With the tourism industry stagnating due to the recent COVID-19 virus issue, the importance of preparing a plan to resume and revitalize the tourism industry after the end of the COVID-19 is being emphasized. In particular, this researcher paid attention to the development of the horse industry as it can contribute to the differentiation of services as it is an experience-oriented tourism, and it can be said to be a field with a high potential for sustainable development in the future. However, in the domestic horse industry, legal problems related to installation, industrial structural problems organized around horse racing, and demand-based problems were scattered. Therefore, this researcher suggested a way to improve these problems, improve the quality of life of the people, and lead the horse industry to increase the income of rural residents. As a representative example, a legal improvement plan for the expansion and growth of equestrian facilities was presented, and a strategic incubating infrastructure construction plan was presented to support horse industry workers to nurture the horse industry as the 6th industry on their own. This movement will lead to qualitative growth through the conversion of the horse industry into local cultural contents, and not only to expand the base of public demand for the horse industry, but also to maximize the creation of added value through diversification of the horse industry, leading to qualitative growth of the horse industry.
The purpose of this study is to present an appropriate management plan as a supplement to the scientific evidence of the currently operated distancing system for preventing COVID-19. The currently being used mathematical models are expressed as simultaneous ordinary differential equations, there is a problem in that it is difficult to use them for the management of entry and exit of small business owners. In order to supplement this point, in this paper, a method for quantitatively expressing the risk of infection by people who gather is presented in consideration of the allowable risk given to the gathering space, the basic infection reproduction index, and the risk reduction rate due to vaccination. A simple quantitative model was developed that manages the probability of infection in a probabilistic level according to a set of visitors by considering both the degree of infection risk according to the vaccination status (non-vaccinated, primary inoculation, and complete vaccination) and the epidemic status of the virus. In a given example using the model, the risk was reduced to 55% when 20% of non-vaccinated people were converted to full vaccination. It was suggested that management in terms of quarantine can obtain a greater effect than medical treatment. Based on this, a generalized model that can be applied to various situations in consideration of the type of vaccination and the degree of occurrence of confirmed cases was also presented. This model can be used to manage the total risk of people gathered at a certain space in a real time, by calculating individual risk according to the type of vaccine, the degree of inoculation, and the lapse of time after inoculation.
After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.
KIPS Transactions on Computer and Communication Systems
/
v.11
no.10
/
pp.363-372
/
2022
Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.5
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pp.317-324
/
2021
This study deals with keywords from social media on domestic portal sites related to COVID-19, which is spreading widely. The data were collected between January 20 and August 15, 2020, and were divided into three stages. The precursor period is before COVID-19 started spreading widely between January 20 and February 17, the serious period denotes the spread in Daegu between February 18 and April 20, and the stable period is the decrease in numbers of confirmed infections up to August 15. The top 50 words were extracted and clustered based on TF-IDF. As a result of the analysis, the precursor period keywords corresponded to congestion of the Situation. The frequent keywords in the serious period were Nation and Infection Route, along with instability surrounding the Treatment of COVID-19. The most common keywords in all periods were infection, mask, person, occurrence, confirmation, and information. People's emotions are becoming more positive as time goes by. Cafes and blogs share text containing writers' thoughts and subjectivity via the internet, so they are the main information-sharing spaces in the non-face-to-face era caused by COVID-19. However, since selectivity and randomness in information delivery exists, a critical view of the information produced on social media is necessary.
The recent spread of novel and highly variant pathogenic viruses, including the coronavirus (SARS-CoV-2), has increased the demand for diagnostic testing for rapid confirmation. This has resulted in investigating the functional capability of each space, and preparing facility guidelines to secure the safety of medical technologists. During viral evaluations, there is a requirement of negative pressure facilities along with thread separation, during pre-treatment of samples and before nucleic acid amplification. Space composition therefore needs to be planned by considering unidirectional air flow. This classification of safety management facilities is designated as biosafety level 2, and personal protective equipment is placed accordingly. In case of handling dangerous materials, they need to be carried out of the biosafety cabinet, and sterilizers are required for suitable disposal of infectious agents. A common feature of domestic laboratories is maintenance of the sample pre-treatment space at a negative pressure of -2.5 Pa or less, and arranging separate pre-treatment and reagent preparation spaces during the test process. We believe that the data generated in this study is meaningful, and offers an efficient direction and detailed flow for separation of the inspection process and space functions. Moreover, this study introduces construction of the laboratory by applying the safety management standards.
The aftermath of the COVID-19 virus continues. There are two potential fears behind the various preventive and quarantine measures. : the fear that "I may be infected" and the fear that "someone may infect me". This subconscious is built on the 'imagination of infection'. This paper attempted to analyze science fiction(SF) narratives and zombie narratives that influenced our imagination of infection. And this paper attempts to examine how SF novels and movies understand and express "infection", and how zombie narratives reveal "infection" and its horror. Mary Shelley's novel "The Last Man" revealed the paradox that the fear of an infectious disease gave humanity an opportunity for reflection. The films and showed that fear and aversion to infectious diseases can lead to riots and conflict. Zombie narrative is a genre that most dramatically expresses the horror of infection. Director Yeon Sangho's zombie trilogy, including , reveals that people around you can turn into the most dangerous source of infection. Through SF and zombie narratives, we can realize that humanity must have a humble sense of solidarity, ethics, and empathy in the face of infectious diseases. Through this narrative texts, we can realize the importance of the imagination of infection. Imagination of infection is the basis for understanding the causes and consequences of the spread of infection, the process and future prospects.
