No description available.

Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-10-06T16:29:28Z No. of bitstreams: 1 Maurício de Oliveira Saraiva_.pdf: 6467007 bytes, checksum: 7a0d95202fd7af8fa777e0b1cb5f6fb0 (MD5) / Made available in DSpace on 2016-10-06T16:29:28Z (GMT). No. of bitstreams: 1 Maurício de Oliveira Saraiva_.pdf: 6467007 bytes, checksum: 7a0d95202fd7af8fa777e0b1cb5f6fb0 (MD5) Previous issue date: 2016-07-28 / UNICO - Universidade Corporativa dos Correios / A evolução da tecnologia tem permitido um suporte cada vez melhor à disciplina de gerenciamento de processos de negócio (BPM). A automação de práticas, a partir de ferramentas de modelagem, possibilita construir modelos visando apoiar as organizações no desenho e gerenciamento de seus processos. Em BPM, a transformação e melhoria contínua de processos são fundamentais para o gerenciamento da organização e os modelos de processos de negócio devem acompanhar essa evolução. Para realizar a composição desses modelos, seja pela transformação de um ou mais processos ou pela fusão de organizações, analistas usam as técnicas disponíveis na literatura. Porém, frequentemente elas são consideradas imprecisas ao não assegurar a correta integração dos modelos. Consequentemente, compor modelos de processos de negócio se torna uma tarefa difícil, custosa e propensa a erros, uma vez que as técnicas existentes criam modelos compostos difíceis de entendimento baseados em grafos e notação genérica que não correspondem à realidade do mercado de trabalho. Portanto, este trabalho propõe uma técnica de composição de modelos de processos de negócio que reúne, em uma única fonte, o conjunto das técnicas mais utilizadas na literatura, bem como dá suporte à composição de modelos direcionada para uma notação largamente conhecida e utilizada pelas organizações. Além disso, propõe a implementação de uma ferramenta, baseada nessa técnica, que foi criada para definir a similaridade e apoiar a integração de modelos de forma semiautomática. Por fim, estudos experimentais foram realizados com analistas que resolveram seis cenários de composição de modelos, tanto de forma manual como com o apoio dessa ferramenta, cujo resultado mostrou que a técnica proposta, de fato, melhora a precisão e reduz o esforço de composição, proporcionando redução de custos e aumento de produtividade. / The evolution of technology has allowed an increasingly better support to the discipline of business process management (BPM). The automation of practices from modeling tools, allows building models to support organizations in the design and management of its processes. In BPM, the transformation and continuous improvement of methods are fundamental to the management of the organization and models of business processes should follow this evolution. To perform the merge of these models, by the transformation of one or more processes, or by merging of organizations, software analysts use the techniques available in the literature. However, frequently they are considered imprecise, by not ensuring the correct integration of models. Consequently, merging business processes models becomes a difficult, error prone task, since existing techniques create composite models difficult to understand based on graphs and generic notation that does not match to the industrial reality. Therefore, this study proposes a merging technique of business process models that combines in a single source, some of the most used techniques available in the literature, and supports merging of models directed to a notation widely known and used by organizations. Furthermore, it also proposes the implementation of a tool, based on this technique, which was created to define the similarity and support the integration of models in a semi-automatic way. Lastly, experimental studies were performed with analysts who solved six scenarios of merging models, both manually and with the help of this tool. The result showed that the proposed technique, in fact, improves the accuracy and reduces composition effort, providing cost savings and increased productivity.

