A Tomografia de Impedância Elétrica (TIE) é uma técnica de imageamento, ainda em desenvolvimento, por meio da qual são extraídas imagens correspondentes à distribuição da impedância elétrica de uma seção transversal de um objeto sob análise a partir de medidas elétricas realizadas em sua superfície. Apesar de seus benefícios e vantagens sobre outras técnicas de imageamento, suas imagens não oferecem uma boa resolução espacial. Em imagens TIE de tórax, um dos maiores desafios reside no tratamento da perfusão pulmonar, pois as perspectivas de uso clínico são inúmeras. Assim sendo, melhorar a localização de seus principais órgãos é um dos grandes objetivos. Com o intuito de melhorar a resolução anatômica foi desenvolvida uma metodologia para identificação de região cardíaca em imagens de tomografia de impedância elétrica de perfusão pulmonar por meio da transformada wavelet, utilizando imagens TIE de porcos. Inicialmente foi realizada uma série de estudos de diferentes abordagens com vistas a identificar aquelas características que pudessem indicar similaridades ou diferenças intrínsecas entre os pixels de diferentes regiões anatômicas. Com base nestes estudos, cinco métodos baseados na análise wavelet foram desenvolvidos. Um primeiro conjunto de experimentos, realizado em um único porco, foi utilizado no desenvolvimento e aperfeiçoamento dos métodos. Posteriormente, outros experimentos, envolvendo quatro porcos em diferentes condições fisiológicas, foram utilizados na avaliação de desempenho destes métodos. As imagens de perfusão wavelet foram comparadas com as imagens de perfusão obtidas pelo método de injeção de uma solução hipertônica, considerada como padrão de referência das imagens de perfusão. A metodologia wavelet proposta por este trabalho foi o método, dentre os cinco desenvolvidos, que obteve os melhores resultados. Ela foi capaz de identificar a região cardíaca de cinco porcos submetidos a diversas condições fisiológicas, demonstrando robustez e resultados muito satisfatórios, não apenas em termos quantitativos, com uma área média da curva ROC de 0,86, mas também na qualidade das imagens obtidas, onde os contornos delimitando a região cardíaca ficaram bem definidos e de formato circular, de acordo com o que se esperava. Portanto, o objetivo maior deste trabalho que era melhorar a resolução espacial de imagens TIE de perfusão pulmonar, foi atingido com excelentes resultados e vantagens adicionais, como por exemplo, a possibilidade de sua implementação em equipamentos TIE de monitoramento do tórax e desta forma colaborar no aperfeiçoamento de sistemas de apoio à decisão médica em ambientes críticos, como é o caso das Unidades de Terapia Intensiva (UTIs). / Electrical Impedance Tomography (EIT) is an imaging technique, still in development, which allows imaging of the distribution of conductivity in a cross section of an object under analysis from electrical measures made on its surface. Despite its benefits and advantages over other imaging techniques, its images still do not offer a good spatial resolution. One of the biggest challenges in EIT thorax images is the treatment of the lung perfusion because the perspectives for clinical use are numerous. Thus, there is a great interest in improving the localization of its main organs. In order to improve the anatomical resolution was developed a methodology for identification of cardiac region in images of electrical impedance tomography of pulmonary perfusion by means of wavelet transform, using EIT images of pigs. Some preliminary studies of different approaches were performed in order to identify those characteristics that would indicate intrinsic similarities or differences among the pixels of different anatomical regions. These studies propitiated the development of five methods based on wavelet transform. A first set of experiments, performed in a single pig, was used in developing and improving of the methods. Subsequently, other experiments, involving four pigs in different physiological conditions, were performed to evaluate the performance of these methods. The wavelet perfusional images were compared with the perfusional images obtained by the method of injection of a hypertonic solution, considered as the perfusional reference standard images. Amongst the five developed methods, the best of them was selected as the wavelet methodology proposed by this work. It was capable to identify the heart region of five pigs under different physiological conditions, demonstrating to robustness and very satisfactory results, not only in quantitative terms, with an average area of the ROC curve of 0.86, but also in the quality of the images, where the contours delimiting the cardiac region were well defined and of circular format, according to what was expected. Therefore, the main objective of this work, that was to improve the spatial resolution of EIT images of pulmonary perfusion, was reached with excellent results and additional benefits such as the possibility of its implementation in EIT equipments for monitoring thorax and thus collaborate in improving of medical decision support systems in critical environments, as for example the Intensive Care Units (ICUs).

