• 한국간호교육학회지
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• 제28권4호
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• pp.444-455
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• 2022

Purpose: This study explored the meaning of the social perceptions of nurses in online news articles during the coronavirus disease 2019 (COVID-19) pandemic. Methods: A total of 339 nurse-related articles published in Korean online newspapers from January 1 to December 31, 2020, were extracted by entering various combinations of OR and AND with the four words "Corona," "COVID," "Nursing," and "Nurse" as search keywords using BIGKinds, a news database provided by the Korea Press Foundation. The collected data were analyzed with a keyword network analysis and topic modeling using NetMiner 4. Results: The top keywords extracted from the nurse-related news articles were, in the following order, "metropolitan area," "protective clothing," "government," "task," and "admission." Four topics representing keywords were identified: "encouragement for dedicated nurses," "poor work environment," "front-line nurses working with obligation during the COVID-19 pandemic," and "nurses' efforts to prevent the spread of COVID-19." Conclusion: The media's attention to the dedication of nurses, the shortage of nursing resources, and the need for government support is encouraging in that it forms the public opinion necessary to lead to substantial improvements in treating nurses. The nursing community should actively promote policy proposals to improve treatment toward nurses by utilizing the net function of the media and proactively seek and apply strategies to improve the image of nurses working in various fields.

• ETRI Journal
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• 제46권2호
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• pp.290-306
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• 2024

To treat the novel COronaVIrus Disease (COVID), comparatively fewer medicines have been approved. Due to the global pandemic status of COVID, several medicines are being developed to treat patients. The modern COVID medicines development process has various challenges, including predicting and detecting hazardous COVID medicine responses. Moreover, correctly predicting harmful COVID medicine reactions is essential for health safety. Significant developments in computational models in medicine development can make it possible to identify adverse COVID medicine reactions. Since the beginning of the COVID pandemic, there has been significant demand for developing COVID medicines. Therefore, this paper presents the transferlearning methodology and a multilabel convolutional neural network for COVID (MLCNN-COV) medicines development model to identify negative responses of COVID medicines. For analysis, a framework is proposed with five multilabel transfer-learning models, namely, MobileNetv2, ResNet50, VGG19, DenseNet201, and Inceptionv3, and an MLCNN-COV model is designed with an image augmentation (IA) technique and validated through experiments on the image of three-dimensional chemical conformer of 17 number of COVID medicines. The RGB color channel is utilized to represent the feature of the image, and image features are extracted by employing the Convolution2D and MaxPooling2D layer. The findings of the current MLCNN-COV are promising, and it can identify individual adverse reactions of medicines, with the accuracy ranging from 88.24% to 100%, which outperformed the transfer-learning model's performance. It shows that three-dimensional conformers adequately identify negative COVID medicine responses.

• 농촌계획
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• 제26권4호
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• pp.27-39
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• 2020

With the COVID-19 pandemic, the global economy has stagnated and our daily lives have changed. The rural economy is also experiencing damage, such as an average of 65% or more decrease in the number of visitors to rural experience resort villages due to the spread of COVID-19. In order to minimize the damage arising from the prolonged coronavirus, a hospitality system in response to changes in rural tourism behavior and consumer demand is needed to revitalize rural areas and maintain continuous economic independence. Therefore, this study attempted to find ways to utilize landscape resources such as education, culture, history, and ecology in order to complement the existing experience programs in connection with local resources and local environment. Wibong Village, which is the subject of the study, attempted to revitalize the village using the resources through the "Creative village creation" project in 2015. Due to poor management of historical resources, difficulty in operating experience programs, and response to changes in the natural environment, the rate of implementation of the project plan was very low. Currently, the demand for experience is also decreasing due to the COVID-19 effect, so it was judged that it was necessary to develop an experience village program suitable for the needs of experienced visitors by discovering additional local resources for the continuous operation of the experience village. In order to solve the problem of the use of landscape resources and the spatial composition of the study site, additional investigations of local resources were made, and an experience program course that could be operated by theme was proposed by configuring a space suitable for the use of landscape resources. By dividing the additionally investigated landscape resources into history, ecology, and region, an experiential course was created to separate the traffic lines, and the space composition for large-scale experienced visitors that had been previously operated was constructed in a form suitable for the post-corona era. In addition, at least two experiential tour courses that can be operated by period were proposed to maintain economic effects. Starting with this study, if further research on the creation and spatial composition of a rural experience village centered on the connection with the region, it will be used as research results that can be referenced in projects such as village creation, rural space planning, and living area analysis. It is expected that it will be able to effectively cope with the construction of a rural area suitable for the post-corona era, where demand is expected to increase in the future.

• 벤처창업연구
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• 제16권1호
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• pp.113-126
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• 2021

