Dissertations / Theses: 'Pandemic Data'

1

Wang, Xinlei. "Electricity-Consumption Data Reveals the Economic Impact and Industry Recovery during the Pandemic." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29233.

Full text

Abstract:

Coping with the outbreak of Coronavirus disease 2019 (COVID-19), many countries have implemented public-health measures and movement restrictions to prevent the spread of the virus. However, the strict mobility control also brought about production stagnation and market disruption, resulting in a severe worldwide economic crisis. Quantifying the economic stagnation and predicting post-pandemic recovery are imperative issues. Besides, it is significant to examine how the impact of COVID-19 on economic activities varied with industries. As a reflection of enterprises' production output, high-frequency electricity-consumption data is an intuitive and effective tool for evaluating the economic impact of COVID-19 on different industries. In the thesis, we quantify and compare economic impacts on the electricity consumption of different industries in eastern China. In order to address this problem, we conduct causal analysis using a difference-in-difference (DID) estimation model to analyze the effects of multi-phase public-health measures. Our model employs the electricity-consumption data ranging from 2019 to 2020 of 96 counties in the Eastern China region, which covers three main economic sectors and their 53 sub-sectors. The results indicate that electricity demand of all industries (other than the information transfer industry) rebounded after the initial shock, and is back to pre-pandemic trends after easing the control measures at the end of May 2020. Emergency response, the combination of all countermeasures to COVID-19 in a certain period, affected all industries, and the higher level of emergency response with stricter movement control resulted in a greater decrease in electricity consumption and production. The pandemic outbreak has a negative-lag effect on industries, and there is greater resilience in industries that are less dependent on human mobility for economic production and activities.

APA, Harvard, Vancouver, ISO, and other styles

2

Long, Zijian. "Towards a Tweet Analysis System to Study Human Needs During COVID-19 Pandemic." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41210.

Full text

Abstract:

Governments and municipalities need to understand their citizens’ psychological needs in critical times and dangerous situations. COVID-19 brings lots of challenges to deal with. We propose NeedFull, an interactive and scalable tweet analysis platform, to help governments and municipalities to understand residents’ real psychological needs during those periods. The platform mainly consists of four parts: data collection module, data storage module, data analysis module and data visualization module. The whole process of how data flows in the system is illustrated as follows: Our crawlers in the data collection module gather raw data from a popular social network website Twitter. Then the data is fed into our human need detection model in the data analysis module before stored into the database. When a user enters a query through the user interface, they will get all the related items in the database by the index system of the data storage module and a comprehensive human needs analysis of these items is then presented and depicted in the data visualization module. We employed the proposed platform to investigate the reaction of people in four big regions including New York, Ottawa, Toronto and Montreal to the ongoing worldwide COVID-19 pandemic by collecting tweets posted during this period. The results show that the most pronounced human need in these tweets is relatedness with 51.32%, followed by autonomy with 22.56% and competence with 18.82%. And the percentages of tweets expressing frustration are larger than those of tweets expressing satisfaction for each psychological need in general.

APA, Harvard, Vancouver, ISO, and other styles

3

Vicente, Tomás Ferreira Martins Pereira. "The impact of Covid-19 on transaction data in Portugal." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/20705.

Full text

Abstract:

Mestrado em Finanças Esta dissertação analisa o impacto da pandemia COVID-19 em dados regionais de transações em Portugal. Mais especificamente, o impacto regional é ponderado, assim como o impacto em diversas características dos municípios. Os dados usados são provenientes do INE, PORDATA e DGS e consideramos características económicas, demográficas e sociais em 278 concelhos de Portugal continental de 2015 a 2020. O método OLS de regressão é usado para efetuar a analise estatística. Estudos anteriormente realizados sugerem um aumento das transações antes da pandemia, como forma de açambarcar, mas também sugerem que o consumo iria diminuir durante o período subsequente à declaração do estado de emergência. Neste estudo analisamos três modelos distintos para compreender os três canais de transações: Levantamentos em ATM, pagamentos usando cartão português e pagamentos usando cartão estrangeiro. Testamos estes três modelos de forma a compreender os efeitos regionais causados pelo COVID-19. Observamos que as regiões com maior número de pacientes infetados com COVID-19 têm um impacto negativo em todos os canais de transação e que os meses de verão fazem aumentar valor de transações dos três canais considerados. Controlamos também diversas outras características regionais como a demográficas, económicas e sociais. This dissertation aims to analyze the impact of COVID-19 on regional transaction data in Portugal. More specifically, the regional impact is assessed, as well as the impact on several characteristics of these counties. The data used is from INE, PORDATA and DGS and we consider economic, demographic and social characteristics in 278 counties in mainland Portugal from 2015 to 2020. An OLS regression method is used to perform the analytic analysis. Previous studies suggest an increase in transactions prior to the pandemic, as a stockpiling behavior, while also suggesting that the overall consumption drops in the months following the emergency state. In this study we analyze three different models to comprehend the three different transaction channels: Automated Teller Machine withdrawals, payments using Portuguese card and payments using foreign card. We use data from the counties in Portugal mainland in order to understand the regional effects caused by COVID-19. We found that regions with more COVID-19 infected people have a negative impact on all transactions and that summertime increases all three transaction channels in consideration. We also control for several other characteristics of each region like demographic, economic and social. info:eu-repo/semantics/publishedVersion

APA, Harvard, Vancouver, ISO, and other styles

4

Cinelli, Ester. "Syndemic : A design prototype of a dashboard to understand pandemics beyond epidemiology." Thesis, Malmö universitet, Institutionen för konst, kultur och kommunikation (K3), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43624.

Full text

Abstract:

This study wants to investigate how Interaction Design techniques can contribute to giving meaning to data visualization in a syndemic dashboard and to gain understanding from it. I am going to present to you a Syndemic Dashboard that has the goal of helping researchers to find trends, patterns and make predictions of the spread of Covid-19 in the Swedish context, collaborating with K3, IUR, DVMT, and the University of Oxford. In order to do this, I will first give an overview of what a dashboard is, dashboarding practices and interaction techniques, cognitive aspects involved to generate meaning, and relevant theories to gain understanding from Big Data. Consequently, I will explain the process and the methodologies applied to achieve the final result. The thesis ends with a discussion about the final result and proposes future investigations.

APA, Harvard, Vancouver, ISO, and other styles

5

Davis, Carisa Renee. "Pandemic Vibrio parahaemolyticus: Defining Strains Using Molecular Typing and a Growth Advantage at Lower Temperatures." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002531.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Mansiaux, Yohann. "Analyse d'un grand jeu de données en épidémiologie : problématiques et perspectives méthodologiques." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066272/document.

