The O2O services in the healthcare sector have only been in full swing for about three years, and unlike existing O2O consumer goods, the scale and scope of the dispute are more complicated due to restrictions on medical treatment. In this study, O2O service platform operators and medical institutions' roles and responsibilities were redefined as a countermeasure for resolving disputes in healthcare O2O services and the laws for changing the transaction environment. A change in institutional mechanisms was proposed. This study looked at the types of consumer disputes related to healthcare O2O services as insufficient information problems, problems in the course of medical service implementation, problems with immunity provisions for platform operators, cancellations, and non-compliance with refunds. All the information generated during transactions in the healthcare sector was extensive in scale and included the most sensitive information among personal information, stressing the importance of ensuring security. The area that started in the O2O range before the medical institution visit also proposed a plan to establish a system for the delivery of proven information as a pre-medical person. The scale and growth will grow faster, given that consumers can experience the information they want anytime, anywhere they want. However, the platform broker's role, a link player, will become more important because consumers who use the service will have their first meeting with non-face-to-face product providers. On the other hand, service providers may have side effects of misleading consumers by providing false information or misleading consumers through exaggerated advertisements. The O2O service market is expected to expand beyond distribution and dining out to the entire industry. However, since it is challenging to check accurate statistics on the detailed market, various disputes and consumer protection measures will be required for each detailed market, and comprehensive leading solutions will be essential in the future.
The negative impact of climate change on the agricultural sector is rapidly increasing, and it is urgent to prepare policies at the government level to mitigate it. In the case of Rwanda's agricultural sector, which lacks the government's budget and farmers' capital, efficient and effective policy implementation is of paramount importance. To this end, rather than establishing related policies in the public sector from the top down, it is necessary to establish a bottom-up customized policy that is reflected in policy establishment by identifying the characteristics and behaviors of farmers who actually participate in adaptation activities. In this study, the effects of farmers' characteristics and farmers' perception status/adaptation status to climate change on the selection of adaptation methods for climate change were analyzed. 357 rice farmers randomly selected from Eastern Rwanda were surveyed to explore the information related to farmers' perception to climate change and adaptation methods as well as basic information of the farm. Research shows that the probability of selecting a variety of adaptation methods rather than not responding to climate change increases the younger the age, the higher the education level, and the easier access to climate information and credit. As a policy proposals, it is judged that public support such as strengthening agricultural technology support services, including more detailed guidance for elderly and low-educated farmers, and improving access to farm loan services by agricultural financial institutions is needed. In addition, it is necessary to adjust the planting time and cultivation method, provide timely information related to climate change, and provide crop variety improvement services to farmers.
Journal of The Korean Society of Integrative Medicine
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v.11
no.1
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pp.141-148
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2023
Purpose : This study examined the relationship between suicidal thoughts, hand grip strength, socioeconomic status, educational level, and disease occurrence. Methods : Korean national health and nutrition examination survey 2017 were used in this study. 5,449 were analysed. For comparison between groups, cross-tabulation analysis and mean comparison were performed. Logistic regression analysis were performed to analyze the influencing factors between grip strength and suicidal ideation. Results : Our results are consistent with the literature on the importance of socioeconomic status in health. The lower the level of education, the higher the suicidal thoughts. Being single or divorced was also significantly associated with suicidal ideation. Moreover, a lower income level was significantly associated with a higher suicide intention. Furthermore, older ages, lower educational levels, and lower income were significantly associated with a higher odds ratio of suicidal thoughts. Interestingly, suicidal thoughts were significantly lower among non-smokers. In contrast, suicide intention did not differ significantly according to gender, age, monthly drinking habit, aerobic physical activity, and disease occurrence. Suicidal thoughts decreased as grip strength increased and this was statistically significant. Socioeconomic status, disease occurrence, and handgrip strength level affected the security of an individual's livelihood and were significant risk factors for suicidal thoughts. These associations remained significant in multiple logistic regression even after controlling for all covariates. Conclusion : Future prevention intervention efforts to reduce suicide risks should consider handgrip strength. Studies to explore the possible proximal risk factors and mediators between handgrip strength and suicidal thoughts are also warranted.
