818 resultados para fuzzy rule base models
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This paper provides an exploratory study of how rewards-based crowdfunding affects business model development for music industry artists, labels and live sector companies. The empirical methodology incorporated a qualitative, semi-structured, three-stage interview design with fifty seven senior executives from industry crowdfunding platforms and three stakeholder groups. The results and analysis cover new research ground and provide conceptual models to develop theoretical foundations for further research in this field. The findings indicate that the financial model benefits of crowdfunding for independent artists are dependent on fan base demographic variables relating to age group and genre due to sustained apprehension from younger audiences. Furthermore, major labels are now considering a more user-centric financial model as an innovation strategy, and the impact of crowdfunding on their marketing model may already be initiating its development in terms of creativity, strength and artist relations.
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Anchoíta (Engraulis anchoita) é uma espécie pelágica encontrada no Sudoeste do Oceano Atlântico. Estima-se que 135000 toneladas/ano desse peixe possam ser exploradas ao longo do litoral sul do Brasil. Entretanto, os recursos pesqueiros do país são ainda inexplorados, o que torna esta matéria prima candidata em potencial para a fabricação de novos produtos a base desse pescado. Com o apoio de programas governamentais sociais, a tendência para o Brasil é para o desenvolvimento de produtos de anchoíta alternativos e que sejam capazes de suprir as necessidades específicas de cada grupo de consumo alvo. Dentro desse cenário, um estudo de novos produtos de pescado frente ao mercado se faz necessário, na tentativa de compreender as variáveis influentes do setor. Para tanto, na presente tese teve objetivou-se desenvolver produtos à base de anchoíta e estudar o comportamento do mercado consumidor frente a esses novos produtos de pescado. Um total de seis artigos foi gerado. O primeiro artigo intitulou-se: “Potencial de inserção de empanados de pescado na merenda escolar mediante determinantes individuais”. Neste objetivou-se detectar os determinantes individuais do consumo de pescado com adolescentes em idade de 12 a 17 anos, visando à inserção de empanados de pescado na merenda escolar. Foi verificado que as variáveis que melhor discriminaram a frequência de consumo foram “gosta de pescado” e “grau de escolaridade dos pais”. Os resultados indicaram um potencial de consumo de empanados de pescado por adolescentes, associado à necessidade de educação alimentar. O segundo artigo “Elaboração de hambúrguer a partir de base proteica de anchoíta (Engraulis anchoita)” no qual se objetivou avaliar o efeito de diferentes combinações de solventes para a obtenção de base proteica de anchoíta visando à elaboração de hambúrguer de pescado. As lavagens com ácido fosfórico e mais dois ciclos de água foram as que apresentaram os melhores valores para a obtenção da base proteica, baseando-se na remoção de nitrogenados e respostas sensoriais. No terceiro artigo “Aceitação de empanados de pescado (Engraulis anchoita) na merenda escolar no extremo sul do Brasil” o objetivo foi avaliar a aceitação de empanados de pescado (Engraulis anchoita) com alunos (n = 830) da rede pública de ensino, em idades entre 5 e 18 anos, de duas cidades do estado do Rio Grande do Sul, Brasil. Os resultados indicaram relação inversa entre a aceitação de empanados de pescado e o aumento da idade das crianças. O quarto artigo estudou “Razões subjacentes ao baixo consumo de pescado pelo consumidor brasileiro.” Neste objetivou-se investigar o comportamento referente ao consumo de pescado de uma população com baixo consumo de pescado (Brasil), aplicando a Teoria do Comportamento Planejado (TCP). Os resultados indicaram que tanto a intenção como a atitude provou serem determinantes significativos na frequência de comer pescado, sendo a atitude inversamente correlacionada com o consumo de pescado. Hábito apareceu como uma importante variável discriminante para o consumo de pescado. O quinto artigo intitula-se “Modelagem de equações estruturais e associação de palavras como ferramentas para melhor compreensão do baixo consumo de pescado”. O objetivo foi desenvolver um modelo e explicar o conjunto das relações entre os construtos do consumo de pescado em uma população com baixo consumo de pescado (Brasil) através da aplicação da TCP e pelo Questionário das Escolhas dos Alimentos. Além disso, a percepção cognitiva de produtos de pescado (Engraulis anchoíta) foi avaliada pela mesma população. Os resultados indicaram um bom ajuste para o modelo proposto e mostraram que os construtos “saúde” e “controle de peso” são bons preditores da intenção. A técnica associação de palavras provou ser um método útil para a análise de percepção de um novo produto de pescado, além de ajudar a explicar os resultados obtidos pelas equações estruturais. O sexto e último artigo “Percepção de saudável em produtos de pescado em uma população com alto consumo de pescado. Uma investigação por eye tracking” em que se objetivou explorar o uso do método eye tracking para estudar a percepção de saudável em diferentes produtos de pescado. Dois pontos importantes podem ser salientados como influentes na percepção de saudável: produtos de pescado processados e alimentos fritos.
