• Journal of Society of Preventive Korean Medicine
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• v.25 no.3
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• pp.117-124
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• 2021

Objectives : The purpose of this study is to analyze the factors affecting the enactment of local municipalities' ordinance for supporting Korean Medicine infertility treatment in the metropolitan area. Methods : For Seoul, Incheon, and Gyeonggi Province, data on the enactment of Korean Medicine infertility treatment and socio-demographic data of the local municipalities were collected through the Enhanced Local laws and regulations Information System and on-line statistical database. Logistic regression analysis was performed to analyze the factors affecting the enactment of the ordinance, The enactment of the ordinance was dependent variable, and the budgeting of local municipalities, the number of population, the number of births, the number of Korean Medicine doctors, and the total fertility rate were used as independent variables. Results : Up to 2000, the ordinances for supporting Korean Medicine infertility treatment were enacted in 16 local municipalities and the budget for that was supported by 18 local municipalities. Regarding the effect on the enactment of the ordinances, it was found that budgeting of Korean Medicine infertility treatment had a positive (+) effect, and the metropolitan government's budgeting and the total fertility rate had a negative (-) effect. Conclusions : This study suggests that the ordinance for Korean Medicine infertility treatment is a policy tool derived based on the problem of low fertility faced by each local municipality rather than the political influence of health provider's groups.

• Health Policy and Management
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• v.32 no.2
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• pp.164-172
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• 2022

Background: The purpose of this study was to the impact of the coronavirus disease 2019 (COVID-19) outbreak on emergency departments (EDs) in patients under the age of 18 years with respiratory disease. Also, we analyzed similarities and differences in patients including revisit before and after the COVID-19 outbreak. Methods: This study population was respiratory patients under the age of 18 years who visited all 403 EDs in Korea between January 1st, 2019 and December 31st, 2020, using the National Emergency Department Information System Database. The primary outcome was the number of respiratory patients according to age, sex, the type of EDs, season, Korean Triage and Acuity Scale (KTAS) levels, the result of ED, and length of stay. The secondary outcome was the number of revisit respiratory patients within 72 hours. We calculated the risk-adjusted revisit rates according to the KTAS level using a multiple logistic regression model. Results: The number of ED visits decreased from 274,526 in 2019 to 79,007 in 2020; this number was 71.2% lower than that before COVID-19. In spring 2020, this number was 90.1% lower than during the same period in 2019. For the revisit rate in the study population, the adjusted odds ratio (95% confidence interval) was 1.22 (1.05-1.41) in 2019 and 1.39 (1.07-1.81) in 2020. Conclusion: Implementing appropriate emergency care policies in severe respiratory patients would have contributed to improving the safety of reducing in revisit rate.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.74-85
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• 2024

Objective: Idiopathic intracranial hypertension (IIH) is a condition of unknown etiology associated with venous sinus stenosis. This study aimed to develop a magnetic resonance venography (MRV)-based radiomics model for predicting a high trans-stenotic pressure gradient (TPG) in IIH patients diagnosed with venous sinus stenosis. Materials and Methods: This retrospective study included 105 IIH patients (median age [interquartile range], 35 years [27-42 years]; female:male, 82:23) who underwent MRV and catheter venography complemented by venous manometry. Contrast enhanced-MRV was conducted under 1.5 Tesla system, and the images were reconstructed using a standard algorithm. Shape features were derived from MRV images via the PyRadiomics package and selected by utilizing the least absolute shrinkage and selection operator (LASSO) method. A radiomics score for predicting high TPG (≥ 8 mmHg) in IIH patients was formulated using multivariable logistic regression; its discrimination performance was assessed using the area under the receiver operating characteristic curve (AUROC). A nomogram was constructed by incorporating the radiomics scores and clinical features. Results: Data from 105 patients were randomly divided into two distinct datasets for model training (n = 73; 50 and 23 with and without high TPG, respectively) and testing (n = 32; 22 and 10 with and without high TPG, respectively). Three informative shape features were identified in the training datasets: least axis length, sphericity, and maximum three-dimensional diameter. The radiomics score for predicting high TPG in IIH patients demonstrated an AUROC of 0.906 (95% confidence interval, 0.836-0.976) in the training dataset and 0.877 (95% confidence interval, 0.755-0.999) in the test dataset. The nomogram showed good calibration. Conclusion: Our study presents the feasibility of a novel model for predicting high TPG in IIH patients using radiomics analysis of noninvasive MRV-based shape features. This information may aid clinicians in identifying patients who may benefit from stenting.

