The use of models for designing and developing Information Systems (IS) has changed in recent years. Models are no longer considered a peripheral documentation medium that is poorly maintained and often neglected. Rather, models are increasingly seen as essential parts of the final product—as central artifacts that drive and guide the development efforts. The knowledge that modelers rely on when designing models is represented as formal models and clearly defined rules for transforming the models. The flexibility, reliability, and effectiveness offered by the formal models and the transformations are making Model Driven Development (MDD) a popular choice for building IS. Models also serve in describing enterprise design, where enterprise-level models capture organizational knowledge and aid in understanding, improving, and growing the enterprise. Enterprise Modeling (EM) offers a structured and unified view of the enterprise, thereby enabling more informed and accurate decisions to be made. Many MDD approaches have been proposed to tackle a wide range of IS-related issues, but little attention is being paid to the source of the knowledge captured by the IS models. EM approaches capture organizational knowledge and provide the necessary input and underlying context for designing IS. However, the results produced by EM approaches need to be manually analyzed by modelers to create the initial MDD model. This interruption of the MDD process represents a gap between enterprise models and MDD models. Limited research has been done to connect EM to MDD in a systematic and structured manner based on the principles of model-driven development. This thesis proposes a unifying meta-model for integrating EM and MDD. The meta-model captures the inherent links that exist between organizational knowledge and IS design. This helps to improve the alignment between organizational goals and the IS that are created to support them. The research presented herein follows the guidelines of the design science research methodology. It starts with a state-of-the-art survey of the current relationship between MDD and prior stages of development. The findings of the survey are used to elicit a set of necessary properties for integrating EM and MDD. The unifying meta-model is then proposed as the basis for an integrated IS development approach that applies the principles of MDD and starts on the enterprise level by considering enterprise models in the development process. The design of the meta-model supports the elicited integration properties. The unifying meta-model is based on the Enterprise Knowledge Development (EKD) approach to EM. A prototype tool is developed to support the unifying meta-model, following a study to choose a suitable implementation environment. The use of the unifying meta-model is demonstrated through the implemented tool platform using an example case study, revealing its advantages and highlighting the potential for improvement and future development.

Certain electrophysiological markers hold promise in distinguishing individuals with major depressive disorder (MDD) and in predicting antidepressant response, thereby assisting with assessment and optimizing treatment, respectively. This thesis examined resting brain activity via electroencephalographic (EEG) recordings, as well as EEG-derived event-related potentials (ERPs) to auditory stimuli and facial expression presentations in individuals with MDD and controls. Additionally, the utility of resting EEG as well as auditory ERPs (AEPs), and the associated loudness-dependence of AEPs (LDAEP) slope, were assessed in predicating outcome to chronic treatment with one of three antidepressant regimens [escitalopram (ESC); bupropion (BUP); ESC+BUP]. Relative to controls, depressed adults had lower pretreatment cortical activity in regions implicated in approach motives/positive processing. Increased anterior cingulate cortex (ACC)-localized theta was observed, possibly reflecting emotion/cognitive regulation disturbances in the disorder. AEPs and LDAEPs, putative indices of serotonin activity (implicated in MDD etiology), were largely unaltered in MDD. Assessment of ERPs to facial expression processing indicated slightly blunted late preconscious perceptual processing of expressions, and prolonged processing of intensely sad faces in MDD. Faces were rated as sadder overall in MDD, indicating a negative processing bias. Treatment responders (vs. non-responders) exhibited baseline cortical hypoactivity; after a week of treatment, cortical arousal emerged in responders. Increased baseline left fronto-cortical activity and early shifts towards this profile were noted in responders (vs. non-responders). Responders exhibited a steep, and non-responders shallow, baseline N1 LDAEP derived from primary auditory cortex activity. P2 LDAEP slopes (primary auditory cortex-derived) increased after a week of treatment in responders and decreased in non-responders. Consistent with overall findings, ESC responders displayed baseline cortical hypoactivity and steep LDAEP-sLORETA slopes (vs. non-responders). BUP responders also exhibited steep baseline slopes and high ACC theta. These results indicate that specific resting brain activity profiles appear to distinguish depressed from non-depressed individuals. Subtle ERP modulations to simple auditory and emotive processing also existed in MDD. Resting alpha power, ACC theta activity and LDAEP slopes predicted antidepressant response in general, but were limited in predicting outcome to a particular treatment, which may be associated with limited sample sizes.