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Cellular models are important tools in various research areas related to colorectal biology and associated diseases. Herein, we review the most widely used cell lines and the different techniques to grow them, either as cell monolayer, polarized two-dimensional epithelia on membrane filters, or as three-dimensional spheres in scaffoldfree or matrix-supported culture conditions. Moreover, recent developments, such as gut-on-chip devices or the ex vivo growth of biopsy-derived organoids, are also discussed. We provide an overview on the potential applications but also on the limitations for each of these techniques, while evaluating their contribution to provide more reliable cellular models for research, diagnostic testing, or pharmacological validation related to colon physiology and pathophysiology.
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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.
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A parameterization of mesoscale eddy fluxes in the ocean should be consistent with the fact that the ocean interior is nearly adiabatic. Gent and McWilliams have described a framework in which this can be approximated in L-coordinate primitive equation models by incorporating the effects of eddies on the buoyancy field through an eddy-induced velocity. It is also natural to base a parameterization on the simple picture of the mixing of potential vorticity in the interior and the mixing of buoyancy at the surface. The authors discuss the various constraints imposed by these two requirements and attempt to clarify the appropriate boundary conditions on the eddy-induced velocities at the surface. Quasigeostrophic theory is used as a guide to the simplest way of satisfying these constraints.
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Dissertação de Mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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Tese (doutorado)—Universidade de Brasília, Instituto de Geociências, Programa de Pós-Graduação em Geologia, 2015.
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Obnoxious single facility location models are models that have the aim to find the best location for an undesired facility. Undesired is usually expressed in relation to the so-called demand points that represent locations hindered by the facility. Because obnoxious facility location models as a rule are multimodal, the standard techniques of convex analysis used for locating desirable facilities in the plane may be trapped in local optima instead of the desired global optimum. It is assumed that having more optima coincides with being harder to solve. In this thesis the multimodality of obnoxious single facility location models is investigated in order to know which models are challenging problems in facility location problems and which are suitable for site selection. Selected for this are the obnoxious facility models that appear to be most important in literature. These are the maximin model, that maximizes the minimum distance from demand point to the obnoxious facility, the maxisum model, that maximizes the sum of distance from the demand points to the facility and the minisum model, that minimizes the sum of damage of the facility to the demand points. All models are measured with the Euclidean distances and some models also with the rectilinear distance metric. Furthermore a suitable algorithm is selected for testing multimodality. Of the tested algorithms in this thesis, Multistart is most appropriate. A small numerical experiment shows that Maximin models have on average the most optima, of which the model locating an obnoxious linesegment has the most. Maximin models have few optima and are thus not very hard to solve. From the Minisum models, the models that have the most optima are models that take wind into account. In general can be said that the generic models have less optima than the weighted versions. Models that are measured with the rectilinear norm do have more solutions than the same models measured with the Euclidean norm. This can be explained for the maximin models in the numerical example because the shape of the norm coincides with a bound of the feasible area, so not all solutions are different optima. The difference found in number of optima of the Maxisum and Minisum can not be explained by this phenomenon.
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The International Space Station (ISS) requires a substantial amount of potable water for use by the crew. The economic and logistic limitations of transporting the vast amount of water required onboard the ISS necessitate onboard recovery and reuse of the aqueous waste streams. Various treatment technologies are employed within the ISS water processor to render the waste water potable, including filtration, ion exchange, adsorption, and catalytic wet oxidation. The ion exchange resins and adsorption media are combined in multifiltration beds for removal of ionic and organic compounds. A mathematical model (MFBMODEL™) designed to predict the performance of a multifiltration (MF) bed was developed. MFBMODEL consists of ion exchange models for describing the behavior of the different resin types in a MF bed (e.g., mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins) and an adsorption model capable of predicting the performance of the adsorbents in a MF bed. Multicomponent ion exchange ii equilibrium models that incorporate the water formation reaction, electroneutrality condition, and degree of ionization of weak acids and bases for mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins were developed and verified. The equilibrium models developed use a tanks-inseries approach that allows for consideration of variable influent concentrations. The adsorption modeling approach was developed in related studies and application within the MFBMODEL framework was demonstrated in the Appendix to this study. MFBMODEL consists of a graphical user interface programmed in Visual Basic and Fortran computational routines. This dissertation shows MF bed modeling results in which the model is verified for a surrogate of the ISS waste shower and handwash stream. In addition, a multicomponent ion exchange model that incorporates mass transfer effects was developed, which is capable of describing the performance of strong acid cation (SAC) and strong base anion (SBA) exchange resins, but not including reaction effects. This dissertation presents results showing the mass transfer model's capability to predict the performance of binary and multicomponent column data for SAC and SBA exchange resins. The ion exchange equilibrium and mass transfer models developed in this study are also applicable to terrestrial water treatment systems. They could be applied for removal of cations and anions from groundwater (e.g., hardness, nitrate, perchlorate) and from industrial process waters (e.g. boiler water, ultrapure water in the semiconductor industry).
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In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.
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Power flow calculations are one of the most important tools for power system planning and operation. The need to account for uncertainties when performing power flow studies led, among others methods, to the development of the fuzzy power flow (FPF). This kind of models is especially interesting when a scarcity of information exists, which is a common situation in liberalized power systems (where generation and commercialization of electricity are market activities). In this framework, the symmetric/constrained fuzzy power flow (SFPF/CFPF) was proposed in order to avoid some of the problems of the original FPF model. The SFPF/CFPF models are suitable to quantify the adequacy of transmission network to satisfy “reasonable demands for the transmission of electricity” as defined, for instance, in the European Directive 2009/72/EC. In this work it is illustrated how the SFPF/CFPF may be used to evaluate the impact on the adequacy of a transmission system originated by specific investments on new network elements
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Abstract : Recently, there is a great interest to study the flow characteristics of suspensions in different environmental and industrial applications, such as snow avalanches, debris flows, hydrotransport systems, and material casting processes. Regarding rheological aspects, the majority of these suspensions, such as fresh concrete, behave mostly as non-Newtonian fluids. Concrete is the most widely used construction material in the world. Due to the limitations that exist in terms of workability and formwork filling abilities of normal concrete, a new class of concrete that is able to flow under its own weight, especially through narrow gaps in the congested areas of the formwork was developed. Accordingly, self-consolidating concrete (SCC) is a novel construction material that is gaining market acceptance in various applications. Higher fluidity characteristics of SCC enable it to be used in a number of special applications, such as densely reinforced sections. However, higher flowability of SCC makes it more sensitive to segregation of coarse particles during flow (i.e., dynamic segregation) and thereafter at rest (i.e., static segregation). Dynamic segregation can increase when SCC flows over a long distance or in the presence of obstacles. Therefore, there is always a need to establish a trade-off between the flowability, passing ability, and stability properties of SCC suspensions. This should be taken into consideration to design the casting process and the mixture proportioning of SCC. This is called “workability design” of SCC. An efficient and non-expensive workability design approach consists of the prediction and optimization of the workability of the concrete mixtures for the selected construction processes, such as transportation, pumping, casting, compaction, and finishing. Indeed, the mixture proportioning of SCC should ensure the construction quality demands, such as demanded levels of flowability, passing ability, filling ability, and stability (dynamic and static). This is necessary to develop some theoretical tools to assess under what conditions the construction quality demands are satisfied. Accordingly, this thesis is dedicated to carry out analytical and numerical simulations to predict flow performance of SCC under different casting processes, such as pumping and tremie applications, or casting using buckets. The L-Box and T-Box set-ups can evaluate flow performance properties of SCC (e.g., flowability, passing ability, filling ability, shear-induced and gravitational dynamic segregation) in casting process of wall and beam elements. The specific objective of the study consists of relating numerical results of flow simulation of SCC in L-Box and T-Box test set-ups, reported in this thesis, to the flow performance properties of SCC during casting. Accordingly, the SCC is modeled as a heterogeneous material. Furthermore, an analytical model is proposed to predict flow performance of SCC in L-Box set-up using the Dam Break Theory. On the other hand, results of the numerical simulation of SCC casting in a reinforced beam are verified by experimental free surface profiles. The results of numerical simulations of SCC casting (modeled as a single homogeneous fluid), are used to determine the critical zones corresponding to the higher risks of segregation and blocking. The effects of rheological parameters, density, particle contents, distribution of reinforcing bars, and particle-bar interactions on flow performance of SCC are evaluated using CFD simulations of SCC flow in L-Box and T-box test set-ups (modeled as a heterogeneous material). Two new approaches are proposed to classify the SCC mixtures based on filling ability and performability properties, as a contribution of flowability, passing ability, and dynamic stability of SCC.
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Con el inicio del periodo Post-Guerra Fría el Sistema Internacional comienza a experimentar un incremento en el fortalecimiento de su componente social; la Sociedad de Estados alcanza un mayor nivel de homogenización, el estado, unidad predominante de esta, comienzan atravesar una serie de transformaciones que obedecerán a una serie de cambios y continuidades respecto al periodo anterior. Desde la perspectiva del Realismo Subalterno de las Relaciones Internacionales se destacan el proceso de construcción de estado e inserción al sistema como las variables que determinan el sentimiento de inseguridad experimentado por las elites estatales del Tercer Mundo; procesos que en el contexto de un nuevo y turbulento periodo en el sistema, tomara algunas características particulares que darán un sentido especifico al sentimiento de inseguridad y las acciones a través de las cuales las elites buscan disminuirlo. La dimensión externa del sentimiento de inseguridad, el nuevo papel que toma la resistencia popular como factor determinante del sentimiento de inseguridad y de la cooperación, así como del conflicto, entre los miembros de la Sociedad Internacional, la inserción como promotor de estrategias de construcción de Estado, son alguno de los temas puntuales, que desde la perspectiva subalterna, parecen salir a flote tras el análisis del sistema en lo que se ha considerado como el periodo Post-Guerra Fría. En este sentido Yemen, se muestra como un caso adecuado no solo para poner a prueba las postulados de la teoría subalterna, veinte años después de su obra más prominente (The third world security Predicament), escrita por M. Ayoob, sino como un caso pertinente que permite acercarse más a la comprensión del papel del Tercer Mundo al interior de la Sociedad Internacional de Estados.
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We modelled the distributions of two toads (Bufo bufo and Epidalea calamita) in the Iberian Peninsula using the favourability function, which makes predictions directly comparable for different species and allows fuzzy logic operations to relate different models. The fuzzy intersection between individual models, representing favourability for the presence of both species simultaneously, was compared with another favourability model built on the presences shared by both species. The fuzzy union between individual models, representing favourability for the presence of any of the two species, was compared with another favourabilitymodel based on the presences of either or both of them. The fuzzy intersections between favourability for each species and the complementary of favourability for the other (corresponding to the logical operation “A and not B”) were compared with models of exclusive presence of one species versus the exclusive presence of the other. The results of modelling combined species data were highly similar to those of fuzzy logic operations between individual models, proving fuzzy logic and the favourability function valuable for comparative distribution modelling. We highlight several advantages of fuzzy logic over other forms of combining distribution models, including the possibility to combine multiple species models for management and conservation planning.
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A problemática relacionada com a modelação da qualidade da água de albufeiras pode ser abordada de diversos pontos de vista. Neste trabalho recorre-se a metodologias de resolução de problemas que emanam da Área Cientifica da Inteligência Artificial, assim como a ferramentas utilizadas na procura de soluções como as Árvores de Decisão, as Redes Neuronais Artificiais e a Aproximação de Vizinhanças. Actualmente os métodos de avaliação da qualidade da água são muito restritivos já que não permitem aferir a qualidade da água em tempo real. O desenvolvimento de modelos de previsão baseados em técnicas de Descoberta de Conhecimento em Bases de Dados, mostrou ser uma alternativa tendo em vista um comportamento pró-activo que pode contribuir decisivamente para diagnosticar, preservar e requalificar as albufeiras. No decurso do trabalho, foi utilizada a aprendizagem não-supervisionada tendo em vista estudar a dinâmica das albufeiras sendo descritos dois comportamentos distintos, relacionados com a época do ano. ABSTRACT: The problems related to the modelling of water quality in reservoirs can be approached from different viewpoints. This work resorts to methods of resolving problems emanating from the Scientific Area of Artificial lntelligence as well as to tools used in the search for solutions such as Decision Trees, Artificial Neural Networks and Nearest-Neighbour Method. Currently, the methods for assessing water quality are very restrictive because they do not indicate the water quality in real time. The development of forecasting models, based on techniques of Knowledge Discovery in Databases, shows to be an alternative in view of a pro-active behavior that may contribute to diagnose, maintain and requalify the water bodies. ln this work. unsupervised learning was used to study the dynamics of reservoirs, being described two distinct behaviors, related to the time of year.