Full text

Abstract:

L'augmentation de la taille des jeux de données est une problématique croissante en épidémiologie. La cohorte CoPanFlu-France (1450 sujets), proposant une étude du risque d'infection par la grippe H1N1pdm comme une combinaison de facteurs très divers en est un exemple. Les méthodes statistiques usuelles (e.g. les régressions) pour explorer des associations sont limitées dans ce contexte. Nous comparons l'apport de méthodes exploratoires data-driven à celui de méthodes hypothesis-driven.Une première approche data-driven a été utilisée, évaluant la capacité à détecter des facteurs de l'infection de deux méthodes de data mining, les forêts aléatoires et les arbres de régression boostés, de la méthodologie " régressions univariées/régression multivariée" et de la régression logistique LASSO, effectuant une sélection des variables importantes. Une approche par simulation a permis d'évaluer les taux de vrais et de faux positifs de ces méthodes. Nous avons ensuite réalisé une étude causale hypothesis-driven du risque d'infection, avec un modèle d'équations structurelles (SEM) à variables latentes, pour étudier des facteurs très divers, leur impact relatif sur l'infection ainsi que leurs relations éventuelles. Cette thèse montre la nécessité de considérer de nouvelles approches statistiques pour l'analyse des grands jeux de données en épidémiologie. Le data mining et le LASSO sont des alternatives crédibles aux outils conventionnels pour la recherche d'associations. Les SEM permettent l'intégration de variables décrivant différentes dimensions et la modélisation explicite de leurs relations, et sont dès lors d'un intérêt majeur dans une étude multidisciplinaire comme CoPanFlu The increasing size of datasets is a growing issue in epidemiology. The CoPanFlu-France cohort(1450 subjects), intended to study H1N1 pandemic influenza infection risk as a combination of biolo-gical, environmental, socio-demographic and behavioral factors, and in which hundreds of covariatesare collected for each patient, is a good example. The statistical methods usually employed to exploreassociations have many limits in this context. We compare the contribution of data-driven exploratorymethods, assuming the absence of a priori hypotheses, to hypothesis-driven methods, requiring thedevelopment of preliminary hypotheses.Firstly a data-driven study is presented, assessing the ability to detect influenza infection determi-nants of two data mining methods, the random forests (RF) and the boosted regression trees (BRT), ofthe conventional logistic regression framework (Univariate Followed by Multivariate Logistic Regres-sion - UFMLR) and of the Least Absolute Shrinkage and Selection Operator (LASSO), with penaltyin multivariate logistic regression to achieve a sparse selection of covariates. A simulation approachwas used to estimate the True (TPR) and False (FPR) Positive Rates associated with these methods.Between three and twenty-four determinants of infection were identified, the pre-epidemic antibodytiter being the unique covariate selected with all methods. The mean TPR were the highest for RF(85%) and BRT (80%), followed by the LASSO (up to 78%), while the UFMLR methodology wasinefficient (below 50%). A slight increase of alpha risk (mean FPR up to 9%) was observed for logisticregression-based models, LASSO included, while the mean FPR was 4% for the data-mining methods.Secondly, we propose a hypothesis-driven causal analysis of the infection risk, with a structural-equation model (SEM). We exploited the SEM specificity of modeling latent variables to study verydiverse factors, their relative impact on the infection, as well as their eventual relationships. Only thelatent variables describing host susceptibility (modeled by the pre-epidemic antibody titer) and com-pliance with preventive behaviors were directly associated with infection. The behavioral factors des-cribing risk perception and preventive measures perception positively influenced compliance with pre-ventive behaviors. The intensity (number and duration) of social contacts was not associated with theinfection.This thesis shows the necessity of considering novel statistical approaches for the analysis of largedatasets in epidemiology. Data mining and LASSO are credible alternatives to the tools generally usedto explore associations with a high number of variables. SEM allows the integration of variables des-cribing diverse dimensions and the explicit modeling of their relationships ; these models are thereforeof major interest in a multidisciplinary study as CoPanFlu

APA, Harvard, Vancouver, ISO, and other styles

7

Widing, Härje. "Business analytics tools for data collection and analysis of COVID-19." Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176514.

Full text

Abstract:

The pandemic that struck the entire world 2020 caused by the SARS-CoV-2 (COVID-19) virus, will have an enormous interest for statistical and economical analytics for a long time. While the pandemic of 2020 is not the first that struck the entire world, it is the first pandemic in history where the data were gathered to this extent. Most countries have collected and shared its numbers of cases, tests and deaths related to the COVID-19 virus using different storage methods and different data types. Gaining quality data from the COVID-19 pandemic is a problem most countries had during the pandemic, since it is constantly changing not only for the current situation but also because past values have been altered when additional information has surfaced. The importance of having the latest data available for government officials to make an informed decision, leads to the usage of Business Intelligence tools and techniques for data gathering and aggregation being one way of solving the problem. One of the mostly used software to perform Business Intelligence is the Microsoft develop Power BI, designed to be a powerful visualizing and analysing tool, that could gather all data related to the COVID-19 pandemic into one application. The pandemic caused not only millions of deaths, but it also caused one of the largest drops on the stock market since the Great Recession of 2007. To determine if the deaths or other reasons directly caused the drop, the study modelled the volatility from index funds using Generalized Autoregressive Conditional Heteroscedasticity. One question often asked when talking of the COVID-19 virus, is how deadly the virus is. Analysing the effect the pandemic had on the mortality rate is one way of determining how the pandemic not only affected the mortality rate but also how deadly the virus is. The analysis of the mortality rate was preformed using Seasonal Artificial Neural Network. Forecasting deaths from the pandemic using the Seasonal Artificial Neural Network on the COVID-19 daily deaths data.

APA, Harvard, Vancouver, ISO, and other styles

8

Alencar, Medeiros Gabriel Henrique. "ΡreDiViD Τοwards the Ρredictiοn οf the Disseminatiοn οf Viral Disease cοntagiοn in a pandemic setting". Electronic Thesis or Diss., Normandie, 2025. http://www.theses.fr/2025NORMR005.

Full text

Abstract:

Les systèmes de surveillance basés sur les événements (EBS) sont essentiels pour détecter et suivre les phénomènes de santé émergents tels que les épidémies et crises sanitaires. Cependant, ils souffrent de limitations, notamment une forte dépendance à l’expertise humaine, des difficultés à traiter des données textuelles hétérogènes et une prise en compte insuffisante des dynamiques spatio-temporelles. Pour pallier ces limites, nous proposons une approche hybride combinant des méthodologies guidées par les connaissances et les données, ancrée dans l’ontologie des phénomènes de propagation (PropaPhen) et le cadre Description-Detection-Prediction Framework (DDPF), afin d’améliorer la description, la détection et la prédiction des phénomènes de propagation. PropaPhen est une ontologie FAIR conçue pour modéliser la propagation spatio-temporelle des phénomènes et a été spécialisée pour le biomédical grâce à l’intégration de UMLS et World-KG, menant à la création du graphe BioPropaPhenKG. Le cadre DDPF repose sur trois modules : la description, générant des ontologies spécifiques ; la détection, appliquant des techniques d'extraction de relations sur des textes hétérogènes ; et la prédiction, utilisant des méthodes avancées de clustering. Expérimenté sur des données du COVID-19 et de la variole du singe et validé avec les données de l’OMS, DDPF a démontré son efficacité dans la détection et la prédiction de clusters spatio-temporels. Son architecture modulaire assure son évolutivité et son adaptabilité à divers domaines, ouvrant des perspectives en santé publique, environnement et phénomènes sociaux Event-Based Surveillance (EBS) systems are essential for detecting and tracking emerging health phenomena such as epidemics and public health crises. However, they face limitations, including strong dependence on human expertise, challenges processing heterogeneous textual data, and insufficient consideration of spatiotemporal dynamics. To overcome these issues, we propose a hybrid approach combining knowledge-driven and data-driven methodologies, anchored in the Propagation Phenomena Ontology (PropaPhen) and the Description-Detection-Prediction Framework (DDPF), to enhance the description, detection, and prediction of propagation phenomena. PropaPhen is a FAIR ontology designed to model the spatiotemporal spread of phenomena. It has been specialized in the biomedical domain through the integration of UMLS and World-KG, leading to the creation of the BioPropaPhenKG knowledge graph. The DDPF framework consists of three modules: description, which generates domain-specific ontologies; detection, which applies relation extraction techniques to heterogeneous textual sources; and prediction, which uses advanced clustering methods. Tested on COVID-19 and Monkeypox datasets and validated against WHO data, DDPF demonstrated its effectiveness in detecting and predicting spatiotemporal clusters. Its modular architecture ensures scalability and adaptability to various domains, opening perspectives in public health, environmental monitoring, and social phenomena

APA, Harvard, Vancouver, ISO, and other styles

9

Bäckström, Pernilla. "Covid-19 pandemins konsekvenser av mäns våld mot kvinnor i nära relationer : data från 9 länder." Thesis, Högskolan i Skövde, Institutionen för hälsovetenskaper, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19812.

