Résumé
In the past few years, significant efforts have been made to investigate the transmission of COVID-19. This paper provides a review of the COVID-19 airborne transmission modeling and mitigation strategies. The simulation models here are classified into airborne transmission infectious risk models and numerical approaches for spatiotemporal airborne transmissions. Mathematical descriptions and assumptions on which these models have been based are discussed. Input data used in previous simulation studies to assess the dispersion of COVID-19 are extracted and reported. Moreover, measurements performed to study the COVID-19 airborne transmission within indoor environments are introduced to support validations for anticipated future modeling studies. Transmission mitigation strategies recommended in recent studies have been classified to include modifying occupancy and ventilation operations, using filters and air purifiers, installing ultraviolet (UV) air disinfection systems, and personal protection compliance, such as wearing masks and social distancing. The application of mitigation strategies to various building types, such as educational, office, public, residential, and hospital, is reviewed. Recommendations for future works are also discussed based on the current apparent knowledge gaps covering both modeling and mitigation approaches. Our findings show that different transmission mitigation measures were recommended for various indoor environments;however, there is no conclusive work reporting their combined effects on the level of mitigation that may be achieved. Moreover, further studies should be conducted to understand better the balance between approaches to mitigating the viral transmissions in buildings and building energy consumption. © 2022
Résumé
While CLT has continued to be one of the most widely applied approach in teaching English as a foreign language (TEFL) worldwide, there has been numerous studies that have pointed out various obstacles in applying CLT in the East Asian context. Jeon (1997) identified key issues in implementing CLT in the Korean context and followed up on the same issues in Jeon (2009) to examine whether there had been any changes after 12 years of implementation. In particular, three research questions were considered: 1) What are the key issues in applying the communicative approach in Korea? 2) Is there an order of priority in the importance of these issues? and 3) Are there any changes in the importance of these issues after 12 years of implementation? The results showed that while some new issues had come up, the top key issues had remained the same. This was a surprising finding since there had not been any major changes in the top key issues 12 years after the first study and pointed out the persistent need to seek out obstacles over the years. As there had been a global upheaval in the educational context due to COVID-19, major changes in English education was expected. Accordingly, this study is another follow up study that focused on revisiting key issues regarding the implementation of CLT in the Korean EFL context. In order to identify the key issues, a three-round Delphi technique was used. A total of 36 teachers participated in identifying the key issues, ranking the issues and revisiting the ranked issues to see if there needs to be any adjustments. The results showed that, after 26 years of implementation, some of the key issues had been modified and have either increased or decreased their importance. While there were some issues that have newly emerged, the issues that had stayed in the top ranking have remained the same. This calls for an urgent need to address such issues as the curriculum continues to stress the importance of CLT in Korea. Without ameliorating the hindering factors, proper implementation of CLT will be challenging for English teachers in Korea. © 2022 AsiaTEFL All rights reserved.
Résumé
This study presents the characteristics of publications in the Journal of Korean Astronomy Society (JKAS) from 1968 to 2021. JKAS has published 763 research articles over the past 54 years. In addition, 376 proceedings were also published with research articles. There were slight increases and decreases in the number of articles published in JKAS in the 1990s and 2000s, and in 2015 there was the highest recorded number of articles published for a given year. Since then, the number of articles has tended to decrease each year, up to and including the most recent period (2020–2021), which includes the Coronavirus pandemic. However, since theory centered research is primarily conducted without being swayed by society and policies, and that the proportion of authors belonging to educational institutions, such as universities, is high, the future direction of JKAS is encouraging. There are also positive developments including sustained researchers affiliated with international institutions at greater than approximately 23%, as well as improvements in the impact factor. Therefore, it is important to not be deterred by the decreasing trends of the quantitative aspect, but to respond positively by determining a future roadmap. © 2022, Korean Astronomical Society. All rights reserved.
Résumé
There is an urgency to improve arts and culture education in public schools in Indonesia. Currently, the sector faces various challenges, such as insufficient course hours, limited topics, as well as inadequate number and expertise of teachers. With the Covid-19 pandemic, the situation has become even more precarious. To solve these problems, ARCOLABS organized an alternative arts and culture education program for local public-school students in 2020 as part of the Official Development Assistance (ODA) for Arts and Culture Education. Entitled `Made in Cirebon', this pilot project served as preliminary research to look for the most appropriate models to encourage innovations and sustainability in arts and culture education in local public schools in Cirebon through cooperation with local artists. This project-based study utilized several research methodologies, including seminars and discussions to develop learning contents, implementation of an online/on-site learning model, a mini showcase of learning outcomes by students, along with participant interviews, surveys, and evaluation by all stakeholders to prepare for a successive project in 2021. Through the inclusive, innovative and productive outcomes of the project, this research has drawn several positive conclusions: (1) various genres and disciplines can be integrated into an interdisciplinary subject that could overcome the limited course hours and topics within the school curriculum;(2) local artists can be important artistic and educational assets that could fill the gaps in formal education;and (3) a creative approach to local issues is a significant catalyst for the sustainability of the implemented model.