An experiment was conducted to investigate the effects of varying levels of hydrolyzed yeast on egg production and egg quality in aged laying randomly allotted to three dietary treatments such that egg production was similar in each treatment (6 replicates of 10 birds each). The layers were fed diets containing 0, 0.1, or 0.2% hydrolyzed yeast for eight weeks. No significant difference was observed in egg production during the first half of the experiment. Egg production and daily egg mass in groups fed diets containing hydrolyzed yeast were significantly higher (P<0.05) than those of the control groups during the second half of the experiment. Egg weight was not affected by the dietary treatment. Eggshell strength and thickness in groups fed diets containing hydrolyzed yeast were significantly higher than those of the control groups during the overall experimental period (P<0.05). Although no significant differences were observed in the Haugh units, yolk color in the group fed diets containing 0.1% hydrolyzed yeast was significantly higher than that in the control group (P<0.05). The mammillary layer thickness increased in a linear manner and significantly following treatment with dietary hydrolyzed yeast (P<0.05). Antibody titer against avian influenza virus in the group fed diets containing 0.2% hydrolyzed yeast was significantly higher (P<0.05) than that in the control group. In conclusion, dietary hydrolyzed yeast improved egg production and eggshell quality of laying hens in the late stages of production.
Kim, Seonjeong;Kim, Yewon;Kim, Ju Won;Hwang, Yu-bin;Kim, Seong Hyeon;Jang, Yo Han
Journal of Life Science
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v.32
no.5
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pp.375-390
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2022
Influenza viruses are zoonotic respiratory pathogens, and influenza infections have caused a substantial burden on public health systems and the livestock industry. Although currently approved seasonal influenza vaccines have shown potent protection efficacy against antigenically well-matched strains, there are considerable unmet needs for the efficient control of viral infections. Enormous efforts have been made to develop broadly protective universal influenza vaccines to tackle the huge levels of genetic diversity and variability of influenza viruses. In addition, antiviral drugs have been considered important interventions for the treatment of viral infections. The viral neuraminidase inhibitor oseltamivir is the most widely used antiviral medication to treat influenza A and influenza B viruses. However, unsatisfactory clinical outcomes resulting from side effects and the emergence of resistant variants have led to greater attention being paid to plants as a natural resource for anti-influenza drugs. In particular, the recent COVID-19 pandemic has underpinned the need for safe and effective antiviral drugs with a broad spectrum of antiviral activity to prevent the rapid spread of viruses among humans. This review outlines the results of the antiviral activities of various natural products isolated from plants against influenza viruses. Special focus is paid to the virucidal effects and the immune-enhancing effects of antiviral natural products, since the products have broad applications as inactivating agents for the preparation of inactivated vaccines and vaccine adjuvants.
Kang Won, Park;Hyeon, Yang;Min Gook, Lee;Sun A, Ock;Hayeon, Wi;Poongyeon, Lee;In-Sul, Hwang;Jae Gyu, Yoo;Choon-Keun, Park;Bo Ram, Lee
Journal of Animal Science and Technology
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v.64
no.6
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pp.1105-1116
/
2022
Recently, we reported the robust in vitro three-dimensional (3D) expansion of intestinal organoids derived from adult bovine (> 24 months) samples. The present study aimed to establish an in vitro 3D system for the cultivation of intestinal organoids derived from growing cattle (12 months old) for practical use as a potential alternative to in vivo systems for various purposes. However, very few studies on the functional characterization and 3D expansion of adult stem cells from livestock species compared to those from other species are available. In this study, intestinal crypts, including intestinal stem cells, from the small intestines (ileum and jejunum) of growing cattle were isolated and long-term 3D cultures were successfully established using a scaffold-based method. Furthermore, we generated an apical-out intestinal organoid derived from growing cattle. Interestingly, intestinal organoids derived from the ileum, but not the jejunum, could be expanded without losing the ability to recapitulate crypts, and these organoids specifically expressed several specific markers of intestinal stem cells and the intestinal epithelium. Furthermore, these organoids exhibited key functionality with regard to high permeability for compounds up to 4 kDa in size (e.g., fluorescein isothiocyanate [FITC]-dextran), indicating that apical-out intestinal organoids are better than other models. Collectively, these results indicate the establishment of growing cattle-derived intestinal organoids and subsequent generation of apical-out intestinal organoids. These organoids may be valuable tools and potential alternatives to in vivo systems for examining host-pathogen interactions involving epithelial cells, such as enteric virus infection and nutrient absorption, and may be used for various purposes.
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