In der Metakontrastmaskierung wird die Sichtbarkeit des ersten Stimulus (Target) durch das Auftreten eines zweiten Stimulus (Maske) reduziert. Zwei Maskierungsfunktionen (MF) treten hauptsächlich auf: Typ A, wenn die Sichtbarkeit mit ansteigender SOA zumimmt, und Typ-B, wenn die Sichtbarkeit in kurzer und langer SOA hoch ist und auf ein Minimum in mittlerer SOA abfällt. In fünf Studien wurde systematisch untersucht welchen Einfluss experimentelle Parameter auf das Auftreten der MF haben. Je länger die Maske im Verhältnis zum Target präsentiert wird, desto weiter verschiebt sich das Minimum der MF hin zu kürzerer SOA und desto mehr ähnelt sie einer Typ-A-MF (monoton ansteigend). Die Maskierung ist in kleinen Stimuli stärker als in großen Stimuli, sowohl im Zentrum als auch in der Peripherie. Bei beiden Stimulusgrößen findet bei der kürzesten SOA die stärkste Maskierung statt. MF unterscheiden sich nicht, wenn sich die Vorhersagbarkeit der Präsentationsorte der Stimuli unterscheidet. Scheinbewegungen werden in langen SOAs eher wahrgenommen als in kurzen SOAs. Darüber hinaus wurden inter-individuelle Unterschiede gefunden, die Einblicke in die Mechanismen erlauben, die in der Metakontrastmaskierung beteiligt sind. Einige Versuchspersonen zeigen eine Typ-A-MF und berichten Scheinbewegungen in der Abfolge der Stimuli wahrzunehmen, hauptsächlich in langen SOAs. Andere zeigen eine Typ-B-MF und berichten negative Nachbilder in Form des Tagets im Inneren der Maske wahrzunehmen, hauptsächlich in kurzen SOAs. Typ-A- und Typ-B-Versuchspersonen unterscheiden sich in ihrer Top-Down-Verarbeitung der Stimuli, nicht aber in ihrer Bottom-Up-Verarbeitung. Zwei Prozesse stellten sich heraus, die in der Verarbeitung der Metakontraststimuli beteiligt sein könnten. Nach der Integrations-Segregations-Theorie steht die getrennte (segregierte) Wahrnehmung zweier Stimuli, die Scheinbewegungen ermöglicht, mit dem Segregationsprozess in Zusammenhang. Dagegen steht die gleichzeitige (integrierte) Wahrnehmung zweier nacheinander folgender Stimuli mit dem Integrationsprozess in Zusammenhang. Da Prozess 1 stark mit einer Typ-A-MF verknüpft ist, einhergehend mit der Wahrnehmung von Scheinbewegungen, könnte dieser Prozess dem Segregationsprozess entsprechen. Da Prozess 2 stark mit einer Typ-B-MF verknüpft ist, einhergehend mit der Wahrnehmung negativer Nachbilder, könnte dieser Prozess dem Integrationsprozess entsprechen. Es wird angenommen, dass diese beiden Prozesse an der bewussten Wahrnehmung des Targets in der Metakontrastmaskierung beteiligt sind.

