952 resultados para Distributed Lag Non-linear Models


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A geração de trajectórias de robôs em tempo real é uma tarefa muito complexa, não existindo ainda um algoritmo que a permita resolver de forma eficaz. De facto, há controladores eficientes para trajectórias previamente definidas, todavia, a adaptação a variações imprevisíveis, como sendo terrenos irregulares ou obstáculos, constitui ainda um problema em aberto na geração de trajectórias em tempo real de robôs. Neste trabalho apresentam-se modelos de geradores centrais de padrões de locomoção (CPGs), inspirados na biologia, que geram os ritmos locomotores num robô quadrúpede. Os CPGs são modelados matematicamente por sistemas acoplados de células (ou neurónios), sendo a dinâmica de cada célula dada por um sistema de equações diferenciais ordinárias não lineares. Assume-se que as trajectórias dos robôs são constituídas por esta parte rítmica e por uma parte discreta. A parte discreta pode ser embebida na parte rítmica, (a.1) como um offset ou (a.2) adicionada às expressões rítmicas, ou (b) pode ser calculada independentemente e adicionada exactamente antes do envio dos sinais para as articulações do robô. A parte discreta permite inserir no passo locomotor uma perturbação, que poderá estar associada à locomoção em terrenos irregulares ou à existência de obstáculos na trajectória do robô. Para se proceder á análise do sistema com parte discreta, será variado o parâmetro g. O parâmetro g, presente nas equações da parte discreta, representa o offset do sinal após a inclusão da parte discreta. Revê-se a teoria de bifurcação e simetria que permite a classificação das soluções periódicas produzidas pelos modelos de CPGs com passos locomotores quadrúpedes. Nas simulações numéricas, usam-se as equações de Morris-Lecar e o oscilador de Hopf como modelos da dinâmica interna de cada célula para a parte rítmica. A parte discreta é modelada por um sistema inspirado no modelo VITE. Medem-se a amplitude e a frequência de dois passos locomotores para variação do parâmetro g, no intervalo [-5;5]. Consideram-se duas formas distintas de incluir a parte discreta na parte rítmica: (a) como um (a.1) offset ou (a.2) somada nas expressões que modelam a parte rítmica, e (b) somada ao sinal da parte rítmica antes de ser enviado às articulações do robô. No caso (a.1), considerando o oscilador de Hopf como dinâmica interna das células, verifica-se que a amplitude e frequência se mantêm constantes para -50.2. A extensão do movimento varia de forma directamente proporcional à amplitude. No caso das equações de Morris-Lecar, quando a componente discreta é embebida (a.2), a amplitude e a frequência aumentam e depois diminuem para - 0.170.5 Pode concluir-se que: (1) a melhor forma de inserção da parte discreta que menos perturbação insere no robô é a inserção como offset; (2) a inserção da parte discreta parece ser independente do sistema de equações diferenciais ordinárias que modelam a dinâmica interna de cada célula. Como trabalho futuro, é importante prosseguir o estudo das diferentes formas de inserção da parte discreta na parte rítmica do movimento, para que se possa gerar uma locomoção quadrúpede, robusta, flexível, com objectivos, em terrenos irregulares, modelada por correcções discretas aos padrões rítmicos.

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OBJECTIVE: To examine whether the low birth weight (LBW) paradox exists in Brazil. METHODS: LBW and cesarean section rates between 1995 and 2007 were estimated based on data from SINASC (Brazilian Live Births Database). Infant mortality rates (IMRs) were obtained using an indirect method that correct for underreporting. Schooling information was obtained from census data. Trends in LBW rate were assessed using joinpoint regression models. The correlations between LBW rate and other indicators were graphically assessed by lowess regression and tested using Spearman's rank correlation. RESULTS: In Brazil, LBW rate trends were non-linear and non-significant: the rate dropped from 7.9% in 1995 to 7.7% in 2000, then increased to 8.2% in 2003 and remained nearly steady thereafter at 8.2% in 2007. However, trends varied among Brazilian regions: there were significant increases in the North from 1999 to 2003 (2.7% per year), and in the South (1.0% per year) and Central-West regions (0.6% per year) from 1995 to 2007. For the entire period studied, higher LBW and lower IMRs were seen in more developed compared to less developed regions. In Brazilian States, in 2005, the higher the IMR rate, the lower the LBW rate (p=0.009); the lower the low schooling rate, the lower the LBW rate (p=0.007); the higher the number of neonatal intensive care beds per 1,000 live births, the higher the LBW rate (p=0.036). CONCLUSIONS: The low birth weight paradox was seen in Brazil. LBW rate is increasing in some Brazilian regions. Regional differences in LBW rate seem to be more associated to availability of perinatal care services than underlying social conditions.

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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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This paper studies the dynamical properties of a system with distributed backlash and impact phenomena. This means that it is considered a chain of masses that interact with each other solely by means of backlash and impact phenomena. It is observed the emergence of non-linear phenomena resembling those encountered in the Fermi-Pasta-Ulam problem.

