Die bruchhafte Fragmentation von höherviskosem Magma ist ein bedeutender Prozess im explosiven Vulkanismus. Deren Fragmentationsenergie ist linear an die Entstehung neugebildeter Bruchfläche gekoppelt. Aus diesem Grund ist es wichtig, die mechanische Energie der Schmelzefragmentation zu quantifizieren, um die physikalischen Vorgänge während dieses vulkanologischen Vorgangs besser verstehen zu können. Deshalb war es das Ziel der vorliegenden Arbeit eine Kenngröße der Fragmentationsleistung von vulkanischen Schmelzen der Phlegräischen Felder (Neapel/Italien) zu definieren und somit ihren vulkanischen Ablagerungen spezifische Fragmentationsenergien zuzuweisen. Das Vulkangebiet der Phlegräischen Felder ist durch langanhaltenden explosiven Vulkanismus gekennzeichnet. Die bruchhaft entstandenen Feinaschen-Ablagerungen intermediärer Zusammensetzung bedecken ein Gebiet von ca. 1000 km2. Dieses Gebiet wird heute von ca. 2 Millionen Menschen bevölkert. Diese Arbeit stellt eine Methodik vor, mit der die Fragmentationsenergie von solchen höher-viskosen Schmelzen intermediärer Zusammensetzung durch Laborexperimente und Granulometrie der erzeugten Partikel ermittelt werden kann. Die Materialparameter der kritischen Schubspannung und des kritischen Scherstress wurden mit einem sogenannten Gasdruck-Fragmentations-Versuch (GFV) experimentell bestimmt. Ferner konnten durch den GFV Erkenntnisse über das Fragmentationsverhalten dieser Schmelzen unter verschiedenen treibenden Gasdrücken gewonnen werden. Dieser spezielle Versuchsaufbau basiert auf Fragmentation von Schmelze durch Druckluft, die von unten in einen Tiegel geleitet wird. Ein individuell einstellbarer Gasdruckluftstoß führt in der Schmelze zu einer Zunahme der Schubspannung und einem Druckaufbau, der vergleichbar mit der Kraftrampe eines Biegeversuchs ist. Während dieser Zeit kommt es zur Mikrobruchbildung, die sich von der Schmelzeoberfläche nach unten fortsetzt. Nach dem Überschreiten der Bruchgrenze relaxiert das Schmelzematerial durch Ausbildung von Sprödbrüchen und wird nach oben ausgeworfen. Die Aufzeichnung der physikalischen Parameter und die optische Versuchsüberwachung erlaubten eine komplette Energiebilanzierung des Vorgangs. Die neugebildete Bruchfläche der entstandenen Partikel wird durch Granulometrie und Anwendung der Methode von Brunnauer-Emmet-Teller (BET) bestimmt. Somit kann die Fragmentationsenergie auf die Bruchfläche bezogen und als Materialparameter des kritischen Scherstresses ausgedrückt werden. Der GFV wurden durch normierte Laborexperimente an dem selben Schmelzematerial ergänzt. Dabei dienten statische Biegeversuche unter Raumtemperatur zur Überprüfung der über GFV bilanzierten Scherstresse. Die Rotationsviskosimetrie zeigte, dass der Materialparameter der Viskosität nicht geeignet ist, um Rückschlüsse über Materialverhalten im bruchhaften Regime zu ziehen. Anschließend wurde einer definierten Tephraschicht der Phlegräischen Felder eine spezifische Fragmentationsenergie zugeordnet, indem die experimentellen Ergebnisse auf Felddaten bezogen wurden. Diese spezifische Energie von ca. 8*1010 kJ entspricht der Sprengkraft von ca. 20.000 Tonnen Trinitrotoluol (TNT). Die Qualität eines hazard assessment gefährdeter Vulkangebiete wie z.B. der Phlegräischen Felder wird durch die Kenntnis der Energieaufteilung während des Eruptionsprozesses (Fragmentationsenergie, Auswurfenergie etc.) wesentlich verbessert. Die Kenntnis der Energien dient beispielsweise der Skalierung ballistischer Modelle, mit deren Hilfe dichtbevölkerte Zonen ausgewiesen werden können, die bei künftigen Eruptionen der Phlegräischen Felder durch den Niedergang von Pyroklastika bedroht sind. / The brittle fragmentation of highly viscous melt is a major part of explosive eruptions. It is important to quantify the mechanical energy needed for the melt-fragmentation in order to assess this volcanic physical process. The Phlegrean Volcanic Field (Naples/Italy) is characterized by long-term explosive volcanism. Fine-ash deposits of brittle origin and intermediate composition cover an area of about 1000 km2. Nowadays this area is inhabitated by about 2 Million people. This thesis presents a method to determine the fragmentation energy of such highly viscous melts of intermediate composition, using laboratory experiments and granulometry data of the produced particles. The rock parameters critical shear stress and fragmentation energy were determined, using the so called “Gas-Fragmentation-Test“ (GFV). Further, the GFV was useful to determine the fragmentation behaviour of these melts under varying driving pressures. This special fragmentation setup is based on a gas pressure blow (applying compressed air) which leads to a shear tension increase in the melt volume. The pressure built-up is comparable to a load force of a centre-loading flexural