Com os grandes avanços recentes dos sistemas computacionais, houve a possibilidade de ascensão de dispositivos inovadores, como os modernos telefones celulares e tablets com telas sensíveis ao toque. Para gerenciar adequadamente estas diversas interfaces é necessário utilizar o software dependente do hardware (HdS), que é responsável pelo controle e acesso a estes dispositivos. Além deste complexo arranjo de componentes, para atender a crescente demanda por mais funcionalidades integradas, o paradigma de multiprocessamento vem sendo adotado para aumentar o desempenho das plataformas. Devido à lacuna de produtividade de sistemas, tanto a indústria como a academia têm pesquisado processos mais eficientes para construir e simular sistemas cada vez mais complexos. A premissa dos trabalhos do estado da arte está em trabalhar com modelos com alto nível de abstração e de precisão que permitam ao projetista avaliar rapidamente o sistema, sem ter que depender de lentos e complexos modelos baseados em ISS. Neste trabalho é definido um conjunto de construtores para modelagem de plataformas baseadas em processadores, com suporte para desenvolvimento de HdS e reusabilidade dos componentes, técnicas para estimativa estática de tempo simulado em ambiente nativo de simulação e suporte para plataformas multiprocessadas. Foram realizados experimentos com aplica- ções de entrada e saída intensiva, computação intensiva e multiprocessada, com ganho médio de desempenho da ordem de 1.000 vezes e precisão de estimativas com erro médio inferior a 3%, em comparação com uma plataforma de referência baseada em ISS._________________________________________________________________________________________ ABSTRACT: The amazing advances of computer systems technology enabled the rise of innovative devices, such as modern touch sensitive cell phones and tablets. To properly manage these various interfaces, it is required the use of the Hardwaredependent Software (HdS) that is responsible for these devices control and access. Besides this complex arrangement of components, to meet the growing demand for more integrated features, the multiprocessing paradigm has been adopted to increase the platforms performance. Due to the system design gap, both industry and academia have been researching for more efficient processes to build and simulate systems with this increasingly complexity. The premise of the state of art works is the development of high level of abstraction and precise models to enable the designer to quickly evaluate the system, without having to rely on slow and complex models based on instruction set simulators (ISS). This work defined a set of constructors for processor-based platforms modeling, supporting HdS development and components reusability, techniques for static simulation timing estimation in native environment and support for multiprocessor platforms. Experiments were carried out with input and output intensive, compute intensive and multiprocessed applications leading to an average performance speed up of about 1,000 times and average timing estimation accuracy of less than 3%, when compared with a reference platform based on ISS.

This thesis is focused on cluster analysis in the field of text mining and its application to real data. The aim of the thesis is to find suitable categories (clusters) in the transcribed calls recorded in the contact center of Česká pojišťovna a.s. by transferring these textual documents into the vector space using basic text mining methods and the implemented clustering algorithms. From the formal point of view, the thesis contains a description of preprocessing and representation of textual data, a description of several common clustering methods, cluster validation, and the application itself.

Role-based modeling has been investigated for over 35 years as a promising paradigm to model complex, dynamic systems. Although current software systems are characterized by increasing complexity and context-dependence, all this research had almost no influence on current software development practice, still being discussed in recent literature. One reason for this is the lack of a coherent, comprehensive, readily applicable notion of roles. Researchers focused either on relational roles or context-dependent roles rather then combining both natures. Currently, there is no role-based modeling language sufficiently incorporating both the relational and context-dependent nature of roles together with the various proposed constraints. Hence, this paper formalizes a full-fledged role-based modeling language supporting both natures. To show its sufficiency and adequacy, a real world example is employed.

Since the year 1977, role modeling has been continuously investigated as promising paradigm to model complex, dynamic systems. However, this research had almost no influence on the design of todays increasingly complex and context-sensitive software systems. The reason for that is twofold. First, most modeling languages focused either on the behavioral, relational or context-dependent nature of roles rather than combining them. Second, there is a lack of tool support for the design, validation, and generation of role-based software systems. In particular, there exists no graphical role modeling editor supporting the three natures as well as the various proposed constraints. To overcome this deficiency, we introduce the Full-fledged Role Modeling Editor (FRaMED), a graphical modeling editor embracing all natures of roles and modeling constraints featuring generators for a formal representation and source code of a rolebased programming language. To show its applicability for the development of role-based software systems, an example from the banking domain is employed.