Full text

Abstract:

Introduktion: Mäns våld mot kvinnor är ett globalt folkhälsoproblem och ett brott mot mänskliga rättigheter. Under 2020-2021, påverkas hela världen av covid-19-pandemin, med restriktioner som hemkarantän och arbeta hemifrån har detta även resulterat i en social isolering, minskat socialt stödsystem samt ökat våld mot kvinnor. Vilket i sin tur innebär att situationen för våldsutsatta kvinnor riskerar att förvärras. Av de kvinnor som utsätts för våldsbrott, inträffar tre av fyra incidenter i kvinnans egen bostad. Detta innebär att för en kvinna är det hennes egna hem som i statistiken är den farligaste platsen för henne att befinna sig. Syfte: Studiens syfte är att belysa covid-19-pandemins konsekvenser av mäns våld mot kvinnor i nära relationer. Metod: En systematisk litteraturstudie med en tematisk analys baserad på tio vetenskapliga originalartiklar. Resultat: Samtliga artiklar rapporterade psykiskt våld som den formen av våldshandling som både ökat och nyttjades mest av män i våld mot kvinnor, men mycket tyder på att mörkertalet för mäns våld mot kvinnor i nära relationer i samband med covid-19 är globalt mycket större än vad som framkommit i dessa studier. Slutsats: Den aktuella studiens resultat fann ett begränsat stöd för sambandet mellan hypoteser i förhållandet mellan olika samhällsåtgärder under covid-19-pandemin och vissa socioekonomiska faktorer, på mäns våld mot kvinnor. När de socioekonomiska faktorerna påverkades av en pandemi samtidigt som den ekonomiska stressen uppkom, ökade mäns våld mot kvinnor. Psykiskt våld var den formen som rapporterades både ökat och användes mest av män i utövandet av våld mot kvinnor under covid-19-pandemin. Introduction: Men's violence against women is a global public health problem and a violation of human rights. In 2020-2021, the entire world is affected by the covid-19-pandemic. Restrictions such as home quarantine and working from home have resulted in social isolation, reduced social support, and increased violence against women. This indicates that the situation for abused women is in danger of deteriorating. Of women who are victims of violence, three of four incidents occur in the woman's own home. This means that for a woman, her own home is the most dangerous place for her to be. Aim: This analysis aims to clarify the covid-19-pandemic's consequences of men's violence against women in intimate relationships. Methods: A systematic review with a thematic analysis based on ten scientific original articles. Results: All articles reported psychological violence as the form of violence that increased and was used the most by men in violence against women. Data indicate that the magnitude of men's violence against women in connection with covid-19 is globally large. Conclusion: The results of the current study found limited support for the hypotheses in the relationship between different society restrictions in connections with the covid-19-pandemic and socio-economic factors on men's violence against women. When the socio-economic factors were affected by the pandemic and at the same time experienced economic stress, men's violence against women increased. Psychological violence was the form of violence that was, reported to be used the most by men in their violence against women during the covid-19-pandemic

APA, Harvard, Vancouver, ISO, and other styles

10

Gustafsson, Johan, and Petter Wallgren. "Utilizing modern technology topromote tourism and reducephysical contact." Thesis, KTH, Hälsoinformatik och logistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296412.

Full text

Abstract:

Tourism is an important factor for economic growth. Unfortunately, the ongoingCOVID-19 pandemic has struck hard on the tourism sector due to the lockdowns andtravel restrictions. The lockdowns have also led to an increasing isolation amongpeople which in the long term can lead to a decline in people’s psychological wellbeing.Together with Cybercom Group AB, an idea to solve this problem was to developan application with the intention to nurture the tourism sector and get peopleout of their homes while keeping the human interactions at a satisfactory level. The main feature of the application developed was a scheduler that carefully plannedout people’s daily activities depending how crowded a specific location was. An applicationsuch as the one developed could lead to an increase in foot traffic whilesimultaneously decreasing the amount of physical contact between people. The result of this thesis mainly focuses on the developed application but more specificallythe developed algorithms to schedule your day using crowd data. The algorithmdeveloped, the Optimal Time Slot Algorithm, averaged a crowding value of18,8% while the average of the best possible crowding value was 17,8%. Turism är en viktig faktor för ekonomisk tillväxt. Tyvärr så har den pågående COVID-19 pandemin slagit hårt mot turismsektorn till följd av nedstängningar och restriktionerpå resande. Nedstängningarna har även lett till en ökad isolering hos personersom långsiktigt kan leda till en försämring av människors psykologiska välmående.Tillsammans med Cybercom Group AB växte en idé fram om att utveckla enapplikation som har till uppgift att främja turismsektorn och hjälpa folk att ta sig utur sina hem samtidigt som de undviker trängsel. Huvudfunktionen hos den utvecklade applikationen var en planerare som noggrantplanerar en persons dagliga aktiviteter beroende på hur mycket folk det var på denspecifika platsen vid ett visst tillfälle. En applikation likt den som utvecklats kan ledatill en ökad mängd personer i rörelse i kombination med att minska mängden fysiskkontakt mellan människor. Resultatet av detta examensarbete fokuserar huvudsakligen på den utvecklade applikationenoch specifikt de algoritmer som utvecklats för att planera din dag genomträngseldata. Den framtagna algoritmen, Optimal Time Slot Algorithm, resulteradei ett trängselsnitt på 17,8% där 18,8% var snittet av det bästa möjliga resultatet.

APA, Harvard, Vancouver, ISO, and other styles

11

Gustafsson, Johan, and Petter Wallgren. "Utilizing modern technology to promote tourism and reduce physical contact." Thesis, KTH, Hälsoinformatik och logistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296412.

Full text

Abstract:

Tourism is an important factor for economic growth. Unfortunately, the on going COVID-19 pandemic has struck hard on the tourism sector due to the lockdowns and travel restrictions. The lockdowns have also led to an increasing isolation among people which in the long term can lead to a decline in people’s psychological wellbeing.Together with Cybercom Group AB, an idea to solve this problem was to developan application with the intention to nurture the tourism sector and get people out of their homes while keeping the human interactions at a satisfactory level. The main feature of the application developed was a scheduler that carefully planned out people’s daily activities depending how crowded a specific location was. An application such as the one developed could lead to an increase in foot traffic while simultaneously decreasing the amount of physical contact between people. The result of this thesis mainly focuses on the developed application but more specifically the developed algorithms to schedule your day using crowd data. The algorithmdeveloped, the Optimal Time Slot Algorithm, averaged a crowding value of18,8% while the average of the best possible crowding value was 17,8%. Turism är en viktig faktor för ekonomisk tillväxt. Tyvärr så har den pågående COVID-19 pandemin slagit hårt mot turismsektorn till följd av nedstängningar och restriktionerpå resande. Nedstängningarna har även lett till en ökad isolering hos personersom långsiktigt kan leda till en försämring av människors psykologiska välmående.Tillsammans med Cybercom Group AB växte en idé fram om att utveckla enapplikation som har till uppgift att främja turismsektorn och hjälpa folk att ta sig utur sina hem samtidigt som de undviker trängsel. Huvudfunktionen hos den utvecklade applikationen var en planerare som noggrantplanerar en persons dagliga aktiviteter beroende på hur mycket folk det var på denspecifika platsen vid ett visst tillfälle. En applikation likt den som utvecklats kan ledatill en ökad mängd personer i rörelse i kombination med att minska mängden fysiskkontakt mellan människor. Resultatet av detta examensarbete fokuserar huvudsakligen på den utvecklade applikationenoch specifikt de algoritmer som utvecklats för att planera din dag genomträngseldata. Den framtagna algoritmen, Optimal Time Slot Algorithm, resulteradei ett trängselsnitt på 17,8% där 18,8% var snittet av det bästa möjliga resultatet.

