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• pp.4-13
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• 2001

Purpose : Since the acquired immune deficiency syndrome (AIDS) was first recognized in the United States in the summer of 1981, the number of these patients has been increasing in the world. But do not find out a cure and a vaccine for ARS (5). And so, the best treatment for AIDS is the prevention. People can find out accurate knowledge about AIDS, and they can prevent themselves from AIDS approximately 100%. In this study, we investigate with AIDS knowledge and attitudes in unmarried young men (<24 age) and suggest accurate preventive education for AIDS and good sexual behaviors. Methods : Un-married young soldiers and college students who were not diagnosed as AIDS until June 30, 2000 were included in the study. The study included a total of 923 men. A self evaluation questionnaire, included questions on 36 items(the part of demographic data - 9; the part of knowledge - 20; the part of attitudes - 8), was drawn up by three physicians. The demographic data, AIDS knowledge and attitudes were analyzed by chi-square analysis, and the total score of AIDS knowledge - comparison according to demographic factors and attitudewere analyzed by one-way ANOVA test. Results : In demographic characteristics, as for the first recognized time of AIDS, most of men knew it when they were in their middle school, as for sources of information on AIDS, most of them knew it through the TV-media, and as for the educational need about AIDS, most of them agreed with it. In AIDS knowledge, mean scores were $14.0{\pm}1.8$ (70.3%). Items of the misconceptions concerning AIDS, reported as less than 50% correct answers, were 6 among 20 items (30%). In AIDS attitudes, as for the item about that if I will be an AIDS patient, I will have an AIDS treatment, it showed that the number of men agreed with 759 (82.2%), and as for the item about that I will help for AIDS patient even though I don't know him, it showed that the number of them agreed with 412 (45.8%). In correlation of AIDS knowledge and demographic factors, the mean scores of knowledge of men with higher than college degree were higher than them of others. The mean scores of knowledge of men with total income of family with more than US$1667 were higher than them of others. The mean scores of knowledge of men with sources of information on AIDS through the TV-media were higher than them of others. And the mean scores of knowledge of men with past medical history of STD(sexually transmitted disease) were higher than them of others. Conclusions : The higher the knowledge he has, the lower the possibility of risk and the more positive the attitude he has. And then we think that the education program for AIDS will be included as a regular part of the curriculum in high school, and young men must be effectively educated by it.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.4
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• pp.279-284
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• 2022

Certain pre-transfusion tests are not commonly performed during emergency blood transfusion. In this study, we reviewed and analyzed the data of post-blood transfusion antibody screening tests to establish the effects of unexpected antibodies causing hemolytic transfusion reactions. We reviewed information published domestically and internationally, and selected the data of 68,602 antibody screening tests and 528 antibody identification tests conducted at P hospital. We found that unexpected antibody positive (1198,1.74%), Rh type (161, 30.49%), Lewis type (67, 12.69%), others (Di (a), 28, 5.30%). The anti-E type positive was 93 (17.61%), and that of the cases with anti-C (13, 2.46%). Only data of domestic cases were included for analysis that were published before 2007, which established the presence of antibodies of the following types and numbers of cases: anti-E (196, 22.45%), anti-Le a (82, 9.39%), and anti-E+C (60, 6.87%). In 2018, anti-E (107, 17.12%), anti-E+Canti-E+C (56, 8.96%), and anti-Di a (28, 4.48%) were detected. In other domestic cases, S hospital was detect to anti-E, anti-Le a, anti-E+C. The Anti-E, anti-D, anti-E+C, and anti-C+E were detected in D hospital. In Saudi Arabia, Anti-D, anti-E, and anti-Jka was detected. The Anti-M, Anti-N, Anti-Le (a), and Anti-D were detected in India. Requests for emergency blood transfusion increased 1.8 times after the opening of the trauma center. This study has the disadvantage of being a cross-sectional study. additional studies are needed to provide basic information on alternative treatments that can increase the safety and reduce the side effects of hemolytic transfusion in emergency transfusion situations.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.25-54
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• 2023

At a time when open data receives attention as an international trend, there is a need to discuss the role of international journals in Korea to support data sharing. Based on surveys and interviews of editors from the international journals, we identified factors affecting the policy adoption and examined the journal editors' perception on the adoption and components of the data sharing policy. As a result, scholarly journals that have adopted or are planning to adopt policies have recognized that data sharing is an international trend and can contribute to research development, but they stressed that efforts to improve the perception of data sharing were still necessary. Educational activities and compensation for sharing data were needed at scholarly journals' and communities' level. Also, components perceived important and selected by more than half of the editors as mandatory were 'data availability statement', 'data sharing level', 'data sharing method', and 'data citation'. While scholarly journals do not always need to mandate data sharing, it was necessary to mention conditions where data cannot be shared through data availability statements. The role of the organization developing and operating a repository appropriate for situations in Korea was also emphasized. In addition, by identifying factors affecting the policy adoption, significant differences were found in Journal Impact Factor quartiles, publication type, and subject area. This finding indicated that journals with a high impact factor are likely to have resources to support data sharing, and open access or hybrid journals are likely to have interest in open data as a part of open science. In the medical research area, active movements for data sharing in academic communities have promoted the adoption of data sharing policies. This study would be used as basic data to facilitate the adopton and operation of scholarly journals' data sharing policies in Korea.

