The cross-disciplinary Nordic Tweet Stream (NTS) is a project aiming at creating a multilingual text corpus consisting of tweets published in the five Nordic countries. The NTS linguists are explicitly interested in tweets having a text formulated by a human where each tweet is a personal statement, not in Tweets generated by bots and other programs or apps since they might skew the results. NTS consists of multiple parts and the part we are responsible for is a language-independent approach, using supervised machine learning, to classify every single tweet as auto-generated (AGT) or human-generated (HGT). The objective of this study is to increase data accuracy in sociolinguistic studies that utilize Twitter by reducing skewed sampling and inaccuracies in linguistic data. We define an AGT as a tweet where all or parts of the natural language content are generated automatically by a bot or other type of program. In other words, while AGT/HGT refers to an individual message, the term bot refers to nonpersonal and automated accounts that post content to online social networks. Our approach classifies a tweet using only metadata that comes with every tweet, and we utilize those metadata parameters that are both language and country independent. The empirical part shows that our results show poor success rates when it comes to unseen data. Using a bilingual training set of two languages tweets, we correctly classified only about 60-70% of all tweets in a test set using a third new language, which is still better than nothing, but probably not good enough to be used (as is) in a real-world scenario to identify AGTs in a given set of multilingual tweets.

En las últimas décadas, la utilización de las Tecnologías de la Información y la Comunicación (TIC) se ha extendido a diferentes ámbitos de nuestra sociedad. Entre dichos ámbitos nos encontramos con la educación. De manera general, las escuelas han ido incorporando diferentes herramientas tecnológicas con el objetivo de mejorar el proceso de enseñanza-aprendizaje del alumnado. Estas herramientas innovadoras mejoran no solo el aprendizaje, sino también la participación y la presencia del alumnado con Necesidades Específicas de Apoyo Educativo en los colegios ordinarios. Entre este grupo de alumnos y alumnas encontramos aquellos con Trastorno del Espectro Autista (TEA). Un trastorno del neurodesarrollo que afecta la capacidad de los individuos para comunicarse y desarrollar interacciones sociales, junto con la presencia de patrones restringidos y conductas, intereses y actividades repetitivas. Esta línea de diagnóstico trae consigo un grupo muy heterogéneo de individuos, para los cuales es muy complicado identificar un método concreto de aprendizaje. La utilización de las TIC ha añadido nuevas posibilidades para su intervención educativa. Entre estas herramientas tecnológicas ha experimentado un gran auge la robótica educativa la cual, gracias a su predictibilidad, su capacidad para actuar como soporte visual y secuenciar la presentación de la información se constituye como una herramienta ideal para la enseñanza de este alumnado. No obstante, el elevado coste de los robots, así como la falta de dispositivos, hace que la mayoría de las aplicaciones se desarrollen en un entorno clínico y no educativo. Ante este panorama, la presente investigación tiene por objetivo general evaluar la competencia en el área de comunicación e interacción social del alumnado con Trastorno del Espectro Autista (TEA) a partir de la aplicación en función de la utilización de la robótica. Para ello, se opta por un enfoque cuantitativo cuasi experimental con un diseño de dos grupos no equivalentes con pretest y postest y grupo control. Donde tanto los participantes del grupo control, quienes realizan las tareas sin utilizar la robótica, como los participantes del grupo experimental, quienes realizan las tareas con mediación del robot Bee-bot, son alumnos y alumnas con TEA. y grupo control. El procedimiento utilizado para la selección de la muestra fue el muestreo no probabilístico disponible entre las unidades específicas de Comunicación y Lenguaje de la ciudad de Alicante (UECil). Por otro lado, el instrumento utilizado fue el cuestionario diseñado adhoc CACIS-TEA y el análisis de datos se realizará con el paquete estadístico SPSS para Windows (Statistical Package for Social Sciences) en su versión 21. El análisis de datos se basa en pruebas no paramétricas. Los resultados indicaron variaciones en un mayor número de ítems del cuestionario para el alumnado del grupo experimental. Asimismo, también indican que alumnado del grupo experimental ha mejorado significativamente sus habilidades en el área de comunicación e interacción social tras el desarrollo del programa de intervención mediado por el robot Bee-Bot, respecto al alumnado del grupo control en el que se ha aplicado una metodología sin TIC. Y, por último, se observan diferencias significativas dentro del grupo experimental en función del tipo de comunicación, el género y el nivel actual de competencia (NAC). Como conclusión se puede afirmar que este la robótica posee potencialidades para el aprendizaje del alumnado con Trastorno del Espectro Autista.

