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Uma abordagem baseada em padrões para o intercâmbio entre especificações de workflows científicosBastos, Bruno Fernandes 20 August 2015 (has links)
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Previous issue date: 2015-08-20 / Workflows científicos vêm sendo utilizados para resolver problemas complexos em diferentes áreas. Sistemas Gerenciadores de Workflows Científicos (SGWfCs) são utilizados para a especificação e gerenciamento desses workflows. Porém, cada SGWfC pode possuir características diferentes e uma linguagem de especificação de workflows própria, dificultando o reuso dos workflows entre diferentes SGWfCs. A inexistência de uma padronização semântica dificulta ainda mais esse reuso, uma vez que elementos de modelagem de workflow presentes em alguns SGWfCS podem não ser mapeáveis em outros SGWfCs. O uso de uma linguagem intermediária para o intercâmbio de workflows científicos facilita o reuso de workflows desenvolvidos em diferentes SGWfCs ao permitir a definição de um arcabouço comum para esses SGWfCs. No entanto, uma linguagem desse tipo não impede que haja perda de informação semântica durante um processo de transformação de especificações entre esses SGWfCs, uma vez que essa linguagem deve ser robusta o suficiente para representar a semântica de diversos workflows desenvolvidos em diferentes SGWfCs. A existência de padrões (patterns) em workflows científicos pode ajudar a explicitar as informações semânticas mais importantes para a construção desses workflows. Assim a proposta deste trabalho é oferecer uma abordagem baseada em padrões para o intercâmbio entre especificações de workflows científicos, empregando uma linguagem intermediária com suporte a informações semânticas obtidas através da descrição dos padrões. Esta dissertação analisa os resultados obtidos com essa proposta a partir da aplicação da abordagem em especificações de workflows armazenadas no repositório myExperiment. / Scientific workflows have been used to solve complex problems in different areas. Scientific Workflow Management Systems (SWfMSs) are used for specifying and managing these workflows. Nevertheless, each SWfMS may have different characteristics and its own workflow specification language, making its reuse accross different SWfMSs a difficult process. The lack of semantic standardization makes this reuse even more difficult, since the workflow modeling elements available in some SWfMSs may not be mapped onto others SWfMSs. The use of an intermediate language for the interchange of scientific workflows may help with the reuse of workflows developed in different SWfMSs, as it allows for the definition of a common framework for these SWfMSs. Nonetheless, such a language does not prevent the loss of some semantic information during a specification transformation process between different SWfMSs, since this language must be robust enough to represent the semantics of diverse workflows developed in different SWfMSs. The identification of scientific workflow patterns may help to describe the most important semantic information for the construction of these workflows. Thus, the purpose of this study is to provide a pattern-based approach for the interchange of scientific workflow specifications, using an intermediate language that supports semantic information obtained through the description of workflow patterns. This thesis also analyses the results obtained with the proposed approach being applied to workflow specifications stored in the myExperiment repository.
