Global ETD Search

161	Dynamic Clustering and Visualization of Smart Data via D3-3D-LSA / with Applications for QuantNet 2.0 and GitHub Borke, Lukas 08 September 2017 (has links) Mit der wachsenden Popularität von GitHub, dem größten Online-Anbieter von Programm-Quellcode und der größten Kollaborationsplattform der Welt, hat es sich zu einer Big-Data-Ressource entfaltet, die eine Vielfalt von Open-Source-Repositorien (OSR) anbietet. Gegenwärtig gibt es auf GitHub mehr als eine Million Organisationen, darunter solche wie Google, Facebook, Twitter, Yahoo, CRAN, RStudio, D3, Plotly und viele mehr. GitHub verfügt über eine umfassende REST API, die es Forschern ermöglicht, wertvolle Informationen über die Entwicklungszyklen von Software und Forschung abzurufen. Unsere Arbeit verfolgt zwei Hauptziele: (I) ein automatisches OSR-Kategorisierungssystem für Data Science Teams und Softwareentwickler zu ermöglichen, das Entdeckbarkeit, Technologietransfer und Koexistenz fördert. (II) Visuelle Daten-Exploration und thematisch strukturierte Navigation innerhalb von GitHub-Organisationen für reproduzierbare Kooperationsforschung und Web-Applikationen zu etablieren. Um Mehrwert aus Big Data zu generieren, ist die Speicherung und Verarbeitung der Datensemantik und Metadaten essenziell. Ferner ist die Wahl eines geeigneten Text Mining (TM) Modells von Bedeutung. Die dynamische Kalibrierung der Metadaten-Konfigurationen, TM Modelle (VSM, GVSM, LSA), Clustering-Methoden und Clustering-Qualitätsindizes wird als "Smart Clusterization" abgekürzt. Data-Driven Documents (D3) und Three.js (3D) sind JavaScript-Bibliotheken, um dynamische, interaktive Datenvisualisierung zu erzeugen. Beide Techniken erlauben Visuelles Data Mining (VDM) in Webbrowsern, und werden als D3-3D abgekürzt. Latent Semantic Analysis (LSA) misst semantische Information durch Kontingenzanalyse des Textkorpus. Ihre Eigenschaften und Anwendbarkeit für Big-Data-Analytik werden demonstriert. "Smart clusterization", kombiniert mit den dynamischen VDM-Möglichkeiten von D3-3D, wird unter dem Begriff "Dynamic Clustering and Visualization of Smart Data via D3-3D-LSA" zusammengefasst. / With the growing popularity of GitHub, the largest host of source code and collaboration platform in the world, it has evolved to a Big Data resource offering a variety of Open Source repositories (OSR). At present, there are more than one million organizations on GitHub, among them Google, Facebook, Twitter, Yahoo, CRAN, RStudio, D3, Plotly and many more. GitHub provides an extensive REST API, which enables scientists to retrieve valuable information about the software and research development life cycles. Our research pursues two main objectives: (I) provide an automatic OSR categorization system for data science teams and software developers promoting discoverability, technology transfer and coexistence; (II) establish visual data exploration and topic driven navigation of GitHub organizations for collaborative reproducible research and web deployment. To transform Big Data into value, in other words into Smart Data, storing and processing of the data semantics and metadata is essential. Further, the choice of an adequate text mining (TM) model is important. The dynamic calibration of metadata configurations, TM models (VSM, GVSM, LSA), clustering methods and clustering quality indices will be shortened as "smart clusterization". Data-Driven Documents (D3) and Three.js (3D) are JavaScript libraries for producing dynamic, interactive data visualizations, featuring hardware acceleration for rendering complex 2D or 3D computer animations of large data sets. Both techniques enable visual data mining (VDM) in web browsers, and will be abbreviated as D3-3D. Latent Semantic Analysis (LSA) measures semantic information through co-occurrence analysis in the text corpus. Its properties and applicability for Big Data analytics will be demonstrated. "Smart clusterization" combined with the dynamic VDM capabilities of D3-3D will be summarized under the term "Dynamic Clustering and Visualization of Smart Data via D3-3D-LSA". GitHub Mining Infrastruktur Software Mining Text Mining Verallgemeinerte Vektorraum-Modelle YAML Visuelles Data Mining Visual Analytics D3.js Clusteranalyse Qualitätsindizes Validierungs-Pipeline Verteilt-paralleles Rechnen Reproduzierbare Kooperationsforschung Risk Analytics GitHub Mining infrastructure Software Mining Text Mining Generalized Vector Space Models YAML Visual Data Mining Visual Analytics D3.js Cluster Analysis Quality Indices Validation Pipeline Cluster and Parallel Computing Collaborative Reproducible Research Risk Analytics 330 Wirtschaft QH 250 ddc:330