Yes / Background: Tuberculosis (TB) is the highest-mortality infectious disease in the world and the main cause of death related to antimicrobial resistance, yet its surveillance is still paper-based. Rifampicin-resistant TB (RR-TB) is an urgent public health crisis. The World Health Organization has, since 2010, endorsed a series of rapid diagnostic tests (RDTs) that enable rapid detection of drug-resistant strains and produce large volumes of data. In parallel, most high-burden countries have adopted connectivity solutions that allow linking of diagnostics, real-time capture, and shared repository of these test results. However, these connected diagnostics and readily available test results are not used to their full capacity, as we have yet to capitalize on fully understanding the relationship between test results and specific rpoB mutations to elucidate its potential application to real-time surveillance. Objective: We aimed to validate and analyze RDT data in detail, and propose the potential use of connected diagnostics and associated test results for real-time evaluation of RR-TB transmission. Methods: We selected 107 RR-TB strains harboring 34 unique rpoB mutations, including 30 within the rifampicin resistance–determining region (RRDR), from the Belgian Coordinated Collections of Microorganisms, Antwerp, Belgium. We subjected these strains to Xpert MTB/RIF, GenoType MTBDRplus v2.0, and Genoscholar NTM + MDRTB II, the results of which were validated against the strains’ available rpoB gene sequences. We determined the reproducibility of the results, analyzed and visualized the probe reactions, and proposed these for potential use in evaluating transmission. Results: The RDT probe reactions detected most RRDR mutations tested, although we found a few critical discrepancies between observed results and manufacturers’ claims. Based on published frequencies of probe reactions and RRDR mutations, we found specific probe reactions with high potential use in transmission studies: Xpert MTB/RIF probes A, Bdelayed, C, and Edelayed; Genotype MTBDRplus v2.0 WT2, WT5, and WT6; and Genoscholar NTM + MDRTB II S1 and S3. Inspection of probe reactions of disputed mutations may potentially resolve discordance between genotypic and phenotypic test results. Conclusions: We propose a novel approach for potential real-time detection of RR-TB transmission through fully using digitally linked TB diagnostics and shared repository of test results. To our knowledge, this is the first pragmatic and scalable work in response to the consensus of world-renowned TB experts in 2016 on the potential of diagnostic connectivity to accelerate efforts to eliminate TB. This is evidenced by the ability of our proposed approach to facilitate comparison of probe reactions between different RDTs used in the same setting. Integrating this proposed approach as a plug-in module to a connectivity platform will increase usefulness of connected TB diagnostics for RR-TB outbreak detection through real-time investigation of suspected RR-TB transmission cases based on epidemiologic linking. / KCN was supported by Erasmus Mundus Joint Doctorate Fellowship grant 2016-1346, and BCdJ, LR, and CJM were supported by European Research Council-INTERRUPTB starting grant 311725.

Whether it is based on current emissions data or future projections of further growth, the building sector currently represent the largest and singular most important contributor to greenhouse gas (GHG) emissions globally. This notion is also supported by the Intergovernmental Panel on Climate Change based on projection scenarios for 2030 that emissions from buildings will be responsible for about one-third of total global emissions. As such, improving the energy efficiency of buildings has become a top priority worldwide. A significant majority of buildings that exist now will still exist in 2030 and beyond; therefore the greatest energy savings and carbon footprint reductions can be made through retrofit of existing buildings. A wide range of retrofit options are readily available, but methods to identify optimal solutions for a particular abatement project still constitute a major technical challenge. Investments in building energy retrofit technologies usually involve decision-making processes targeted at reducing operational energy consumption and maintenance bills. For this reason, retrofit decisions by building stakeholders are typically driven by financial considerations. However, recent trends towards environmentally conscious and resource-efficient design and retrofit have focused on the environmental merits of these options, emphasising a lifecycle approach to emissions reduction. Retrofit options available for energy savings have different performance characteristics and building stakeholders are required to establish an optimal solution, where competing objectives such as financial costs, energy consumption and environmental performance are taken into account. These key performance parameters cannot be easily quantified and compared by building stakeholders since they lack the resources to perform an effective decision analysis. In part, this is due to the inadequacy of existing methods to assess and compare performance indicators. Current methods to quantify these parameters are considered in isolation when making decisions about energy conservation in buildings. To effectively manage the reduction of lifecycle environmental impacts, it is necessary to link financial cost with both operational and embodied emissions. This thesis presents a novel deterministic decision support system (DSS) for the evaluation of economically and environmentally optimal retrofit of non-domestic buildings. The DSS integrates the key variables of economic and net environmental benefits to produce optimal decisions. These variables are used within an optimisation scheme that consists of integrated modules for data input, sensitivity analysis and takes into account the use of a set of retrofit options that satisfies a range of criteria (environmental, demand, cost and resource constraints); hierarchical course of action; and the evaluations of ‘best’ case scenario based on marginal abatement cost methods and Pareto optimisation. The steps involved in the system development are presented and its usefulness is evaluated using case study applications. The results of the applications are analysed and presented, verifying the feasibility of the DSS, whilst encouraging further improvements and extensions. The usefulness of the DSS as a tool for policy formulation and developments that can trigger innovations in retrofit product development processes and sustainable business models are also discussed. The methodology developed provides stakeholders with an efficient and reliable decision process that is informed by both environmental and financial considerations. Overall, the development of the DSS which takes a whole-life CO2 emission accounting framework and an economic assessment view-point, successfully demonstrates how value is delivered across different parts of the techno-economic system, especially as it pertains to financial gains, embodied and operational emissions reduction potential.