APA, Harvard, Vancouver, ISO, and other styles

12

Riminucci, Stefania. "COVID-19,Open data e data visualization:interazione con dati epidemiologici." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21577/.

Full text

Abstract:

L’obiettivo di questa tesi è quello di analizzare l’efficacia di diverse strategie di data visualization utilizzate per presentare open data in forma grafica alla popolazione. Come caso di studio, si è presa in considerazione la pandemia di COVID-19, e le molteplici visualizzazioni che sfruttano gli open data messi a disposizione dalle comunità scientifiche, offrendo informazioni sull'evoluzione dei contagi a livello nazionale e internazionale. Per valutare l’efficacia delle diverse visualizzazioni, è stato sviluppato e proposto al pubblico un questionario per la raccolta di dati per avere una percezione di quali siano i livelli di comprensione ed utilizzo di varie tipologie di grafici e dashboard messi a disposizione dalle diverse piattaforme online. Il questionario prevedeva sia proposte di grafici da valutare che azioni richieste agli utenti per la ricerca di informazioni su piattaforme esterne. 99 utenti hanno risposto al questionario. Analizzando i dati raccolti è emerso che i risultati relativi ai grafici proposti non hanno mostrato una netta predominanza di alcuna delle proposte presentate, fornendo solamente qualche indicazione relativamente alla preferenza di istogrammi e cartogrammi rispetto ad altre tipologie di grafici. Allo stesso modo, l’analisi sui dati relativi alla facilità di reperire le informazioni sulle diverse piattaforme esterne non ha restituito risultati rilevanti, enfatizzando l’impatto della componente soggettiva e del background della singola persona.

APA, Harvard, Vancouver, ISO, and other styles

13

Ahmed, Wasim. "Using Twitter data to provide qualitative insights into pandemics and epidemics." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/20367/.

Full text

Abstract:

Background: One area of public health research specialises in examining public views and opinions surrounding infectious disease outbreaks. Although interviews and surveys are valid sources of this information, views and opinions are necessarily generated by the context, rather than spontaneous. As such, social media has increasingly been viewed as legitimate source of pragmatic, unfiltered public opinion. Objectives: This research attempts to better understand how users converse about infectious disease outbreaks on the social media platform Twitter. The study was undertaken in order to address a gap in knowledge because previous empirical studies that have analysed infectious disease outbreaks on Twitter have focused on employing quantitative methods as the primary form of data analysis. After analysing individual cases on Ebola, Zika, and swine flu, the study performs an important comparison in the types of discussions taking place on Twitter and is the first empirical study to do so. Methods: A number of pilot studies were initially designed and conducted in order to help inform the main study. The study then manually labels tweets on infectious disease outbreaks assisted by the qualitative analysis programme NVivo, and performs an analysis using the Health Belief Model, concepts around information theory, and a number of sociological principles. The data were purposively sampled according to when Google Trends Data showed a heightened interest in the respective outbreaks, and a case study approach was utilised. Results: A substantial number of themes were uncovered which were not reported in previous literature, demonstrating the potential of qualitative methodologies for extracting greater insight into public health opinions from Twitter data. The study noted several limitations of Twitter data for use in qualitative research. However, results demonstrated the potential of Twitter to identify discussions around infectious diseases that might not emerge in an interview and/or which might not be included in a survey.

APA, Harvard, Vancouver, ISO, and other styles

14

Teurneau, Birger, and Edvin Mlivić. "Programmering På Distans: En Studie Kring Påtvingad Distansundervisning Under En Rådande Pandemi." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43474.

Full text

Abstract:

Den akuta situationen med Covid-19 har haft en global påverkan på utbildning. Vid studiens tidpunkt hade pandemin pågått i drygt ett år och normala förhållanden var inte inom synhåll. Författarna av denna uppsats har själva genomgått en radikal förändring och har känt behovet av att undersöka kring ämnet programmering vid distansundervisning. För att sätta ljus på de positiva aspekterna och hitta möjligheter för vidareutveckling, vill författarna förmedla det som varit bra respektive mindre bra. Uppsatsen genomsyras av en tematisk analys efter ett antal genomförda kvalitativa intervjuer. Studien har huvudsakligen sökt efter berättelser, upplevelser och känslor som studenter och lärare på programmet Informationsarkitekt vid Malmö Universitet delar med sig. Trots att studieresultaten inte påvisade någon märkbar skillnad i förhållande till föregående år, verkar pandemin ha haft en stor inverkan på många områden. Lärarna upplevde att klyftan mellan högpresterande och lågpresterande studenter blivit större. Detta tros delvis bero på att de lågpresterande studenterna drar sig för att be om hjälp, trots att de är i behov av det. Samtidigt tycks de högpresterande studenterna blivit duktigare på att söka information på egen hand. The emergent situation regarding Covid-19 has had an effect on education globally. At the time of this study, the pandemic had been going on for about a year. The usual everyday life was nowhere to be seen. The authors of this paper have experienced the radical changes and felt the need to investigate the remote education of programming. To shed some light on the positive outcomes and to find possibilities for further improvements, the authors want to relay the successful and unsuccessful aspects. The paper contains a thorough thematic analysis of the conducted qualitative interviews. In the study, stories, experiences and feelings from the students and teachers from the information architect programme at Malmö University have been the main part of the data collected. Though the grades didn’t show any noticeable differences in comparison to the last few years, the pandemic seems to have had a major impact in many areas. The teachers have witnessed an increasing gap between high performing students and low performing students. It is believed that this may be caused by the low performing students' tendency not to seek help when they need it the most. While the high performing students seem to have gotten better at searching for information by themself.

APA, Harvard, Vancouver, ISO, and other styles

15

Mattiussi, Vlad. "Una Rassegna di Dataset e Applicazioni Innovative di Intelligenza Artificiale per Affrontare la Pandemia da COVID19." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21844/.

Full text

Abstract:

Il machine learning e la computer vision hanno avuto rilevanti sviluppi negli ultimi anni, compiendo progressi in molti settori. L’IA ha contribuito ad affrontare la pandemia di coronavirus (COVID-19). La scienza e la tecnologia hanno contribuito in modo significativo all’attuazione di queste politiche in questo caotico periodo senza precedenti. Ad esempio, i robot vengono utilizzati negli ospedali per fornire cibo e medicine ai pazienti con coronavirus o i droni vengono utilizzati per disinfettare strade e spazi pubblici I ricercatori di informatica, d’altra parte, sono riusciti a rilevare precocemente i pazienti infettivi utilizzando tecniche in grado di elaborare e comprendere i dati di imaging medico come immagini a raggi X e scansioni di tomografia computerizzata (CT). Tutte queste tecniche computazionali fanno parte dell’intelligenza artificiale, che è stata applicata con successo in vari campi.