The use of design process models is of great importance for developing better products. Indeed, it is one of the factors that may differentiate the best companies from the rest. However, their adoption in companies is declining. Usefulness and usability issues may be responsible for process models not to meet the needs of its users. The goal of this research is to provide deeper understanding of the users needs of design process models. Three main perspectives are provided: (1) why organizations use process models, (2) who are the users of process models, and (3) how the context of use of process models is. The research methodology adopted was the Design Research Methodology (DRM). Three stages were performed: (i) Research Clarification, (ii) Descriptive Study I, and (iii) Prescriptive Study. In the first stage, an initial literature review was carried out to collect evidences of why researching process models and their users needs is relevant for the design theory. During the second stage (Descriptive Study I), literature was reviewed to identify the purposes of use of design process models and its potential users; a focusgroup section with 24 subject matter experts was carried out to evaluate these purposes and identify process model users; and, lastly, a case study was perfomed to investigate the context of use of design process models in one organization and to portray the profile of the core users. Finally, the third stage (Prescriptive Study) aimed to uncover directions for organizations develop user-centered design process models. Four main results were achieved through this research. The first result is a deep understanding of three types of application of the design process models: (a) develop the design activity, (b) manage the design project, and (c) improve the design process. The purposes for these aplications were investigated and their level of importance were revealed. In addition, it was mapped the core users of process models for the three applications. The second result is the definition of the context of use of the models.Three dimensions of the context were depicted: the product, the design process, and the organizational structure. The third result is the set of users profiles. Empathy Maps were elaborated to represent the profiles of product engineers, project managers, and technical leaders. The last result consists in recommendations regarding the content provided to users and the process models system design. Finally, industrial practitioners will benefit from this research once it was provided evidences that the activity development application type is not properly considered in organization and that important users needs are not getting proper attention in the current models. Therefore, they will be able to make use of the recommendations outlined here. / O uso de modelos de processo de design é de grande importância no desenvolvimento de novos produtos. De fato, isto é um dos fatores que pode diferenciar as melhores empresas das outras. De qualquer modo, a adoção dos modelos nas empresas esta declinando. Problemas em utilidade e usabilidade podem ser responsáveis pelos modelos não satisfazerem as necessidades de seus usuários. Nesta pesquisa, busca-se entender as necessidades dos usuários dos modelos de processo de design. Três perspectivas são dadas: (1) porquê organizações usam modelos de processo, (2) quem são os usuários dos modelos de processo e (3) como é o contexto de uso de modelos de processo. A metodologia de pesquisa adotada foi a Metodologia de Pesquisa em Design (DRM). Três estágios foram realizados: (i) Clarificação de Pesquisa, (ii) Estudo Descritivo I, e (iii) Estudo Prescritivo. No primeiro estágio, uma revisão inicial da literatura foi executada para coletar evidências do porquê estudar modelos de processo e as necessidades de seus usuários é relevante para a teoria de design. No segundo estágio (Estudo Descritivo I), revisão da literatura ajudou a identificar os propósitos de uso de modelos de processo de design e os seus potenciais usuários; uma seção de focus group com 24 especialistas no assunto foi executado para avaliar estes propósitos e identificar usuários dos modelos de processo; e, por fim, um estudo de caso foi realizado para investigar o contesto de uso dos modelos em uma organização e para retratar o perfil dos usuários principais. Finalmente, o terceiro estágio (Estudo Prescritivo) buscou revelar direções para que as organizações desenvolvam modelos de processo de design centrados em seus usuários. Quatro principais resultados foram alcançados por meio desta pesquisa. O primeiro resultado é um entendimento profundo dos três tipos de aplicação dos modelos de processo: (a) desenvolver atividade de design, (b) gerenciar o projeto de design, e (c) melhorar o processo de design. O propósito destas três aplicações foram investigadas e os níveis de importância evidenciados. Além disso, os usuários centrais dos modelos de processo foram mapeados. O segundo resultado é a definição do contexto de uso dos modelos. Três dimensões do contexto foram retratados: o produto, o processo de design, e a estrutura organizacional. O terceiro resultado é o conjunto de perfis dos usuários. Mapas de Empatia foram elaborados para representar os perfis de engenheiros de produto, gerentes de projeto, e líderes técnicos. O último resultado consiste em recomendações feitas a respeito do conteúdo fornecido aos usuários e o sistema a ser desenvolvido. Finalmente, profissionais da indústria podem beneficiar desta pesquisa uma vez que evidências são fornecidas de que a aplicação de desenvolvimento das atividades não é adequadamente considerada em organizações e que necessidades importantes dos usuários não recebem atenção satisfatória nos modelos atuais. Sendo assim, eles serão capazes de fazer uso das recomendações aqui feitas.

Heavy episodic drinking is linked with poorer academic performance, injury, and risk behaviors among college students. Understanding the cognitive and motivational factors that influence self-control of alcohol use is critical to identifying students' risk factors and developing interventions. Dual process models characterize alcohol use patterns as a function of automatic appetitive responses to alcohol-related stimuli and executive control functions. These processes may be influenced by contextual cues such as mood. The present research sought to better understand the cognitive-motivational mechanisms through which an established contextual cue for drinking - positive mood - influences alcohol use. Two studies examined the influence of positive mood induction on undergraduate drinkers' approach biases for alcohol cues and executive functioning using established and modified Stimulus Response Compatibility Tasks (SRC). Undergraduates who used alcohol at least once in the past month were recruited from the introductory psychology subject pool and randomized to positive or neutral mood induction conditions to determine whether positive mood: (1) increased approach bias or (2) impaired efforts to control alcohol cue responses. Prior to mood induction, participants completed individual difference measures related to alcohol use to evaluate potential moderators. Experiment 1 (N=93) examined post-induction alcohol approach bias and approach response inhibition using a stop-signal task within SRCs. Those in the positive mood condition did not exhibit greater approach bias or less inhibition, and mood effects were not moderated by individual differences as hypothesized. Experiment 2 (N=141) examined the influence of mood on approach bias and the ability to reverse established SRC responses to alcohol cues, with a pre-induction SRC to control for baseline approach biases. Again, positive mood did not significantly influence alcohol approach bias or executive control. Discussion: Results did not support positive mood influences on cognitive-motivational processes associated with drinking. The absence of mood effects may be a function of the type of positive mood induced or sensitivity of the SRC to detect alcohol-specific approach bias in this population. Future studies should explore these processes using alternate measures of alcohol-specific approach bias, response inhibition, and mood states that may be more specific to drinking.