Unternehmen agieren heute in einer hochdynamischen Umwelt, wodurch die Anforderungen an Business Intelligence-Systeme (BI-Systeme) sich stetig verändern. Durch zügiges Reagieren darauf können sich Unternehmen Wettbewerbsvorteile verschaffen. Die dazu notwendige Wandlungsfähigkeit von BI-Systemen setzt voraus, dass bereits die BI-Architektur auf Flexibilität ausgelegt ist. Die Anwendung des Paradigmas der modellgetriebenen Softwareentwicklung auf die Domäne des Data Warehouse Engineerings (DWE) kommt diesem Bedarf nach. Zudem muss neben der Agilität von BI-Systemen auch der Faktor der Korrektheitsprüfung nach vorgenommenen Änderungen betrachtet werden. Es soll untersucht werden, inwieweit sich die im modellgetriebenen DWE anfallenden Metadaten zur Unterstützung und Automatisierung von Softwaretests zur Korrektheitsprüfung nutzen lassen. Die so erzielte Verringerung des Überprüfungsaufwandes führt zu einer verbesserten Wandlungsfähigkeit von BI-Architekturen und kommt somit dem Bedarf von effizienten agilen BI-Lösungen nach.

A abordagem de desenvolvimento dirigido por modelos (DDM) propõe que modelos (e transformações entre modelos) assumam o papel principal no desenvolvimento de sistemas. Entretanto, não há uma notação consensual para modelagem de persistência baseada em arcabouços de mapeamento objeto-relacional: enquanto a UML não possui recursos específicos para a modelagem de persistência, o modelo entidade-relacionamento não expressa os conceitos dinâmicos existentes na UML. Este trabalho propõe o perfil UML MD-JPA (Model Driven JPA) para a modelagem de persistência baseada na já difundida API de persistência Java (JPA), buscando a modelagem dos elementos persistentes e transientes de forma mais coerente e integrada. São especificadas as principais características do perfil MD-JPA, assim como a maneira pela qual modelos que adotam este perfil podem ser transformados em implementação Java, através de transformações de modelos propostas em uma abordagem DDM. Por fim, uma ferramenta de código livre foi desenvolvida para disponibilizar para comunidade os resultados deste trabalho. / The model driven development (MDD) approach proposes that models (and modelto- model transformations) play the main role on system development. However, there is not a consensual notation to model persistence based upon object relational mapping frameworks: while UML lacks specific resources for persistence modeling, the entityrelationship model does not make reference to the dynamic concepts existing in UML. This work proposes MD-JPA, a UML profile for persistence modeling based on the well-known Java Persistence API (JPA), pursuing the modeling of transient and persistent elements in a more coherent and integrated way. This work describes the main characteristics of MD-JPA as well as the way that models that adopt such profile can them be used to generate a Java implementation by the application of the proposed model transformations on a MDD approach. Finally, an open source tool was developed to make the results of this work available to the community.

A abordagem de desenvolvimento dirigido por modelos (DDM) propõe que modelos (e transformações entre modelos) assumam o papel principal no desenvolvimento de sistemas. Entretanto, não há uma notação consensual para modelagem de persistência baseada em arcabouços de mapeamento objeto-relacional: enquanto a UML não possui recursos específicos para a modelagem de persistência, o modelo entidade-relacionamento não expressa os conceitos dinâmicos existentes na UML. Este trabalho propõe o perfil UML MD-JPA (Model Driven JPA) para a modelagem de persistência baseada na já difundida API de persistência Java (JPA), buscando a modelagem dos elementos persistentes e transientes de forma mais coerente e integrada. São especificadas as principais características do perfil MD-JPA, assim como a maneira pela qual modelos que adotam este perfil podem ser transformados em implementação Java, através de transformações de modelos propostas em uma abordagem DDM. Por fim, uma ferramenta de código livre foi desenvolvida para disponibilizar para comunidade os resultados deste trabalho. / The model driven development (MDD) approach proposes that models (and modelto- model transformations) play the main role on system development. However, there is not a consensual notation to model persistence based upon object relational mapping frameworks: while UML lacks specific resources for persistence modeling, the entityrelationship model does not make reference to the dynamic concepts existing in UML. This work proposes MD-JPA, a UML profile for persistence modeling based on the well-known Java Persistence API (JPA), pursuing the modeling of transient and persistent elements in a more coherent and integrated way. This work describes the main characteristics of MD-JPA as well as the way that models that adopt such profile can them be used to generate a Java implementation by the application of the proposed model transformations on a MDD approach. Finally, an open source tool was developed to make the results of this work available to the community.