2020년 상반기 코로나19 팬데믹 사태 이후 비즈니스의 세계는 매우 다른 모습으로 변화되었다. 향후 비즈니스의 키워드는 디지털로 수렴하는 비대면(Untact)이라 할 수 있다. 코로나19 사태로 인해 사람들이 온라인으로 쏠리면서 디지털 미디어 기기 활용역량이 중요한 화두로 떠올랐다. 코로나 사태가 모든 접점에서 디지털화가 얼마나 중요한지를 일깨워 준 것이다. 본 연구를 통해 디지털 미디어 기기 및 커뮤니케이션 활용역량이 창업에 있어서도 유의한 영향을 미치는지를 검증하고, 디지털 미디어 기기 및 커뮤니케이션 활용역량이 창업의도에 영향을 미치는 과정에서 위험감수성과 진취성이 매개역할을 할 수 있는지를 규명하고자 한다. 본 연구를 위해 일반인 250명을 대상으로 한 설문조사를 진행하였고, 최종적으로 212개의 유효한 설문지를 수집하였다. 통계기법은 Amos23을 사용하여 분석하였다. 수집된 자료의 분석결과, 디지털 미디어 기기 활용역량과 커뮤니케이션 활용역량은 직접적으로 창업의도에 정(+)의 영향을 주지 못하는 것으로 나타났으나, 기업가정신의 위험감수성을 추구할 때 창업의도를 갖게 된다는 것이 확인되었다. 이를 통해 정보통신 중심의 스마트 사회에서는 기업가정신 및 디지털 미디어 활용역량에 기초한 창업 프로그램 개발을 정책적으로 강화해야 디지털 미디어 기기 활용과 커뮤니케이션 활용역량이 월등한 디지털 세대의 일자리 창출이 확대될 수 있다는 시사점을 도출하였다.

• 공업화학
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• 제32권2호
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• pp.219-223
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• 2021

Considering the current COVID 19 pandemic, herein, we developed a material that can be used to fabricate a device for checking the body temperature of a person who has been exposed to influenza or corona virus. This material was formed by mixing pluronic F127 (F127) with a polydiacetylene (PDA) vesicle, which was formed with 10,12-pentacosadiynoic acid. The color of the system started to change from blue to light purple at 37 ℃, finally turning reddish at 40 ℃. Thus, the developed material can be used to detect changes in body temperature, and thus, detect signs of fever. The mixing ratio of the PDA vesicle and F127 was an important factor for controlling the temperature at which the color change started. The results showed that the color change accompanied by the separation of the PDA vesicle with F127. We believe that this phenomenon plays an important role in reducing the conjugation length in the double and triple bond of PDA.

• 대한방사선기술학회지:방사선기술과학
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• 제43권6호
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• pp.511-518
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• 2020

In the pandemic situation due to corona 19, we examined the satisfactory level of students' between non-face-to-face and online classes in the first year of radiology. In the case of online non-face classes related to radiation majors, it is considered better to conduct real-time lectures than recorded lectures, which allows students to understand difficult radiation majors throughout real-time questions and answers, and at the same time allows them to sympathize with difficult subjects such as intimacy and bonds between students. As a result of the analysis of the answers to questionnaires, the coefficient of answer correlation between first and second grade students is P>0.05, and there is no answer correlation between grades, and it can be seen that the higher the grade, the higher the demand for face-to-face classes was.

• 한국정보시스템학회지:정보시스템연구
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• 제29권4호
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• pp.123-135
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• 2020

Purpose The purpose of this study is to investigate the development process and the effectiveness of the EISS (epidemiological investigation support system), which prevents the spread of infectious diseases like a novel corona virus disease, COVID-19. Design/methodology/approach This study identified the existing epidemiological support system for MERS through prior research and studied the case of the development of a newly developed epidemiological support system based on cloud computing infrastructure for COVID-19 through inter-ministerial collaboration in 2020. Findings The outbreak of COVID-19 drove the Korean Government began the development of the EISS with private companies. This system played a significant role in flattening the spread of infection during several waves in which the number of confirmed cases increased rapidly in Korea, However, we need to be careful in handling confirmed patients' private data affecting their privacy.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.225-233
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• 2022

The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.

• International Journal of Advanced Culture Technology
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• 제10권1호
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• pp.204-210
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• 2022

From the 1970s to the present, the number of new infectious diseases such as SARS, Ebola virus, and MERS has steadily increased. The new infectious disease, COVID-19, which began in Wuhan, Hubei Province, China, has pushed the world into a pandemic era. As a result, Countries imposed restrictions on entry to foreign countries due to concerns over the spread of COVID-19, which led to a decrease in the movement of tourists. Due to the restriction of travel, keywords such as "Corona blue" have soared and depression has increased. Therefore, this study aims to analyze the stress meaning network of the COVID-19 era to derive keywords and come up with a plan for a travel-related platform of the Post-COVID 19 era. This study conducted analysis of travel and stress caused by COVID-19 using TEXTOM, a big data analysis tool, and conducted semantic network analysis using UCINET6. We also conducted a CONCOR analysis to classify keywords for clustering of words with similarities. However, since we have collected travel and stress-oriented data from the start to the present, we need to increase the number of analysis data and analyze more data in the future.

• 한국산업융합학회 논문집
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• 제25권6_2호
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• pp.1029-1036
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• 2022

The traditional outdoor advertising market has been stagnant recently, but the digital advertising market has been steadily increasing, and the digital signage market has been expanding despite the recent corona pandemic. However, in terms of hardware, new displays are required due to excessive power consumption, lack of visibility in sunlight, and continuous operating expenses. Since the e-paper display does not require a light emitting device therein, it is advantageous to solve above problems. In addition, it has the advantage of consuming power only when converting an image due to bistability, so it is suitable as hardware that implements images rather than moving pictures. Currently, one of the most successful examples of commercializing e-paper displays is ESL devices. According to a recent market study, the market for large-sized panels larger than 10 inches has grown at an annual rate of 21.6%, and the market is expected to exceed 30% by 2026. It is judged that it will be relatively easy to apply the roll-to-roll technology, which is currently developing the technology applied to OLED, to the e-paper display. Therefore, mass production technology and market expansion for ESL panel enlargement are expected, and a new market is also expected to be formed at the same time. New markets will be traffic signs, public displays, billboards, façades, kiosks, digital signage, and so on.