test. During this time microcrack propagation migrates from the upper melt surface downward. After exceeding the fragmentation limit the melt relaxes, resulting in brittle fractures. The monitoring of the partition of energies as well as the highspeed video recording of the process allows the calculation of the total fragmentation energy. The total fracture area of particles was quantified, using granulometry and the multipoint Brunnauer-Emmett-Teller method. Thus the fragmentation energy was related to the total fracture area and expressed as critical shear stress, which represents a material parameter. The GFV were complemented by standardised laboratory experiments. Static centre-loading flexural tests were carried out on the same material to check the ambient temperature shear stress values. Moreover measurements showed that determination of the melts viscosity this parameter is not useful to describe fragmentation in the brittle field. Afterwards the fragmentation energy needed to produce one tephra layer of the Phlegrean material was calculated, using the experimental results and field data. This energy value of approx. 8*1010 kJ corresponds to the explosive power of approx. 20.000 tons of trinitrotoluene (TNT). Finally, the knowledge of energy-partitioning is a useful tool to scale numerical models of the eruption and to improve the quality of hazard assessment in vulnerable volcanic regions like the Phlegrean Volcanic Field. In this way densely urbanized regions, which are threatened by the deposit of pyroclastics, were determined.

Thesis (M.F.A.)--Georgia State University, 2009. / Title from file title page. Cheryl Goldsleger, committee chair; Teresa Reeves, Craig Dongoski, committee members. Description based on contents viewed Aug. 6, 2009. Includes bibliographical references (p. 26).

Universiẗat, Diss., 2004--Würzburg.

This thesis [written in German] is the first known study to analyze the writings of the Austrian, Franz Michael Felder, as an educative device, which the author himself utilized to enlighten and instruct his country folk in Bregenzerwald, Vorarlberg. An attempt is made to uncover the basic message inherent in all of Felder’s works: close family relationship, high moral standards and diligence are important to him; he fights petty prejudice, meaningless tradition and hypocrisy. The many native customs peculiar to the region are, of course, immanent in his literary production and, what is particularly significant, he stages a continuous battle against the social and political pressures of the time. He sees the need for community action in pooling meager resources to combat influential outside monopolies which stifle the economy of his remote alpine region. Franz Michael Felder’s message is somber. It lacks the folksy homespun qualities observed in similar writers, such as Rosegger, Gotthelf, Hansjacob , Huggenberger, Löns, Schönherr and Ludwig Thoma. Felder educates his people to a better understanding of themselves and a greater tolerance of others. He seeks equality of rights and equal justice for everyone. With a seriously discerning attitude he probes local problems confronting his people; these he portrays in true to life situations, attempting to search the causes. While Felder does not advocate to change customs and established ways of life, he wants to better his people’s situation for their own welfare and self-improvement. Felder’s literary importance is manifold: he writes from true experience, which he incorporates into beneficial teaching for his people; Austria in its entirety and much of Europe is quite akin to the style of rural living described by Felder for the Vorarlberg. Thus he captures a true picture of nineteen-century village life with its economic and social implications. This study treats of Felder’s literary achievements only. It casually mentions his other, more visible accomplishments, such as the foundation of a dairy association, an agricultural produce co-op, a cattle insurance company, a weaving co-op. He established a library and a reading club. This he did in a relatively brief span of time for he died at the age of twenty-nine. Not only did Felder make material life easier for his countrymen, he freed them spiritually as well. The research of this thesis concludes that Felder, though relatively unknown in literature is possibly the most influential and lasting of all Vorarlberg writers. His description does not have the pastoral serenity usually peculiar to village tales; there is little to see of the pretty mountain landscapes, or the cool green meadows with rustling brooks and cowbells ringing. Felder does not indulge the reader – instead he describes reality, actual people and their problems – the reader gets what he needs. This, then, is the universality of Felder’s work: in essence, he reflects truth.