A Tomografia de Impedância Elétrica (TIE) é uma técnica de imageamento, ainda em desenvolvimento, por meio da qual são extraídas imagens correspondentes à distribuição da impedância elétrica de uma seção transversal de um objeto sob análise a partir de medidas elétricas realizadas em sua superfície. Apesar de seus benefícios e vantagens sobre outras técnicas de imageamento, suas imagens não oferecem uma boa resolução espacial. Em imagens TIE de tórax, um dos maiores desafios reside no tratamento da perfusão pulmonar, pois as perspectivas de uso clínico são inúmeras. Assim sendo, melhorar a localização de seus principais órgãos é um dos grandes objetivos. Com o intuito de melhorar a resolução anatômica foi desenvolvida uma metodologia para identificação de região cardíaca em imagens de tomografia de impedância elétrica de perfusão pulmonar por meio da transformada wavelet, utilizando imagens TIE de porcos. Inicialmente foi realizada uma série de estudos de diferentes abordagens com vistas a identificar aquelas características que pudessem indicar similaridades ou diferenças intrínsecas entre os pixels de diferentes regiões anatômicas. Com base nestes estudos, cinco métodos baseados na análise wavelet foram desenvolvidos. Um primeiro conjunto de experimentos, realizado em um único porco, foi utilizado no desenvolvimento e aperfeiçoamento dos métodos. Posteriormente, outros experimentos, envolvendo quatro porcos em diferentes condições fisiológicas, foram utilizados na avaliação de desempenho destes métodos. As imagens de perfusão wavelet foram comparadas com as imagens de perfusão obtidas pelo método de injeção de uma solução hipertônica, considerada como padrão de referência das imagens de perfusão. A metodologia wavelet proposta por este trabalho foi o método, dentre os cinco desenvolvidos, que obteve os melhores resultados. Ela foi capaz de identificar a região cardíaca de cinco porcos submetidos a diversas condições fisiológicas, demonstrando robustez e resultados muito satisfatórios, não apenas em termos quantitativos, com uma área média da curva ROC de 0,86, mas também na qualidade das imagens obtidas, onde os contornos delimitando a região cardíaca ficaram bem definidos e de formato circular, de acordo com o que se esperava. Portanto, o objetivo maior deste trabalho que era melhorar a resolução espacial de imagens TIE de perfusão pulmonar, foi atingido com excelentes resultados e vantagens adicionais, como por exemplo, a possibilidade de sua implementação em equipamentos TIE de monitoramento do tórax e desta forma colaborar no aperfeiçoamento de sistemas de apoio à decisão médica em ambientes críticos, como é o caso das Unidades de Terapia Intensiva (UTIs). / Electrical Impedance Tomography (EIT) is an imaging technique, still in development, which allows imaging of the distribution of conductivity in a cross section of an object under analysis from electrical measures made on its surface. Despite its benefits and advantages over other imaging techniques, its images still do not offer a good spatial resolution. One of the biggest challenges in EIT thorax images is the treatment of the lung perfusion because the perspectives for clinical use are numerous. Thus, there is a great interest in improving the localization of its main organs. In order to improve the anatomical resolution was developed a methodology for identification of cardiac region in images of electrical impedance tomography of pulmonary perfusion by means of wavelet transform, using EIT images of pigs. Some preliminary studies of different approaches were performed in order to identify those characteristics that would indicate intrinsic similarities or differences among the pixels of different anatomical regions. These studies propitiated the development of five methods based on wavelet transform. A first set of experiments, performed in a single pig, was used in developing and improving of the methods. Subsequently, other experiments, involving four pigs in different physiological conditions, were performed to evaluate the performance of these methods. The wavelet perfusional images were compared with the perfusional images obtained by the method of injection of a hypertonic solution, considered as the perfusional reference standard images. Amongst the five developed methods, the best of them was selected as the wavelet methodology proposed by this work. It was capable to identify the heart region of five pigs under different physiological conditions, demonstrating to robustness and very satisfactory results, not only in quantitative terms, with an average area of the ROC curve of 0.86, but also in the quality of the images, where the contours delimiting the cardiac region were well defined and of circular format, according to what was expected. Therefore, the main objective of this work, that was to improve the spatial resolution of EIT images of pulmonary perfusion, was reached with excellent results and additional benefits such as the possibility of its implementation in EIT equipments for monitoring thorax and thus collaborate in improving of medical decision support systems in critical environments, as for example the Intensive Care Units (ICUs).

