3-dimensional (3D) massive multiple-input-multiple-output (MIMO)/full dimensional (FD) MIMO and application of artificial intelligence are two main driving forces for next generation wireless systems. This dissertation focuses on aspects of channel estimation and precoding for 3D massive MIMO systems and application of deep reinforcement learning (DRL) for MIMO broadcast beam synthesis. To be specific, downlink (DL) precoding and power allocation strategies are identified for a time-division-duplex (TDD) multi-cell multi-user massive FD-MIMO network. Utilizing channel reciprocity, DL channel state information (CSI) feedback is eliminated and the DL multi-user MIMO precoding is linked to the uplink (UL) direction of arrival (DoA) estimation through estimation of signal parameters via rotational invariance technique (ESPRIT). Assuming non-orthogonal/non-ideal spreading sequences of the UL pilots, the performance of the UL DoA estimation is analytically characterized and the characterized DoA estimation error is incorporated into the corresponding DL precoding and power allocation strategy. Simulation results verify the accuracy of our analytical characterization of the DoA estimation and demonstrate that the introduced multi-user MIMO precoding and power allocation strategy outperforms existing zero-forcing based massive MIMO strategies. In 3D massive MIMO systems, especially in TDD mode, a base station (BS) relies on the uplink sounding signals from mobile stations to obtain the spatial information for downlink MIMO processing. Accordingly, multi-dimensional parameter estimation of MIMO channel becomes crucial for such systems to realize the predicted capacity gains. In this work, we also study the joint estimation of elevation and azimuth angles as well as the delay parameters for 3D massive MIMO orthogonal frequency division multiplexing (OFDM) systems under a parametric channel modeling. We introduce a matrix-based joint parameter estimation method, and analytically characterize its performance for massive MIMO OFDM systems. Results show that antenna array configuration at the BS plays a critical role in determining the underlying channel estimation performance, and the characterized MSEs match well with the simulated ones. Also, the joint parametric channel estimation outperforms the MMSEbased channel estimation in terms of the correlation between the estimated channel and the real channel. Beamforming in MIMO systems is one of the key technologies for modern wireless communication. Creating wide common beams are essential for enhancing the coverage of cellular network and for improving the broadcast operation for control signals. However, in order to maximize the coverage, patterns for broadcast beams need to be adapted based on the users' movement over time. In this dissertation, we present a MIMO broadcast beam optimization framework using deep reinforcement learning. Our proposed solution can autonomously and dynamically adapt the MIMO broadcast beam parameters based on user' distribution in the network. Extensive simulation results show that the introduced algorithm can achieve the optimal coverage, and converge to the oracle solution for both single cell and multiple cell environment and for both periodic and Markov mobility patterns. / Doctor of Philosophy / Multiple-input-multiple-output (MIMO) is a technology where a transmitter with multiple antennas communicates with one or multipe receivers having multiple antennas. 3- dimensional (3D) massive MIMO is a recently developed technology where a base station (BS) or cell tower with a large number of antennas placed in a two dimensional array communicates with hundreds of user terminals simultaneously. 3D massive MIMO/full dimensional (FD) MIMO and application of artificial intelligence are two main driving forces for next generation wireless systems. This dissertation focuses on aspects of channel estimation and precoding for 3D massive MIMO systems and application of deep reinforcement learning (DRL) for MIMO broadcast beam synthesis. To be specific, downlink (DL) precoding and power allocation strategies are identified for a time-division-duplex (TDD) multi-cell multi-user massive FD-MIMO network. Utilizing channel reciprocity, DL channel state information (CSI) feedback is eliminated and the DL multi-user MIMO precoding is linked to the uplink (UL) direction of arrival (DoA) estimation through estimation of signal parameters via rotational invariance technique (ESPRIT). Assuming non-orthogonal/non-ideal spreading sequences of the UL pilots, the performance of the UL DoA estimation is analytically characterized and the characterized DoA estimation error is incorporated into the corresponding DL precoding and power allocation strategy. Simulation results verify the accuracy of our analytical characterization of the DoA estimation and demonstrate that the introduced multi-user MIMO precoding and power allocation strategy outperforms existing zero-forcing