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A unified framework for design, deployment, execution, and recommendation of machine learning experiments = Uma ferramenta unificada para projeto, desenvolvimento, execução e recomendação de experimentos de aprendizado de máquina / Uma ferramenta unificada para projeto, desenvolvimento, execução e recomendação de experimentos de aprendizado de máquinaWerneck, Rafael de Oliveira, 1989- 25 August 2018 (has links)
Orientadores: Ricardo da Silva Torres, Anderson de Rezende Rocha / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-25T19:48:27Z (GMT). No. of bitstreams: 1
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Previous issue date: 2014 / Resumo: Devido ao grande crescimento do uso de tecnologias para a aquisição de dados, temos que lidar com grandes e complexos conjuntos de dados a fim de extrair conhecimento que possa auxiliar o processo de tomada de decisão em diversos domínios de aplicação. Uma solução típica para abordar esta questão se baseia na utilização de métodos de aprendizado de máquina, que são métodos computacionais que extraem conhecimento útil a partir de experiências para melhorar o desempenho de aplicações-alvo. Existem diversas bibliotecas e arcabouços na literatura que oferecem apoio à execução de experimentos de aprendizado de máquina, no entanto, alguns não são flexíveis o suficiente para poderem ser estendidos com novos métodos, além de não oferecerem mecanismos que permitam o reuso de soluções de sucesso concebidos em experimentos anteriores na ferramenta. Neste trabalho, propomos um arcabouço para automatizar experimentos de aprendizado de máquina, oferecendo um ambiente padronizado baseado em workflow, tornando mais fácil a tarefa de avaliar diferentes descritores de características, classificadores e abordagens de fusão em uma ampla gama de tarefas. Também propomos o uso de medidas de similaridade e métodos de learning-to-rank em um cenário de recomendação, para que usuários possam ter acesso a soluções alternativas envolvendo experimentos de aprendizado de máquina. Nós realizamos experimentos com quatro medidas de similaridade (Jaccard, Sorensen, Jaro-Winkler e baseada em TF-IDF) e um método de learning-to-rank (LRAR) na tarefa de recomendar workflows modelados como uma sequência de atividades. Os resultados dos experimentos mostram que a medida Jaro-Winkler obteve o melhor desempenho, com resultados comparáveis aos observados para o método LRAR. Em ambos os casos, as recomendações realizadas são promissoras, e podem ajudar usuários reais em diferentes tarefas de aprendizado de máquina / Abstract: Due to the large growth of the use of technologies for data acquisition, we have to handle large and complex data sets in order to extract knowledge that can support the decision-making process in several domains. A typical solution for addressing this issue relies on the use of machine learning methods, which are computational methods that extract useful knowledge from experience to improve performance of target applications. There are several libraries and frameworks in the literature that support the execution of machine learning experiments. However, some of them are not flexible enough for being extended with novel methods and they do not support reusing of successful solutions devised in previous experiments made in the framework. In this work, we propose a framework for automating machine learning experiments that provides a workflow-based standardized environment and makes it easy to evaluate different feature descriptors, classifiers, and fusion approaches in a wide range of tasks. We also propose the use of similarity measures and learning-to-rank methods in a recommendation scenario, in which users may have access to alternative machine learning experiments. We performed experiments with four similarity measures (Jaccard, Sorensen, Jaro-Winkler, and a TF-IDF-based measure) and one learning-to-rank method (LRAR) in the task of recommending workflows modeled as a sequence of activities. Experimental results show that Jaro-Winkler yields the highest effectiveness performance with comparable results to those observed for LRAR. In both cases, the recommendations performed are very promising and might help real-world users in different daily machine learning tasks / Mestrado / Ciência da Computação / Mestre em Ciência da Computação
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Efficient support for data-intensive scientific workflows on geo-distributed clouds / Support pour l'exécution efficace des workflows scientifiques à traitement intensif de données sur les cloud géo-distribuésPineda Morales, Luis Eduardo 24 May 2017 (has links)
