Distinguishing between information and disinformation is an ever growing issue. The dramatic structure of a conspiracy theory easily captures a large audience and with the advent of social media, this disinformation can spread at an ever growing rate. This is especially true with the infodemic following the Covid-19 pandemic in early 2020, where there was a drastic increase in Covid-19 related misinformation on social media. When misinformation replaces fact, some people will inevitably follow borderline dangerous advice. This could unfortunately be seen in the ivermection issue where people injected this substance in hope of preventing/curing a Covid-19 infection. This is why finding patterns in disinformation that distinguishes it from facts would allow us to take measures against the spread of conspiracy theories. We have found patterns in our dataset suggesting that there is a significant difference in the language patterns for terms relating to conspiracy theories, and non-conspiratorial terms. We find that the sentiment of conspiracy theories is very volatile when compared to that of non-conspiratorial terms which follow a more neutral pattern in terms of sentiment. Suggesting that the language usage in a post can be used as a factor when determining the credibility of its content. We also find that conspiracy theories tend to see a drastic increase in mentions when previously being relatively lowin mentions. The result of this thesis could therefore be used as a start for developing tools and processes which would seek to combat the spread of conspiracy theories and limit the potential harm that could come from them.

Alzheimer’s is one of the most costly illnesses that exists today and the number of people with alzheimers diease is expected to increase with 100 million until the year 2050. The medication that exists today is most effective if Alzheimer’s is detected during early stages since these medications do not cure Alzheimer’s but slows down the progression of the disease. Electroencephalography (EEG) is a relatively cheap method in comparison to for example Magnetic Resonance Imaging when it comes to diagnostic tools. However it is not clear how to deduce whether a patient has Alzheimer’s disease just from EEG data when the analyst is a human. This is the underlying motivation for our investigation; can supervised machine learning methods be used for pattern recognition using only the spectral power of EEG data to tell whether an individual has alzheimer’s disease or not? The output accuracy of the trained supervised machine learning models showed an average accuracy of above 80%. This indicates that there is a difference in the neural oscillations of the brain between healthy individuals and alzheimer’s disease patients which the machine learning methods are able to detect using pattern recognition. / Alzheimer är en av de mest kostsamma sjukdomar som existerar idag och antalet människor med alzheimer förväntas öka med omkring 100 miljoner människor tills 2050. Den medicinska hjälp som finns tillgänglig idag är som mest effektiv om man upptäcker Alzheimer i ett tidigt stadium eftersom dagens mediciner inte botar sjukdomen utan fungerar som bromsmedicin. Elektroencefalografi är en relativt billig metod för diagnostisering jämfört med Magnetisk resonanstomografi. Det är emellertid inte tydligt hur en läkare eller annan tränad individ ska tolka EEG datan för att kunna avgöra om det är en patient med alzheimers som de kollar på. Så den bakomliggande motivation till vår undersökning är; Kan man med hjälp av övervakad maskininlärning i kombination med spektral kraft från EEG datorn skapa modeller som kan avgöra om en patient har alzheimers eller inte. Medelvärdet av våra modellers noggrannhet var över 80%. Detta tyder på att det finns en faktiskt skillnad mellan hjärna signalerna hos en patient med alzheimer och en frisk individ, och att man med hjälp av maskininlärning kan hitta dessa skillnader som en människa enkelt missar.

This report documents the experimental study for four different three-dimensional turbulent flows. The investigation focuses on near wall measurements in these flows. Several experimental techniques are used in the studies; however, the bulk of the investigation focuses on a three-orthogonal-velocity-component fiber-optic laser Doppler anemometer (3D-LDA) system. The control volume of the 3D-LDA is on the order of 50 micro-meter in size, or a y⁺ distance of around 2.3 units (using average values of U_&#964 and ν from the experiment). An auxiliary small boundary layer wind tunnel (auxiliary tunnel) and a low speed linear compressor cascade wind tunnel (cascade tunnel) are utilized in this study. One of four flow experiments is done in the auxiliary tunnel the other three are in the cascade tunnel. The first three-dimensional turbulent flow is a vortical flow created by two half-delta wing vortex generators. Near wall secondary flow features are found. The second flow is an investigation of the first quarter chord tip gap flow in the cascade tunnel. Strong three-dimensional phenomena are found. The third flow investigated is the inflow to the compressor cascade with the moving wall. The experiment records shear layer interaction between the upstream flow and moving wall. Finally the fourth flow investigated is the inflow to the compressor cascade with the moving wall with half-delta wing vortex generators attached. Phase-averaged data reveal asymmetrical vortex structures just downstream of the vortex generators. This is the first time any near wall data has been taken on any of these flows. / Master of Science

