52 research outputs found

    University of Windsor Graduate Calendar 2023 Spring

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    https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1027/thumbnail.jp

    University of Windsor Graduate Calendar 2023 Winter

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    https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1026/thumbnail.jp

    On-premise containerized, light-weight software solutions for Biomedicine

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    Bioinformatics software systems are critical tools for analysing large-scale biological data, but their design and implementation can be challenging due to the need for reliability, scalability, and performance. This thesis investigates the impact of several software approaches on the design and implementation of bioinformatics software systems. These approaches include software patterns, microservices, distributed computing, containerisation and container orchestration. The research focuses on understanding how these techniques affect bioinformatics software systems’ reliability, scalability, performance, and efficiency. Furthermore, this research highlights the challenges and considerations involved in their implementation. This study also examines potential solutions for implementing container orchestration in bioinformatics research teams with limited resources and the challenges of using container orchestration. Additionally, the thesis considers microservices and distributed computing and how these can be optimised in the design and implementation process to enhance the productivity and performance of bioinformatics software systems. The research was conducted using a combination of software development, experimentation, and evaluation. The results show that implementing software patterns can significantly improve the code accessibility and structure of bioinformatics software systems. Specifically, microservices and containerisation also enhanced system reliability, scalability, and performance. Additionally, the study indicates that adopting advanced software engineering practices, such as model-driven design and container orchestration, can facilitate efficient and productive deployment and management of bioinformatics software systems, even for researchers with limited resources. Overall, we develop a software system integrating all our findings. Our proposed system demonstrated the ability to address challenges in bioinformatics. The thesis makes several key contributions in addressing the research questions surrounding the design, implementation, and optimisation of bioinformatics software systems using software patterns, microservices, containerisation, and advanced software engineering principles and practices. Our findings suggest that incorporating these technologies can significantly improve bioinformatics software systems’ reliability, scalability, performance, efficiency, and productivity.Bioinformatische Software-Systeme stellen bedeutende Werkzeuge für die Analyse umfangreicher biologischer Daten dar. Ihre Entwicklung und Implementierung kann jedoch aufgrund der erforderlichen Zuverlässigkeit, Skalierbarkeit und Leistungsfähigkeit eine Herausforderung darstellen. Das Ziel dieser Arbeit ist es, die Auswirkungen von Software-Mustern, Microservices, verteilten Systemen, Containerisierung und Container-Orchestrierung auf die Architektur und Implementierung von bioinformatischen Software-Systemen zu untersuchen. Die Forschung konzentriert sich darauf, zu verstehen, wie sich diese Techniken auf die Zuverlässigkeit, Skalierbarkeit, Leistungsfähigkeit und Effizienz von bioinformatischen Software-Systemen auswirken und welche Herausforderungen mit ihrer Konzeptualisierungen und Implementierung verbunden sind. Diese Arbeit untersucht auch potenzielle Lösungen zur Implementierung von Container-Orchestrierung in bioinformatischen Forschungsteams mit begrenzten Ressourcen und die Einschränkungen bei deren Verwendung in diesem Kontext. Des Weiteren werden die Schlüsselfaktoren, die den Erfolg von bioinformatischen Software-Systemen mit Containerisierung, Microservices und verteiltem Computing beeinflussen, untersucht und wie diese im Design- und Implementierungsprozess optimiert werden können, um die Produktivität und Leistung bioinformatischer Software-Systeme zu steigern. Die vorliegende Arbeit wurde mittels einer Kombination aus Software-Entwicklung, Experimenten und Evaluation durchgeführt. Die erzielten Ergebnisse zeigen, dass die Implementierung von Software-Mustern, die Zuverlässigkeit und Skalierbarkeit von bioinformatischen Software-Systemen erheblich verbessern kann. Der Einsatz von Microservices und Containerisierung trug ebenfalls zur Steigerung der Zuverlässigkeit, Skalierbarkeit und Leistungsfähigkeit des Systems bei. Darüber hinaus legt die Arbeit dar, dass die Anwendung von SoftwareEngineering-Praktiken, wie modellgesteuertem Design und Container-Orchestrierung, die effiziente und produktive Bereitstellung und Verwaltung von bioinformatischen Software-Systemen erleichtern kann. Zudem löst die Implementierung dieses SoftwareSystems, Herausforderungen für Forschungsgruppen mit begrenzten Ressourcen. Insgesamt hat das System gezeigt, dass es in der Lage ist, Herausforderungen im Bereich der Bioinformatik zu bewältigen und stellt somit ein wertvolles Werkzeug für Forscher in diesem Bereich dar. Die vorliegende Arbeit leistet mehrere wichtige Beiträge zur Beantwortung von Forschungsfragen im Zusammenhang mit dem Entwurf, der Implementierung und der Optimierung von Software-Systemen für die Bioinformatik unter Verwendung von Prinzipien und Praktiken der Softwaretechnik. Unsere Ergebnisse deuten darauf hin, dass die Einbindung dieser Technologien die Zuverlässigkeit, Skalierbarkeit, Leistungsfähigkeit, Effizienz und Produktivität bioinformatischer Software-Systeme erheblich verbessern kann

    Universal Database System Analysis for Insight and Adaptivity

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    Database systems are ubiquitous; they serve as the cornerstone of modern application infrastructure due to their efficient data access and storage. Database systems are commonly deployed in a wide range of environments, from transaction processing to analytics. Unfortunately, this broad support comes with a trade-off in system complexity. Database systems contain many components and features that must work together to meet client demand. Administrators responsible for maintaining database systems face a daunting task: they must determine the access characteristics of the client workload they are serving and tailor the system to optimize for it. Complicating matters, client workloads are known to shift in access patterns and load. Thus, administrators continuously perform this optimization task, refining system design and configuration to meet ever-changing client request patterns. Researchers have focused on creating next-generation, natively adaptive database systems to address this administrator burden. Natively adaptive database systems construct client-request models, determine workload characteristics, and tailor processing strategies to optimize accordingly. These systems continuously refine their models, ensuring they are responsive to workload shifts. While these new systems show promise in adapting system behaviour to their environment, existing, popularly-used database systems lack these adaptive capabilities. Porting the ideas in these new adaptive systems to existing infrastructure requires monumental engineering effort, slowing their adoption and leaving users stranded with their existing, non-adaptive database systems. In this thesis, I present Dendrite, a framework that easily ``bolts on'' to existing database systems to endow them with adaptive capabilities. Dendrite captures database system behaviour in a system-agnostic fashion, ensuring that its techniques are generalizable. It compares captured behaviour to determine how system behaviour changes over time and with respect to idealized system performance. These differences are matched against configurable adaption rules, which deploy user-defined functions to remedy performance problems. As such, Dendrite can deploy whatever adaptions are necessary to address a behaviour shift and tailor the system to the workload at hand. Dendrite has low tracking overhead, making it practical for intensive database system deployments

    University of Windsor Graduate Calendar 2022 Fall

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    https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1025/thumbnail.jp

    University of Windsor Graduate Calendar 2022 Winter

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    https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1023/thumbnail.jp

    University of Windsor Graduate Calendar 2022 Spring

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    https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1024/thumbnail.jp

    Applications and Experiences of Quality Control

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    The rich palette of topics set out in this book provides a sufficiently broad overview of the developments in the field of quality control. By providing detailed information on various aspects of quality control, this book can serve as a basis for starting interdisciplinary cooperation, which has increasingly become an integral part of scientific and applied research

    University of Windsor Graduate Calendar 2021 Fall

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    https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1022/thumbnail.jp
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