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  • Effizientes Retrieval und Extraktion von Entscheidungswissen mit k-d-Bäumen

    In dieser Arbeit wird eine Kombinationsmöglichkeit von fallbasiertem und induktivem Schliessen, basierend auf k-d- und Entscheidungsbäumen, entwickelt. Dabei wurde versucht, die Vorteile des induktiven Mechanismus, wie z. B. die sehr effiziente Klassifiz ierung und automatische Generierung, in den fallbasierten Mechanismus zu integrieren. Die Aufgabe zerfällt dabei in zwei Teilaufgaben, die im folgenden zusammengefasst werden.

    Molecular Containers for Anions Based on Triply-Linked Bis(Cyclopeptides)

    The research presented in this PhD thesis is a contribution to the field of anion recognition in competitive aqueous solvent mixtures. Neutral anion receptors having a cage-type architecture have been developed on the basis of triply-linked bis(cyclopeptides) and their binding properties toward various inorganic anions have been studied. The synthetic approaches chosen to assemble the targeted container molecules rely on dynamic chemistry under the template effects of anions such as sulfat...

    PBP2x-Mutationen in Streptococcus pneumoniae: Auswirkungen auf beta-Laktam-Resistenz und Zellphysiologie

    Die Entwicklung von beta-Laktam-Resistenz in dem Pathogen Streptococcus pneumoniae (S. pneu-moniae) stellt einen komplexen Prozess dar, welcher auf einer Modifikation der Penicillin-Bindeproteine (PBP), der Targetstrukturen von beta-Laktam-Antibiotika beruht. PBP sind Membran-gebundene Enzyme, welche essentielle Reaktionen bei der bakteriellen Zellwand-Synthese katalysieren. Diese Proteine werden im Zuge der Resistenzentstehung so verändert, dass beta-Laktame nicht mehr oder nur noch mit geri...

    Competitive Algorithms for Multistage Online Scheduling

    We study an online flow shop scheduling problem where each job consists of several tasks that have to be completed in t different stages and the goal is to maximize the total weight of accepted jobs. The set of tasks of a job contains one task for each stage and each stage has a dedicated set of identical parallel machines corresponding to it that can only process tasks of this stage. In order to gain the weight (profit) associated with a job j, each of its tasks has to be executed betwee...

    A uniform central limit theorem for neural network based autoregressive processes with applications to change-point analysis

    We consider an autoregressive process with a nonlinear regression function that is modeled by a feedforward neural network. We derive a uniform central limit theorem which is useful in the context of change-point analysis. We propose a test for a change in the autoregression function which - by the uniform central limit theorem - has asymptotic power one for a large class of alternatives including local alternatives.
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