abstract: Programming is quickly becoming as ubiquitous and essential a skill as general mathematics. However, many elementary and high school students are still not aware of what the computer science field entails. To make matters worse, students who are introduced to computer science are frequently being fed only part of what it is about rather than its entire construction. Consequently, they feel out of their depth when they approach college. Research has discovered that by teaching computer science and programming through a problem-driven approach and focusing on a combination of syntax and computational thinking, students can be prepared when entering higher levels of computer science education. This thesis describes the design, development, and early user testing of a theory-based virtual world for computer science instruction called System Dot. System Dot was designed to visually manifest programming instructions into interactable objects, giving players a way to see coding as tangible entities rather than text on a white screen. In order for System Dot to convey the true nature of computer science, a custom predictive recursive descent parser was embedded in the program to validate any user-generated solutions to pre-defined logical platforming puzzles. Steps were taken to adapt the virtual world to player behavior by creating a system to detect their learning style playing the game. Through a dynamic Bayesian network, System Dot aims to classify a player’s learning style based on the Felder-Sylverman Learning Style Model (FSLSM). Testers played through the first half of System Dot, which was enough to test out the Bayesian network and initial learning style classification. This classification was then compared to the assessment by Felder’s Index of Learning Styles Questionnaire (ILSQ). Lastly, this thesis will also discuss ways to use the results from the user testing to implement a personalized feedback system for the virtual world in the future and what has been learned through the learning style method. / Dissertation/Thesis / Masters Thesis Computer Science 2017

Com efeito, diversos estudos nas áreas de psicologia cognitiva e pedagogia apontam que cada indivíduo possui diferentes maneiras de captar, processar, analisar e organizar informações durante o processo de aprendizado, o que fundamenta o conceito de Estilos de Aprendizagem (EA). Em vista disso, diversos sistemas educacionais adaptativos foram propostos com o intuito de proporcionar conteúdo personalizado em seus cursos. Porém, em boa parte dos casos, estes sistemas fazem uso de questionários para identificar os estilos de aprendizagem, e este método pode mostrar-se inviável em algumas situações. Isso ocorre pois o preenchimento dos questionários demanda um esforço adicional por parte do aluno, além fazer uma avaliação estática dos EA, desconsiderando possíveis variações em suas preferências ao longo do tempo. Supõe-se que uma estratégia de detecção automática e dinâmica dos EA baseada no comportamento dos estudantes pode ser mais proveitosa neste sentido, pois é isenta destas limitações. Deste modo, a proposta neste trabalho é investigar diferentes técnicas relacionadas ao aprendizado de máquina (especialmente algoritmos de classificação) aplicadas à predição automática dos estilos de aprendizagem de estudantes, a partir de suas interações em um ambiente virtual de ensino. Dentre os inúmeros modelos de EA propostos na literatura, optou-se por usar o modelo de Felder-Silverman como base para os experimentos. Como estudo de caso, foram rastreadas as interações de 105 estudantes de um curso de pós-graduação em fonoaudiologia ministrado integralmente pelo sistema Moodle. Além disso, estes alunos foram solicitados a responder ao questionário ILS, o qual indica a preferência de cada indivíduo de acordo com o modelo de Felder-Silverman. Para a construção dos conjuntos de dados, foram coletadas informações como a quantidade de visitas, tempo gasto e interação dos usuários em cada tipo de recurso (recursos de vídeo, formulários de avaliação, fórum, etc.). Estes conjuntos de dados no formato atributo-valor serviram de entrada para quatro algoritmos de classificação: Naïve Bayes, aprendizado baseado