Mathematical Modeling of COVID-19 Spread Using Genetic Programming Algorithm

This paper analyses the possibilities of using Machine learning to develop a forecasting model for COVID-19 with a publicly available dataset from the Johns Hopkins University COVID-19 Data Repository and with the addition of a percentage of each variant from the GISAID Variant database. Genetic programming (GP), a symbolic regressor algorithm, is used for the estimation of new confirmed infected cases, hospitalized cases, cases in intensive care units (ICUs), and deceased cases. This metaheuristics method algorithm was used on a dataset for Austria and neighboring countries Czechia, Hungary, Slovenia, and Slovakia. Machine learning was done to create individual models for each country. Variance-based sensitivity analysis was initiated using the obtained mathematical models. This analysis showed us which input variables the output of the obtained models is sensitive to, like in the case of how much each covid variant affects the spread of the virus or the number of deceased cases. Individual short-term models have achieved very high R2 scores, while long-term predictions have achieved lower R2 scores. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Analysis of the relationship between bitcoin, oil prices, and the Dow Jones Industrial Average using a wavelet-based approach

This paper analyzes the correlation between bitcoin, oil price fluctuations and the DOW Jones Industrial Index in the time-frequency framework. Coherent wavelet method applied to recent daily data in the United States (1863 in total). Our research has several implications and supports for policy makers and asset managers. We find that oil prices lead the U.S. market at both low and high frequencies throughout the observation period. This result suggests that sanctions against Russia by a number of countries, including the U.S., are influencing oil prices, while oil remains a major source of systemic risk to the U.S. economy and economic uncertainty between the international level is exacerbated by tensions between Russia and Ukraine. © COPYRIGHT SPIE.

Comparing Deep and Machine Learning Models for Sentiment and Emotion Classification from Vaccine #sideffects

The accelerated development of Covid-19 vaccines offered tremendous promise and hope, yet stirred significant trepidation and fear. These conflicting emotions motivated many to turn to social media to share their experiences and side effects during the process of getting vaccinated. This paper analyzes sentiment and emotions from tweets collected using the hashtag #sideffects during the early roll out of the Covid-19 vaccine. Each tweet was labeled according to its sentiment polarity (positive vs. negative), and was assigned one of four emotion labels (joy, gratitude, apprehension, and sadness). Exploratory analysis of the tweets through word cloud visualizations revealed that the negativity of emotions intensified with the severity of side effects. Word and numerical features extracted from the text of the tweets and metadata were used to train conventional machine learning and deep learning models. These models resulted in an accuracy of 81% for binary sentiment classification, and 71 % for multi-label emotion identification. The proposed framework, which yielded competitive performance, may be employed to gain insights into people's thoughts and feelings from vaccine-related conversations. These insights can be helpful in devising communication and education strategies to mitigate vaccine hesitancy. © 2022 IEEE.

Charging after Lockdown: The Aftermath of COVID-19 Policies on Electric Vehicle Charging Behaviour in The Netherlands

During the COVID-19—related lockdowns (2020–2022), mobility patterns and charging needs were substantially affected. Policies such as work from home, lockdowns, and curfews reduced traffic and commuting significantly. This global pandemic may have also substantially changed mobility patterns on the long term and therefore the need for electric vehicle charging infrastructure. This paper analyzes changes in electric charging in the Netherlands for different user groups during different phases of the COVID-19 lockdown to assess the effects on EV charging needs. Charging needs dropped significantly during this period, which also changed the distribution of the load on the electricity grid throughout the day. Curfews affected the start times of charging sessions during peak hours of grid consumption. Infrastructure dedicated to commuters was used less intensively, and the charging needs of professional taxi drivers were drastically reduced during lockdown periods. These trends were partially observed during a post–lockdown measuring period of roughly 8 months, indicating a longer shift in mobility and charging patterns. © 2023 by the authors.