A abordagem de desenvolvimento dirigido por modelos (DDM) propõe que modelos (e transformações entre modelos) assumam o papel principal no desenvolvimento de sistemas. Entretanto, não há uma notação consensual para modelagem de persistência baseada em arcabouços de mapeamento objeto-relacional: enquanto a UML não possui recursos específicos para a modelagem de persistência, o modelo entidade-relacionamento não expressa os conceitos dinâmicos existentes na UML. Este trabalho propõe o perfil UML MD-JPA (Model Driven JPA) para a modelagem de persistência baseada na já difundida API de persistência Java (JPA), buscando a modelagem dos elementos persistentes e transientes de forma mais coerente e integrada. São especificadas as principais características do perfil MD-JPA, assim como a maneira pela qual modelos que adotam este perfil podem ser transformados em implementação Java, através de transformações de modelos propostas em uma abordagem DDM. Por fim, uma ferramenta de código livre foi desenvolvida para disponibilizar para comunidade os resultados deste trabalho. / The model driven development (MDD) approach proposes that models (and modelto- model transformations) play the main role on system development. However, there is not a consensual notation to model persistence based upon object relational mapping frameworks: while UML lacks specific resources for persistence modeling, the entityrelationship model does not make reference to the dynamic concepts existing in UML. This work proposes MD-JPA, a UML profile for persistence modeling based on the well-known Java Persistence API (JPA), pursuing the modeling of transient and persistent elements in a more coherent and integrated way. This work describes the main characteristics of MD-JPA as well as the way that models that adopt such profile can them be used to generate a Java implementation by the application of the proposed model transformations on a MDD approach. Finally, an open source tool was developed to make the results of this work available to the community.