based massive MIMO strategies. In 3D massive MIMO systems, especially in TDD mode, a BS relies on the uplink sounding signals from mobile stations to obtain the spatial information for downlink MIMO processing. Accordingly, multi-dimensional parameter estimation of MIMO channel becomes crucial for such systems to realize the predicted capacity gains. In this work, we also study the joint estimation of elevation and azimuth angles as well as the delay parameters for 3D massive MIMO orthogonal frequency division multiplexing (OFDM) systems under a parametric channel modeling. We introduce a matrix-based joint parameter estimation method, and analytically characterize its performance for massive MIMO OFDM systems. Results show that antenna array configuration at the BS plays a critical role in determining the underlying channel estimation performance, and the characterized MSEs match well with the simulated ones. Also, the joint parametric channel estimation outperforms the MMSE-based channel estimation in terms of the correlation between the estimated channel and the real channel. Beamforming in MIMO systems is one of the key technologies for modern wireless communication. Creating wide common beams are essential for enhancing the coverage of cellular network and for improving the broadcast operation for control signals. However, in order to maximize the coverage, patterns for broadcast beams need to be adapted based on the users' movement over time. In this dissertation, we present a MIMO broadcast beam optimization framework using deep reinforcement learning. Our proposed solution can autonomously and dynamically adapt the MIMO broadcast beam parameters based on user' distribution in the network. Extensive simulation results show that the introduced algorithm can achieve the optimal coverage, and converge to the oracle solution for both single cell and multiple cell environment and for both periodic and Markov mobility patterns.

This thesis examines the integration crisis that the City of Norfolk, Virginia underwent between 1954 and 1959 with an epilogue that carries Norfolk's desegregation story through to 1986. / Master of Arts

La première partie de cette thèse traite des théories de gravité massive. L'étude de ces théories a connu un regain d'intérêt depuis la découverte de l'accélération de l'expansion de l'univers, car elles pourraient expliquer cette dernière sans avoir à recourir à une constante cosmologique. La découverte, en 2010 d'une théorie cohérente de gravité massive, dite dRGT, a ouvert un vaste et prometteur champ d'investigation. Dans cette thèse nous déterminons, dans une formulation métrique et covariante, la linéarisation autour d'espace-temps arbitraires de ces théories, et de leur extension bimétrique. Ce travail nous permet ensuite de compter par une méthode lagrangienne le nombre de degrés de liberté qui se propagent. La seconde partie de cette thèse s'inscrit dans le cadre des ondes gravitationnelles en relativité générale et porte plus précisément sur la dynamique de systèmes binaires d'objets compacts. Ce travail est important dans la perspective de leur détection par les détecteurs interférométriques d'ondes gravitationnelles terrestres et spatial. Nous étudions le problème de la dynamique de systèmes binaires d¿objets compacts en relativité générale, à l¿aide de la méthode d'approximation dites des développements post-newtoniens (PN). Nous dérivons les équations du mouvement à l'ordre $4$PN en coordonnées harmoniques. Nous utilisons une méthode basée sur une action de Fokker adaptée au formalisme post-newtonien, en dérivant notamment les effets de sillage d'onde qui apparaissent à $4$PN. / The first part of this thesis deals with massive gravity theories. There has been a renewal of interest in these theories since the discovery of the acceleration of the expansion of the universe, because they could explain it without having to resort to a cosmological constant. The discovery in 2010 of a coherent theory of massive gravity, named dRGT, has opened a vast and promising field of investigation. In this thesis we determine, in a metric and covariant formulation, the linearization around arbitrary backgrounds of these theories and their bimetric extension. This result then allows us to count with a Lagrangian method the number of degrees of freedom that are propagating. The second part of this thesis concerns gravitational waves in general relativity and especially the dynamics of coalescing compact binary systems. This work is important in view of their detection by interferometric detectors, both terrestrial and spacial. We study the dynamics of compact binary systems in general relativity, using the approximation method based on post-Newtonian developments (PN). We derive the equations of motion to $4$ PN order in harmonic coordinates. We use a method based on a Fokker action adapted to the post-Newtonian formalism, in particular deriving the tail effects appearing at $4$PN.