Communication with customers is a major part of customer experience as well as a great source of data mining. More businesses are engaging with consumers via text messages. Before 2020, 39% of businesses already use some form of text messaging to communicate with their consumers. Many more were expected to adopt the technology after 2020[1]. Email response rates are merely 8%, compared to a response rate of 45% for text messaging[2]. A significant portion of this communication involves customer enquiries or support messages sent in both directions. According to estimates, more than 80% of today’s data is stored in an unstructured format (suchas text, image, audio, or video) [3], with a significant portion of it being stated in ambiguous natural language. When analyzing such data, qualitative data analysis techniques are usually employed. In order to facilitate the automated examination of huge corpora of textual material, researchers have turned to natural language processing techniques[4]. Under the light of shared statistics above, Billogram[5] has decided that support messages between creditors and recipients can be mined for predictive maintenance purposes, such as early identification of an outlier like a bug, defect, or wrongly built feature. As one sentence goal definition, Billogram is looking for an answer to ”why are people reaching out to begin with?” This thesis project discusses implementing unsupervised clustering of support messages by benefiting from natural language processing methods as well as performance metrics of results to answer Billogram’s question. The research also contains intent recognition of clustered messages in two different ways, one automatic and one semi-manual, the results have been discussed and compared. LDA and manual intent assignment approach of the first research has 100 topics and a 0.293 coherence score. On the other hand, the second approach produced 158 clusters with UMAP and HDBSCAN while intent recognition was automatic. Creating clusters will help identifying issues which can be subjects of increased focus, automation, or even down-prioritizing. Therefore, this research lands in the predictive maintenance[9] area. This study, which will get better over time with more iterations in the company, also contains the preliminary work for ”labeling” or ”describing”clusters and their intents.

In the traditional agenda-setting theory, the agenda-setters were the news media and the public has a minimal role in the process of agenda-setting, which makes the public a passive receiver located at the bottom in the top-down agenda-setting dynamics. This study claims that with the development of Information communication technologies, primarily social media, the networked public may be able to set their own agendas through connective actions, outside the influence of the news media agenda. There is little empirical research focused on development and dynamics of public agenda-setting through social media platforms. Understanding the development and dynamics of public agenda-setting may be key to accounting for and overcoming conflicting findings in previous reverse agenda-setting research. This study examined the public agenda-setting dynamics through a case of gun violence prevention activism Twitter network, the #MarchForOurLives Twitter network. This study determined that the agenda setters of the #MarchForOurLives Twitter network are the key Never Again MSD student leaders and the March For Our Lives. The weekly reflected important events and issues and the identified topics were highly co-related with the themes examined in the tweets created by the agenda setters. The amplifiers comprised the vast majority of the tweets. The advocates and the supporters consisted of 0.44% and 4.43% respectively. The tweets made by the agenda setters accounted for 0.03%. The young activists and the like-minded and participatory public could continuously make changes taking advantage of technologies, and they could be the hope in the current and future society.