L’usine du futur et les performances environnementales sont de nos jours au cœur des préoccupations. Les produits et services éco-labellisés sont de plus en plus populaires. En plus des coûts financiers engendrés, les processus d’éco-labellisation sont longs et complexes, ce qui démotive parfois les fabricants et les fournisseurs de services à demander des certifications. Dans ce contexte, ce travail de recherche, propose une démarche et une plateforme d’aide à la décision visant à améliorer et à accélérer ce processus afin de démocratiser l’accès à la certification écologique. Les bases de connaissances traditionnelles étant généralement peu interopérables, difficiles à être réutilisées et ne supportant pas les inférences, la plate-forme proposée repose sur une base de connaissances composée de diverses ontologies de domaine construites selon la documentation officielle européenne sur les écolabels. Cette base est composée de modules d'ontologies interconnectées couvrant divers produits et services. Elle permet d’automatiser le raisonnement sur ces connaissances et de les interroger en tenant compte de la sémantique. Un schéma de modularisation orienté suivant le domaine et la catégorie du produit, et portant sur les critères d’écolabels européens des produits détergents est utilisé comme cas d'application. Afin de permettre une réutilisation aisée des modules d'ontologie pour différents groupes de produits, ce schéma de modularisation fait la distinction entre la connaissance de base du domaine et les connaissances variables concernant les critères de labélisation de chaque groupe. La méthode de raisonnement utilisée exploite les mécanismes d'inférence sur des règles SWRL, et fournit des résultats argumentés pour l’aide à la décision. La modélisation adoptée pour la représentation des connaissances n’est pas uniquement dédiée à la plateforme proposée. Elle permet également une exploitation des connaissances via des outils du Web sémantique. Afin de favoriser la réutilisation des modules d'ontologie, une approche de contextualisation pour la fédération d’ontologies a été proposée. Elle permet de pallier les inconvénients de "OWL: imports". Contrairement aux approches existantes, où il est nécessaire de réaliser soit un mapping, soit d’ajouter des relations sémantiques modifiant les modules d’ontologies de base, notre approche n’affecte pas et ne nécessite pas l’importation de tous les concepts de ces ontologies. Pour faciliter la mise en œuvre de cette approche, nous proposons un nouveau plug-in pour l'éditeur d'ontologie « Protégé ». / With the rising concern of sustainability and environmental performance, eco-labeled products and services are becoming more and more popular. In addition to the financial costs, the long and complex process of eco-labeling sometimes demotivates manufacturers and service providers to be certificated. In this research work, we propose a decision support process and implement a decision support platform aiming at further improvement and acceleration of the eco-labeling process in order to democratize a broader application and certification of eco-labels. The decision support platform is based on a comprehensive knowledge base composed of various domain ontologies that are constructed according to official eco-label criteria documentation. Traditional knowledge base in relational data model is low interoperable, lack of inference support and difficult to be reused. In our research, the knowledge base composed of interconnected ontologies modules covers various products and services, and allows reasoning and semantic querying. A domain-centric modularization scheme about EU Eco-label laundry detergent product criteria is introduced as an application case. This modularization scheme separates the entity knowledge and rule knowledge so that the ontology modules can be reused easily in other domains. We explore a reasoning methodology based on inference with SWRL (Semantic Web Rule Language) rules which allows decision making with explanation. Through standard RDF (Resource Description Framework) and OWL (Web Ontology Language) ontology query interface, the assets of the decision support platform will stimulate domain knowledge sharing and can be applied into other application. In order to foster the reuse of ontology modules, we also proposed a usercentric approach for federate contextual ontologies (mapping and integration). This approach will create an ontology federation by a contextual configuration that avoid the “OWL:imports” disadvantages. Instead of putting mapping or new semantics in ontology modules, our approach will conserve the extra contextual information separately without impacting original ontologies or without importing all ontologies’ concepts. By introducing this contextualization, it becomes easier to support more expressive semantics in term of ontology integration itself, then it will also facilitate application agents to access and reuse ontologies. To realize this approach, we elaborate a new plug-in for the Protégé ontology editor.