Made available in DSpace on 2016-12-23T14:33:45Z (GMT). No. of bitstreams: 1 Igor Magri Vale.pdf: 2520269 bytes, checksum: caaadd79754ab599c95d04a12447722b (MD5) Previous issue date: 2011-04-15 / With the definition of the Brazilian System of Digital Television, and the possibility of creating interactive applications, the field of Digital Television (DTV) is an environment to be explored by innovative applications, such as Context-Aware Applications. Context-aware applications use contextual information from the user to trigger services according user s needs or his current situation, and therefore can potentially enrich the user experience when watching TV. The objective of this dissertation is to propose a model-driven methodology to assist the development of these applications in the DTV environment, starting from the modeling phase all the way to the implementation. The target platform is called Ginga, which is the middleware defined by SBTVD in order to support the development of interactive applications. The methodology proposed by this work offers support for (i) modeling the universe of discourse of context-aware applications by means of context models, situation models and (ii) specifying the reactive behaviours of these applications using a rule-based approach. For that, this work proposes a domain-specific language, coined ECA-DL TVD, which allows the specification of reactive behaviours by means of events, conditions and actions. This work also defines a conceptual architecture, which is used to structure the Ginga Component called Context Manager. One of the main contributions of this work lies in the automatic generation of NCL code concerning part of this conceptual architecture, using transformation frameworks and other Model-Driven Development techniques. Finally, two application scenarios are presented in order to demonstrate the viability of such methodology / Com a implantação do Sistema Brasileiro de Televisão Digital, e com a possibilidade de criação de aplicações interativas, o domínio de Televisão Digital (TVD) é um ambiente a ser explorado por aplicações inovadoras, como é o caso das Aplicações Sensíveis ao Contexto. Aplicações Sensíveis ao Contexto utilizam informações contextuais do usuário para acionar serviços de acordo com a necessidade ou a situação atual do usuário, e podem, portanto, potencialmente enriquecer a experiência do usuário ao assistir TV. O objetivo desta dissertação é propor uma metodologia orientada a modelos para auxiliar o desenvolvimento dessas aplicações no ambiente de TV Digital, desde a fase de modelagem à realização, tendo como alvo de implementação a plataforma Ginga, que é o middleware definido pelo SBTVD para desenvolvimento de aplicações interativas. A metodologia oferece suporte à modelagem do universo de discurso da aplicação através de modelos de contexto e situação, bem como à definição de comportamentos reativos de aplicações usando uma abordagem baseada em regras. Para isso, este trabalho propõe uma linguagem baseada em regras denominada ECA-DL TVD, que permite a especificação de comportamentos reativos através de eventos, condições e ações. Este trabalho também define uma arquitetura conceitual, que visa estruturar o Gerenciador de Contexto, um dos componentes do Ginga. Uma das principais contribuiçoes deste trabalho volta-se para a geração automática de código NCL referente a (parte) dessa arquitetura conceitual. O trabalho propõe a utilização de técnicas da área de desenvolvimento orientado a modelos (MDD) e frameworks de transformação para que, a partir de modelos de contexto, situações e regras ECA-DL TVD, seja gerado código NCL. Finalmente, são apresentados dois cenários de aplicação que visam demonstrar a validade da metodologia proposta

Certain electrophysiological markers hold promise in distinguishing individuals with major depressive disorder (MDD) and in predicting antidepressant response, thereby assisting with assessment and optimizing treatment, respectively. This thesis examined resting brain activity via electroencephalographic (EEG) recordings, as well as EEG-derived event-related potentials (ERPs) to auditory stimuli and facial expression presentations in individuals with MDD and controls. Additionally, the utility of resting EEG as well as auditory ERPs (AEPs), and the associated loudness-dependence of AEPs (LDAEP) slope, were assessed in predicating outcome to chronic treatment with one of three antidepressant regimens [escitalopram (ESC); bupropion (BUP); ESC+BUP]. Relative to controls, depressed adults had lower pretreatment cortical activity in regions implicated in approach motives/positive processing. Increased anterior cingulate cortex (ACC)-localized theta was observed, possibly reflecting emotion/cognitive regulation disturbances in the disorder. AEPs and LDAEPs, putative indices of serotonin activity (implicated in MDD etiology), were largely unaltered in MDD. Assessment of ERPs to facial expression processing indicated slightly blunted late preconscious perceptual processing of expressions, and prolonged processing of intensely sad faces in MDD. Faces were rated as sadder overall in MDD, indicating a negative processing bias. Treatment responders (vs. non-responders) exhibited baseline cortical hypoactivity; after a week of treatment, cortical arousal emerged in responders. Increased baseline left fronto-cortical activity and early shifts towards this profile were noted in responders (vs. non-responders). Responders exhibited a steep, and non-responders shallow, baseline N1 LDAEP derived from primary auditory cortex activity. P2 LDAEP slopes (primary auditory cortex-derived) increased after a week of treatment in responders and decreased in non-responders. Consistent with overall findings, ESC responders displayed baseline cortical hypoactivity and steep LDAEP-sLORETA slopes (vs. non-responders). BUP responders also exhibited steep baseline slopes and high ACC theta. These results indicate that specific resting brain activity profiles appear to distinguish depressed from non-depressed individuals. Subtle ERP modulations to simple auditory and emotive processing also existed in MDD. Resting alpha power, ACC theta activity and LDAEP slopes predicted antidepressant response in general, but were limited in predicting outcome to a particular treatment, which may be associated with limited sample sizes.