Dans le present travail de recherche notre équipe s'est interessé à l'étude de la composition chimique -au niveau moléculaire- d'un groupe d'échantillons résineuses provenant d'objects Aztecs et Mayas. Le but ultime de cette étude a été d'établir l'origin botanique de ces résines et d'avoir une vue d'ensemble des formulations utilisées dans les adhésifs ou les figurines, afin de mieux comprendre leurs propriétes physiques.Pour aboutir à cet objectif une stratégie analytique très spécifique a été créeé et mise en oeuvre. Cette stratégie a inclus l'analyse d'échantillons des résines archéologiques mais aussi de résines d'origine botanique certifiée et de résines commerciales, achetées dans des marchés traditionels au Mexique dans une région qui correspond a la one géographique occupée autre fois par l'empire aztèque.L'étude des matériaux a fait appel à des techniques tels que l'observation a l'échelle microscopique, la spectroscopie infrarouge (IRTF), la chromatographie liquide-DAD (HPLC-UV/Vis) et la chromatographie en phase gazeuse couplée à la spéctroscopie de masse (CPG-SM).L'étude moléculaire de ces échantillons, et plus précisement, l'étude leur fraction tritérpenique a permis de : Établir un profil moléculaire des résines pour chaque origine botanique étudiée Idéntifier précisement certain composées tritérpeniques présents dans toutes les échantillons Réperer les molécules tritérpeniques susceptibles d'être utilisées dans l'avenir comme des marqueurs moléculaires d'origine botanique pour les résines frais des espèces étudiées Suggèrer une origine botanique pour les échantillons archéologiques Aztèques Écarter des origines botaniques possibles pour l'échantillon Maya Avoir une vue d'ensemble de l'origine botanique des résines commercialisées au territoire mexicain sous le nom de «copal» Créer un protocole d'analyse simple pour permettre aux professionnels de la conservation et des biomatériaux d'établir l'origine botanique et un profil moléculaire des résines utilisées dans des expériences diverses Caractériser le comportement du copal lors du vieillisement naturel et artificiel Établir des molécules susceptibles de devenir marqueurs moléculairs pour les deux types de vieillisement Établir que l'origine botanique d'un échantillon résineux peut être retrouvée malgré son âge (archéologique) / In the present work, the molecular composition of series of resinous aztec and maya archaeological samples were investigated to determinate their nature.Thus an analytical strategy was specifically designed. This analytical strategy included the analysis of botanically certified resins, freshly collected. It included as well the analysis of commercial samples bought in Mexican traditional markets.The study of all the samples included microscopical techniques, Fourier Inverse Infrared Spectrometry (FTIR) , High Performance Liquid Chromatography coupled to Ultraviolet-visible spectrometry (HPLC-UV/Vis) and Gas Chromatography coupled to Mass Spectrometry (GC-MS).The molecular study of these samples, in particular of their trterpenic composition allowed to : establish the molecular profile of resins from certified botanical origin. Identifiy some of the triterpenic compounds present in samples; Identify triterpenic molecules that could be uses as molecular markers for each botanical origin. Find the botanical origin of archeological astec samples. Discard possible botanic origins for maya archaeological sample. Have an overview of the origin of commercial samples of mexican copal. Create a simple protocol that allows conservation and biomaterials professionals to establish the botanical origin of archaeological and commercial resins, used in conservation interventions. Observe the behavior of copal materials upon ageing, establishing potential markers for natural ageing in copal, under darkness. Asses the botanical origin of a sample can be found regardless the age of the resin

Thema der vorliegenden Arbeit ist die Untersuchung ausgewählter niederdimensionaler Schichtgittersysteme, wobei das Hauptinteresse in der Erforschung der elektronischen Struktur im Zusammenhang mit Interkalationsexperimenten liegt. Einkristalline Graphit-, TiSe2- und TaSe2-Proben wurden vor und nach der Interkalation mit winkelaufgelöster Photoemission, Fermi- und Isoenergieflächenmessungen und Elektronenbeugung (LEED) analysiert. Als Interkalationsmaterialien wurden U, Eu, Gd und Cs verwendet. Die experimentellen Daten wurden mit Ergebnissen von LDA-LCAO-Bandstrukturrechnungen und Simulationen im Rahmen eines Single-Impurity-Anderson-Modells verglichen. Neben dem Einfluß unterschiedlicher Valenzelektronen der interkalierten Atome auf den Einlagerungsprozeß werden Fragen zum Lokalisierungsverhalten von 4f- und 5f-Zuständen und zu den Veränderungen in der Dimensionalität der Verbindungen durch die Einlagerung diskutiert. Ein weiterer Schwerpunkt dieser Arbeit befaßt sich mit Untersuchungen zur temperaturabhängigen Ausbildung von Ladungsdichtewellen in 1T-TaSe2. / Subject of the present thesis are investigations of selected low-dimensional layered lattice systems, with the principal goal to study the electronic structure in relation to intercalation experiments. Single-crystalline graphite-, TiSe2 - and TaSe2- samples were analyzed by angle-resolved photoemission, Fermi- and isoenergy-surface measurements, and low energy electron diffraction experiments before and after intercalation. U, Eu, Gd, and Cs were used as materials for the intercalation process. The experimental results were compared with theoretical LDA-LCAO band-structure calculations and with simulations in the framework of a single-impurity Anderson model. In addition to the influence of different numbers of valence electrons from intercalated atoms, questions concerning the localization of 4f and 5f states and changes in the dimensionality of the compounds due to the intercalation process are discussed. Investigations of the temperature dependent formation of charge density waves in 1T-TaSe2 complete this work.