Crop productivity can be obstructed by various biotic and abiotic stresses and thus these stresses are a threat to universal food security. The information on the use of viruses providing efficacy to plants facing growth challenges owing to stress is lacking. The role of induction of pathogen-related genes by microbes is also colossal in drought-endurance acquisition. Studies put forward the importance of viruses as sustainable means for defending plants against dual stress. A fundamental part of research focuses on a positive interplay between viruses and plants. Notably, the tomato yellow leaf curl virus (TYLCV) and tomato chlorosis virus (ToCV) possess the capacity to safeguard tomato host plants against severe drought conditions. This study aims to explore the combined effects of TYLCV, ToCV, and drought stress on two tomato cultivars, Money Maker (MK, UK) and Shalala (SH, Azerbaijan). The expression of pathogen-related four cellulose synthase gene families (CesA/Csl) which have been implicated in drought and virus resistance based on gene expression analysis, was assessed using the quantitative real-time polymerase chain reaction method. The molecular tests revealed significant upregulation of Ces-A2, Csl-D3,2, and Csl-D3,1 genes in TYLCV and ToCV-infected tomato plants. CesA/Csl genes, responsible for biosynthesis within the MK and SH tomato cultivars, play a role in defending against TYLCV and ToCV. Additionally, physiological parameters such as "relative water content," "specific leaf weight," "leaf area," and "dry biomass" were measured in dual-stressed tomatoes. Using these features, it might be possible to cultivate TYLCV-resistant plants during seasons characterized by water scarcity.
As the method of collecting and utilizing structured and unstructured data develops due to the influence of the Fourth Industrial Revolution, unwanted personal information data is also being collected and utilized, and hackers are attempting various attacks to steal information. As a result, the importance of information protection has increased, and various protection techniques have emerged, among which many studies have been conducted using decentralized techniques of blockchain and various algorithms to strengthen the security of biometric authentication techniques. This paper proposed a public blockchain biometric authentication system that allows users to protect their data in a safer biometric authentication method in the public blockchain and use it in the blockchain through signature with authenticated information.
The purpose of this study is to find out how work participation of the elderly and their general characteristics - socio-demographic, economic, and health traits - influence on their self-esteem. The data was collected through one on one interviews of 295 elderly. Data on general attributes and the discrepancies in the level of self-esteem between work participants and non-participants were analyzed by using t-test and ANOVA, while the effects of work participation on their self-esteem were analyzed by multiple regression analysis. Results of this study shows us that work participation is the strongest predictor that determine the level of self-esteem for the elderly. In other words, work participation can make the aged better off and give them a sense of security and satisfaction. Finally, these findings may be used for realizing us the importance of the work participation program and developing and designing new promising approaches of work participation program, which meet psychological needs of the elderly as well as their economic needs.
Background: Some working conditions may pose a higher physical or psychological demand to pregnant women leading to increased risks of pregnancy complications. Objectives: We assessed the association of woman's employment status and the industrial classification with obstetric complications. Methods: We conducted a national population study using the National Health Information Service database of Republic of Korea. Our analysis encompassed 1,316,310 women who experienced first-order live births in 2010-2019. We collected data on the employment status and the industrial classification of women, as well as their diagnoses of preeclampsia (PE) and gestational diabetes mellitus (GDM) classified as A1 (well controlled by diet) or A2 (requiring medication). We calculated odds ratios (aORs) of complications per employment, and each industrial classification was adjusted for individual risk factors. Results: Most (64.7%) were in employment during pregnancy. Manufacturing (16.4%) and the health and social (16.2%) work represented the most prevalent industries. The health and social work exhibited a higher risk of PE (aOR = 1.11, 95% confidence interval [CI]: 1.03-1.21), while the manufacturing industry demonstrated a higher risk of class A2 GDM (1.20, 95% CI: 1.03-1.41) than financial intermediation. When analyzing both classes of GDM, women who worked in public administration and defense/social security showed higher risk of class A1 GDM (1.04, 95% CI: 1.01, 1.07). When comparing high-risk industries with nonemployment, the health and social work showed a comparable risk of PE (1.02, 95% CI: 0.97, 1.07). Conclusion: Employment was associated with overall lower risks of obstetric complications. Health and social service work can counteract the healthy worker effect in relation to PE. This highlights the importance of further elucidating specific occupational risk factors within the high-risk industries.