<p>The demand for shorter lead-times and increased delivery reliability puts pressure on companies to provide more efficient logistic services. One strategy to deal with this demand is by outsourcing logistics to a third part. The development of logistics information systems enables increased control over business supply chains. This is why Green Cargo aims to create a Logistics Control Tower (LCT) solution to provide it’s customers with better information with higher availability. One such system is the Green Cargo control tower solution, which aims to improve information quality and availability alike. This is also the origin of this thesis at Green Cargo Division Logistics. The aim of this project was to identify the information needs in the logistic processes connected to Green Cargo Division Logistics, and to present a requirement specification for a LCT. The LCT will be designed to work as an information and decision support system. The main source of information was collected through interviews with customers of Green Cargo, as well as personnel at Green Cargo. </p><p>The research findings suggest that there is potential for improvement within the information flow between Green Cargo and the other parties involved in the logistic process. A need for improved information flows and communication became apparent through the investigation. We therefore suggest that Green Cargo develops a LCT containing functions such as cost follow-up, statistics, stock level information, order information, proof of delivery, track&trace, notification, environment information, and invoice control. Whilst some of these functions are yet to be introduced, others are basic functions already provided for by Green Cargo, but could nonetheless be improved. Most of the suggested functions are generated through the customers needs while invoice control and automated notification is a demand from Green Cargo personnel. A web interface with the possibility to adapt the content to different customers could serve as a solution to these needs. Input to the LCT is collected from different information systems such as vendor management systems and databases at logistic service providers.</p>

The demand for shorter lead-times and increased delivery reliability puts pressure on companies to provide more efficient logistic services. One strategy to deal with this demand is by outsourcing logistics to a third part. The development of logistics information systems enables increased control over business supply chains. This is why Green Cargo aims to create a Logistics Control Tower (LCT) solution to provide it’s customers with better information with higher availability. One such system is the Green Cargo control tower solution, which aims to improve information quality and availability alike. This is also the origin of this thesis at Green Cargo Division Logistics. The aim of this project was to identify the information needs in the logistic processes connected to Green Cargo Division Logistics, and to present a requirement specification for a LCT. The LCT will be designed to work as an information and decision support system. The main source of information was collected through interviews with customers of Green Cargo, as well as personnel at Green Cargo. The research findings suggest that there is potential for improvement within the information flow between Green Cargo and the other parties involved in the logistic process. A need for improved information flows and communication became apparent through the investigation. We therefore suggest that Green Cargo develops a LCT containing functions such as cost follow-up, statistics, stock level information, order information, proof of delivery, track&amp;trace, notification, environment information, and invoice control. Whilst some of these functions are yet to be introduced, others are basic functions already provided for by Green Cargo, but could nonetheless be improved. Most of the suggested functions are generated through the customers needs while invoice control and automated notification is a demand from Green Cargo personnel. A web interface with the possibility to adapt the content to different customers could serve as a solution to these needs. Input to the LCT is collected from different information systems such as vendor management systems and databases at logistic service providers.

In diesem Beitrag wird das am Leibniz-Institut für ökologische Raumentwicklung eV. (IÖR) entwickelte Informations- und Entscheidungsunterstützungssystem „Weißeritz-Info“ vorgestellt, das der Aufbereitung und Bereitstellung von Informationen zum Hochwasserrisikomanagement für das Einzugsgebiet der Weißeritz dient. Zielgruppen sind sowohl Bürger und Landnutzer als auch Entscheidungsträger in Kommunen, Behörden und Verbänden. Erstellt wurde das WebGIS-basierte System für die Initiative „Weißeritz-Regio“, einem Verbund von 26 Institutionen, die seit Ende 2003 auf informeller Basis zusammenarbeiten, um die Hochwasservorsorge im Flussgebiet zu verbessern.