• Journal of Preventive Medicine and Public Health
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• v.57 no.1
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• pp.65-72
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• 2024

Objectives: Protecting people against financial hardship caused by illness stands as a fundamental obligation within healthcare systems and constitutes a pivotal component in achieving universal health coverage. The objective of this study was to analyze the prevalence and determinants of catastrophic health expenditures (CHE) in Iran, over the period of 2013 to 2019. Methods: Data were obtained from 7 annual national surveys conducted between 2013 and 2019 on the income and expenditures of Iranian households. The prevalence of CHE was determined using a threshold of 40% of household capacity to pay for healthcare. A binary logistic regression model was used to identify the determinants influencing CHE. Results: The prevalence of CHE increased from 3.60% in 2013 to 3.95% in 2019. In all the years analyzed, the extent of CHE occurrence among rural populations exceeded that of urban populations. Living in an urban area, having a higher wealth index, possessing health insurance coverage, and having employed family members, an employed household head, and a literate household head are all associated with a reduced likelihood of CHE (p<0.05). Conversely, the use of dental, outpatient, and inpatient care, and the presence of elderly members in the household, are associated with an increased probability of facing CHE (p<0.05). Conclusions: Throughout the study period, CHE consistently exceeded the 1% threshold designated in the national development plan. Continuous monitoring of CHE and its determinants at both household and health system levels is essential for the implementation of effective strategies aimed at enhancing financial protection.

• Journal of Distribution Science
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• v.11 no.6
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• pp.31-40
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• 2013

Purpose - The Northeast Asian Logistic Hub strategy was established to create a national competitive advantage in northeast Asia. Countries in this region are competing fiercely to become the central base distribution port as the volume of container shipping continues to increase due to the northeast Asian (especially Chinese) economic growth. The primary method by which shippers are improving their customer service and distribution is enhancing profits by minimizing call ports on the key route through strategic affiliations and the use of large vessels. Each nation is planning large-scale investments in the construction of sea ports that can accommodate large vessels. This paper proposes ways by which the logistical strategies of domestic corporations can keep pace with changes in government policy concerning the Northeast Asian Business Hub policy. It examines the logistics system in the Northeast Asian region, analyzes the government's Northeast Asian Business Hub policy, and suggests logistical strategies for domestic corporations through an analysis based on a questionnaire designed to grasp domestic firms' needs and goals. Research design, data and methodology - The purpose of this study is to determine how shipping companies establish partnerships with third-party logistics providers and draws out the implications of the results. The survey methods used were personal interviews and questionnaires distributed to a sample population through e-mail, fax, mail, and telephone. A total of 600 questionnaires were distributed, of which 165 were returned. Among these, ten were excluded due to insufficient content; ultimately, 155 were used for the sample. The statistical data collection process was analyzed through data coating and a statistical package program. Results - This study argues that greater flexibility in policies, administration, and systems will be needed to significantly improve established business practices. In this dissertation, we primarily identify that in order to become a center of northeast Asian logistics, Korea must adopt a new paradigm and abandon the existing systems that are based on the economic and social systems that have stemmed from bureaucracy, inflexibility, chauvinism, and equalitarianism. Flexible policies, administration, and systems will be necessary to improve business practices. Domestic corporations must establish a strategic logistics hub and related network while simultaneously pursuing value-added logistics businesses by increasing their manpower and building a logistics information system. This will strengthen their competitive edge and lead to system improvements. Conclusions - Domestic corporations must adopt a new paradigm and use more reasonable business laws, systems, and policies that are based on market-driven flexibility and transparency. Moreover, social norms and regulations should be established to help ensure political and social security. Korea must also develop a culture of tolerance for foreign companies. Finally, the paradigm defining the policy governing the development of the capital city and its satellite cities in this context must be changed.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.675-681
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• 2021