Vi behöver minska vår materialkonsumtion, idag gör vi av med mer resurser än vad vi har tillgång till. I den här studien har först en materialkonstruktion tagits fram och därefter ett produktkoncept för konstruktionen. För att ta fram materialkonstruktionen har biomimicry använts. Biomimicry är designmetoder för att lösa designproblem med inspiration från naturen. Naturen använder sig av så lite material som möjligt. Materialkonstruktionen är inspirerad av växtceller. Konstruktionen har två hierarkier som går i två olika riktningar, en riktning som går längs med och en riktning som går i djupled.För att hitta ett produktkoncept för materialkonstruktionen har material driven design (MDD) använts. MDD är en experimentell metod för att lära känna ett material och förstå dess användningsområde. Produktkonceptet är en stapelbar pall.För att minska på resurser används 3d-printning. 3d-printning är en additiv teknik och minskar på så sätt materialåtgång. Dessutom kan allt material lätt återanvändas eftersom det bara behövs ett material.Produkten kan produceras lokalt vilket minskar på transporter. PLA har använts som material i den här studien. / We need to reduce our material consumption, today we are wasting more resources than we have access to. In this study, a material construction was first developed and then a product concept for the construction. Biomimicry has been used to develop the material construction. Biomimicry are design methods for solving design problems with inspiration from nature. Nature uses as little material as possible. The material construction is inspired by plant cells. The construction has two hierarchies that go in two different directions.To find a product concept for the construction, material driven design (MDD) has been used. MDD is an experimental method used to get to know a material and understand its application. The product concept is a stackable pallet.To reduce resources, 3D printing is used. 3D printing is an additive technology and thus reduces material consumption. In addition, all material can be easily reused as only one material is needed.The product can be produced locally, which reduces on transport. PLA has been used as material in this study.

In addition to mood symptoms, major depressive disorder (MDD) is characterized by cognitive impairments that can have detrimental impacts on quality of life and daily function, and have been found to persist into remission. In particular, altered affective cognition (e.g. biased attention to negative stimuli) has been reported in MDD, and may continue into remission. Unfortunately, current pharmacotherapies do not adequately address cognitive dysfunction in acute or remitted MDD. Understanding the neurobiological underpinnings of affective cognitive dysfunction in remitted MDD may help inform the development of new interventions to address this lingering problem and the associated poorer functional outcomes. The triple network model posits that altered functioning of three key networks implicated in normal cognitive function – the default mode network (DMN), central executive network (CEN) and salience network (SN) – underlies cognitive dysfunction in a variety of psychiatric illnesses, including MDD. Though notable exceptions exist, work in acutely depressed MDD patients has found evidence of DMN hyperconnectivity, CEN hypoconnectivity and abberant SN connectivity both at rest and during the completion of various cognitive tasks. The evidence for triple network connectivity alterations persisting into remission is less robust, and warrants further investigation. Furthermore, there is a paucity of studies examining remitted MDD connectivity during affective tasks. As such, the primary objectives of this thesis were to: 1) compare resting-state and task triple network connectivity profiles in remitted MDD patients (rMDDs) and healthy volunteers (HVs) at rest, during an affective (emotional Stroop [eStroop]) task, and during rest vs. the task and, 2) assess the relationship between DMN and CEN connectivity and measures of daily functioning, quality of life and/or negative, self-relational rumination in the rMDD cohort. Behaviourally, there were findings of an affective attentional bias and impaired processing speed in the rMDD vs. HVs, as revealed by a computerized cognitive test battery. However, we found no evidence of DMN hyperconnectivity or CEN hyperconnectivity in the rMDD study sample. We did find evidence of altered intrinsic CEN and CEN-SN connectivity between the rest and task conditions that seemed driven by the rMDD sample, as well as positive CEN-DMN correlations across the entire sample both at rest and during the eStroop task. Suprisingly, we also found higher intrinsic DMN connectivity during the eStroop task vs. at rest across the whole sample. Finally, we found a positive relationship between task-based CEN connectivity and hopeless rumination, and a significant negative relationship between resting state and task-based DMN connectivity and psychosocial dysfunction in the rMDD sample. These findings contribute to our understanding of large-scale intrinsic network connectivity alterations during remitted depression, and their relationship to functional outcomes.