The use of process models to support business analysts' idea-generation tasks has been a long-standing topic of interest in process improvement. We examine how two types of representations of organizational processes - textual and diagrammatic - assist analysts in developing innovative solutions to process-redesign tasks. The results of our study clarify the types of process-redesign ideas generated by analysts who work with text versus those who work with models. We find that the volume and originality of process-redesign ideas do not differ significantly but that appropriateness of ideas varies. We discuss the implications of these findings for research and practice in process improvement.

The use of design process models is of great importance for developing better products. Indeed, it is one of the factors that may differentiate the best companies from the rest. However, their adoption in companies is declining. Usefulness and usability issues may be responsible for process models not to meet the needs of its users. The goal of this research is to provide deeper understanding of the users needs of design process models. Three main perspectives are provided: (1) why organizations use process models, (2) who are the users of process models, and (3) how the context of use of process models is. The research methodology adopted was the Design Research Methodology (DRM). Three stages were performed: (i) Research Clarification, (ii) Descriptive Study I, and (iii) Prescriptive Study. In the first stage, an initial literature review was carried out to collect evidences of why researching process models and their users needs is relevant for the design theory. During the second stage (Descriptive Study I), literature was reviewed to identify the purposes of use of design process models and its potential users; a focusgroup section with 24 subject matter experts was carried out to evaluate these purposes and identify process model users; and, lastly, a case study was perfomed to investigate the context of use of design process models in one organization and to portray the profile of the core users. Finally, the third stage (Prescriptive Study) aimed to uncover directions for organizations develop user-centered design process models. Four main results were achieved through this research. The first result is a deep understanding of three types of application of the design process models: (a) develop the design activity, (b) manage the design project, and (c) improve the design process. The purposes for these aplications were investigated and their level of importance were revealed. In addition, it was mapped the core users of process models for the three applications. The second result is the definition of the context of use of the models.Three dimensions of the context were depicted: the product, the design process, and the organizational structure. The third result is the set of users profiles. Empathy Maps were elaborated to represent the profiles of product engineers, project managers, and technical leaders. The last result consists in recommendations regarding the content provided to users and the process models system design. Finally, industrial practitioners will benefit from this research once it was provided evidences that the activity development application type is not properly considered in organization and that important users needs are not getting proper attention in the current models. Therefore, they will be able to make use of the recommendations outlined here. / O uso de modelos de processo de design é de grande importância no desenvolvimento de novos produtos. De fato, isto é um dos fatores que pode diferenciar as melhores empresas das outras. De qualquer modo, a adoção dos modelos nas empresas esta declinando. Problemas em utilidade e usabilidade podem ser responsáveis pelos modelos não satisfazerem as necessidades de seus usuários. Nesta pesquisa, busca-se entender as necessidades dos usuários dos modelos de processo de design. Três perspectivas são dadas: (1) porquê organizações usam modelos de processo, (2) quem são os usuários dos modelos de processo e (3) como é o contexto de uso de modelos de processo. A metodologia de pesquisa adotada foi a Metodologia de Pesquisa em Design (DRM). Três estágios foram realizados: (i) Clarificação de Pesquisa, (ii) Estudo Descritivo I, e (iii) Estudo Prescritivo. No primeiro estágio, uma revisão inicial da literatura foi executada para coletar evidências do porquê estudar modelos de processo e as necessidades de seus usuários é relevante para a teoria de design. No segundo estágio (Estudo Descritivo I), revisão da literatura ajudou a identificar os propósitos de uso de modelos de processo de design e os seus potenciais usuários; uma seção de focus group com 24 especialistas no assunto foi executado para avaliar estes propósitos e identificar usuários dos modelos de processo; e, por fim, um estudo de caso foi realizado para investigar o contesto de uso dos modelos em uma organização e para retratar o perfil dos usuários principais. Finalmente, o terceiro estágio (Estudo Prescritivo) buscou revelar direções para que as organizações desenvolvam modelos de processo de design centrados em seus usuários. Quatro principais resultados foram alcançados por meio desta pesquisa. O primeiro resultado é um entendimento profundo dos três tipos de aplicação dos modelos de processo: (a) desenvolver atividade de design, (b) gerenciar o projeto de design, e (c) melhorar o processo de design. O propósito destas três aplicações foram investigadas e os níveis de importância evidenciados. Além disso, os usuários centrais dos modelos de processo foram mapeados. O segundo resultado é a definição do contexto de uso dos modelos. Três dimensões do contexto foram retratados: o produto, o processo de design, e a estrutura organizacional. O terceiro resultado é o conjunto de perfis dos usuários. Mapas de Empatia foram elaborados para representar os perfis de engenheiros de produto, gerentes de projeto, e líderes técnicos. O último resultado consiste em recomendações feitas a respeito do conteúdo fornecido aos usuários e o sistema a ser desenvolvido. Finalmente, profissionais da indústria podem beneficiar desta pesquisa uma vez que evidências são fornecidas de que a aplicação de desenvolvimento das atividades não é adequadamente considerada em organizações e que necessidades importantes dos usuários não recebem atenção satisfatória nos modelos atuais. Sendo assim, eles serão capazes de fazer uso das recomendações aqui feitas.