Les recherches sur les instationnarités des Interactions Ondes de Choc Couches Limites (IOCCL) turbulentes ont permis une description détaillée de celles-ci tant expérimentalement que numériquement . Ceci a conduit à plusieurs schémas susceptibles d'expliquer les respirations à basses fréquences observées dans de tels écoulements. Les configurations avec des conditions amont laminaires ou transitionnelles ont été moins étudiées.Dans le cadre du programme Européen TFAST, un important effort a été mené afin de développer des dispositifs expérimentaux, conjointement à des simulations numériques, permettant une étude détaillée de ces configurations. Dans le cadre de cette thèse, on a mis en place une configuration de réflexion d'onde de choc sur une couche limite laminaire pour un nombre de Mach de 1.68. L'utilisation des métrologies classiques (Anémométrie Laser Doppler, Anémométrie Fil Chaud), adaptées à ces conditions expérimentales particulières, a permis de décrire les propriétés spatio-temporelles de ces écoulements. Le champ moyen a été caractérisé et comparé aux théories classique et aux résultats obtenus dans différentes souffleries.Un schéma décrivant le mécanisme de transition à la turbulence au sein de l'interaction a été développé. Sa sensibilité aux conditions amont a été étudiée en plaçant des perturbations en amont de l'interaction. Dans tous les cas, des instationnarités convectives (haute fréquence) et stationnaires (basse fréquence) ont été observées et comparées à celles existantes pour les configurations amont turbulentes. Une gamme intermédiaire d'instationnarités convectives (moyenne fréquence) a été mise en évidence et caractérisée. / Research dedicated to the study of the unsteadiness of turbulent Shock Wave Boundary Layer Interaction (SWBLI) has allowed a detailed description of this kind of interaction both experimentally and numerically. Several scenario were proposed to explain the low frequency unsteadiness observed in separated SWBLI. Nevertheless, the literature on this kind of flow involving either upstream laminar or transitional conditions is quite reduce. Within the framework of the European TFAST program, an important effort was made to develop experimental devices, in conjunction with numerical simulations, allowing a detailed study of these laminar or transitional configurations. In particular, within the framework of this thesis, a shock wave reflection configuration on a laminar boundary layer was set-up, with a nominal free stream Mach number of 1.68. Using classical metrology (Laser Doppler Anemometry, Hot WireAnemometry) that have been adapted to these particular experimental conditions, we have been able to describe the spatio-temporal properties of the interaction. The mean field has been characterized and compared with the classical theories and the results obtained in other configurations.A model describing the transition mechanisms to turbulence within the interaction has been developed. Its sensitivity to upstream conditions was studied by placing perturbations upstream of the interaction. In all cases, convective (high frequency) and stationary (low frequency) unsteadiness were observed and compared with those existing for upstream turbulent configurations. An intermediate range of convective unsteadiness (medium frequency) has been demonstrated and characterized.