Transnational lived citizenship turns local: Covid-19 and Eritrean and Ethiopian diaspora in Nairobi

This paper analyses how migrant community practices of transnational lived citizenship were altered by both, COVID-19 and the policy response from the Kenyan government. It is based on interviews with members of the Eritrean and Ethiopian diaspora residing in Nairobi. The paper demonstrates how policies introduced because of the pandemic caused migrant communities to lose local and remittance income. More than the loss of material resources, however, they were impacted by the elimination of social spaces that enable diaspora lives. These two dynamics have intensified a trend that may have been present before the pandemic, a local turn of transnational lived citizenship. By focusing on lived experiences and how they have been re-assessed during the pandemic, the paper argues that transnational lived citizenship is always in flux and can easily become reconfigured as more localized practices. The concept of transnational lived citizenship is demonstrated to be a useful lens for analysing shifting migrant livelihoods and belonging. © 2022 The Authors. Global Networks published by Global Networks Partnership and John Wiley & Sons Ltd.

The Role of School Teachers' and International Education Project Leaders' Digital Competence during Covid-19 Pandemic

This paper analyses the significance of digital competence in the light of the impact of the Covid-19 on formal and non-formal education settings. The Authors discuss the definition of digital competence, as provided by the European Commission, and quote key international research data on digital competence in education. Furthermore, based on research carried out by the Authors during the Covid-19 pandemic among school teachers familiar with digital technologies in learning, and international education project coordinators, the Authors claim that digital competence has become one of the most substantial elements in contemporary classroom and international education project management. © 2022 WMSCI.All rights reserved.

Possible Understanding and Model-Based Prediction of Time Evolution of Number of Infected People in COVID-19 Pandemic in Japan

This paper analyzes the time evolution of the number of infected people in Japan since 2020, and important aspects are discovered. It is found out that the time evolution of the number of infected people exhibits two critical aspects of time evolution of infection;that is, the discovered specific intervals between the peak values and the valley values are useful in predicting the next peak. In addition, it is revealed that the time evolution of the increase in the number of infected people in Japan over the present 6th peak is non-linear, which is different from past characteristics since 2020. A possible background mechanism is discussed, and a possible prediction is also introduced. © 2022 IEEE.

Application progress of telemedicine in bipolar disorder patients under the COVID-19 pandemic

Bipolar disorder (BD) is a highly pathological disorder that is often misdiagnosed or undiagnosed. The main treatment is a combination of psychotherapy and medication. Traditional psychotherapy is affected by factors such as time, space, shortage of professional psychotherapists and patients' stigma, and has low availability. In terms of drug therapy, patients' medication compliance is poor, leading to repeated illness. The epidemic of coronavirus in 2019, closed management and telemedicine provide new ideas for the treatment of BD. Telemedicine can provide convenient medical services, promote disease rehabilitation, effectively guide patients' self-management, improve patients' treatment compliance, and prevent disease recurrence. This paper analyzes and summarizes the research related to telemedicine in BD, including the origin and significance, technical methods and application effects. To provide a reference for the application of telemedicine in patients with BD. © 2022 ACM.

Analysis On the Challenges for Smart Elderly Care to Face in the Post-pandemic Era of Covid-19

Based on the investigation of the current situation of smart elderly care services in Wuhan, Hubei Province, combined with the results of field visits, this paper combs and analyzes the common problems faced by smart elderly care and the new problems and opportunities brought by the epidemic. Put forward countermeasures and suggestions to solve the problems faced by smart elderly care, so as to enhance the suitability and availability of smart elderly care services, and finally achieve the purpose of improving the well-being of the elderly and sharing the fruits of social development with the elderly. © 2022 ACM.

Study on the mechanism of container port congestion under the epidemic

First, this paper analyzes the congestion of container ports at home and abroad under the current epidemic situation, then takes Yantian port of Shenzhen as the key research object to analyze the waiting time at anchorage and the stopping time at berth of the main container ports in China based on the data statistics. It studies the anchorage demand of ships with random and fluctuating arrival based on queuing theory. It gives the relationship between the stopping time of ship at berth and the maximum waiting time of the arriving ship, and reveals that the increase of ship stopping time and uneven arrival at the port are the main factors causing the current container port congestion, and puts forward some countermeasures to alleviate the port congestion. © 2022 SPIE