Nowadays, botnet attacks that aim to overwhelm the network layer by malformed packets and other means are usually mitigated by hardware intrusion detection systems. Application layer botnet attacks, on the other hand, are still a problem. In case of web applications, these attacks contain legitimate traffic that needs to be processed. If enough bots partake in this attack, it can lead to inaccessibility of services provided and other problems, which in turn can lead to financial loss. In this thesis, we propose a detection and mitigation system that can detect botnet attacks in realtime using statistical approach. This system is divided into several modules that together cooperate on the detection and mitigation. These parts can be further expanded. During the testing phase, the system was able to capture approximately 60% of botnet attacks that often focused on spam, login attacks and also DDoS. The number of false positive addresses is below 5%.

Diplomová práce Hodnocení motorických dovedností dětí s OI Abstract The thesis deals with the assessment of motor skills and quality of life in children with osteogenesis imperfecta. The theoretical part summarizes aetiopathogenesis, clinical features, kinesiological abnormalities and the treatment strategies. A particular part describes therapeutic interventions during the various stages of childhood with an alignment to multidisciplinary cooperation. Furthermore, tests of motor skills and quality of life are presented. The practical part assesses the applicability of the BOT-2 for the evaluation of motor skills and PedsQL for the evaluation of the quality of life in children with OI. Moreover, the BOT-2 standardized test score evaluates and compares motor skills and quality of life in children with osteogenesis imperfecta to their peers. Contemporaneously, it investigates the effect of motor skills on the quality of life in children with OI. Based on the results the thesis confirms the hypothesis - worsened both gross motor skills and fine motor skills and the dependency of quality of life on the level of motor skills. The discussion part deals with the feasibility of BOT-2 and PedsQL for the assessment of children with OI, it comments the main limitations of children with OI, and based on up-to-date...

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Recently a new method for training generative neural networks called Generative Adversarial Networks (GAN) has shown great results in the computer vision domain and shown potential in other generative machine learning tasks as well. GAN training is an adversarial training method where two neural networks compete and attempt to outperform each other, and in the process they both learn. In this thesis the effectiveness of GAN training is tested on conversational agents also called chat bots. To test this, current state-of-the-art training methods such as Maximum Likelihood Estimation (MLE) models are compared with GAN method trained models. Model performance was measured by closeness of the model distribution from the target distribution after training. This thesis shows that the GAN method performs worse the MLE in some scenarios but can outperform MLE in some cases. / Nyligen har en ny metod för att träna generativa neurala nätverk kallad Generative Adversarial Networks (GAN) visat bra resultat inom datorseendedomänen och visat potential inom andra maskininlärningsområden också GAN-träning är en träningsmetod där två neurala nätverk tävlar och försöker överträffa varandra, och i processen lär sig båda. I detta examensarbete har effektiviteten av GAN-träning testats på konversationsagenter, som också kallas Chat bots. För att testa det här jämfördes modeller tränade med nuvarande state-of- the-art träningsmetoder, så som Maximum likelihood-metoden (ML), med GAN-tränade modeller. Modellernas prestation mättes genom distans från modelldistribution till måldistribution efter träning. Det här examensarbetet visar att GAN-metoden presterar sämre än ML-metoden i vissa scenarier men kan överträffa ML i vissa fall.