162	An in-depth study of the causative factors of suicide and attempted suicide amongst adolescent learners of Tshwane North (D3) area Kgosana, Mongalo Maria 12 1900 (has links) Adolescent suicide and attempted suicide is an unhealthy practice that involves mental illness which led the suicidal behavior to be an important public health problem globally and in Africa. Suicide prevalence rates in young people in South Africa and in all major ethnic groups are a significant cause for concern. The adolescent mental illness causes sleepless nights on the education system. Though much research has been done on this problem it still remains one of the leading causes of death amongst adolescent learners locally and globally. As a parent and an educator reading news articles, attending memorial services and funerals of adolescent learners who took their own lives, gave me enough reason for actions to be taken in order to find out what is causing adolescents to commit suicide. During this emotional experience as the researcher, I have discovered that the adolescent stage is a very fragile stage. I also discovered that when life stresses strike, coping as an adolescent becomes difficult. This study focuses on an in-depth study of the causative factors of suicide and attempted suicide amongst the adolescent learners of Tshwane North (D3) area. The topic was investigated by means of a literature study and an empirical investigation using a qualitative approach. Data was collected by means of focus group discussion and one to one interview using a tape recorder and taking notes. Participant's answers were analysed individually and compared with all others. Findings shows that adolescent suicide and attempted suicide is a mental disorder that need to be addressed by including physicians and psychologists, upon realizing the warning signs of suicide in order to minimalize the practice. It is also clear that adolescence is a fragile stage of growth and adolescents struggle to cope with life challenges such as peer pressure, parent separations, socialization, pregnancy, chronic illness and academic pressure. It is recommended that NGOs in collaboration with the Health and Education Departments need to take action by organizing workshops to address causative factors of suicide and how to find help when realizing a suicidal adolescent learner. The department of education needs to ensure that adolescent suicide and attempted suicide preventative strategies should be taught from primary school level and be added to life skills subject in all grades. Life Orientation educator's to be trained about adolescent suicide to be well equipped to teach learners on how to recognize warning signs in their peers and friends. / Inclusive Education / M. Ed. (Inclusive Education) Suicide Attempted suicide Suicidal Adolescent Causative factors Warning signs Behaviour Stressors Tshwane North (D3) area Learner 618.9285844500968227
163	An in-depth study of the causative factors of suicide and attempted suicide amongst adolescent learners of Tshwane North (D3) area Kgosana, Mongalo Maria 12 1900 (has links) Adolescent suicide and attempted suicide is an unhealthy practice that involves mental illness which led the suicidal behavior to be an important public health problem globally and in Africa. Suicide prevalence rates in young people in South Africa and in all major ethnic groups are a significant cause for concern. The adolescent mental illness causes sleepless nights on the education system. Though much research has been done on this problem it still remains one of the leading causes of death amongst adolescent learners locally and globally. As a parent and an educator reading news articles, attending memorial services and funerals of adolescent learners who took their own lives, gave me enough reason for actions to be taken in order to find out what is causing adolescents to commit suicide. During this emotional experience as the researcher, I have discovered that the adolescent stage is a very fragile stage. I also discovered that when life stresses strike, coping as an adolescent becomes difficult. This study focuses on an in-depth study of the causative factors of suicide and attempted suicide amongst the adolescent learners of Tshwane North (D3) area. The topic was investigated by means of a literature study and an empirical investigation using a qualitative approach. Data was collected by means of focus group discussion and one to one interview using a tape recorder and taking notes. Participant's answers were analysed individually and compared with all others. Findings shows that adolescent suicide and attempted suicide is a mental disorder that need to be addressed by including physicians and psychologists, upon realizing the warning signs of suicide in order to minimalize the practice. It is also clear that adolescence is a fragile stage of growth and adolescents struggle to cope with life challenges such as peer pressure, parent separations, socialization, pregnancy, chronic illness and academic pressure. It is recommended that NGOs in collaboration with the Health and Education Departments need to take action by organizing workshops to address causative factors of suicide and how to find help when realizing a suicidal adolescent learner. The department of education needs to ensure that adolescent suicide and attempted suicide preventative strategies should be taught from primary school level and be added to life skills subject in all grades. Life Orientation educator's to be trained about adolescent suicide to be well equipped to teach learners on how to recognize warning signs in their peers and friends. / Inclusive Education / M. Ed. (Inclusive Education) Suicide Attempted suicide Suicidal Adolescent Causative factors Warning signs Behaviour Stressors Tshwane North (D3) area Learner 618.9285844500968227