em instâncias (kNN), Redes Neurais Artificiais (MultiLayer Perceptron) e Árvores de Decisão (J48), combinados com métodos de seleção de atributos e executados em validação cruzada. Para fins de experimentação, foram avaliadas as taxas de acertos e erros dos algoritmos em relação aos resultados apontados pelo questionário ILS, em cada umas das dimensões do modelo de Felder-Silverman. Os resultados apontaram para o uso de mais de um classificador - Naïve Bayes e aprendizagem baseada em instância - dependendo da dimensão do estilo de aprendizagem. A metodologia aplicada foi comparada com sete trabalhos correlatos da literatura; Os resultados demonstraram uma performance superior aos trabalhos anteriores em quase todas as dimensões. Portanto, o presente trabalho contribui para o contexto da informática aplicada à educação, especificamente no que diz respeito à implementação de sistemas educacionais adaptativos, com base em uma análise comparativa entre diferentes técnicas aplicadas ao mesmo problema. Sendo assim, as conclusões obtidas devem colaborar para o aprimoramento do processo de modelagem de estudantes. Além disso, são levantadas discussões a respeito dos resultados, que podem auxiliar na direção de futuros trabalhos da área. / In fact, several studies in the areas of cognitive psychology and pedagogy point out that each individual has different ways of capturing, processing, analyzing and organizing information during the learning process, which supports the concept of Learning Styles (LS). Therefore, several adaptive educational systems were proposed with the aim of providing personalized content in their courses. However, in most cases, these systems use questionnaires to identify learning styles, and this method may prove unfeasible in some situations. This is because filling in the questionnaires requires an additional effort on the part of the student, besides, this approach makes a static evaluation of the LS, disregarding possible variations in their preferences over time. It is assumed that an automatic and dynamic detection of LS based on student behavior may be more useful in this sense, since it is exempt from these limitations. In this way, the proposal in this work is to investigate different techniques related to machine learning (especially classification algorithms) applied to the automatic prediction of student learning styles, based on their interactions in a virtual teaching environment. Among the many LS models proposed in the literature, we chose to use the Felder-Silverman model (FSLSM). As a case study, the interactions of 105 students from a post-graduate course in speech therapy were studied. In addition, these students were asked to respond to the ILS questionnaire, which indicates the preference of each individual according to FSLSM. In order to construct the data sets, information was collected such as the number of visits, time spent and user interaction in each type of resource (video resources, evaluation forms, forum, etc.). These data sets in the attribute-value format served as input to four classification algorithms: Naïve Bayes, instance-based learning (kNN), MultiLayer Perceptron and Decision Trees (J48), combined with attribute selection methods and executed in cross-validation. For the experimentation, the accuracy and error rates of the algorithms were evaluated in relation to the results indicated by the ILS questionnaire, in each one of FSLSM dimensions. Our results pointed out to the use of more than one classifier, Naïve Bayes and Instance-based Learning, depending on the learning style dimension. We compared our methodology to seven works of the literature; the results demonstrated a performance superior to the previous works in almost every dimension. The present work contributes to the context of informatics applied to education, specifically with regard to the implementation of adaptive educational systems, based on a comparative analysis of different methods applied to the same problem. Therefore, the conclusions obtained should contribute to the improvement of the student modeling process. In addition, discussions are held regarding the results, which may assist in the direction of future work in this area.