Résumé
This research shows how face masks took on discursive political significance during the early stages of the coronavirus disease 2019 pandemic in the United States. The authors argue that political divisions over masks cannot be understood by looking to partisan differences in mask-wearing behaviors alone. Instead, they show how the mask became a political symbol enrolled into patterns of affective polarization. This study relies on qualitative and computational analyses of opinion articles (n = 7,970) and supplemental analyses of Twitter data, the transcripts of major news networks, and longitudinal survey data. First, the authors show that antimask discourse was consistently marginal and that backlash against mask refusal came to prominence and did not decline even as masking behaviors normalized and partly depolarized. Second, they show that backlash against mask refusal, rather than mask refusal itself, was the primary way masks were discussed in relation to national electoral, governmental, and partisan themes. © The Author(s) 2022.
Résumé
Due to the COVID-19 pandemic, domestic universities have been forced to become a vast experimental ground for using technology for online classes. Despite the decades’ research on the use of technology in the field of English education, these online classes, which were suddenly and involuntarily administered to both teachers and learners, puzzled everyone. Considering a crisis can work as an opportunity, this unfamiliar non-face-to-face situation can be an opportunity to look at the teachers’ response to the crisis more clearly than the usual face-to-face situation. This study explored the experience of the college instructors, facing unprecedented challenges. In-depth interviews were conducted for four university professors who managed on-line-only English classes during the pandemic in 2020, asking the difficulties, emotions, solutions, and any changes while they were facing challenges this time. All interviews were recorded and transcribed to generate initial codes for each participant. The concepts with similar attributes were categorized through the process of integrating and reducing the codes. As a result, the challenges experienced by the participants were broadly categorized into two levels—individual and institutional. Participants’ emotions along with the obstacles they perceived;the ways they dealt with those obstacles;and any internal or external changes were further explored. The implications are discussed based on these results. © 2021 KASELL All rights reserved.
Résumé
In case of pneumonia often accompanied by serious complications, sometimes lead to death, early diagnosis and continuous monitoring can greatly reduce the dangerousness. Moreover, the COVID-19 pandemic has demonstrated the need for new diagnostic tools that can minimize medical personnel engagement while avoiding equipment being exposed to afflicted patients. In this study, we developed cough monitoring algorithm by detecting the vibrations of human body. The acceleration response at each part of body was measured to determine propagation characteristics of vibration when cough occurs. and it was confirmed that the monitoring accuracy was improved when use the vibration signal compared to the case of using only acoustic signal. After that, we analyzed the cough sounds in terms of psych-acoustical and sound-energy aspects. For the characteristic features derived by quantifying the results of analysis, the data augmentation process was applied, and finally AI-based pneumonia diagnosis algorithm was constructed. To estimate the performance of algorithm, the accuracy of pneumonia determination in new cough cases was verified. It showed the higher value than the accuracy of pulmonologists with only cough sounds. Therefore, developed algorithm that perform continuous cough monitoring and reliable pneumonia diagnosis can be used as an effective supplementary tool for early diagnosis and prognosis of pneumonia. © INTER-NOISE 2021 .All right reserved.
Résumé
The coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented impacts (e.g., labor shortage, suspension and cancellation of projects, and disrupted supply and logistics) on the US construction industry. To address challenges caused by the pandemic, it is critical for the construction industry to develop a clear understanding of how the pandemic has affected the industry and how it will change in the future. However, assessing the impacts of COVID-19 on the construction industry is challenging due to the broad influence of the pandemic and the dynamic nature of the industry. The Purdue Index for Construction (Pi-C), which was developed as an indicator based on five dimensions and corresponding metrics to measure the health status of the construction industry, offers an opportunity to understand the impact of the pandemic. In this context, this paper presents a study to reveal the relationship between COVID-19 and the health status of the industry as measured through Pi-C and predict the future trend of the construction industry. This study achieves the objective via the three steps. First, the relationship between the pandemic and Pi-C metrics is identified using the Granger causality test and structural equation modeling (SEM) analysis. Second, multivariable prediction models are developed based on a long short-term memory (LSTM) network - a deep learning algorithm - to predict Pi-C metrics in the future. Third, forecasted Pi-C metrics are integrated into the existing Pi-C structure to analyze the impacts of the COVID-19 pandemic and predict its trends in 2021-2022. The results revealed that the impacts of the pandemic were conspicuous in two Pi-C dimensions (economy and stability), whereas no significant impacts were observed in the remaining Pi-C dimension (social). In addition, the Pi-C forecasted that there would be no significant adverse impacts on the US construction industry caused by the pandemic until the end of 2022. © 2021 American Society of Civil Engineers.
Résumé
This paper develops a new approach to learning high-dimensional linear structural equation models (SEMs) without the commonly assumed faithfulness, Gaussian error distribution, and equal error distribution conditions. A key component of the algorithm is componentwise ordering and parent estimations, where both problems can be efficiently addressed using '1-regularized regression. This paper proves that sample sizes n = (d2 log p) and n = (d2p2=m) are sufficient for the proposed algorithm to recover linear SEMs with sub- Gaussian and (4m)-th bounded-moment error distributions, respectively, where p is the number of nodes and d is the maximum degree of the moralized graph. Further shown is the worst-case computational complexity O(n(p3 + p2d2)), and hence, the proposed algorithm is statistically consistent and computationally feasible for learning a high-dimensional linear SEM when its moralized graph is sparse. Through simulations, we verify that the proposed algorithm is statistically consistent and computationally feasible, and it performs well compared to the state-of-the-art US, GDS, LISTEN and TD algorithms with our settings. We also demonstrate through real COVID-19 data that the proposed algorithm is well-suited to estimating a virus-spread map in China. © 2021 Microtome Publishing. All rights reserved.