164	Homology modeling and structural analysis of the antipsychotic drugs receptorome López Muñoz, Laura 22 June 2010 (has links) Classically it was assumed that the compounds with therapeutic effect exert their action interacting with a single receptor. Nowadays it is widely recognized that the pharmacological effect of most drugs is more complex and involves a set of receptors, some associated to their positive effects and some others to the side effects and toxicity. Antipsychotic drugs are an example of effective compounds characterized by a complex pharmacological profile binding to several receptors (mainly G protein-coupled-receptors, GPCR). In this work we will present a detailed study of known antipsychotic drugs and the receptors potentially involved in their binding profile, in order to understand the molecular mechanisms of the antipsychotic pharmacologic effects.The study started with obtaining homology models for all the receptors putatively involved in the antipsychotic drugs receptorome, suitable for building consistent drug-receptor complexes. These complexes were structurally analyzed and compared using multivariate statistical methods, which in turn allowed the identification of the relationship between the pharmacological properties of the antipsychotic drugs and the structural differences in the receptor targets. The results can be exploited for the design of safer and more effective antipsychotic drugs with an optimum binding profile. / Tradicionalmente se asumía que los fármacos terapéuticamente efectivos actuaban interaccionando con un único receptor. Actualmente está ampliamente reconocido que el efecto farmacológico de la mayoría de los fármacos es más complejo y abarca a un conjunto de receptores, algunos asociados a los efectos terapéuticos y otros a los secundarios y toxicidad. Los fármacos antipsicóticos son un ejemplo de compuestos eficaces que se caracterizan por unirse a varios receptores simultáneamente (principalmente a receptores unidos a proteína G, GPCR). El trabajo de la presente tesis se ha centrado en el estudio de los mecanismos moleculares que determinan el perfil de afinidad de unión por múltiples receptores de los fármacos antipsicóticos.En primer lugar se construyeron modelos de homología para todos los receptores potencialmente implicados en la actividad farmacológica de dichos fármacos, usando una metodología adecuada para construir complejos fármaco-receptor consistentes. La estructura de estos complejos fue analizada y se llevó a cabo una comparación mediante métodos estadísticos multivariantes, que permitió la identificación de asociaciones entre la actividad farmacológica de los fármacos antipsicóticos y diferencias estructurales de los receptores diana. Los resultados obtenidos tienen interés para ser explotados en el diseño de fármacos antipsicóticos con un perfil farmacológico óptimo, más seguros y eficaces. Receptor 5-HT2A Receptor D3 Receptor D2 Ligando Clozapina Derivados Benzofuranonas Risperidona Olanzapina esquizofrenia métodos de regresión campos de interacción Molecular (MIF) Perfil Multireceptorial modelado por homología Docking sitio de unión interacciones moleculares selectividad afinidad de unión Diana Meta-Diana efectos secundarios fármaco antipsicótico típico fármaco antipsicótico atípico agonista antagonista membrana receptoroma rhodopsina estructura de rayos X descriptores moleculares farmacología análisis multivariante procedimiento integrado Computer-aided drug design Integrated approach Multivariate analysis Pharmacology Molecular descriptors X-ray structure Rhodopsin Receptorome Membrane Antagonist Agonist Atypical antipsychotic drug Typical antipsychotic drug Side effects Off-target Target Selectivity Binding affinity Molecular interactions Binding site Homology modeling Docking Multireceptor profile Molecular interaction Field (MIF) Partial Least Squares (PLS) Principal Component Analysis (PCA) Schizophrenia Benzolactam Derivatives Benzofuranone Derivatives Risperidone Olanzapine Clozapine Ligand Adrenergic receptors Muscarinic receptors Histamine receptors Serotonin receptors Dopamine receptors beta2-Adrenergic receptor D2 receptor D3 receptor 5-HT2A receptor G protein-coupled receptors (GPCR) 57

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