Par la révolution du Cloud Computing et des Smartphones, une quantité énorme de données devrait traverser le réseau chaque seconde où la plupart de ces données sont fournies par des mobiles utilisant des services Internet. La croissance rapide de la bande passante et des demandes de QoS rend les réseaux mobiles du 4ème G insuffisants. Le système de prochaine génération doit avoir un taux de sommation de 100Mbps à 1Gbps par terminal utilisateur (UT), avec une densité de connexion supérieure à 1M connexion / Km2, la mobilité des véhicules à grande vitesse jusqu'à 500 km / h et une fin à la fin (E2E) retardent moins de 10 ms. Un candidat prometteur qui peut répondre à ces demandes est le système sans fil à multiples sorties multiples (MIMO) Multi-Cell Multi-Cell. Cependant, la capacité Massive MIMO est délimitée par l'Inter-cell Interference (ICI) en raison de la réutilisation du pilote et, par conséquent, de la contamination du pilote. Dans cette thèse, nous étudions la contamination du pilote de liaison montante dans le système de formation à la division temporelle (TDD) des réseaux sans fil MIMO massifs. En supposant un canal de décoloration, l'intervalle de cohérence sera temporairement limité, où l'estimation du canal, la réception des symboles et le précodage des symboles doivent être effectués dans le même intervalle. Cela dit, la longueur du pilote de formation est limitée. De même, le nombre de terminaux de l'utilisateur (UT) par zone d'interférence est également limité. Inspiré par la variation de la taille de l'intervalle de cohérence parmi les UT, cette recherche présente deux nouvelles contributions indépendantes pour faire face à la contamination pilote de liaison montante dans le MIMO massif. La première contribution répertorie la région de couverture de la cellule de base (BS) dans une carte d'information d'état de chaîne (CSI). Cette carte est créée et mise à jour à l'aide d'un algorithme spécial d'apprentissage machine, et elle est exploitée pour prédire UT CSI au lieu d'estimer ses canaux. Compte tenu de cela, la formation des pilotes aériens et de liaison montante est considérablement réduite. La deuxième contribution classe les UT en fonction de la taille de leur intervalle de cohérence de canal. En outre, nous appliquons une technique de changement de pilote pour déplacer des pilotes similaires vers différentes positions temporelles (qui sont considérées comme vides en raison de trames TDD pilotes vides). Les résultats de la simulation montrent une augmentation à l'échelle de la performance du MIMO massif, en particulier dans la performance de l'efficacité énergétique et spectrale, UT par cellule et taux d'addition. En particulier, la troisième contribution évolue le MIMO massif multi-cellulaire à une performance de cellule unique et même surmonté un simple énorme conventionnel dans l'efficacité énergétique et UT par cellule. / By the revolution of Cloud Computing and Smartphones, an enormous amount of data should traverse the network every second where most of this data are delivered by mobiles using internet services. The fast growth in bandwidth and QoS demands makes the 4th G mobile networks insufficient. The next generation system must afford a sum rate from 100Mbps up to 1Gbps per User Terminal (UT), with a connection density that exceeds 1M connection/Km2, the mobility of high-speed vehicles up to 500 km/hr and an End to End (E2E) delay less than 10ms. A promising candidate that can offer those demands is the Multi-User Multi-Cell Massive Multiple-Input Multiple-Output (MIMO) wireless system. However, Massive MIMO capacity is upper bounded by the Inter-cell Interference (ICI) due to pilot reuse and thus, pilot contamination. In this thesis, we investigate the uplink pilot contamination in Time Division Duplexing (TDD) training scheme of massive MIMO wireless networks. Assuming block-fading channel, the coherence interval will lag for a limited duration, where channel estimation, symbol reception, and symbol precoding must be done within the same interval. Having said that, the training pilot length is limited. Likewise, the number of User Terminal’s (UT’s) per interference region is also limited. Inspired by the variation of coherence interval size among UT’s, this research introduces two independent novel contributions to deal with uplink pilot contamination in massive MIMO. The first contribution maps the Base Station (BS) cell coverage region into a Channel State Information (CSI) Map. This map is created and updated using a special machine-learning algorithm, and it is exploited to predict UT CSI instead of estimating their channels. In view of this, training overhead and uplink pilots are reduced significantly. The second contribution classifies UT’s based on the size of their channel coherence interval. Furthermore, we apply a pilot shifting technique to shift similar pilots to different time position (that considered empty due to empty pilot TDD frames). Simulation results show a scaled increase in the performance of massive MIMO especially in the performance of energy and spectral efficiency, UT per cell and sum-rate. In particular, the third contribution evolves multi-cell massive MIMO to a single cell performance and even overcome single conventional huge in the energy efficiency and UT per cell.