Com efeito, diversos estudos nas áreas de psicologia cognitiva e pedagogia apontam que cada indivíduo possui diferentes maneiras de captar, processar, analisar e organizar informações durante o processo de aprendizado, o que fundamenta o conceito de Estilos de Aprendizagem (EA). Em vista disso, diversos sistemas educacionais adaptativos foram propostos com o intuito de proporcionar conteúdo personalizado em seus cursos. Porém, em boa parte dos casos, estes sistemas fazem uso de questionários para identificar os estilos de aprendizagem, e este método pode mostrar-se inviável em algumas situações. Isso ocorre pois o preenchimento dos questionários demanda um esforço adicional por parte do aluno, além fazer uma avaliação estática dos EA, desconsiderando possíveis variações em suas preferências ao longo do tempo. Supõe-se que uma estratégia de detecção automática e dinâmica dos EA baseada no comportamento dos estudantes pode ser mais proveitosa neste sentido, pois é isenta destas limitações. Deste modo, a proposta neste trabalho é investigar diferentes técnicas relacionadas ao aprendizado de máquina (especialmente algoritmos de classificação) aplicadas à predição automática dos estilos de aprendizagem de estudantes, a partir de suas interações em um ambiente virtual de ensino. Dentre os inúmeros modelos de EA propostos na literatura, optou-se por usar o modelo de Felder-Silverman como base para os experimentos. Como estudo de caso, foram rastreadas as interações de 105 estudantes de um curso de pós-graduação em fonoaudiologia ministrado integralmente pelo sistema Moodle. Além disso, estes alunos foram solicitados a responder ao questionário ILS, o qual indica a preferência de cada indivíduo de acordo com o modelo de Felder-Silverman. Para a construção dos conjuntos de dados, foram coletadas informações como a quantidade de visitas, tempo gasto e interação dos usuários em cada tipo de recurso (recursos de vídeo, formulários de avaliação, fórum, etc.). Estes conjuntos de dados no formato atributo-valor serviram de entrada para quatro algoritmos de classificação: Naïve Bayes, aprendizado baseado em instâncias (kNN), Redes Neurais Artificiais (MultiLayer Perceptron) e Árvores de Decisão (J48), combinados com métodos de seleção de atributos e executados em validação cruzada. Para fins de experimentação, foram avaliadas as taxas de acertos e erros dos algoritmos em relação aos resultados apontados pelo questionário ILS, em cada umas das dimensões do modelo de Felder-Silverman. Os resultados apontaram para o uso de mais de um classificador - Naïve Bayes e aprendizagem baseada em instância - dependendo da dimensão do estilo de aprendizagem. A metodologia aplicada foi comparada com sete trabalhos correlatos da literatura; Os resultados demonstraram uma performance superior aos trabalhos anteriores em quase todas as dimensões. Portanto, o presente trabalho contribui para o contexto da informática aplicada à educação, especificamente no que diz respeito à implementação de sistemas educacionais adaptativos, com base em uma análise comparativa entre diferentes técnicas aplicadas ao mesmo problema. Sendo assim, as conclusões obtidas devem colaborar para o aprimoramento do processo de modelagem de estudantes. Além disso, são levantadas discussões a respeito dos resultados, que podem auxiliar na direção de futuros trabalhos da área. / In fact, several studies in the areas of cognitive psychology and pedagogy point out that each individual has different ways of capturing, processing, analyzing and organizing information during the learning process, which supports the concept of Learning Styles (LS). Therefore, several adaptive educational systems were proposed with the aim of providing personalized content in their courses. However, in most cases, these systems use questionnaires to identify learning styles, and this method may prove unfeasible in some situations. This is because filling in the questionnaires requires an additional effort on the part of the student, besides, this approach makes a static evaluation of the LS, disregarding possible variations in their preferences over time. It is assumed that an automatic and dynamic detection of LS based on student behavior may be more useful in this sense, since it is exempt from these limitations. In this way, the proposal in this work is to investigate different techniques related to machine learning (especially classification algorithms) applied to the automatic prediction of student learning styles, based on their interactions in a virtual teaching environment. Among the many LS models proposed in the literature, we chose to use the Felder-Silverman model (FSLSM). As a case study, the interactions