APA, Harvard, Vancouver, ISO, and other styles

16

Huamán, Diaz Nora Ivon. "Propuesta de una plataforma virtual para el registro de nacimiento en el Reniec y la eficiencia en la data en el contexto de la pandemia en Lima Metropolitana 2020." Master's thesis, Universidad Nacional Mayor de San Marcos, 2021. https://hdl.handle.net/20.500.12672/17463.

Full text

Abstract:

El Reniec es una institución pública que tiene como misión según su portal de transparencia (2020) el “registrar la identidad, los hechos vitales y los cambios de estado civil de las personas. Participar del sistema electoral y promover el uso de la identificación y certificación digital, con inclusión social y enfoque intercultural” (p. s/n). En ese contexto se hace necesario hoy, en las actuales circunstancias que nos encontramos debido a la Pandemia una plataforma virtual que haga posible el registro de nacimiento. El objetivo del estudio es proponer una plataforma virtual para registrar los nacimientos y su relación con la eficiencia de la data en la coyuntura sanitaria. El tipo de investigación es aplicada y su diseño corresponde al no experimental con un enfoque cuantitativo. La muestra seleccionada la conformaron 35 profesionales en tecnología que de alguna manera se encuentran involucrados con la gestión en el Reniec. En cuanto a la técnica fue la encuesta que se tomó a través de un cuestionario con las preguntas basadas en los indicadores y subindicadores. Para la corroboración de la hipótesis se trabajó con la correlación de Spearman que arrojó como resultado un valor de 0.57.

APA, Harvard, Vancouver, ISO, and other styles

17

Leite, Beatriz Costa Gomes. "Proteção de Dados e Privacidade em Linha." Master's thesis, 2021. http://hdl.handle.net/10316/98822.

Full text

Abstract:

Dissertação de Mestrado em Ciências Jurídico-Forenses apresentada à Faculdade de Direito A presente dissertação versa sobre a Proteção de Dados e Privacidade em Linha (online), a qual tem vindo a ser fortemente discutida, atendendo aos consideráveis avanços tecnológicos ocorridos desde o século XX, cada vez mais incisivos a partir do século XXI, mas também, mais recentemente devido à Pandemia provocada pelo Covid-19, durante a qual foram adotadas várias medidas que careciam de acesso e tratamento a dados pessoais.Para tanto, o presente trabalho foi dividido em três capítulos, nos quais se pretende realizar uma abordagem gradual do tema, facilitando assim a sua melhor compreensão.O primeiro Capítulo, é dedicado à Privacidade e a Proteção de Dados, ou seja, a Privacidade (direito sobre a reserva da intimidade da vida privada) como fonte primária, mas distinta da Proteção de Dados. A origem da Privacidade e a sua Proteção a nível supranacional, europeu e nacional. O Direito de Proteção de Dados e respetiva evolução (nos Estados Unidos da América e Europa). E, por último, as Fontes de Direito de Proteção de Dados (tanto na Europa como em Portugal). O segundo Capítulo, aborda o Regulamento Geral de Proteção de Dados, os seus conceitos básicos, princípios, âmbito de aplicação material e territorial, os direitos dos titulares de proteção de dados, o responsável pelo tratamento, a autoridade de controlo e a lei de execução. Por fim, o terceiro capítulo, discorre acerca do Direito à Proteção de dados em tempos de pandemia, mais concretamente, sobre até que ponto podem ser limitados os direitos de proteção dos dados pessoais aos seus titulares com fundamento na crise de saúde pública e, no seu combate através as aplicações de “contact tracing”, mais especificamente, a StayAway Covid-19. The present dissertation deals with Online Data Protection and Privacy, which has been strongly discussed, given the considerable technological advances that have occurred since the 20th century, increasingly more incisive as of the 21st century, but also, more recently due to the Pandemic caused by Covid-19, during which several measures were adopted that required access and processing of personal data.To this end, the present work has been divided into three chapters, in which a gradual approach to the subject is intended, thus facilitating its better understanding.The first Chapter, is dedicated to Privacy and Data Protection, that is, Privacy (right over the privacy of private life) as a primary source, but distinct from Data Protection. The origin of Privacy and its Protection at the supranational, European and national levels. The Data Protection Law and its evolution (in the United States and Europe). And finally, the Sources of Data Protection Law (both in Europe and in Portugal). The second chapter discusses the General Data Protection Regulation, its basic concepts, principles, material and territorial scope of application, the rights of data subjects, the data controller, the supervisory authority and the enforcement law. Finally, the third chapter discusses the Right to Data Protection in times of pandemics, more specifically, to what extent can the rights of personal data protection of data subjects be limited based on the public health crisis and its combat through contact tracing applications, more specifically, StayAway Covid-19.

APA, Harvard, Vancouver, ISO, and other styles

18

Lannes, Leonardo Motta Perazzo. "Unsupervised Learning Applied to the Segmentation of Users of Online Gambling Platforms in Portugal - The effects of the Covid-19 Pandemic on User Behavior and Segmentation." Master's thesis, 2022. http://hdl.handle.net/10362/135874.

Full text

Abstract:

Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science Online gambling has become an increasingly relevant activity in the last years and is now available through a wide variety of technologies and platforms. This can be seen as an important addition to the entertainment industry since it has the potential of generating great economic impacts. The phenomenon, however, is not free of concerns considering that, like in any other type of gambling activities, online gamblers are susceptible to developing behavioral addiction. This has become a reason of concern to many governmental bodies around the world which are studying this issue due to its social impacts on the population. In this context machine learning algorithms can be applied to understand the behavior of online gamblers and to identify the characteristics of gambling addiction. This work project has the objective of segmentizing users of online gambling platforms in Portugal according to the tendency of these users to have compulsive gambling behavior. It also intends to evaluate the impacts of the Covid-19 pandemic on online gambling addiction by analyzing changes in user segmentation during the initial periods of the pandemic. This will be done by applying unsupervised learning algorithms, specifically K-Means and Self-Organizing Maps and by comparing user clusters from the years 2019 and 2020.

APA, Harvard, Vancouver, ISO, and other styles

19

Pereira, João Filipe Peixoto. "Can we sense shift in consumer behaviour in Portuguese retail companies due to the pandemic?" Master's thesis, 2021. http://hdl.handle.net/10071/24150.