The concepts of processes and services can be used to structure both businesses and software systems. From a business perspective, the use of processes promises efficient management of organizations. From a software perspective, executable process descriptions provide a way to structure software systems according to the business process the systems should support. Furthermore, the concept of software services allows systems to be partitioned in a modular fashion, thereby enabling large-scale system integration on a technical level. By combining process descriptions with software services in service-based processes, it is feasible to address both business and more technical software needs. Aligning the business and software perspectives of processes and software services is, however, challenging, since implemented executable processes and software services need to cater for operational and strategic business needs as well as existing legacy software systems. In this thesis, several instruments are presented that aim at aiding the design and evolution of service-based processes. The aligning of operational business and software perspectives on process descriptions is addressed by the introduction of business and technical process model levels. These levels can be aligned by the use of a set of model transformations and associated transformation rules. Furthermore, the aligning is aided by introducing means for achieving flexibility on both the business and technical model levels. The development of service-based processes from a strategic business point of view is aided by the introduction of novel models and methods for goal-based design of software services. Taken together, the instruments can be used for the design and evolution of service-based processes. / QC 20100810 / REMS / Serviam

This thesis develops techniques for adjusting for selection bias using Gaussian process models. Selection bias is a key issue both in sample surveys and in observational studies for causal inference. Despite recently emerged techniques for dealing with selection bias in high-dimensional or complex situations, use of Gaussian process models and Bayesian hierarchical models in general has not been explored. Three approaches are developed for using Gaussian process models to estimate the population mean of a response variable with binary selection mechanism. The first approach models only the response with the selection probability being ignored. The second approach incorporates the selection probability when modeling the response using dependent Gaussian process priors. The third approach uses the selection probability as an additional covariate when modeling the response. The third approach requires knowledge of the selection probability, while the second approach can be used even when the selection probability is not available. In addition to these Gaussian process approaches, a new version of the Horvitz-Thompson estimator is also developed, which follows the conditionality principle and relates to importance sampling for Monte Carlo simulations. Simulation studies and the analysis of an example due to Kang and Schafer show that the Gaussian process approaches that consider the selection probability are able to not only correct selection bias effectively, but also control the sampling errors well, and therefore can often provide more efficient estimates than the methods tested that are not based on Gaussian process models, in both simple and complex situations. Even the Gaussian process approach that ignores the selection probability often, though not always, performs well when some selection bias is present. These results demonstrate the strength of Gaussian process models in dealing with selection bias, especially in high-dimensional or complex situations. These results also demonstrate that Gaussian process models can be implemented rather effectively so that the benefits of using Gaussian process models can be realized in practice, contrary to the common belief that highly flexible models are too complex to use practically for dealing with selection bias.

For industrial processes high availability and efficiency are important goals in plant operation. This thesis presents studies and development of tools for on-line treatment of process deterioration and model and sensor errors in order to achieve these goals. Deterioration of measurement devices, process components and process models has caused economical losses, plant failure and human losses. The development of on-line methods to prevent such losses is of special interest and has been conducted at The Department of Energy Technology, Mälardalen University. Important technological obstacles to implementing automatic on-line methods have been identified, such as data selection for adaptation and adaptation of data-driven models to new states. A new method has been developed for decision support by combining artificial intelligence methods and heat and mass balance models, and concepts are proposed for decision support in order to detect developing faults and to conduct appropriate maintenance actions. The methods have been implemented in simulation environment and evaluated on real process data when available. The results can be sumarised as successful development of a decision support method on a steam turbine by combining artificial neural networks and Bayesian networks, and identification of important obstacles for automation of methods for adaptation of heat and mass balance process models and data-driven models when they are subject to deterioration.