The technological revolution brought about by the Internet has affected numerous aspects of our everyday life, including the way we conceive and perform information and communication practices. In this sense, the Internet has drastically reduced the cost of data accessibility and data sharing, by increasing both the amount of information freely available for consultation and the speed at which it is possible to access and exchange it. Social Networking Platforms (SNPs) – such as Facebook, Twitter, and YouTube – are of particular interest in this sense, having become fully-fledged information environments themselves in the last decade, with an increasing number of individuals identifying such platforms as their main source for news, including political news. Given such an informative role, SNPs have attracted increasing attention regarding the proliferation of propaganda – definable as information that, though not necessarily fabricated, is specifically designed to rally public support and disparage opposing views rather than serve an informative purpose. Even though compelling evidence has revealed the widespread tendency of political actors to employ automated tools to propagate this kind of content on SNPs, scholars have also demonstrated how social media users themselves play a crucial role in this proliferation. Thus, understanding how individuals interact with and are affected by these information environments is of crucial importance to untangle the functioning of this political communication phenomenon. In particular, identifying the mechanisms underlying the evaluation of political propaganda has major relevance not only for the assessment of the persuasive power this communication practice exerts, but also for the development of countermeasures able to mitigate its impact on social media users’ deliberations. Therefore, the main aim of this doctoral research is to unravel the functioning of this multidimensional phenomenon by adopting a cognitive-sociological approach that draws on the Dual Process Model of Cognition when theoretically conceptualizing and empirically assessing the effectiveness of this communication practice. By addressing the specific cognitive mechanisms that regulate information processing, the goal is to assess whether reasoning style – and, in particular, heuristic thinking – affects judgments concerning the validity and shareability of political propaganda, thus enhancing its circulation. Given the goals of this project and the characteristics of the phenomenon under investigation, a mixed-methods approach encompassing computational social science techniques and experimental design has been adopted to explore the role played by reasoning in this kind of persuasion processes. The first set of methods has been employed to collect and analyze social media data on the 2019 European Parliament elections to assess the extent to which automation (i.e., political bots) and heuristic-based persuasion strategies have been employed consistently by political actors. Results indicate the presence of both factors among the political communication techniques deployed for this electoral event. Building on these findings, the second set of methods has been employed to design and implement a Discrete Choice Experiment (DCE). By means of this experimental technique – which is designed to elicit individual preferences in contexts where revealed preference data is unavailable – it was possible to assess how individuals interpret and respond to online propaganda messages and which factors affect this evaluation process. Two main factors have been explored in this sense, namely message features of online propaganda and the cognitive context in which information processing takes place. Specifically, this experimental assessment concerned six different informational cues (i.e., source, endorsement, popularity, emotional salience, stereotyping, and moral valence) and two different cognitive contexts (i.e., a “cognitive scarcity” and a “debiasing” one, in which heuristic thinking and analytic reasoning were prompted respectively). Findings highlighted that both message features and the cognitive context in which evaluation is performed affect the likelihood of considering political messages valid and shareable on SNPs. Moreover, they also indicate that individual characteristics ascribable to supra-individual, cultural factors (e.g., perception of diversity) moderate such an effect. Overall, this research project and its outputs contribute to the existing literature on online propaganda by exploring the mechanisms underlying the persuasion processes triggered by this political communication practice. By adopting a research approach that puts recipients at the center of the investigation without neglecting the social context they are part of, this work proposes a suitable way to investigate the functioning of online propaganda and, thus, assess its actual effectiveness.

Syftet med följande examensarbete är att undersöka teorier och få fram idéer om hur man kan bygga en bot som spelar poker. Ett viktigt ämne som studeras är artificiell intelligens och hur ett AI kan utvecklas hos en bot som ska ersätta en mänsklig pokerspelare spelandes i ett nätverk. Studien ger en inblick om spelregler för Texas Hold’em och går även in på teori om betydelsefull statistik, sannolikhet och odds. Resultatet av denna undersökning består av framtagna algoritmer som kan användas vid utveckling av en bot som spelar poker på ett bord med tio spelare. / The aim of the following thesis is to explore and develop ideas on how to build a bot that plays poker. An important topic that is studied is artificial intelligence and how an AI is implemented for a bot that replaces a human poker player playing in a network.The study provides insight of the playing rules for Texas Hold’em and theory of meaningful statistics, probability and odds will be used.The results of this study consist of algorithms that can be used in the development of a bot that plays poker on a table with ten players.