Les disruptions du plasma sont des phénomènes se produisant dans les tokamaks et qui entraînent une perte totale du confinement du plasma et la fin de la décharge. Ces disruptions sont des phénomènes rapides et violents et peuvent endommager les murs du tokamak ainsi que sa structure si elles ne sont pas contrôlées. Un système de mitigation des disruptions est donc indispensable pour ITER afin de réduire les forces électromagnétiques, mitiger les charges thermiques et éviter les électrons runaways générés par les disruptions du plasma. Remplir tous ces objectifs fait du design de ce système une tâche difficile, pour laquelle un apport conséquent de l’expérience et de la modélisation est nécessaire. Nous présentons dans cette thèse des résultats de modélisation sur l’amortissement des disruptions par injection massive de gaz, qui est une des méthodes principales envisagées sur ITER pour le système de mitigation. Premièrement, un modèle issu des premiers principes pour décrire le transport des neutres dans un plasma est donné et est appliqué à l’étude de l’interaction entre l’injection massive de gaz et le plasma. Les principaux mécanismes en jeu sont décrits et étudiés. L’échange de charge entre les neutres et les ions du plasma est isolée comme jouant un rôle majeur dans cette dynamique. Ensuite, le code 3D de Magnétohydrodynamique non linéaire JOREK est appliqué à l’étude des disruptions déclenchées par injection massive de gaz. Un intérêt particulier est porté sur la phase de quench thermique et les phénomènes MHD qui le déclenchent. Les résultats obtenus avec ce code sont comparés avec les expériences effectuées sur le tokamak JET. / Plasma disruptions are events occuring in tokamaks which result in the total loss of the plasma confinement and the end of the discharge. These disruptions are rapid and violent events and they can damage the tokamak walls and its structure if they are not controlled. A Disruption Mitigation System (DMS) is thus mandatory in ITER in order to reduce electromagnetic forces, mitigate heat loads and avoid Runaway Electrons (RE) generated by plasma disruptions. These combined objectives make the design of the DMS a complex and challenging task, for which substantial input from both experiments and modeling is needed. We present here modeling results on disruption mitigation by Massive Gas Injection (MGI), which is one of the main methods considered for the DMS of ITER. First, a model which stems from first principles is given for the tranport of neutrals in a plasma and applied to the study of the interaction of the MGI with the plasma. Main mechanisms responsible for the penetration of the neutral gas are described and studied. Charge-exchange processes between the neutrals and the ions of the plasma is found to play a major role. Then, the 3D non linear MHD code JOREK is applied to the study of MGI-triggered disruptions with a particular focus on the thermal quench phase and the MHD events which are responsible for it. The simulation results are compared to experiments done on the JET tokamak.

Massive Open Online Courses (MOOCs) sind darauf ausgelegt, im tertiären Bildungsbereich den Wissenserwerb zu fördern, ohne dass die formalen Strukturen einer Ausbildungseinrichtung relevant sind. Dazu werden die Teilnehmer nicht persönlich von Dozenten betreut, sondern sind selbstgesteuert, oder werden durch kollaborative Lernmethoden aktiviert. Der Leistungszwang ist daher geringer, die Anzahl derjenigen, die Kurse abbrechen, jedoch ungleich höher. Durchschnittlich schließen maximal 10% der Teilnehmer ihren MOOC-Kurs ab.