Full text

Abstract:

The 2019 coronavirus pandemic (COVID-19) has effects in the most diverse fields of our society, from mental health and lifestyle to commerce and education. A huge adaptation by the population and restructuring of habits was necessary to make progress in this new reality, leading several companies to reinvent the way they conducted their businesses and a complete metamorphosis of their business plans. As such, there was an interest in conducting this research to understand how consumer behaviour in Portuguese retail companies was affected by the lockdown in the country, aiming to identify the change in the purchase intention of consumers living in Portugal and what motivated this same change, allowing extracting information to help organizations in the decision making. Thus, 15,000 comments were collected from the social network Facebook referring to the pre-lockdown, lockdown, and post-lockdown period in Portugal. Then, data mining techniques and processes were used to clean the set of collected data and extract knowledge. Furthermore, an Intention Mining analysis was carried out to assess the collected comments and draw conclusions. Finally, the results of this study indicate a negative evolution in the purchase intention of consumers, verifying that the relationship with the company deteriorated and problems in the supply chain increased, indicating that it is necessary to redirect strategies to improve the service of customer support and distribution channels to meet customer satisfaction and may apply to other countries in similar contexts. A pandemia do coronavírus 2019 (COVID-19) tem efeitos nos mais diversos campos da sociedade, desde a saúde mental e estilo de vida, ao comércio e educação. Foi necessária uma enorme adaptação da população e reestruturação de hábitos para conseguir avançar nesta nova realidade, levando várias empresas a reinventar a forma como conduziam os seus negócios e a uma completa metamorfose dos respetivos planos de negócio. Como tal, surgiu o interesse em realizar esta investigação para compreender como o comportamento do consumidor nas empresas de retalho portuguesas foi afetado pelo confinamento no país, tendo como objetivo identificar a mudança na intenção de compra dos consumidores a viver em Portugal e o que motivou essa mesma mudança, permitindo extrair informações que permitam auxiliar na tomada de decisão das organizações. Assim, recolheram-se 15,000 comentários da rede social Facebook referentes ao período pré-confinamento, confinamento e pós-confinamento em Portugal. Em seguida, foram utilizados técnicas e processos de mineração de dados para limpeza do conjunto de dados recolhidos e extração de conhecimento. Ainda, realizou-se uma análise de mineração de intenções para avaliar os comentários recolhidos e extrair conclusões. Por fim, os resultados deste estudo indicam uma evolução negativa na intenção de compra dos consumidores, verificando-se que a relação com a empresa deteriorou-se e problemas ao nível da supply chain aumentaram, indicando ser necessário redirecionar as estratégias para melhorar o serviço de apoio ao cliente e os canais de distribuição para ir ao encontro da satisfação dos clientes, podendo ser aplicável a outros países em contextos semelhantes.

APA, Harvard, Vancouver, ISO, and other styles

20

Encantado, David Miguel Lobo. "Adding Value Through Information Management." Master's thesis, 2022. http://hdl.handle.net/10362/134981.

Full text

Abstract:

Internship Report presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing Intelligence To ensure relevancy in today’s world, companies need to ensure that their focus is on the client and on every experience they provide. The objective of the internship was to be materialize this concept by updating and restructuring an annual report that is given to Médis Corporate clients. This report wasn’t adding any value to its readers, the clients. The objective was to trans-form simple data into knowledge, transforming what was a simple report into a source of knowledge, not only to the client but also to Médis, giving the company new tools to negoti-ate the insurance contracts. Effective changes were made, for example introducing the topic of Covid or even creating a set of clusters, having the possibility to apply them in many ways. Next steps for the project include the creation of a questionnaire to the clients as well as monitoring the level of satis-faction with the report for the next years.

APA, Harvard, Vancouver, ISO, and other styles

21

Ракуш, Віталій Володимирович, та Vitalii Rakush. "Огляд сучасних технологій у боротьбі з пандемією коронавірусу (COVID-19): штучний інтелект та великі дані". Bachelor's thesis, 2021. http://elartu.tntu.edu.ua/handle/lib/35796.

Full text

Abstract:

У кваліфікаційній роботі розглянуто огляд сучасних рішень у боротьбі з пандемією COVID-19. Огляду наукової літератури показав, що великі дані відіграють важливу роль у боротьбі з пандемією COVID-19 завдяки ряду перспективних застосувань, включаючи прогнозування спалахів, відстеження поширення вірусу, діагностику / лікування коронавірусів та виявлення вакцини / ліків. Використання Big Data дає змогу передбачити спалах у глобальному масштабі, використовуючи аналітичні інструменти для величезних наборів даних, зібраних із доступних джерел. Big Data підтримують процеси діагностики та лікування COVID-19. The qualification work reviews the current solutions in the fight against the COVID-19 pandemic. A review of the scientific literature has shown that big data play an important role in controlling the COVID-19 pandemic through a number of promising applications, including outbreak prediction, virus tracking, coronavirus diagnosis / treatment, and vaccine / drug detection. Using Big Data makes it possible to predict an outbreak globally, using analytical tools for huge data sets collected from available sources. Big Data supports the diagnosis and treatment of COVID-19. Вступ 1 Огляд публікацій по COVID-19 1.1 Пандемія COVID-19 1.2 Штучний інтелект 1.3 Великі дані 2 Застосування штучного інтелекту та великих даних при виявленні пандемії COVID-19 2.1 Застосування штучного інтелекту для боротьби з COVID-19 2.1.1 Штучний інтелект для виявлення та діагностики COVID-19 2.1.2 Визначення, відстеження та прогнозування спалаху 2.1.3 Штучний інтелект з питань інфодеміології та інформаційного спостереження 2.1.4 Штучний інтелект для біомедицини та фармакотерапії 2.2 Застосування великих даних для боротьби з covid-19 2.2.1 Прогноз спалаху 2.2.2 Відстеження поширення вірусів 2.2.3 Діагностика / лікування коронавірусу 2.2.4 Відкриття вакцини / ліків 2.3 Приклади структур на основі ші і великих даних для боротьби з covid-19 2.3.1 Рішення для виявлення та спостереження на основі смартфону 2.3.2 Штучний інтелект та великі дані для нейтралізації виявлення антитіл 2.4 Завдання, уроки та рекомендації 3 Безпека життєдіяльності, основи хорони праці 3.1 Вимоги і норми охорони праці приміщень де використовується комп’ютерна техніка 3.2 Класифікація надзвичайних ситуацій Висновки Список використаних джерел

APA, Harvard, Vancouver, ISO, and other styles

22

Martins, Raquel Sofia de Sousa. "Are stock markets asymptomatic to daily covid19 cases or deaths?: an empirical study based on twenty-four countries." Master's thesis, 2021. http://hdl.handle.net/10071/24730.

Full text

Abstract:

After battling the Severe Acute Respiratory Syndrome in 2002 and the Middle East Respiratory Syndrome in 2012, the world is witnessing its third severe coronavirus outbreak in less than two decades. The disease promptly progressed from a local outbreak to an international crisis event. COVID-19 pandemic is causing more human infections, deaths, and economic disruption while also negatively harming the stock market more than any other known disease. This work aims to understand the relationship between the announcement of daily COVID- 19 cases and its consequent deaths on stock market returns. With this in mind, the research uses daily coronavirus growth and daily stock market quotations data from twenty-four countries across five continents. To do so, we employ a panel data regression accounting for daily fixed- effects dummy variables and country-level control variables, with data from December 31, 2019, to December 31, 2020. Results uncover that stock markets were sensitive to casualties between December 31, 2019, to May 31, 2020. However, for the remaining time, there is no evidence of such impact. This seems to indicate that, even though the pandemic still haunts the world, the stock market regained balance as uncertainty faded. On the other hand, stock markets do not react to COVID- 19 fatalities. These findings can significantly interest policymakers, investment professionals, governments, and investors concerned with the pandemic implications on stock markets. Após a Síndrome Respiratória Aguda Grave em 2002 e a Síndrome Respiratória do Médio Oriente em 2012, o mundo assiste ao terceiro surto de coronavírus em menos de duas décadas. A doença, que de surto local evoluiu para pandemia mundial, originou um enorme leque de infeções e mortes, despoletou uma crise internacional única com devastadores consequências económicas e perturbou inquestionavelmente o mercado financeiro. A presente dissertação pretende compreender o eventual impacto existente entre os casos diários de COVID-19 (e as respetivas mortes) no mercado das ações. Para isso, aplicamos o método de dados em painel, utilizando o crescimento diário de casos e mortes e as cotações dos principais índices de mercado de vinte e quatro países de cinco continentes. O modelo conta com variáveis dummy de efeitos fixos diários e variáveis de controlo por país, com observações desde 31 de dezembro de 2019 a 31 de dezembro de 2020. Assim, verificámos que o mercado de ações reagiu negativamente ao aumento de casos entre 31 de dezembro de 2019 e 31 de maio de 2020. Contudo, para o restante tempo, não há evidência de tal impacto. Isto parece indicar que, embora a pandemia ainda assombre o mundo, o mercado de ações vai recuperando o equilíbrio à medida que a incerteza vai desaparecendo. Paradoxalmente, relativamente às mortes, o mercado não parece reagir. Esta conclusão pode revelar-se de grande interesse para os profissionais da banca de investimento, dos governos e investidores preocupados com as implicações da pandemia nos mercados financeiros.