Infrastructure privatization decisions have an enormous financial and social impact on all stakeholders, including the public sector, the private sector, and the general public. Appropriate privatization decisions, however, are difficult to make due to the conflicting nature of the objectives of the various stakeholders. This research introduces a multi-criteria decision-making framework for evaluating and comparing a wide range of privatization schemes for infrastructure facilities. The framework is designed to resolve conflicts that arise because of the varying points of view of the stakeholders, and accordingly, determine the most appropriate decision that satisfies all stakeholders’ preferences. The developed framework is expected to help in re-engineering the traditional conflict resolution process, particularly for construction conflict resolution and infrastructure privatization decisions. The framework provides decision support at the management level through three successive decision support processes related to 1. Screening of feasible solutions using the Elimination Method of multiple criteria decision analysis (MCDA); 2. Analyzing the actions and counteractions of decision makers using conflict resolution and decision stability concepts to determine the most stable resolution; and 3. Considering the uncertainty in decision maker’s preferences using Info-gap Theory to evaluate the robustness of varying uncertainty levels of the decisions. Based on the research, a procedure and a decision support system (DSS) have been developed and tested on real-life case studies of a wastewater treatment plant and a construction conflict. The results of the two case studies show that the proposed DSS can be used to support decisions effectively with respect to both construction conflicts and infrastructure privatization. The developed system is simple to apply and can therefore save time and avoid the costs associated with unsatisfactory decisions. This research is expected to contribute significantly to the understanding and selecting of proper Public-Private-Partnership (PPP) programs for infrastructure assets.

In economically turbulent times, Business Intelligence (BI) is increasingly being used to mitigate risk and increase certainty. The evolution of BI from a series of technologies to a platform for supporting strategies is analyzed in this thesis. The concentration is on how BI can streamline manufacturing, quality assurance, marketing and customer service are evaluated, as are the potential payoffs of increasing the level of insight an organization has. The thesis also includes analysis of how the more complex value chain processes including build-to-order, configure-to-order and quote-to-order can be made more efficient and profitable through the inclusion of BI and its associated analytics and technologies. The inclusion of the Delphi research technique makes this paper unique and strong in its content as well. The role of BI has shifted from being used in specific functional areas of an organization to being strategic in scope. The intent of this thesis is to evaluate its contributions to the customer-facing processes that are the most complex and most challenging to sustain, making BI an indispensible platform for their successful execution on the base of theories and practical experience of the BI experts.

Infrastructure privatization decisions have an enormous financial and social impact on all stakeholders, including the public sector, the private sector, and the general public. Appropriate privatization decisions, however, are difficult to make due to the conflicting nature of the objectives of the various stakeholders. This research introduces a multi-criteria decision-making framework for evaluating and comparing a wide range of privatization schemes for infrastructure facilities. The framework is designed to resolve conflicts that arise because of the varying points of view of the stakeholders, and accordingly, determine the most appropriate decision that satisfies all stakeholders’ preferences. The developed framework is expected to help in re-engineering the traditional conflict resolution process, particularly for construction conflict resolution and infrastructure privatization decisions. The framework provides decision support at the management level through three successive decision support processes related to 1. Screening of feasible solutions using the Elimination Method of multiple criteria decision analysis (MCDA); 2. Analyzing the actions and counteractions of decision makers using conflict resolution and decision stability concepts to determine the most stable resolution; and 3. Considering the uncertainty in decision maker’s preferences using Info-gap Theory to evaluate the robustness of varying uncertainty levels of the decisions. Based on the research, a procedure and a decision support system (DSS) have been developed and tested on real-life case studies of a wastewater treatment plant and a construction conflict. The results of the two case studies show that the proposed DSS can be used to support decisions effectively with respect to both construction conflicts and infrastructure privatization. The developed system is simple to apply and can therefore save time and avoid the costs associated with unsatisfactory decisions. This research is expected to contribute significantly to the understanding and selecting of proper Public-Private-Partnership (PPP) programs for infrastructure assets.

Data warehousing and Online Analytical Processing (OLAP) technology has been used to access, visualize and analyze multidimensional, aggregated, and summarized data. Large part of data contains spatial components. Thus, these spatial components convey valuable information and must be included in exploration and analysis phases of a spatial decision support system (SDSS). On the other hand, Geographic Information Systems (GISs) provide a wide range of tools to analyze spatial phenomena and therefore must be included in the analysis phases of a decision support system (DSS). In this regard, this study aims to search for answers to the problem how to design a spatially enabled data warehouse architecture in order to support spatio-temporal data analysis and exploration of multidimensional data. Consequently, in this study, the concepts of OLAP and GISs are synthesized in an integrated fashion to maximize the benefits generated from the strengths of both systems by building a spatial data warehouse model. In this context, a multidimensional spatio-temporal data model is proposed as a result of this synthesis. This model addresses the integration problem of spatial, non-spatial and temporal data and facilitates spatial data exploration and analysis. The model is evaluated by implementing a case study in weather pattern searching.