D’ici 2020, l’univers numérique atteindra 44 zettaoctets puisqu’il double tous les deux ans. Les données se présentent sous les formes les plus diverses et proviennent de sources géographiquement dispersées. L’explosion de données crée un besoin sans précédent en terme de stockage et de traitement de données, mais aussi en terme de logiciels de traitement de données capables d’exploiter au mieux ces ressources informatiques. Ces applications à grande échelle prennent souvent la forme de workflows qui aident à définir les dépendances de données entre leurs différents composants. De plus en plus de workflows scientifiques sont exécutés sur des clouds car ils constituent une alternative rentable pour le calcul intensif. Parfois, les workflows doivent être répartis sur plusieurs data centers. Soit parce qu’ils dépassent la capacité d’un site unique en raison de leurs énormes besoins de stockage et de calcul, soit car les données qu’ils traitent sont dispersées dans différents endroits. L’exécution de workflows multisite entraîne plusieurs problèmes, pour lesquels peu de solutions ont été développées : il n’existe pas de système de fichiers commun pour le transfert de données, les latences inter-sites sont élevées et la gestion centralisée devient un goulet d’étranglement. Cette thèse présente trois contributions qui visent à réduire l’écart entre les exécutions de workflows sur un seul site ou plusieurs data centers. Tout d’abord, nous présentons plusieurs stratégies pour le soutien efficace de l’exécution des workflows sur des clouds multisite en réduisant le coût des opérations de métadonnées. Ensuite, nous expliquons comment la manipulation sélective des métadonnées, classées par fréquence d’accès, améliore la performance des workflows dans un environnement multisite. Enfin, nous examinons une approche différente pour optimiser l’exécution de workflows sur le cloud en étudiant les paramètres d’exécution pour modéliser le passage élastique à l’échelle. / By 2020, the digital universe is expected to reach 44 zettabytes, as it is doubling every two years. Data come in the most diverse shapes and from the most geographically dispersed sources ever. The data explosion calls for applications capable of highlyscalable, distributed computation, and for infrastructures with massive storage and processing power to support them. These large-scale applications are often expressed as workflows that help defining data dependencies between their different components. More and more scientific workflows are executed on clouds, for they are a cost-effective alternative for intensive computing. Sometimes, workflows must be executed across multiple geodistributed cloud datacenters. It is either because these workflows exceed a single site capacity due to their huge storage and computation requirements, or because the data they process is scattered in different locations. Multisite workflow execution brings about several issues, for which little support has been developed: there is no common ile system for data transfer, inter-site latencies are high, and centralized management becomes a bottleneck. This thesis consists of three contributions towards bridging the gap between single- and multisite workflow execution. First, we present several design strategies to eficiently support the execution of workflow engines across multisite clouds, by reducing the cost of metadata operations. Then, we take one step further and explain how selective handling of metadata, classified by frequency of access, improves workflows performance in a multisite environment. Finally, we look into a different approach to optimize cloud workflow execution by studying some parameters to model and steer elastic scaling.
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Transformation monolithischer Business-Softwaresysteme in verteilte, workflowbasierte Client-Server-ArchitekturenKrellner, Björn, Reichel, Thomas, Rünger, Gudula, Ferber, Marvin, Hunold, Sascha, Rauber, Thomas, Berndt, Jürgen, Nobbers, Ingo 22 July 2010 (has links) (PDF)
Im Projekt TransBS wurden existierende, über viele Jahre gewachsene Softwaresysteme zur Realisierung von Geschäftsprozessen betrachtet, in denen Aspekte wie Verteiltheit, Anpassbarkeit an heterogene Plattformen oder Skalierbarkeit zunehmend Bedeutung erlangen. Die notwendigen Anpassungen der Systeme sind nur schwierig und mit erheblichem Aufwand zu realisieren, da sie eine vollständige Reorganisation erfordern. Deshalb wurde im Projekt eine Methodik entwickelt und prototypisch realisiert, die monolithische Legacy-Business-Softwaresysteme in eine komponentenbasierte, verteilte Client-Server-Architektur mit konfigurierbaren Workflows für heterogene Plattformen schrittweise überführt. Die entwickelten Werkzeuge zur Transformation wurden exemplarisch mit einem gegebenen Softwaresystem evaluiert und können für weitere Problemstellungen der Analyse und Transformation von Business-Software eingesetzt werden.
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Dokumenthantering i en kommunal organisation. / Document management at the city planning department.Ribbershed, Håkan January 2001 (has links)
Examensarbetet berör frågor kring arkivering och dokumenthantering på stads-byggnadsförvaltningen i Trollhättans kommun. Problem som kommunen har är dagslägets hantering av digitala filer. / Se mailadressen
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Aplikace procesního řízení v podniku / The Proposal of Process Management in the CompanyČáchová, Barbora January 2013 (has links)
The master thesis is focused on the application of process management in the company PROFI am BAU CM, Ltd. The theoretical part deals with the explanation of the process approach in business management and defines the basic concepts used, as well as analysis of the current situation in the company. Based on the acquired knowledge are described and analyzed the main business processes and proposed optimization steps.