Alors que les applications spatiales prennent une place de plus en plus cruciale dans nos vies, les coûts d'opération des satellites doivent être réduits. Ceci peut être obtenu par l'utilisation de systèmes de propulsion électriques, plus efficients que leurs homologues chimiques traditionnellement utilisés. Une des technologies de propulsion électrique la plus performante et la plus utilisée est le propulseur à effet Hall, toutefois ce système reste complexe et peu compris. En effet de nombreuses questions, concernant le transport anormal des électrons ou les interactions plasma/paroi, sont encore ouvertes.Les réponses à ces questions sont basées sur des mécanismes cinétiques et donc ne peuvent être résolues par des modèles fluides. De plus les caractéristiques géométriques et temporelles de ces mécanismes les rendent difficilement observables expérimentalement. Par conséquent nous avons, pour répondre à ces questions, développé un code cinétique bi-dimensionnel.Grâce à un modèle simplifié de propulseur à effet Hall, nous avons observé l'importance de l'instabilité de dérive électronique pour le transport anormal. Ensuite en utilisant un modèle réaliste de propulseur, nous avons pu étudier les effets des interactions plasma/paroi sur la décharge plasma. Nous avons également pu quantifier les effets intriqués des émissions électroniques secondaires et de l'instabilité de dérive sur le transport anormal. Par une étude paramétrique sur les émissions électroniques secondaires, nous avons pu identifier trois régimes de décharge plasma. Finalement l'impact des ergols alternatifs a pu être étudié en utilisant des processus collisionnels réalistes. / As space applications are increasingly crucial in our daily life, satellite operating costs need to be decreased. This can be achieved through the use of cost efficient electric propulsion systems. One of the most successful and competitive electric propulsion system is the Hall effect thruster, but this system is characterized by its complexity and remains poorly understood. Indeed some key questions, concerning electron anomalous transport or plasma/wall interactions, are still to be answered.Answers to both questions are based on kinetic mechanisms, and thus cannot be solved with fluid models. Furthermore the temporal and geometrical scales of these mechanisms make them difficult to be experimentally measured. Consequently we chose, in order to answer those questions, to develop a bi-dimensional fully kinetic simulation tool.Using a simplified simulation of the Hall effect thruster, we observed the importance of the azimuthal electron drift instability for anomalous cross-field electron transport. Then, using a realistic model of a Hall effect thruster, we were able to study the effects of plasma/wall interactions on the plasma discharge characteristics, as well as to quantify the coupled effects of secondary electron emission and electron drift instability on the anomalous transport. Through parametric study of secondary electron emission, three plasma discharge regimes were identified. Finally the impact of alternative propellants was studied.

As the world becomes more globalised, user equipment such as smartphones and Internet of Things devices require increasingly more data, which increases the demand for wireless data traffic. Hence, the acceleration of next-generational networks (5G and beyond) focuses mainly on increasing the bitrate and decreasing the latency. A crucial technology for 5G and beyond is the massive MIMO. In a massive MIMO system, a detector processes the received signals from multiple antennas to decode the transmitted data and extract useful information. This has been implemented in many ways, and one of the most used algorithms is the Zero Forcing (ZF) algorithm. This thesis presents a novel parallel design to accelerate the ZF algorithm using the Cholesky decomposition. This is implemented on a GPU, written in the CUDA programming language, and compared to the existing state-of-the-art implementations regarding latency and throughput. The implementation is also validated from a MATLAB implementation. This research demonstrates promising performance using GPUs for massive MIMO detection algorithms. Our approach achieves a significant speedup factor of 350 in comparison to a serial version of the implementation. The throughput achieved is 160 times greater than a comparable GPU-based approach. Despite this, our approach reaches a 2.4 times lower throughput than a solution that employed application-specific hardware. Given the promising results, we advocate for continued research in this area to further optimise detection algorithms and enhance their performance on GPUs, to potentially achieve even higher throughput and lower latency. / <p>Our examiner Mahdi wants to wait six months before the thesis is published. </p>