Analysis of liquidity, solvency and profitability levels of Ecuadorian technology companies: The case of app services before and after the pandemic

This paper analyzes the financial situation of Ecuadorian technology companies, particularly those that provide app services, and how they were affected by the Covid 19 pandemic. The primary goal was to analyze the technology industry's financial behavior in the years 2018, 2019 and 2020, particularly companies which provide app services, by applying financial ratios of liquidity, solvency and profitability.The current liquidity ratio and the acid test ratio were applied to measure liquidity levels;the debt to assets ratio, the equity ratio, the debt to fixed assets ratio, leverage and financial leverage ratios were used to measure solvency levels;and finally, the DUPONT model, based on the net profit margin, total asset turnover and leverage were applied to determine profitability.The methodology used for this paper is the quali - quantitative method with a descriptive approach through the documentary review method.Statistical sampling was used for the finite population, based on sources such as the Internal Revenue Service website and information from the Superintendence of companies, the sample size is 20 companies which enabled a comparative and analytical study.Results showed that there were changes in consumption in e - commerce due to new needs that consumers had to adapt to, in addition to a marked growth in the number of people using these apps. In conclusion, the technology industry grew in profitability in the face of the covid-19 pandemic during the first quarter of 2020. © 2022 IEEE.

Insights about Helpful Covid-19 Learning Resources from Caregivers of Elementary School Children

Media resources are a central component of children's learning ecologies in the U.S. However, much of the coverage of the Covid-19 pandemic came through channels for adult audiences, and the "infodemic” added to the difficulty of interpreting information from media sources. This paper analyzes learning resources collected in a diary study conducted with 109 families with elementary school aged children at the beginning of the Covid-19 pandemic. Findings show that the resources caregivers found useful in communicating with their children about the pandemic are intertwined with their life experiences and interpretation of their children's information needs. © ISLS.

A Study on the Development of an Online Book Publishing Funding Platform This paper analyzes further into the creation of an online platform to fund book publishing processes

The process of publishing printed books require initial capital investment from publishers, which limits the number of new book titles published in Indonesia. Additionally, publishers lack the funds to publish new titles due to the decline in book sales caused by the Covid-19 pandemic. This research aims to solve funding issues towards book publishing, which is allocated towards printing physical copies. A business analysis was conducted to analyze the feasibility of the business model of the proposed solution and the unique value proposition that is offered to the market. A prototype is also developed as a proof of concept to demonstrate how the proposed solution would take form. The prototype was demonstrated to interviewees to gain feedback for evaluation, which concludes that the proposed solution has promising value to be used by Indonesian publishers. © 2022 ACM.

How Citizens have Informed themselves about Covid-19 during the Pandemic

Fake news is defined as "false stories that appear to be news, spread on the Internet or using other media, usually created to influence political views or as a joke", thus, it is not necessary false information, although often refers to false information [1]. COVID-19 pandemic has accelerated the generation as well as consumption of fake news. Afraid of the unknown virus, people started to consume all possible information they found on internet, while various parties with specific opinions or ideas started to generate and circulate false information and fake news. Fake news have impacted even to the health of people [2]. The paper analyses the five on-line surveys conducted by the author and her research team between December 2020 and March 2022. There are differences among the answers, mostly due to the COVID-19 situation as well as the differences in government measures. From these surveys, it emerged that the personality strongly impacts one's perception as well as behaviour changes. The paper discusses about the findings from the surveys in comparison to the literature to identify the limitation and future research topics. © 2022 ACM.

Analysis of Emerging Technologies Proposed to Reduce the Impact of the COVID-19 Pandemic: A Review

The pandemic caused by COVID-19 has changed the way people live, forcing them to adopt measures to avoid transmission, so much so that countries have had to develop containment strategies because this virus continues to spread throughout the planet. It is important to define strategies that support physicians to prevent and improve the incidence of cases and thus avoid the collapse of health systems. The implementation of different technologies is convenient because it allows monitoring and prevention to be done more quickly. This paper analyzes emerging technologies such as mobile applications, devices (IoT) and artificial intelligence models as alternatives to traditional processes. © 2022 IEEE.