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An Evaluation Platform for Semantic Web TechnologyÅberg, Cécile January 2006 (has links)
The vision of the Semantic Web aims at enhancing today's Web in order to provide a more efficient and reliable environment for both providers and consumers of Web resources (i.e. information and services). To deploy the Semantic Web, various technologies have been developed, such as machine understandable description languages, language parsers, goal matchers, and resource composition algorithms. Since the Semantic Web is just emerging, each technology tends to make assumptions about different aspects of the Semantic Web's architecture and use, such as the kind of applications that will be deployed, the resource descriptions, the consumers' and providers' requirements, and the existence and capabilities of other technologies. In order to ensure the deployment of a robust and useful Semantic Web and the applications that will rely on it, several aspects of the technologies must be investigated, such as whether the assumptions made are reasonable, whether the existing technologies allow construction of a usable Semantic Web, and the systematic identification of which technology to use when designing new applications. In this thesis we provide a means of investigating these aspects for service discovery, which is a critical task in the context of the Semantic Web. We propose a simulation and evaluation platform for evaluating current and future Semantic Web technology with different resource sets and consumer and provider requirements. For this purpose we provide a model to represent the Semantic Web, a model of the evaluation platform, an implementation of the evaluation platform as a multi-agent system, and an illustrative use of the platform to evaluate some service discovery technology in a travel scenario. The implementation of the platform shows the feasibility of our evaluation approach. We show how the platform provides a controlled setting to support the systematic identification of bottlenecks and other challenges for new Semantic Web applications. Finally, the evaluation shows that the platform can be used to assess technology with respect to both hardware issues such as the kind and number of computers involved in a discovery scenario, and other issues such as the evaluation of the quality of the service discovery result.
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RAfEG: Referenz-Systemarchitektur und prototypische Umsetzung -- Ausschnitt aus dem Abschlussbericht zum Projekt "Referenzarchitektur für E-Government" (RAfEG) --Kunis, Raphael, Rünger, Gudula 07 December 2007 (has links) (PDF)
Das Ziel des RAfEG-Projektes bestand in der Entwicklung einer Referenzarchitektur "E-Government", die die notwendigen Komponenten zur Realisierung informations- und kommunikationstechnischer Systeme (IuK-Systeme) für typische Prozesse in nachgeordneten Behörden der Innenministerien der Bundesländer bereitstellte. Die Architektur RAfEG stellt einen ganzheitlichen Ansatz dar, der viele wesentliche Aspekte, beginnend mit der formalen Beschreibung der fachlichen Zusammenhänge bis hin zur Entwicklung von verteilt agierenden Softwarekomponenten behördlicher Geschäftsprozesse umfasst. Die Architektur liefert unter Berücksichtigung hardwareseitiger Voraussetzungen die Struktur von Softwarekomponenten zur Verwaltungsautomatisierung. Die Architektur RAfEG wurde als räumlich verteiltes komponentenbasiertes Softwaresystem entworfen. Dabei war es notwendig, Konzepte zur effizienten Nutzung von heterogenen Systemen für interaktive Anwendungen im Bereich E-Government zu entwickeln. Die prototypische Umsetzung der Architektur erfolgte für Planfeststellungsverfahren/Plangenehmigungsprozesse am Beispiel des Regierungspräsidiums Leipzig. Das Vorhaben war geprägt von der Entwicklung eines durchgängigen Konzeptes zur optimalen IuK-technischen Unterstützung von Verwaltungsprozessen. Dies führte von der Modellierung der fachlichen Zusammenhänge (Fachkonzept) über die entwicklungsorientierte, methodische Abbildung der zu implementierenden Sachverhalte (Datenverarbeitungskonzept) bis zur komponentenbasierten Softwareentwicklung (Implementierungskonzept). Dieses Konzept mündete in einer Referenzarchitektur für typische E-Government-Prozesse. Dazu wurden neben den rein fachlichen, aufgabenbezogenen Aspekten insbesondere Sicherheitsaspekte sowie technische und organisatorische Schnittstellen ausführlich betrachtet. Der durchgängige Einsatz von Open Source Software führt hierbei zu einer kosteneffizienten, flexiblen Referenzlösung, die durch ihre komponentenbasierte Struktur als weiteren Aspekt sehr gut an spezielle Anforderungen anpassbar ist.