Providing high quality of topics inference in today's large and dynamic corpora, such as Twitter, is a challenging task. This is especially challenging taking into account that the content in this environment contains short texts and many abbreviations. This project proposes an improvement of a popular online topics modelling algorithm for Latent Dirichlet Allocation (LDA), by incorporating supervision to make it suitable for Twitter context. This improvement is motivated by the need for a single algorithm that achieves both objectives: analyzing huge amounts of documents, including new documents arriving in a stream, and, at the same time, achieving high quality of topics’ detection in special case environments, such as Twitter. The proposed algorithm is a combination of an online algorithm for LDA and a supervised variant of LDA - labeled LDA. The performance and quality of the proposed algorithm is compared with these two algorithms. The results demonstrate that the proposed algorithm has shown better performance and quality when compared to the supervised variant of LDA, and it achieved better results in terms of quality in comparison to the online algorithm. These improvements make our algorithm an attractive option when applied to dynamic environments, like Twitter. An environment for analyzing and labelling data is designed to prepare the dataset before executing the experiments. Possible application areas for the proposed algorithm are tweets recommendation and trends detection. / Tillhandahålla högkvalitativa ämnen slutsats i dagens stora och dynamiska korpusar, såsom Twitter, är en utmanande uppgift. Detta är särskilt utmanande med tanke på att innehållet i den här miljön innehåller korta texter och många förkortningar. Projektet föreslår en förbättring med en populär online ämnen modellering algoritm för Latent Dirichlet Tilldelning (LDA), genom att införliva tillsyn för att göra den lämplig för Twitter sammanhang. Denna förbättring motiveras av behovet av en enda algoritm som uppnår båda målen: analysera stora mängder av dokument, inklusive nya dokument som anländer i en bäck, och samtidigt uppnå hög kvalitet på ämnen "upptäckt i speciella fall miljöer, till exempel som Twitter. Den föreslagna algoritmen är en kombination av en online-algoritm för LDA och en övervakad variant av LDA - Labeled LDA. Prestanda och kvalitet av den föreslagna algoritmen jämförs med dessa två algoritmer. Resultaten visar att den föreslagna algoritmen har visat bättre prestanda och kvalitet i jämförelse med den övervakade varianten av LDA, och det uppnådde bättre resultat i fråga om kvalitet i jämförelse med den online-algoritmen. Dessa förbättringar gör vår algoritm till ett attraktivt alternativ när de tillämpas på dynamiska miljöer, som Twitter. En miljö för att analysera och märkning uppgifter är utformad för att förbereda dataset innan du utför experimenten. Möjliga användningsområden för den föreslagna algoritmen är tweets rekommendation och trender upptäckt.

Thema der vorliegenden Arbeit ist die Untersuchung ausgewählter niederdimensionaler Schichtgittersysteme, wobei das Hauptinteresse in der Erforschung der elektronischen Struktur im Zusammenhang mit Interkalationsexperimenten liegt. Einkristalline Graphit-, TiSe2- und TaSe2-Proben wurden vor und nach der Interkalation mit winkelaufgelöster Photoemission, Fermi- und Isoenergieflächenmessungen und Elektronenbeugung (LEED) analysiert. Als Interkalationsmaterialien wurden U, Eu, Gd und Cs verwendet. Die experimentellen Daten wurden mit Ergebnissen von LDA-LCAO-Bandstrukturrechnungen und Simulationen im Rahmen eines Single-Impurity-Anderson-Modells verglichen. Neben dem Einfluß unterschiedlicher Valenzelektronen der interkalierten Atome auf den Einlagerungsprozeß werden Fragen zum Lokalisierungsverhalten von 4f- und 5f-Zuständen und zu den Veränderungen in der Dimensionalität der Verbindungen durch die Einlagerung diskutiert. Ein weiterer Schwerpunkt dieser Arbeit befaßt sich mit Untersuchungen zur temperaturabhängigen Ausbildung von Ladungsdichtewellen in 1T-TaSe2. / Subject of the present thesis are investigations of selected low-dimensional layered lattice systems, with the principal goal to study the electronic structure in relation to intercalation experiments. Single-crystalline graphite-, TiSe2 - and TaSe2- samples were analyzed by angle-resolved photoemission, Fermi- and isoenergy-surface measurements, and low energy electron diffraction experiments before and after intercalation. U, Eu, Gd, and Cs were used as materials for the intercalation process. The experimental results were compared with theoretical LDA-LCAO band-structure calculations and with simulations in the framework of a single-impurity Anderson model. In addition to the influence of different numbers of valence electrons from intercalated atoms, questions concerning the localization of 4f and 5f states and changes in the dimensionality of the compounds due to the intercalation process are discussed. Investigations of the temperature dependent formation of charge density waves in 1T-TaSe2 complete this work.