With the recent growth of the AI speaker market, the demand for speech synthesis technology that enables natural conversation with users is increasing. Therefore, there is a need for a multi-speaker speech synthesis system that can generate voices of various tones. In order to synthesize natural speech, it is required to train with a large-capacity. high-quality speech DB. However, it is very difficult in terms of recording time and cost to collect a high-quality, large-capacity speech database uttered by many speakers. Therefore, it is necessary to train the speech synthesis system using the speech DB of a very large number of speakers with a small amount of training data for each speaker, and a technique for naturally expressing the tone and rhyme of multiple speakers is required. In this paper, we propose a technology for constructing a speaker encoder by applying the deep learning-based x-vector technique used in speaker recognition technology, and synthesizing a new speaker's tone with a small amount of data through the speaker encoder. In the multi-speaker speech synthesis system, the module for synthesizing mel-spectrogram from input text is composed of Tacotron2, and the vocoder generating synthesized speech consists of WaveNet with mixture of logistic distributions applied. The x-vector extracted from the trained speaker embedding neural networks is added to Tacotron2 as an input to express the desired speaker's tone.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.201-220
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• 2019

Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.72-87
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• 2022

For the sustainable development and conservation of the national land, planned development and efficient environmental conservation must be accompanied. To this end, it is possible to induce development and conservation to harmonize by deriving factors affecting development through analysis of previously developed areas and applying appropriate management measures to areas with high development pressure. In this study, the relationship between the area where the land cover changed from forest to urbanization and various social, geographical, and restrictive factors was implemented in a regression formula through logistic regression analysis, and potential development sites were analyzed for Yongin City. The factor that has the greatest impact on the analysis of potential development area is the restrict factors such as Green Belt and protected areas, and the factor with the least impact is the population density. About 148km²(52%) of Yongin-si's forests were analyzed as potential development area. Among the potential development sites, the area with excellent environmental value as a protected area and 1st grade on the Environment Conservation Value Assessment Map was derived as about 13km². Protected areas with high development potential were riparian buffer zone and special measurement area, and areas with excellent natural scenery and river were preferred as development areas. Protected areas allow certain actions to protect individual property rights. However, there is no clear permit criteria, and the environmental impact of permits is not understood. This is identified as a factor that prevents protected areas from functioning properly. Therefore, it needs to be managed through clear exception permit criteria and environmental impact monitoring.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1460-1466
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• 2008

The purpose of this study is to verify how the accounting information of a bankrupt firm which is defined as a dishonor, an impaired total capital, a poor financial performance of a business, a rejection of auditor's opinion and an incongruity of auditor's opinion differs from that of a healthy firm on the basis of the index of financial affairs if the accounting information released by KOSDAQ is valuable. The sampling firms consists of 45 KOSDAQ firms that went bankrupt from 2000 to 2007 and 45 healthy firms which are selected in accordance with the sizes of assets. It has also selected the 30 sampling firms for the confirmation of the model in the same way. According to the result of the in-depth analysis, the variables related to security among the 17 indexes of financial affairs that have been used in this study for 5 years show a noticeable difference between a bankrupt firm and a healthy one. The accuracy of failed firms using this model for confirmation demonstrates 76.7% in 5 years before the bankruptcy, 76.7% in 4 years before that, 65.0% in 3 years before it, 76.7% in 2 years, 88.3% in 1 year. This data shows that the process from a healthy firm to a bankrupt one has progressed gradually and confirms the value of the index of financial affairs, exhibiting the accuracy with 83.8% of a presuming sample and 76.7% of a confirming sample for 5 years.

• Management & Information Systems Review
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• v.28 no.3
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• pp.1-23
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• 2009

Prior bankruptcy studies have established that bankrupt firm's pre-filing financial ratios are different from those of healthy firms or of randomly selected going concerns. However, they may not be sufficiently different from the financial ratios of other firms in financial distress to allow the development of a ratio-based model that predicts bankruptcy with reasonable accuracy. As the result, in the multiple discriminant model, independent variables divided firms into bankrupt firms and healthy firms are retained earnings to total asset, receivable turnover, net income to sales, financial expenses, inventory turnover, owner's equity to total asset, cash flow to current liability, and current asset to current liability. Moreover four variables Retained earnings to total asset, net income to sales, total asset turnover, owner's equity to total asset indicate that these valuables classify bankrupt firms and distress firms. On the other hand, Owner's Equity to borrowed capital, Ordinary income to Net Sales, Operating Income to Total Asset, Total Asset Turnover and Inventory Turnover are selected to predict bankruptcy possibility in the Logistic regression model.