APA, Harvard, Vancouver, ISO, and other styles

23

Marques, Carolina Maria Silva. "AS APLICAÇÕES MÓVEIS CRIADAS NO CONTEXTO DA PANDEMIA COVID-19: A Garantia do Direito à Liberdade e o Tratamento de Dados na Europa e nos Países Asiáticos." Master's thesis, 2021. http://hdl.handle.net/10316/98817.

Full text

Abstract:

Dissertação de Mestrado em Ciências Jurídico-Forenses apresentada à Faculdade de Direito A presente investigação intitulada "As Aplicações Móveis criadas no contexto da pandemia COVID-19: A Garantia do Direito à Liberdade e Tratamento de Dados na Europa e nos Países Asiáticos" visa contribuir para uma visão comparada do enquadramento jurídico das aplicações móveis criadas no contexto da pandemia Covid-19 (Doença por Coronavírus 2019) resultante da infeção causada pelo SARSCoV2 (Síndrome Respiratória Aguda-Grave – Coronavírus 2), na Europa e nos Países Asiáticos. Estas ferramentas que surgiram como uma novidade no combate à propagação de contágios baseados no uso das tecnologias para o rastreio de contactos (suprindo as insuficiências e deficiências do rastreio mediante contacto pessoal), não corresponderam às expetativas por terem sido consideradas, na sua maioria, como instrumentos potencialmente restritivos dos direitos, liberdades e garantias e por falta de incentivo e critérios concretos na sua utilização. Sabíamos que a Europa e os Países Asiáticos eram culturalmente diferentes (demográfica e territorialmente, na forma de viver e pensar), por isso, não nos surpreendeu inteiramente o sucesso que estas ferramentas granjearam na Ásia, nem que as sociedades europeias acabassem por rejeitar o seu uso, apenas procurámos as explicações para estes factos. Partimos da análise de todas as APPs existentes, procurámos compreender os critérios das aplicações móveis e os regimes de tratamento de dados pessoais nos diversos territórios, bem como a origem e a atualidade dos direitos fundamentais, em essencial da proteção da privacidade e da liberdade pessoais. É esta a estrutura em que assenta o nosso estudo e apresentamos à faculdade. This study - "New App Born in the Covid-19 context: The right to liberty guarantee and the Access to data in European and Asian Countries" - aims to contribute to a broader view of the legal framework of mobile applications created in the context of the Covid-19 pandemic (Coronavirus 2019 Disease) resulting from the infection caused by SARSCoV2 (Severe Respiratory Syndrome – Coronavirus 2) in Europe and Asian countries.These tools that emerged as a novelty in the fight against the spread of contamination based on the use of technologies for contact tracing (supplying the insufficiencies and deficiencies of the trace based on personal contact) did not meet expectations as most of them were considered potential instruments to restrict rights, freedoms and guarantees and for the lack of incentives and concrete criteria in their usage. We knew that Europe and Asian countries were culturally different (demographically and territorially, in the way people live and how they think), so it was not entirely surprising how successful these tools were in Asia, nor that European societies ended up rejecting their use. We just looked for explanations for these facts. We have started by analysing all existing APPs, we have sought to understand the criteria of mobile applications and the regimes for processing personal data in the different territories, as well as the origin and current status of fundamental rights, in particular the protection of privacy and personal freedom. This is the framework (structure) on which our study is based and which we present to the faculty.

APA, Harvard, Vancouver, ISO, and other styles

24

Квашнін, Дмитро Олександрович, та Dmytro Kvashnin. "Дослідження контрольованого машинного навчання для прогнозування зараження COVID-19 на основі епідеміологічних наборів даних". Bachelor's thesis, 2021. http://elartu.tntu.edu.ua/handle/lib/35713.

Full text

Abstract:

Кваліфікаційна робота присвячена дослідженню методів контрольованого машинного навчання котрі використовуються для прогнозування зараження COVID-19 на основі епідеміологічних наборів даних. Метою даної кваліфікаційної роботи освітнього рівня «Бакалавр» є підвищення рівня поінформованості громадян щодо інфікування COVID-19 шляхом аналітичного опрацювання епідеміологічних наборів даних з використанням методів контрольованого машинного навчання. В першому розділі кваліфікаційної роботи освітньоого рівня «Бакалавр» проаналізовано предметну область засобів та методів машинного навчання в контексті їх використання для опрацювання відомостей щодо COVID-19. Виконано аналіз літературних джерел. В другому розділі кваліфікаційної роботи проаналізовано матеріали та методи дослідження. Описано методи контрольованого машинного навчання. Подано аналіз коефіцієнта кореляції. Розглянуто прогнозні моделі щодо зараження COVID-19. Виконано аналіз дерева рішень. Та подано оцінювання результатів. The qualification work is devoted to the study of controlled machine learning methods used to predict COVID-19 infection based on epidemiological data sets. The purpose of this qualification work of the educational level "Bachelor" is to increase the level of awareness of citizens about the infection of COVID-19 by analytical processing of epidemiological data sets using the methods of controlled machine learning. The first section of the qualification work of the educational level "Bachelor" analyzes the subject area of tools and methods of machine learning in the context of their use for processing information on COVID-19. The analysis of literary sources is executed. In the second section of the qualification work the materials and research methods are analyzed. Methods of controlled machine learning are described. The analysis of the correlation coefficient is given. Predictive models for COVID-19 infection are considered. The analysis of the decision tree is performed. And an evaluation of the results is given. ВСТУП 7 1 ПРЕДМЕТНА ОБЛАСТЬ, ЛІТЕРАТУРНІ ДЖЕРЕЛА ТА НАБОРИ ДАНИХ 9 1.1 Аналіз предметної області 9 1.2 Аналіз літературних джерел 13 1.3 Підготовка та попередній аналіз структури наборів даних 16 1.4 Висновок до першого розділу 20 2 ДОСЛІДЖЕННЯ КОНТРОЛЬОВАНОГО МАШИННОГО НАВЧАННЯ ДЛЯ ПРОГНОЗУВАННЯ ЗАРАЖЕННЯ COVID-19 НА ОСНОВІ ЕПІДЕМІОЛОГІЧНИХ НАБОРІВ ДАНИХ 21 2.1 Матеріали і методи 21 2.2 Методи контрольованого машинного навчання 22 2.3 Аналіз коефіцієнта кореляції 25 2.4 Прогнозні моделі щодо зараження COVID-19 28 2.5 Аналіз дерева рішень 30 2.6 Оцінювання результатів 31 2.7 Висновок до другого розділу 34 3 БЕЗПЕКА ЖИТТЄДІЯЛЬНОСТІ, ОСНОВИ ХОРОНИ ПРАЦІ 35 3.1 Долікарська допомога при кровотечах 35 3.2 Допомога при теплових і сонячних ударах 36 3.3 Висновок до третього розділу 38 ВИСНОВКИ 39 ПЕРЕЛІК ДЖЕРЕЛ 40

APA, Harvard, Vancouver, ISO, and other styles

25

Carmo, Francisca Morais Moura do. "Pornografia em tempo de pandemia : um olhar sobre as experiências dasa mulheres portuguesas durante o distanciamento social." Master's thesis, 2021. http://hdl.handle.net/10400.12/8021.