O rápido desenvolvimento da tecnologia da informação traz oportunidades para área da educação, colocando a educação a distância e aprendizagem online como opções para o modelo tradicional, sobretudo os Massive Open Online Courses (MOOCs), os quais, no contexto do movimento de educação aberta, são apresentados como meio para aumentar o acesso e a qualidade da educação, proporcionando redução dos custos e da desigualdade educacional, sobretudo nos países em desenvolvimento. A revisão sistemática de 74 artigos evidenciou que as IES estão incorporando os MOOCs às suas práticas - em parte, produzindo seus próprios MOOCs, mas também os integrando a seus currículos, tanto para revisar conteúdo do Ensino Médio com alunos ingressantes no Ensino Superior quanto para melhorar seus cursos.Assim, considerando que as pesquisas que avaliam a incorporação dos MOOCs aos currículos das IES investigam, sobretudo, o desempenho e o nível de satisfação dos alunos, o objetivo principal desse estudo foi compreender como os MOOCs estão sendo incorporados aos cursos presenciais de graduação e qual o valor funcional percebido pelos alunos com relação a essa prática. Para tal, foi realizada uma revisão sistemática da literatura e um estudo de caso de caráter exploratório e descritivo, que integra os enfoques qualitativo e quantitativo. A unidade de análise do estudo de caso foi a disciplina de Fundamentos de Administração, lecionada no primeiro ano do curso bacharelado em Administração, e quatro fontes de evidências foram utilizadas: documentos sobre o MOOC, documentação sobre a disciplina que utilizou o MOOC, entrevistas com o Chefe de Departamento e os professores responsáveis pela disciplina e levantamento (survey) com 101 alunos. As evidências obtidas nas etapas de investigação documental e entrevistas foram analisadas baseando-se nas questões de pesquisas, enquanto o levantamento com os alunos valeu-se da técnica de análise estatística de modelagem de equações estruturais, utilizando o software R. Os resultados do estudo permitiram identificar que, assim como sugerido pela literatura, o MOOC foi utilizado como recurso online no método blended learning em uma disciplina introdutória e substituindo parte da carga horária presencial, possibilitando o aumento do número de alunos por professor, além de tornar a disciplina mais atrativa para o alunado. Além disso, que o MOOC foi usado como recurso online para apresentação do conteúdo, enquanto os exercícios de fixação, as avaliações e as atividades complementares foram desenvolvidos pelos professores. As hipóteses propostas no estudo foram validadas: valor funcional percebido tem efeito positivo (r=0,801) na intenção de recompra (R2=64,15%), a qualidade percebida com relação ao processo de blended learning e a qualidade percebida com relação ao MOOC têm efeitos positivos (r=0,22e r=0,2929, respectivamente) no valor funcional percebido pelo aluno (R2=20,46%); a preferência e autodisciplina para realização de cursos a distância têm efeito positivo na qualidade percebida com relação ao processo de blended learning (r=0,2636 e R2=6,95%) e com relação ao MOOC (r=0,347 e R2=12,04%). Conclui-se que o valor funcional percebido pelo aluno é favorável, com escore de 4,53 (escala de 7 pontos), e é influenciado pela qualidade percebida com relação ao MOOC e ao processo de blended learning. / The rapid development of information technology brings opportunities for education, putting distance education and online learning as options for the traditional model of education, especially the Massive Open Online Courses (MOOCs), which in the context of the open education are presented as a means to increase access and quality of education, proportionate educational costs and inequality, especially in developing countries. The systematic review of 74 articles showed that HEIs are incorporating MOOCs into their practices. In part, by producing their own MOOCs, but also integrating them into their curricula, both to revise high school content with incoming higher education students and to improve their courses. Thus, considering that research evaluating the incorporation of MOOCs into The main objectives of this study were to understand how the MOOCs are being incorporated into undergraduate courses and what functional value students perceive in relation to this practice. For such, a systematic review of the literature and an exploratory and descriptive case study were carried out, integrating the qualitative and quantitative approaches. The unit of analysis of the case study was the Fundamentals of Administration discipline taught in the first year of the baccalaureate course in Administration and four sources of evidence were used: documents about the MOOC, documentation about the discipline that used the MOOC, interviews with teachers responsible for discipline and survey with the students. The evidence obtained in the documentary analysis and interviews were analyzed based on the research questions while the student lifting was based on the technique of statistical analysis modeling of structural equations using software R. The results of the study allowed to identify, that as suggested by the literature, the MOOC was used as an online resource in the blendedlearning method in an introductory discipline and replacing part of the classroom workload, making it possible to increase the number of students per teacher, in addition to making the course more attractive for the student. The MOOC was used as an online resource for content presentation, while the attachment exercises, assessments, and complementary activities were developed by teachers. The hypotheses proposed in the study were validated: perceived functional value has a positive effect (r = 0.801) on the intention to buy back (R2 = 64.15%), the quality perceived in relation to the blended learning process and perceived quality in relation to the MOOC have positive effects (r = 0.22 and r = 0.2929, respectively) on the functional value perceived by the student (R2 = 20.46%); (r = 0.2636 and R2 = 6.95%) and in relation to the MOOC (r = 0.347 and R 2 = 12), the preference and self-discipline for distance courses have a positive effect on the perceived quality of the blended learning process , 04%).It is concluded that the functional value perceived by the student is favorable, obtaining a score of 4.53 on a 7-point scale, and that this is influenced by the perceived quality in relation to the MOOC and in relation to the process of blended learning.

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