Analysis of the Textual Information Extracted from News Portals

The primary means of informing the population in modern society is through news portals. This paper analyses the characteristics and effects that such way of communication creates. The influence was studied in particular on an example of current global phenomenon 'vaccination' (hr. cijepljenje). The research method follows the CRISP-DM process adapted to the digitalized form of textual data. The analysed corpus, in the form of natural spoken language, was scraped from Croatian news portals. The subsequent processing extracts information from unstructured textual sources and provides valuable insights, like how much a particular topic is represented in the article. Modeling is based on the application of multiple text mining algorithms, like Words Cloud, Topic Modelling, Concordance and Sentiment Analysis. The implemented model produces indicators for objective information interpretation. The findings suggest that the portals associated the notion of vaccination with the COVID-19 pandemic. Furthermore, this term was often used in a political context. The words used and predominantly negative character of texts dealing with vaccination has led to the transmission of negative emotions to readers. A significant aspect of the study is the fact that it was conducted on the corpus of texts written in Croatian - a relatively small and morphologically complex language. © 2022 University of Split, FESB.

The design and research of cargo seat cover for transport of cargo in passenger aircraft cabin under the COVID-19 pandemic

This paper analyses the current situation of passenger aircraft cabin cargo and the measures taken by airlines under the COVID-19 pandemic crisis. An innovative product cargo seat cover for flexible passenger-to-cargo conversion is proposed in response to potential problems, and product styling, material composition, design philosophy, cost and application value are researched. The aim of paper is to meet the changing requirements and challenges under the COVID-19 pandemic by exploring new models and innovative products for aircraft passenger-to-cargo conversion, and bring more possibilities to the aviation industry by breaking the inherent passenger-to-cargo mindset. © 2022 SPIE.

UNIVERSITY STUDENTS GRADING BEFORE AND DURING COVID-19 CRISIS

The paper analyses the grades assigned by the professors of the University of Milan to their students at the end of written exams, comparing what happened in academic year 2018-19 and in academic year 2020-21, i.e., before and during the crisis caused by the Covid-19 pandemic. In March 2020, the lockdown closed the classrooms, stopping face-to-face interactions among professors and students: it became then necessary to identify possible scenarios for carrying on written exams online, suitably monitoring student behaviors, and to propose them to the University professors. Main purpose of the analysis reported in this paper is a preliminary evaluation of the effectiveness of these scenarios, through comparison of the grades the professors assigned to their students. © Proceedings of the International Conference on E-Learning 2022, EL 2022 - Part of the Multi Conference on Computer Science and Information Systems 2022, MCCSIS 2022. All rights reserved.

CovRelex: A COVID-19 Retrieval System with Relation Extraction

This paper presents CovRelex, a scientific paper retrieval system targeting entities and relations via relation extraction on COVID-19 scientific papers. This work aims at building a system supporting users efficiently in acquiring knowledge across a huge number of COVID-19 scientific papers published rapidly. Our system can be accessed via https://www.jaist.ac.jp/is/labs/ nguyen-lab/systems/covrelex/.

Tips, Tidings, and Tech: Governmental Communication on Facebook during the COVID-19 Pandemic

The COVID-19 pandemic led governments to rely on the versatility of social media to communicate with their citizens. This paper analyzes the Facebook communication of political leaders and health departments from 17 countries during the COVID-19 pandemic. We evaluate the citizen's response under the frameworks of media richness and user engagement. We note that governments and leaders communicate primarily through richer media (photos and videos), despite a negative correlation between media richness and user engagement. Plain-Text messages posted by country leaders attract the most engagement, while their COVID-19 communication tends to generate lower engagement. On the other hand, health departments' pages experienced a sharp increase in engagement around COVID-19 communication as citizens sought information during the pandemic. Finally, topical analysis shows that Discussions and Co-Use of COVID-19 with other topics can boost citizens' engagement. Our comparative analysis shows practical implications for social media users and social media designers. Our findings can help governments and organizations design effective social media communication during crises. © 2022 ACM.