Full text

Abstract:

Dissertação de Mestrado realizada sob a orientação do Prof. Doutor Csongor Juhos, apresentada no ISPA – Instituto Universitário para obtenção de grau de Mestre na especialidade de Psicologia Clínica. Foi observado um aumento na frequência de visualização de pornografia durante o distanciamento social que ocorreu como medida de contenção face à pandemia provocada pela COVID-19. São várias as possíveis causas para este aumento, no entanto, a literatura face ao tema é ainda escassa. Objectivo: Compreender e explorar as experiências das mulheres com pornografia durante o distanciamento social, dando ênfase aos sentimentos de solidão, aborrecimento e ansiedade, às alterações na frequência de relações sexuais e às alterações nas rotinas de trabalho e de estudo. Método: A amostra foi constituída por 197 mulheres com mais de 18 anos, que reportaram ter visto pornografia no último ano. Foi criado um questionário com base na literatura, que se dividiu em cinco secções: dados demográficos, dados relativos ao distanciamento social, hábitos sexuais e de visualização de pornografia antes e durante o distanciamento social, impacto do distanciamento social na visualização de pornografia e uma última secção que consistia numa questão aberta relativa às alterações na visualização de pornografia durante o distanciamento social. Resultados: Os resultados foram divididos em duas secções: análise estatística e análise temática (referente à questão aberta). Na análise estatística não foram observadas diferenças na frequência de visualização de pornografia antes e durante o distanciamento social. Especificamente não foram observadas diferenças na frequência de visualização em participantes que se sentiram mais sozinhas, mais aborrecidas, mais ansiosas, que tiveram relações sexuais com menos frequência durante o distanciamento social ou que trabalharam a partir de casa ou não trabalharam durante o distanciamento social. No entanto, várias participantes reportaram que o distanciamento social teve impacto na sua visualização de pornografia. No âmbito da análise temática foram identificados três temas: 1) Pornografia enquanto ferramenta, 2) Pornografia como prescindível e 3) Não há espaço para a pornografia. Our review of the literature seems to imply an increase in the frequency of pornography visualization during the social distancing that occurred has a measure for containing the pandemic caused by COVID-19. There are several possible causes for this increase but the literature on the subject is still scarce. Objective: Understand and explore the experiences of women with pornography during social distancing, emphasizing feelings of loneliness, boredom and anxiety, changes in the frequency of sexual intercourse, and changes in work and study routines. Method: The sample consisted of 197 women over 18, who reported seeing pornography in the last year. We created a questionnaire based on the literature, which was divided into five sections: demographic data, data relating to the period of social distancing, sexual habits and pornography viewing habits before and during social distancing, the impact of social distancing on pornography viewing, and one last section with an open question regarding the changes in viewing pornography during social distancing. Results: The results were divided into two sections: statistical analysis and thematic analysis (referring to the open question). In the statistical analysis, no differences were observed in the frequency of pornography viewing before and during social distancing. Specifically, no differences were observed regarding the frequency of visualization by participants who felt more alone, bored or anxious, who had sex less frequently or who worked from home or did not work during social distancing. However, several participants reported that social distancing had an impact on their pornography viewing. Within the thematic analysis, three themes were identified: 1) Pornography as a tool, 2) Pornography as dispensable, and 3) There is no space for pornography.

APA, Harvard, Vancouver, ISO, and other styles

26

Fernandes, Alexandra Marisa de Sousa Capelão Teixeira. "A importância do transporte de carga aérea em tempo de pandemia COVID-19 : estudo de caso da Emirates na rota LIS-DXB-LIS numa aplicação com a PLSR." Master's thesis, 2021. http://hdl.handle.net/10437/12082.

Full text

Abstract:

Orientação: José Manuel Ivo Carvalho Vicente ; co-orientação: Eliana Cristina Agostinho Mendes O transporte aéreo comercial é, atualmente, um setor essencial no desenvolvimento económico pois funciona como agente facilitador nas trocas comerciais e culturais entre países e representa cerca de 35% do comércio mundial (Comunicação da Comissão 2020/C 100 I/01). Em março de 2020, a Organização Mundial de Saúde anuncia o COVID-19 como pandemia, levando a que todos os países tomassem medidas rigorosas para conter o surto pandémico. As restrições foram aplicadas pelos países sem uniformidade de critérios, contudo, na indústria do transporte aéreo a decisão foi internacional e culminou com o encerramento dos aeroportos, resultando numa grave crise económica para a aviação civil. A presente investigação tem como objetivo demonstrar a importância estratégica do transporte da carga aérea em contexto de pandemia. Este estudo trata de analisar a forma como o COVID-19 influenciou o transporte de carga aérea, designadamente, na companhia aérea Emirates na rota Lisboa-Dubai-Lisboa. Para este efeito, estabeleceu-se uma relação entre as diferentes variáveis e o problema identificado, utilizando dados estatísticos trabalhados através dos Dados de Painel e do método de Regressão dos Mínimos Quadrados Parciais (PLSR), em virtude desta metodologia ter um algoritmo robusto e de minimizar os efeitos da multicolinearidade de amostras de reduzida dimensão como as analisadas no presente estudo. Em síntese, o cenário provocado pela pandemia COVID-19 teve um impacto negativo na indústria do transporte de carga aérea. No entanto, a Emirates ajustou a sua estratégia ao contexto pandémico com o transporte de frete na cabine de passageiros, mitigando as suas perdas durante a crise COVID-19. The commercial air transportation is currently an essential sector for the economic development as it enables commercial and cultural exchange between countries, and it represents about 35% of the world commerce (Comunicação da Comissão 2020/C 100 I/01). In March 2020, the World Health Organization announced COVID-19 as a pandemic, prompting all countries to adopt strict measures to contain the outbreak. The restrictions were applied by countries without uniformity of criteria, nevertheless, in the air transportation industry the decision was international and led to airports closure, resulting in a serious economic crisis for civil aviation. The following presentation aims to demonstrate the strategic importance of air freight transportation during a pandemic context. This study analyses the way COVID-19 has influenced Air Freight, namely in Emirates airline on the Lisbon-Dubai-Lisbon route. For this purpose, a relationship was established between the different variables and the identified issue, based on statistical data worked through the Panel Data and Partial Least Squares Regression method (PLSR), due to this methodology having a robust algorithm and minimizing multicollinearity effects in smaller samples as the ones presented in this study. In synthesis, the scenario caused by COVID-19 pandemic had a negative impact in air freight transport. However, Emirates has adjusted its strategy to the pandemic context with cargo transportation in the passenger cabin, mitigating their losses during COVID-19 crise.

APA, Harvard, Vancouver, ISO, and other styles

Dissertations / Theses on the topic 'Pandemic Data'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles