915 resultados para Database search Evidential value Bayesian decision theory Influence diagrams


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In almost all industrialized countries, the energy sector has suffered a severe restructuring that originated a greater complexity in market players’ interactions. The complexity that these changes brought made way for the creation of decision support tools that facilitate the study and understanding of these markets. MASCEM – “Multiagent Simulator for Competitive Electricity Markets” arose in this context providing a framework for evaluating new rules, new behaviour, and new participants in deregulated electricity markets. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. ALBidS is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This tool’s goal is to force the thinker to move outside his habitual thinking style. It was developed to be used mainly at meetings in order to “run better meetings, make faster decisions”. This dissertation presents a study about the applicability of the Six Thinking Hats technique in Decision Support Systems, particularly with the multiagent paradigm like the MASCEM simulator. As such this work’s proposal is of a new agent, a meta-learner based on STH technique that organizes several different ALBidS’ strategies and combines the distinct answers into a single one that, expectedly, out-performs any of them.

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Folk medicine is a relevant and effective part of indigenous healthcare systems which are, in practice, totally dependent on traditional healers. An outstanding coincidence between indigenous medicinal plant uses and scientifically proved pharmacological properties of several phytochemicals has been observed along the years. This work focused on the leaves of a medicinal plant traditionally used for therapeutic benefits (Angolan Cymbopogon citratus), in order to evaluate their nutritional value. The bioactive phytochemical composition and antioxidant activity of leaf extracts prepared with different solvents (water, methanol and ethanol) were also evaluated. The plant leaves contained ~60% of carbohydrates, protein (~20%), fat (~5%), ash (~4%) and moisture (~9%). The phytochemicals screening revealed the presence of tannins, flavonoids, and terpenoids in all extracts. Methanolic extracts also contained alkaloids and steroids. Several methods were used to evaluate total antioxidant capacity of the different extracts (DPPH; NO; and H2O2 scavenging assays, reducing power, and FRAP). Ethanolic extracts presented a significantly higher antioxidant activity (p < 0.05) except for FRAP, in which the best results were achieved by the aqueous extracts. Methanolic extracts showed the lowest radical scavenging activities for both DPPH; and NO; radicals.

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Cu2ZnSnSe4 (CZTSe) is a p-type semiconductor with a high absorption coefficient, 104 to 105 cm-1, and is being seen as a possible replacement for Cu(In,Ga)Se2 in thin film solar cells. Yet, there are some fundamental properties of CZTSe that are not well known, one of them is its band gap. In order to resolve its correct value it is necessary to improve the growth conditions to ensure that single phase crystalline thin films are obtained. One of the problems encountered when growing CZTSe is the loss of Sn through evaporation of SnSe. Stoichiometric films are then difficult to obtain and usually there are other phases present. One possible way to overcome this problem is to increase the pressure of growth of CZTSe. This can be done by introducing an atmosphere of an inert gas like Ar or N2. In this work we report the results of morphological, structural and optical studies of the properties of CZTSe thin films grown by selenization of DC magnetron sputtered metallic layers under different Ar pressures. The films are analysed by SEM/EDS, Raman scattering and XRD.

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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

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Prostate cancer (PCa), a leading cause of cancer-related morbidity and mortality, arises through the acquisition of genetic and epigenetic alterations. Deregulation of histone methyltransferases (HMTs) or demethylases (HDMs) has been associated with PCa development and progression. However, the precise influence of altered HMTs or HDMs expression and respective histone marks in PCa onset and progression remains largely unknown. To clarify the role of HMTs and HDMs in prostate carcinogenesis, expression levels of 37 HMTs and 20 HDMs were assessed in normal prostate and PCa tissue samples by RT-qPCR. SMYD3, SUV39H2, PRMT6, KDM5A, and KDM6A were upregulated, whereas KMT2A-E (MLL1-5) and KDM4B were downregulated in PCa, compared with normal prostate tissues. Remarkably, PRMT6 was the histone modifier that best discriminated normal from tumorous tissue samples. Interestingly, EZH2 and SMYD3 expression levels significantly correlated with less differentiated and more aggressive tumors. Remarkably, SMYD3 expression levels were of independent prognostic value for the prediction of disease-specific survival of PCa patients with clinically localized disease submitted to radical prostatectomy. We concluded that expression profiling of HMTs and HDMs, especially SMYD3, might be of clinical usefulness for the assessment of PCa patients and assist in pre-therapeutic decision-making.

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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Energia

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Mestrado em Gestão e Empreendedorismo

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The foot and the ankle are small structures commonly affected by disorders, and their complex anatomy represent significant diagnostic challenges. SPECT/CT Image fusion can provide missing anatomical and bone structure information to functional imaging, which is particularly useful to increase diagnosis certainty of bone pathology. However, due to SPECT acquisition duration, patient’s involuntary movements may lead to misalignment between SPECT and CT images. Patient motion can be reduced using a dedicated patient support. We aimed at designing an ankle and foot immobilizing device and measuring its efficacy at improving image fusion. Methods: We enrolled 20 patients undergoing distal lower-limb SPECT/CT of the ankle and the foot with and without a foot holder. The misalignment between SPECT and CT images was computed by manually measuring 14 fiducial markers chosen among anatomical landmarks also visible on bone scintigraphy. Analysis of variance was performed for statistical analysis. Results: The obtained absolute average difference without and with support was 5.1±5.2 mm (mean±SD) and 3.1±2.7 mm, respectively, which is significant (p<0.001). Conclusion: The introduction of the foot holder significantly decreases misalignment between SPECT and CT images, which may have clinical influence in the precise localization of foot and ankle pathology.

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Constrained and unconstrained Nonlinear Optimization Problems often appear in many engineering areas. In some of these cases it is not possible to use derivative based optimization methods because the objective function is not known or it is too complex or the objective function is non-smooth. In these cases derivative based methods cannot be used and Direct Search Methods might be the most suitable optimization methods. An Application Programming Interface (API) including some of these methods was implemented using Java Technology. This API can be accessed either by applications running in the same computer where it is installed or, it can be remotely accessed through a LAN or the Internet, using webservices. From the engineering point of view, the information needed from the API is the solution for the provided problem. On the other hand, from the optimization methods researchers’ point of view, not only the solution for the problem is needed. Also additional information about the iterative process is useful, such as: the number of iterations; the value of the solution at each iteration; the stopping criteria, etc. In this paper are presented the features added to the API to allow users to access to the iterative process data.

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The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, there were identified five broad selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. After the identification criteria, a survey was elaborated and companies were contacted in order to understand which factors have more weight in their decisions to choose the partners. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Value Analysis. The goal of the paper it's to supply a selection reference model that can represent an orientation/pattern for a decision making on the suppliers/partners selection process

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Dissertação para obtenção do grau de Mestre em Música - Interpretação Artística

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This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

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Titanate nanotubes (TNT) with different sodium contents have been synthesised using a hydrothermal approach and a swift and highly controllable post-washing processes. The influence of the sodium/proton replacement on the structural and morphological characteristics of the prepared materials was analysed. Different optical behaviour was observed depending on the Na+/H+ samples’ content. A band gap energy of 3.27±0.03 eV was estimated for the material with higher sodium content while a value of 2.81±0.02 eV was inferred for the most protonated material, which therefore exhibits an absorption edge in the near visible region. The point of zero charge of the materials was determined and the influence of the sodium content on the adsorption of both cationic and anionic organic dyes was studied. The photocatalytic performance of the TNT samples was evaluated in the rhodamine 6G degradation process. Best photodegradation results were obtained when using the most protonated material as catalyst, although this material has shown the lowest R6G adsorption capability.