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Rigorous Coupled Wave Analysis (RCWA) method is highly efficient for the simulation of diffraction efficiency and field distribution patterns in periodic structures and textured optoelectronic devices. GPU has been increasingly used in complex scientific problems such as climate simulation and the latest Covid-19 spread model. In this paper, we break down the RCWA simulation problem to key computational steps (eigensystem solution, matrix inversion/multiplication) and investigate speed performance provided by optimized linear algebra GPU libraries in comparison to multithreaded Intel MKL CPU library running on IRIDIS 5 supercomputer (1 NVIDIA v100 GPU and 40 Intel Xeon Gold 6138 cores CPU). Our work shows that GPU outperforms CPU significantly for all required steps. Eigensystem solution becomes 60% faster, Matrix inversion improves with size achieving 8x faster for large matrixes. Most significantly, matrix multiplication becomes 40x faster for small and 5x faster for large matrix sizes. © 2023 SPIE.
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PurposeSmart furniture is an essential part of research that has been designed to best complement easy and safe human interaction. The purpose of smart furniture is to save the space of the house and make the products unique, awesome and safe, functional, strong and also make it works better so the people can live better with it. This research aims to explore the key supply chain strategies implemented by the Indian smart furniture industry to reduce the impact of a post-COVID-19 pandemic.Design/methodology/approachThis work utilized a case study and conducted semi-structured interviews with the top leadership of the smart furniture manufacturing industry to explore key supply chain strategies to reduce the influence of the post-COVID-19 pandemic. Additionally, key supply chain strategies have been analyzed using a multi-criteria decision-making technique known as grey relational analysis (GRA) to determine their ranking significance in the smart furniture industry.FindingsThe results of this study discovered that "Inventory-Categorization” is essential in ensuring business continuity during the COVID-19 pandemic and helps reduce the amount of stock they have on hand. It enhanced the opportunity for employees to properly focus on their work and an opportunity for better work-life balance. The results of the study can also help supply chain stakeholders in their establishment of critical strategies.Research limitations/implicationsThe implications of this research work help the Indian furniture industry to make supply chain investment decisions that benefit the organization to sustain itself.Originality/valueThis is the first study to explore key supply chain strategies for the post-COVID-19 era. This work will assist managers and practitioners in helping the organization decide which supply chain strategies are more critical to the betterment of the organization.
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Microplastics (MPs) are emerging environmental contaminants pervasive in the environment. Studies have revealed that the majority of airborne MPs are in the form of fiber. Inhaled atmospheric MPs adversely impact human health, causing inflammation and oxidative stress. Atmospheric MPs may also carry hazardous chemical pollutants in addition to heavy metals. Many research studies have been conducted about MPs' presence in the environmental components, however questions about the presence and identification of atmospheric MPs remained unanswered. Based on the mentioned research gaps, this study examined the sources and abundance of MPs in the atmosphere and their generation, accumulation, and fate. The paper further studies and evaluates current methods for identifying and assessing airborne MPs and their impact on human health and the environment. According to the study findings, there are flaws and complexity in MPs assessment and technical procedures, which further challenges data comparability and dependability. In order to ensure data comparability and reliability, the abundance of atmospheric MPs needs to be expressed using a unified and standard methodology. Innovative and well-established identification methods, strategies to minimize the impacts of MPs, and appropriate steps to reduce this global pollution are required for the current state of MPs. It also provides an overview of atmospheric MPs' characteristics, sources, and airborne transmission and deposition mechanisms. Advances in bacterial degradation, sunlight-driven photocatalysts, fuels, and biodegradable plastics could revolutionize future studies on reducing plastic pollution. Future studies should include more research on the various aspects of atmospheric MPs. Despite several research studies conducted on the presence and identification of MPs in various environmental components, many questions regarding MPs in the atmosphere and from the perspectives of COVID-19 and One Health still need to be answered. This study will help the key stakeholders and policymakers in safeguarding public health and environment from the threats posed by airborne MPs.
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In this paper, a new method for obtaining the basic reproduction number is proposed, called the path analysis method. Compared with the traditional next-generation method, this method is more convenient and less error-prone. We develop a general model that includes most of the epidemiological characteristics and enumerate all disease transmission paths. The path analysis method is derived by combining the next-generation method and the disease transmission paths. Three typical examples verify the effectiveness and convenience of the method. It is important to note that the path analysis method is only applicable to epidemic models with bilinear incidence rates. The Volterra-type Lyapunov function is given to prove the global stability of the system. The simulations prove the correctness of our conclusions.
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Aiming at the multi-attribute group decision-making problem with interval-valued probabilistic uncertain linguistic term set (IVPULTS) and unknown expert weights, this paper proposed a decision-making method combining distance and similarity. Firstly, it employed the interval dominance degree method to rank interval-valued probabilities to form an ordered IVPULTS since the disorder of elements in IVPULTS causes the existing distance measure and decision-making result to be non-unique. At the same time, it expanded the existing distance by using the interval linguistic term distance measuring method considering the poor discriminative power. Secondly, based on the dual relationship between distance and similarity measures, this paper defined the distance similarity formula and determined the weights of different experts using the improved similarity-trust network analysis method. Next, it designed a TOPSIS decision-making method based on improved distance and similarity-trust network (IDSTN-TOPSIS) to obtain a unique and stable ranking of the alternatives. Finally, taking the selection of resilient suppliers of a medical supplies manufacturing company under COVID-19 as an example, experimental results verify the effectiveness and superiority of the proposed method. (English) [ FROM AUTHOR] 针对属性值为区间值概率不确定语言术语集（interval-valued probabilistic uncertain linguistic term set, IVPULTS）、专家权重未知的多属性群决策问题，提出一种融合距离和相似度的决策方法。首先，由于现有的 IVPULTS中元素的无序性导致距离测度及决策结果不唯一，利用区间优势度方法对区间值概率进行排序，从而 形成有序的IVPULTS；同时考虑到现有距离测度区分能力不高，利用不确定语言距离度量方法扩充现有距离公 式。其次，基于距离与相似测度存在的对偶关系，为IVPULTS定义了距离相似度公式，并利用改进的相似—信 任网络分析法确定不同专家的权重。再次，设计了基于改进距离和相似—信任网络的TOPSIS决策方法（improved distance and similarity-trust network TOPSIS，IDSTN-TOPSIS），从而得到唯一且稳定的方案排序。最后，以新 冠疫情下某医疗用品制造公司熔喷布弹性供应商选择为例，验证了所提方法的有效性和优越性。 (Chinese) [ FROM AUTHOR] Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Under the Covid-19 situation, the older people's lack of understanding of the epidemic information, resulting in poor self-protection, limited travel, affects the purchase of life and medical items. These made a significant threat to their health. Due to the rules of home isolation, the Internet has become the primary source of information. But this leads to the digital divide faced by the elderly becoming more prominent, which has already existed before. This research studies the specific difficulties faced by the elderly in the digital divide in the epidemic. This paper used a semi-structured interview and recruited 25 older people to participate. By analyzing the interview content, this study used the content analysis method to analyze the difficulties of information acquisition and utilization of the elderly. In addition, this study analyzed the main reasons for the digital divide faced by the elderly from internal and external factors. Then, this study proposed suggestions for IT enterprises and government to solve the digital divide in the Covid-19 from the perspective of the elderly. Through this study, the findings can help solve the digital divide faced by the elderly in the epidemic, help them better obtain accurate information, and help them better protect their health. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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COVID-19 has dramatically changed people's mobility patterns. This report aims to analyze the impact of COVID-19 on people's mobility through statistics and comparing the visits of POIs (Point-Of-Interests) in New York State in 2019 and 2020. The report uses data from SafeGraph, which is a data company. The raw data contains POI visits across the United States in 2019 and 2020. Considering the analysis size and difficulty of the data, POI visits from New York State are extracted for analysis, and POI locations are classified according to the tags provided by the source data. The scale of analysis is from macro to micro, and they are the total POI visits data of New York State based on different ways in 2019 and 2020, the POI visits of CBG (Census Block Group) division in New York City, and three representative POI samples to do individual analysis. The analysis methods are: (1) use line plot and bar plot statistics to compare the trends of POI visits data from 2019 to 2020, and (2) make the spatial visualization comparison, which includes grid map, scatter map, heatmap, and OD map, between the first peak of epidemic impact in the first full week of April 2019 and April 2020, and the scope is narrowed to New York City. Wherein the OD maps are drawn based on the CBG division. Compared to related work, the analysis object includes CBG, categories, and individual POI. In addition, the analysis method combines statistical graphs and spatial visualizations and explores the policy impact of the New York City government. This report adopts more multidimensional analysis methods and objects to improve the comprehensiveness and reliability of the analysis content. © 2022 IEEE.
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Tea culture tourism is a product of the combination of agricultural tourism and ecotourism. After the COVID-19 period, this product is more and more popular. Tourism performance is an important index for measuring the development level of tourist destinations, and research on the influencing factors of tourism performance is an important way to promote the high-quality development of tea culture tourism. Using the tea tourism town of Wushan as a case study, 452 valid questionnaires were used as research data, and exploratory factor analysis, paired sample t-test and IPA analysis were applied. The results indicate that: (1) tourism performance is mainly divided into 5 dimensions and 22 specific indicators, including service quality, resource environment, tourism transportation, tourism-supporting facilities and tea tourism products;(2) there is a significant difference between the degree of importance and performance of visitors to each indicator, and the overall tourism performance of the case sites at an average level;(3) convenient service, professional service, business management, park traffic, parking conditions, environmental design, shopping environment, tea quality, and tea culture characteristics are potential advantageous factors, and ‘service with a smile', accessibility, trail layout, overall image, air quality, natural scenery, landscape vignettes, network communication, public toilets, sanitation facilities, tourist service centers, tea travel activities, and tourism souvenirs are areas in need of improvement. © 2023 by the authors.
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Indonesia is in 4th position in the scope of sharia economics. This potency allows Indonesia to develop the halal industry, including the halal food and beverage industry. The COVID-19 pandemic has resulted in SMIs (Small and Medium Industries) experiencing a decline in sales. This study aims to design a marketing strategy for the beverage industry sales, provide suggestions and find out the main demands and challenges faced by SMIs related to halal logistics. Data were collected on 10 SMI beverage industries using observation techniques, interviews, and historical data. Marketing strategy analysis using the SOAR analysis method was carried out as a strategy to increase sales. Strategic management found that each SMI owned strengths, opportunities, aspirations, and results. The SOAR analysis method was then developed into four parts: S-A, O-A, S-R, and O-R. This analysis is used as an alternative strategy for each SMI in the beverage industry based on the existing factors. Proposals for the marketing strategy improvement were given, as well as the results of the interviews demonstrating that SMI's actors understand the importance of halal in every process. Yet, several obstacles were found in its implementation, such as a lack of education, the need for thorough socialization, complex and time-consuming administration, and constraints originating from the government and expedition services. © 2023 IEEE.
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Since the outbreak of COVID-19, many countries began to try to use online platforms and digital tools for distance learning. This study focuses on the effectiveness of information technology and teaching strategies in distance learning to improve the learning effect of K-12 students. By using the meta-analysis method and screening criteria of empirical research, it focuses on methodological and substantive research, and examines the relationship between information technology and learning effect, and the relationship between teaching strategies and learning effect in distance learning. The final analysis included 85 qualified studies with a total sample size of 79,928 K-12 students: 35 primary school studies (n = 35,155) and 50 secondary school studies (n = 44,773). The results show that compared with offline learning, the application of information technology in distance learning usually has a positive impact (ES=+2.26). However, the impact may vary depending on the type of information technology. From the perspective of teaching strategies, case-based teaching strategies can improve students' learning effect. Therefore, when applying information technology and teaching strategies to students' distance learning effect, we should strengthen the design of process objectives, pay attention to the role of sharing and co-construction technologies in distance learning, and adopt case-based teaching strategies to stimulate students' high-level cognitive activities and cognitive achievements, so as to promote distance learning. © 2022 Association for Computing Machinery.
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The pandemic has led to the production and accumulation of various types of data related to coronavirus disease 2019 (COVID-19). To understand the features and characteristics of COVID-19 data, we summarized representative databases and determined the data types, purpose, and utilization details of each database. In addition, we categorized COVID-19 associated databases into epidemiological data, genome and protein data, and drug and target data. We found that the data present in each of these databases have nine separate purposes (clade/variant/lineage, genome browser, protein structure, epidemiological data, visualization, data analysis tool, treatment, literature, and immunity) according to the types of data. Utilizing the databases we investigated, we created four queries as integrative analysis methods that aimed to answer important scientific questions related to COVID-19. Our queries can make effective use of multiple databases to produce valuable results that can reveal novel findings through comprehensive analysis. This allows clinical researchers, epidemiologists, and clinicians to have easy access to COVID-19 data without requiring expert knowledge in computing or data science. We expect that users will be able to reference our examples to construct their own integrative analysis methods, which will act as a basis for further scientific inquiry and data searching.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2/genetics , Genomics , Pandemics , Databases, FactualABSTRACT
The spread of COVID-19 has brought negative impacts on the life and study of college students and thus aggravated their mental stress in this environment. Existing research has focused more on the status quo of the problem while having ignored its process variability, and there is no research on the correlation between the mental stress of college students and their learning initiative during the outbreak of COVID-19. To this end, this paper conducts an analysis of the correlation between the mental stress of college students and their learning initiative during the outbreak of COVID-19. In-depth analysis was carried out by the factor analysis method in SPSS, and an evaluation model was built for the mental stress of college students during the outbreak of COVID-19 based on four stressors, with the process of how to obtain the evaluation results given. The grey correlation analysis method was used to quantitatively analyze the correlation between the mental stress of college students and their learning initiative during the outbreak of COVID-19, that is, the factors affecting college students' learning initiative during the outbreak of COVID-19 were investigated through the grey correlation analysis. Finally, the relevant experimental results were given © 2022, International Journal of Emerging Technologies in Learning.All Rights Reserved.
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Based on the data of COVID-19 epidemic and online tourism review, this paper explores the impact of COVID-19 on tourists' tourism emotion. First, based on the existing theory, the hypothetical relationship between COVID-19 and tourists' PAD (Pleasure-Around-Dominion) emotion is established. Then, the PAD emotion variables in tourism reviews are extracted through the emotion analysis method, and then an empirical econometric model is established. Finally, the model is estimated using the double difference method, and a series of robustness tests are conducted. The empirical results show that COVID-19 has a significant negative impact on tourists' PAD sentiment. © 2022 IEEE.
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This research aims determine the literacy practices used by government officials to prevent the spread of hoaxes and misinformation. The pandemic created a crisis that crowded information sources;in that situation, social media users had to decide which information to trust and use as the primary reference. As a result of the Covid-19 cases, the spread of false information has increased. This study employs a qualitative narrative analysis method with the MAXDA software tool to investigate the government's digital literacy function. According to the study's findings, the government used social media under the ministry of information and communication to filter information for social media users. To support this step, the government also campaigned for an electronic transaction law as a preventive measure to prevent the spread of hoaxes on social media. In addition, to create massive information, the ministry of information and communication uses several accounts under the coordination of the ministry to provide information. The findings underline the ability to create digital literacy by the ministry of information and communication through the electronic transaction law. In the last three years, the intensity of tweets by the Ministry of Communication and Information account has increased;this is based on the increase in Covid-19 cases and the implementation of large-scale social distancing policies in Indonesia. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Purpose - Smart furniture is an essential part of research that has been designed to best complement easy and safe human interaction. The purpose of smart furniture is to save the space of the house and make the products unique, awesome and safe, functional, strong and also make it works better so the people can live better with it. This research aims to explore the key supply chain strategies implemented by the Indian smart furniture industry to reduce the impact of a post-COVID-19 pandemic. Design/methodology/approach - This work utilized a case study and conducted semi-structured interviews with the top leadership of the smart furniture manufacturing industry to explore key supply chain strategies to reduce the influence of the post-COVID-19 pandemic. Additionally, key supply chain strategies have been analyzed using a multi-criteria decision-making technique known as grey relational analysis (GRA) to determine their ranking significance in the smart furniture industry. Findings - The results of this study discovered that "Inventory-Categorization" is essential in ensuring business continuity during the COVID-19 pandemic and helps reduce the amount of stock they have on hand. It enhanced the opportunity for employees to properly focus on their work and an opportunity for better work-life balance. The results of the study can also help supply chain stakeholders in their establishment of critical strategies. Research limitations/implications - The implications of this research work help the Indian furniture industry to make supply chain investment decisions that benefit the organization to sustain itself. Originality/value - This is the first study to explore key supply chain strategies for the post-COVID-19 era. This work will assist managers and practitioners in helping the organization decide which supply chain strategies are more critical to the betterment of the organization.
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This study proposes an internet design framework for users to improve their positive emotions when they are in a negative mood. First, the literature review focuses on the definition of emotion, positive emotional design in internet experiences, and emotion regulation. Second, in order to construct an internet design framework that improves positive emotion, this paper adopts a qualitative analysis method to analyze 70 collected studies in the area of regulating emotion and stimulating positive emotions. Additionally, bibliometrics and statistics are conducted to summarize the framework and strategies. Third, two cases of internet design are presented: (a) Internet design that improves users' positive emotions is examined under the background of extreme rainstorm as an example;an applet service design is provided by case study;(b) in the context of COVID-19, we developed an Internet of things interactive design that improves users' positive emotions. Fourth, the internet design framework and the results of the case studies are analyzed and discussed. Finally, an internet design framework is proposed to improve users' positive emotions when they are in a negative mood, which includes the Detachment-empathy framework, External-protection framework, Ability-strengthen framework, Perspective-transformation framework, and Macro-cognitive framework. The framework can help designers to generate design ideas accurately and quickly when users are in a negative mood, to improve subjective well-being, and contribute to the development of internet experience design. Copyright © 2022 KSII.
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Recognizing the impact of COVID-19 on economic structure is an urgently required task for the post-pandemic era. However, studies have been hampered in undertaking this task by a lack of current data and the use of inappropriate methods. This paper fills the gap in the literature by applying a network analysis method using the newly released input-output tables of China and evaluating the structural impacts on the economy, including the changes in the sectoral closeness, betweenness, risk condition, and network backbone. The modelling results demonstrate that the pandemic has accelerated the structural transformation process of the Chinese economy: the traditional growth engines, such as the petroleum and finance industries, have lagged, whereas new growth engine sectors, including the digital services and scientific research industries, have expanded rapidly. Accordingly, we propose that the government formulate policies to stabilize old growth engine industries and foster new drivers to promote a sustainable economic recovery in China.
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In this era of social media, people share anything they feel or experience on social media in the form of posts or comments. These posts, comments or reviews of the people can be analyzed using sentimental analysis, which is emerging field in text mining. COVID-19 has people's life all over the globe and thus has declared as pandemic. Due to COVID, people are feeling panic, anxiety, rage, sorrow, misery, stress and other issues. In this review, we have presented the sentimental analysis data sources, approaches, scenarios, methods and tools by comparing thirty studies. The results illustrated that most researchers have used SVM and Naive Bayes for sentimental analysis on COVID research. We also concluded that most of the researchers work on the sentiments of students, reopening sentiments, vaccine sentiments etc. © 2022 CEUR-WS. All rights reserved.
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The prospects of China's sports sector hinge on how sports cities can thrive sustainably in the context of the new global pandemic, unlocking consumer potential and boosting domestic demand. In this study, 35 Chinese cities were chosen as research samples, and research methods such as literature, logical analysis, and fuzzy-set qualitative comparative analysis were used to select conditional variables such as government policy promotion and assistance, expert human resources, sports competitions and events, stadiums and facilities, and sponsorship by sports enterprises to examine how Chinese sports-consuming cities can develop sustainably. The research discovered that sports contests and events, as well as stadiums and facilities, are the essential prerequisites for the sustainable growth of sports-consuming cities, and that diverse combinations of the two may play a vital role in different circumstances. For the sustainable development of sports-consuming cities, there are four clusters and three models, which correspond to the "Venue + Event" model (Clusters 1 and 2), the "Event-led" model (Cluster 3), and the "Venue-led" model (Cluster 4). To encourage the high-quality growth of China's sports business, each city may establish its development strategy based on its unique qualities. The goal is to supply Chinese expertise for the long-term growth of Western sports cities.
Subject(s)
Sports , Sustainable Development , China , Cities , Government , HumansABSTRACT
Sentiment analysis is an approach to determine individual's emotional state by investigating text from web. Due to COVID-19 the entire worldwide population was driven by fear of erroneous information across the web. This article explores public opinion and examines people's attitudes and emotions using tweets during the pandemic. To analyze the changes in sentiments and emotions, tweets from Indian users in 2020 were collected during April 11-14, June 4-8, and August 20-24. The proposed work compares TextBlob and NRC Lexicon sentiment analysis methods. TextBlob performs better in sentiment classification whereas the NRC Lexicon technique evaluates emotional states in larger depth. The proposed work examines the sentiment variations from three different tweets time slots and compares the results from both experimental methods. The outcomes from both the methods indicate that neutral sentiments are the majority and positive sentiments overshadow negative sentiments © 2022 IEEE.