of 105 students from a post-graduate course in speech therapy were studied. In addition, these students were asked to respond to the ILS questionnaire, which indicates the preference of each individual according to FSLSM. In order to construct the data sets, information was collected such as the number of visits, time spent and user interaction in each type of resource (video resources, evaluation forms, forum, etc.). These data sets in the attribute-value format served as input to four classification algorithms: Naïve Bayes, instance-based learning (kNN), MultiLayer Perceptron and Decision Trees (J48), combined with attribute selection methods and executed in cross-validation. For the experimentation, the accuracy and error rates of the algorithms were evaluated in relation to the results indicated by the ILS questionnaire, in each one of FSLSM dimensions. Our results pointed out to the use of more than one classifier, Naïve Bayes and Instance-based Learning, depending on the learning style dimension. We compared our methodology to seven works of the literature; the results demonstrated a performance superior to the previous works in almost every dimension. The present work contributes to the context of informatics applied to education, specifically with regard to the implementation of adaptive educational systems, based on a comparative analysis of different methods applied to the same problem. Therefore, the conclusions obtained should contribute to the improvement of the student modeling process. In addition, discussions are held regarding the results, which may assist in the direction of future work in this area.

This study investigates existing learning management systems practices, in this case Canvas and Moodle in relation to user personalization and students’ learning styles as both factors are closely contribute to the design of a meaningful learning experience for learners. With the expansion of these teaching tools and methods, it seems crucial to determine to what extent they actually serve the learner and what role is really given to the student using these online platforms. Factors such as instructors’ feedback, peer communication, learning objects and follow-up will be examined. This study is anchored in a Swedish academic setting, and aims to provide a comprehensive overview of learners' needs, expectations, and preferences to benefit educational institutions as well as LMS developers. The goal is to assess how such factors play an essential role in the personalization of learning tools and to suggest that their consideration can lead to the development of more intuitive LMS platforms that do not solely rely on content uploaded by teachers, but that can in turn potentially offer relevant content tailored to each user. / Den här uppsatsen undersöker befintliga praxis för lärande hanteringssystem, i detta fall Canvas och Moodle, i förhållande till användaranpassning och studenternas inlärningsstilar, eftersom båda faktorerna bidrar till utformningen av en meningsfull inlärningsupplevelse för studenterna. På grund av expansionen av dessa undervisningsverktyg verkar det avgörande att bestämma i vilken utsträckning de faktiskt tjänar inläraren och vilken roll studenten verkligen får när hen använder dessa plattformar. Faktorer som lärarnas återkoppling, kommunikation med andra elever, lärandeobjekt och uppföljning kommer att undersökas noggrant. Studien är förankrad i en svensk akademisk miljö och syftar att ge en heltäckande översikt av inlärarnas behov, förväntningar och preferenser. Målet är att förstå hur dessa faktorer spelar en väsentlig roll i personaliseringen av lärverktyg och att föreslå att deras beaktande kan leda till utveckling av mer intuitiva LMS-plattformar som inte enbart förlitar sig på innehåll som laddas upp av lärare, utan som i sin tur potentiellt kan erbjuda relevant innehåll som är skräddarsytt för varje användare.

No description available.

This review concentrates on findings described in the recent literature on the response of cells and tissues to electromagnetic fields (EMF). Models of the causal interaction between different forms of EMF and ions or biomolecules of the cell will be presented together with our own results in cell surface recognition. Naturally occurring electric fields are not only important for cell-surface interactions but are also pivotal for the normal development of the organism and its physiological functions. A further goal of this review is to bridge the gap between recent cell biological studies (which, indeed, show new data of EMF actions) and aspects of EMF-based therapy, e.g., in wounds and bone fractures. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.