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Verifying Modal Specifications of Workflow Nets : using Constraint Solving and Reduction Methods / Vérification de spécifications modales de réseaux worklows à l'aide de solveurs de contraintes et de methodes de résolutionBride, Hadrien 24 October 2016 (has links)
De nos jours, les workflows sont largement utilisés par les entreprises et les organisations en vue d’améliorer l’efficacité organisationnelle, la réactivité et la rentabilité en gérant les tâches et les étapes de processus opérationnels. La vérification des spécifications est devenue obligatoire afin d’assurer que ces processus sont correctement conçus et atteignent le niveau de confiance et de qualité attendu.Dans ce contexte, cette thèse porte sur la vérification de spécifications modales – comportements nécessaires ou recevables impliquant plusieurs activités et leurs causalités – de workflows nets – une classe de réseaux de Petri adaptés à la description de workflows. En particulier, cette thèse définit un cadre novateur permettant de modéliser les exécutions de workflow nets,avec ou sans données, et de vérifier des spécifications modales à l’aide de systèmes de contraintes. Elle présente également deux méthodes de réduction préservant la "generalised soundness" et la validité d’une spécification modale donnée. Ces méthodes de réduction sont ensuite présentées comme des étapes de prétraitement réduisant la taille des workflow nets, de sorte que la vérification des propriétés conservées puisse être effectuée sur de plus petites instances. Enfin, cette thèse présente les outils qui ont été mis en oeuvre ainsi que des expérimentations qui ont été menées sur un grand nombre de workflows industriels afin de valider les approches proposées dans cette thèse. Ces résultats expérimentaux convaincants mettent en évidence l’efficacité, l’efficience et le passage à l’échelle de la méthode vérification de spécification modales ainsi que des méthodes de réduction introduites dans cette thèse. / Nowadays workflows are extensively used by companies and organisations in order to improve organizationaleffciency, responsiveness and profitability by managing the tasks and steps of business processes. Theverification of specifications has become mandatory to ensure that such processes are properly designedand reach the expected level of trust and quality. In this context, this thesis addresses the verification ofmodal specifications – necessary or admissible behaviour involving several activities and their causalities –of workflow nets – a Petri nets class suited for the description of workflows.In particular, it defines an innovative constraint system based framework to model executions of ordinary as wellas coloured workflow nets, and verify modal specifications. Further, it presents powerful reduction methodspreserving properties of interest such as generalised soundness and correctness of a given modal specification.Such reduction methods are then portrayed as pre-processing steps reducing workflow nets size, so that theverification of preserved properties can be carried out on smaller instances.Finally, as a practical contribution, this thesis introduces the tools that have been implemented as well asexperimentations that have been carried out over industrial workflow nets in order to validate the approachesproposed in this thesis. The convincing experimental results highlight the effectiveness, effciency andscalability of the modal specification verification method and reduction methods introduced in this thesis.
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Supporting Interdisciplinary Healthcare Team Dynamics with Business Process ManagementCatal, Nihan January 2016 (has links)
[Context] Interdisciplinary healthcare teams (IHTs) include practitioners from different disciplines who collaborate for providing care to patients. IHTs often follow clinical workflows composed of tasks that must be executed by practitioners with specific capabilities. The membership in an IHT can however evolve over time for a given patient. [Problem] Existing Business Process Management (BPM) suites and their workflow execution engines are designed for supporting and monitoring general workflows, but they are insufficient in supporting the allocation of tasks to the most suitable practitioners during the execution of healthcare workflows in a dynamic context. [Methodology] Using Design Science Research, this thesis builds on top of an existing semantic layer, which includes an ontology defining IHT team concepts and relationships that are used to reason automatically about team dynamics, in order to add dynamic team management to BPM suites. It does so by proposing and designing middleware (including a generic interface) that enables the semantic layer to command the BPM suite to allocate suitable practitioners to tasks during the execution of clinical workflows. The design and implementation of this middleware are discussed, and the latter is tested on a commercial BPM suite for two realistic clinical processes. [Results] The proof-of-concept implementation demonstrates the feasibility of using middleware with a generic interface to add support for IHT executing BPM suite when managing a patient. In addition, the thesis also demonstrates that the ontology used in the semantic layer is minimal, that is, all of its concepts and relationships are necessary for the required team functionalities (usually absent from BPM tools) to work properly.
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