• 한국노년학
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• v.27 no.2
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• pp.459-472
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• 2007

This research has its purpose of developing a tool to assess the needs of the Korean elderly at home population and to provide adequate services by evaluating their physical, psychological, and socio-environmental aspects. This developed tool is composed of two hundred questions and has the advantage of combined physical, psychological and social environmental situation assessment of the elderly at home. The tool also contains not only the objective view of the professionals, but also the subjective appeals of the elderly at home population so that it can reflect their substantial desires. The assessment tool was developed over 21 months from July, 2004 to March, 2006 and this period can be divided into three different stages. In the first stage, collecting of questions for the desire-focused assessment of the elderly by literature investigation and researching foreign source materials was carried out, and this ultimately developed assessment tool was applied to the long-term care insurance pilot project in the second stage. In this process, we revised some insufficiencies of this tool after we applied to elderly of 250 from the pilot project and other 200 elderly from this research team. For the last stage, the tool was completed by using inquiries of the focused group and the group of professionals to ensure its reliability and validity. In the process of developing the tool, the total of 200 questions under 13 subcategories was selected. The 13 subcategories are basic information, subjective appeals, information of the main helper, use of services, house environment, condition of health, condition of rehabilitation, daily living(ADL, IADL, defecation, assistance), social maintenance, behavioral disability, medical health, living habits, and strength. This tool is on the purpose to assess thoroughly the desires that the elderly at home population has and to provide the best service they need.

• Korea Trade Review
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• v.48 no.3
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• pp.131-150
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• 2023

The purpose of this study was to find a countermeasure to the U.S. import refusals for the Korean healthcare and life sciences industry. To this end, an analysis of trends during the pandemic was conducted using the KITA Border Rejection Database, which includes information on items and types of import refusals. The reason for rejection was also analyzed according to the FDA violation codes. The degree of countermeasure for import refusals was identified by measuring the unit rejection rate (URR). The results of the analysis showed that the major U.S. import refusals for the Korean healthcare and life sciences industry had expanded from contact lenses to COVID-19 diagnostic kits and drugs after the pandemic broke out. The major reasons for import refusals were non-compliance with the Predicate Device and Drugs Act and non-approval by the FDA for products and facilities. On the other hand, the unit rejection rate (URR) of major items in the Korean healthcare and life sciences industry was measured higher than the industry average. The results therefore showed a low level of response to U.S. import refusals. The results of the analysis of reasons for import refusals by item according to FDA violation codes were as follows. First of all, the main violation for contact lenses and COVID-19 diagnostic kits corresponded to misbranding. This was often due to the fact that Korean companies did not provide the relevant notices and information required by the FDA. Many cases also failed to demonstrate a substantial equivalency compared to predicate devices already on the market. On the other hand, applications for new unapproved drugs were not accepted as they had yet to pass relevant regulations that would prove their safety and efficacy. In conclusion, import refusals for the Korean healthcare and life sciences industry were found to be closely related to technical barriers to trade (TBT).

• Journal of the Korean Society of Radiology
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• v.82 no.6
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• pp.1505-1523
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• 2021

Purpose Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review chest CT protocols and radiation doses in COVID-19 publications and explore the number needed to diagnose (NND) and the number needed to predict (NNP) if CT is used as a first-line test. Materials and Methods We searched nine highly cited radiology journals to identify studies discussing the CT-based diagnosis of COVID-19 pneumonia. Study-level information on the CT protocol and radiation dose was collected, and the doses were compared with each national diagnostic reference level (DRL). The NND and NNP, which depends on the test positive rate (TPR), were calculated, given a CT sensitivity of 94% (95% confidence interval [CI]: 91%-96%) and specificity of 37% (95% CI: 26%-50%), and applied to the early outbreak in Wuhan, New York, and Italy. Results From 86 studies, the CT protocol and radiation dose were reported in 81 (94.2%) and 17 studies (19.8%), respectively. Low-dose chest CT was used more than twice as often as standard-dose chest CT (39.5% vs.18.6%), while the remaining studies (44.2%) did not provide relevant information. The radiation doses were lower than the national DRLs in 15 of the 17 studies (88.2%) that reported doses. The NND was 3.2 scans (95% CI: 2.2-6.0). The NNPs at TPRs of 50%, 25%, 10%, and 5% were 2.2, 3.6, 8.0, 15.5 scans, respectively. In Wuhan, 35418 (TPR, 58%; 95% CI: 27710-56755) to 44840 (TPR, 38%; 95% CI: 35161-68164) individuals were estimated to have undergone CT examinations to diagnose 17365 patients. During the early surge in New York and Italy, daily NNDs changed up to 5.4 and 10.9 times, respectively, within 10 weeks. Conclusion Low-dose CT protocols were described in less than half of COVID-19 publications, and radiation doses were frequently lacking. The number of populations involved in a first-line diagnostic CT test could vary dynamically according to daily TPR; therefore, caution is required in future planning.