The COVID-19 outbreak in 2020 caused continuous damage worldwode, especially the smart tourism industry was hit directly by the blockade of sky roads and restriction of going out. At a time when overseas travel and domestic travel have decreased significantly, the number of tourist hotels that are colsed and closed due to the continued deficit is increasing. Therefore, in this study, licensing data from the Ministry of Public Administraion and Security were collected and visualized to understand the operation status of the tourism and lodging industry. The machine learning classification algorithm was applied to implement the business status prediction model of the tourist hotel, the performance of the prediction model was optimized using the ensemble algorithm, and the performance of the model was evaluated through 5-Fold cross-validation. It was predicted that the survival rate of tourist hotels would decrease somewhat, but the actual survival rate was analyzed to be no different from before COVID-19. Through the prediction of the business status of the hotel industry in this paper, it can be used as a basis for grasping the operability and development trends of the entire tourism and lodging industry.
Korea's LNG and crude oil are the most important energy and export raw materials, but 100% import resources by overseas. However, tanker shipping companies, which play the most crucial role in energy cargo security, are very small in number and size, which can be a factor in the supply chain crisis. Therefore, this paper studied the policy of expanding tanker transportation necessary for the transport of crude oil and LNG in Korea. In the existing literature, there was no policy study necessary for tanker ships, but referring only to the importance of overseas energy development and transportation, so we tried to derive various demands necessary for expanding the tanker fleet through expert interviews and AHP which was conducted on 89 related energy institutions to derive policies and their priorities. The results of the study are as follows. As for the policy, the financial support policy was the highest priority, followed by the business and the mutual cooperation policy of related agencies. Tax support (22.6%) and ship financing (19.4%) were the highest priorities, followed by the Energy Intermediate Promotion Act (11.9%), Tanker Guarantee Insurance (10.6%), Energy Budget Independence (9.3%), and Korea Trader Development (8.2%). Energy governance (6.3%), information center establishment (6.2%), and energy procurement committee (5.5%) ranked seventh, eighth, and ninth. The research results show that it is necessary to supply sufficient ships to the market through the expansion of ship finance for tankers and to follow business support policies such as guarantee insurance. In addition, it was also possible to derive that the financial resources need to be determined by law and independent budgets for consistency and continuity.
Journal of the Microelectronics and Packaging Society
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v.30
no.4
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pp.69-78
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2023
With the rapid growth of artificial intelligence, the demand for semiconductors is enormously increasing everywhere. To ensure the manufacturing quality and quantity simultaneously, the importance of automatic defect detection during the packaging process has been re-visited by adapting various deep learning-based methodologies into automatic packaging defect inspection. Deep learning (DL) models require a large amount of data for training, but due to the nature of the semiconductor industry where security is important, sharing and labeling of relevant data is challenging, making it difficult for model training. In this study, we propose a new framework for securing sufficient data for DL models with fewer computing resources through a divide-and-conquer approach. The proposed method divides high-resolution images into pre-defined sub-regions and assigns conditional labels to each region, then trains individual sub-regions and boundaries with boundary loss inducing the globally coherent and seamless images. Afterwards, full-size image is reconstructed by combining divided sub-regions. The experimental results show that the images obtained through this research have high efficiency, consistency, quality, and generality.
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