Introduktion: Attention Deficit (Hyperactivity) Disorder (AD(H)D/ ADD) och Autismspektrumstillstånd (AST) är livslånga tillstånd som ger påtagliga konsekvenser för individen. Förekomst av andra utvecklingsrelaterade tillstånd liksom fysisk och psykisk samsjuklighet är vanligt. Kunskapen om den motoriska förmågan hos vuxna med neuropsykiatriska tillstånd är begränsad. Syfte: Undersöka och beskriva den motoriska förmågan hos vuxna med ADHD, ADD och Autismspektrumstörning. Jämföra diagnosgrupperna och undersöka eventuella skillnader. Metod: I studien ingick 151 personer som diagnostiserats i vuxen ålder. Den motoriska förmågan undersöktes med Bruininks-Oseretsky Test of Motor Proficiency, BOT-2. BOT-2 är ett normbaserat, validerat testbatteri som utgörs av fyra motoriska områden uppdelat på åtta delområden, som ger en sammanlagd poäng. Datamaterialet har analyserats med One Way ANOVA, oberoende t-test, Kruskal- Wallis test och Mann Whitney U-test. Deskriptiva data jämfördes med normvärden i BOT-2. Resultat: Jämfört med normvärden i BOT-2 låg 56% av studiepopulationen på en genomsnittlig nivå, 39 % under genomsnittet och övriga väl under genomsnittet i totalpoäng. I området handmotorisk kontroll låg medelvärdet i alla tre grupper under det normerade medelvärdet. Gruppen med Autismspektrumtillstånd hade nedsättningar inom flest områden jämfört med normvärden I AST gruppen låg resultaten i balans och bilateral koordination signifikant lägre jämfört med grupperna ADHD och ADD. I finmotorisk kontroll presterade ADD gruppen signifikant högre än i ADHD gruppen. Konklusion: Nedsättningar i den motoriska förmågan förefaller vanligt hos vuxna med ADHD, ADD och Autismspektrumtillstånd, och särskilt hos dem med AST. Vid neuropsykiatriska utredningar av vuxna bör också den motoriska förmågan bedömas. Mer forskning om förekomsten och behandling av motoriska nedsättningar vid neuropsykiatriska tillstånd är angeläget. / Introduction: Attention Deficit (Hyperactivity) Disorder (ADHD/ADD) and Austim Spectrums Disorder (ASD) are lifelong conditions that often causes severe consequences for the individual. The co-existens of related neurodevelopmental disorders as well as mental and physical illness is common. Knowledge about motor performance in adults is limited. Aims: To explore och describe motor performance in adults diagnosed with ADHD, ADD och Austism Spectrum Disorder. To performe group comparisons and explore differences between groups. Methods: The population consisted of 151 inividuals diagnosed as adults. Motor abilities were examined using the Bruininks-Oseretsky Test of Motor Proficiency, second edition, a reference-based test of fine och gross motor skills. BOT-2 consits of eight subscales organized in four composits, and a total score. One Way ANOVA, independent t-test, Kruskal- Wallis test and Mann Whitney U statistic tests were used in the analysis. Descriptive data was analysed according to normbased data in  BOT-2. Resultat: In the population 56% perform within average and 39 % below average in Total Point score, compared to values in BOT-2. All groups performed below average in Manual Coordination. Most deficits appeared in the ASD group. The ASD group scored significantly lower in bilateral coordination and balance compared to the ADHD and ADD group. In Fine Motor Control the ADHD group performed significantly lower than the ADD group. Conclusion: Deficits in motor performance appears to be common in adults with the diagnosis ADHD, ADD och ASD, especially among individuals with ASD. When adults are clinically investigated, motor abilities should also be adressed. Further studies exploring motor abilities is recommended.

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