No description available.

Background: Patient empowerment is viewed as a priority by policy makers, patients and practitioners worldwide. Although there are a number of measures available, none have been developed specifically for patients in the UK with long-term conditions. It is the aim of this study to report the development and preliminary validation of an empowerment instrument for patients with long-term conditions in primary care.Methods: The study involved three methods. Firstly, a systematic review was conducted to identify existing empowerment instruments, and to describe, compare and appraise their content and quality. The results supported the need for a new instrument. Item content of existing instruments helped support development of the new instrument. Secondly, empowerment was explored in patients with long-term conditions and primary care practitioners using qualitative methods, to explore its meaning and the factors that support or hinder empowerment. This led to the development of a conceptual model to support instrument development. Thirdly, a new instrument for measuring empowerment in patients with long-term conditions in primary care was developed. A cross-sectional survey of patients was conducted to collect preliminary data on acceptability, reliability and validity, using pre-specified hypotheses based on existing theoretical and empirical work. Results: Nine instruments meeting review inclusion criteria were identified. Only one instrument was developed to measure empowerment in long-term conditions in the context of primary care, and that was judged to be insufficient in terms of content and purpose. Five dimensions (‘identity’, ‘knowledge and understanding’, ‘personal control’, personal decision-making’, and ‘enabling other patients’) of empowerment were identified through published literature and the qualitative work and incorporated into a preliminary version of the new instrument. A postal survey achieved 197 responses (response rate 33%). Almost half of the sample reported circulatory, diabetic or musculoskeletal conditions. Exploratory factor analysis suggested a three factor solution (‘identity’, ‘knowledge and understanding’ and ‘enabling’). Two dimensions of empowerment (‘identity’ and ‘enabling’) and total empowerment showed acceptable levels of internal consistency. The measure showed relationships with external measures (including quality of chronic illness care, self-efficacy and educational qualifications) that were generally supportive of its construct validity.Conclusion: Initial analyses suggest that the new measure meets basic psychometric criteria and has potential for the measurement of patient empowerment in long-term conditions in primary care. The scale may have a role in research on quality of care for long-term conditions, and could function as a patient-reported outcome measure. However, further validation is required before more extensive use of the measure.

Livestock grazing is the most important type of land-use in arid and semi-arid regions. In these regions, uncertain and highly variable climate conditions cause scarce and spatio-temporally variable resource availability. The major challenge to livestock grazing is the efficient utilisation of these resources without running the risk of degradation. Therefore, well adapted grazing strategies that consider both local environmental characteristics and the farmers' individual needs and perceptions are crucial for sustaining human livelihoods. Particularly, rotational grazing is presumed to render adaptation to spatio-temporal heterogeneities possible. A systematic investigation, however, that analyses the interrelations between the major components of rotational grazing systems on appropriate spatial and temporal scales was missing so far. This doctoral thesis investigates different management strategies for sustainable livestock grazing in semi-arid rangelands. Using an integrated modelling approach, it enters into the question: how to adapt grazing systems to spatio-temporal heterogeneous rangeland conditions, variable and changing climate conditions, and different individual needs and goals of livestock farmers? In order to address these issues, the taken approach tackles both methodical challenges and applied concerns. In the first part of this study, a generic modelling framework is developed that incorporates important components of grazing systems on appropriate spatial and temporal scales. To parameterise the model, a pattern-oriented approach is developed that uses qualitative patterns to derive a broad range of plausible parameter sets supporting a general model analysis. In the second part, a variety of management strategies is explored under different climatic, ecological, and economic conditions. The research focuses in particular on combined effects between and relative importance of different management components. The question how the results of different management strategies depend on the type of vegetation is investigated. Furthermore, the performance of rotational grazing strategies is analysed under different economic requirements and rainfall conditions. The study also identifies management strategies that are suitable to adapt a grazing system to spatio-temporally variable rangeland conditions. Overall, this thesis contributes to a general understanding of basic principles for adaptation to spatio-temporal heterogeneities as well as the interplay of different management components. The results allow an evaluation of management strategies for specific situations and the identification of strategies that are robust to a broad range of situations including different aspects of global change.