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The increasing integration of larger amounts of wind energy into power systems raises important operational issues, such as the balance between power generation and demand. The pumped storage hydro (PSH) units are one possible solution to mitigate this problem, once they can store the excess of energy in the periods of higher generation and lower demand. However, the behaviour of a PSH unit may differ considerably from the expected in terms of wind power integration when it operates in a liberalized electricity market under a price-maker context. In this regard, this paper models and computes the optimal PSH weekly scheduling in a price-taker and price-maker scenarios, either when the PSH unit operates in standalone and integrated in a portfolio of other generation assets. Results show that the price-maker standalone PSH will integrate less wind power in comparison with the price-taker situation. Moreover, when the PSH unit is integrated in a portfolio with a base load power plant, the role of the price elasticity of demand may completely change the operational profile of the PSH unit. (C) 2014 Elsevier Ltd. All rights reserved.

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ABSTRACT OBJECTIVE To analyze the impact of air pollution on respiratory and cardiovascular morbidity of children and adults in the city of Vitoria, state of Espirito Santo. METHODS A study was carried out using time-series models via Poisson regression from hospitalization and pollutant data in Vitoria, ES, Southeastern Brazil, from 2001 to 2006. Fine particulate matter (PM10), sulfur dioxide (SO2), and ozone (O3) were tested as independent variables in simple and cumulative lags of up to five days. Temperature, humidity and variables indicating weekdays and city holidays were added as control variables in the models. RESULTS For each increment of 10 µg/m3 of the pollutants PM10, SO2, and O3, the percentage of relative risk (%RR) for hospitalizations due to total respiratory diseases increased 9.67 (95%CI 11.84-7.54), 6.98 (95%CI 9.98-4.17) and 1.93 (95%CI 2.95-0.93), respectively. We found %RR = 6.60 (95%CI 9.53-3.75), %RR = 5.19 (95%CI 9.01-1.5), and %RR = 3.68 (95%CI 5.07-2.31) for respiratory diseases in children under the age of five years for PM10, SO2, and O3, respectively. Cardiovascular diseases showed a significant relationship with O3, with %RR = 2.11 (95%CI 3.18-1.06). CONCLUSIONS Respiratory diseases presented a stronger and more consistent relationship with the pollutants researched in Vitoria. A better dose-response relationship was observed when using cumulative lags in polynomial distributed lag models.

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Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for column design for any type of packing and contaminant which avoids the necessity of an arbitrary chosen diameter. It also avoids the employment of the usual graphical Eckert correlations for pressure drop. The hydraulic features are previously chosen as a project criterion. The design procedure was translated into a convenient algorithm in C++ language. A column was built in order to test the design, the theoretical steady-state and dynamic behaviour. The experiments were conducted using a solution of chloroform in distilled water. The results allowed for a correction in the theoretical global mass transfer coefficient previously estimated by the Onda correlations, which depend on several parameters that are not easy to control in experiments. For best describe the column behaviour in stationary and dynamic conditions, an original mathematical model was developed. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting ODE can be solved by analytical methods, and in dynamic state the discretization of the PDE by finite differences allows for the overcoming of this difficulty. To estimate the contaminant concentrations in both phases in the column, a numerical algorithm was used. The high number of resulting algebraic equations and the impossibility of generating a recursive procedure did not allow the construction of a generalized programme. But an iterative procedure developed in an electronic worksheet allowed for the simulation. The solution is stable only for similar discretizations values. If different values for time/space discretization parameters are used, the solution easily becomes unstable. The system dynamic behaviour was simulated for the common liquid phase perturbations: step, impulse, rectangular pulse and sinusoidal. The final results do not configure strange or non-predictable behaviours.

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The objective of this contribution is to extend the models of cellular/composite material design to nonlinear material behaviour and apply them for design of materials for passive vibration control. As a first step a computational tool allowing determination of optimised one-dimensional isolator behaviour was developed. This model can serve as a representation for idealised macroscopic behaviour. Optimal isolator behaviour to a given set of loads is obtained by generic probabilistic metaalgorithm, simulated annealing. Cost functional involves minimization of maximum response amplitude in a set of predefined time intervals and maximization of total energy absorbed in the first loop. Dependence of the global optimum on several combinations of leading parameters of the simulated annealing procedure, like neighbourhood definition and annealing schedule, is also studied and analyzed. Obtained results facilitate the design of elastomeric cellular materials with improved behaviour in terms of dynamic stiffness for passive vibration control.

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The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

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The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

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This work refers to the development of modelling tools to create Ammonite shells in order to produce animated models for scientific dissemination and didactic purposes. In the approach here proposed we assume that the growth of those shells from an initial stage – the protoconch – can be interpreted as a succession of revolutions in turn of a central axis; thus the conch’s section will increase as a non-linear progression. So, we emphasise that the shape of many type of shells, e.g. gastropods and bivalves, is based on the equation of the logarithmic spiral deduced by R. Descartes. Pixels 3d (Pixels Digital Inc., 2005) is a TCL – scriptable modelling and animation software that allows extendable interapplication communication. Hence a standalone prototype (Shellia) with shell assignable parameters was produced and some of their issues and results will be presented here.

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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 the 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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Os Estados-Membros da União Europeia têm tido a preocupação de reduzirem a dimensão da Administração Pública na economia, a par de a tornar muito mais eficiente de forma a promover o crescimento económico. Neste artigo analisam-se as relações entre a despesa pública e o crescimento económico em 14 Estados-Membros da União Europeia dos 15, com o objectivo de determinar a dimensão óptima das Administrações Públicas, tendo por base teórica a Curva de Armey. Os resultados, para o período 1965-2007, sugerem uma dimensão do sector público maximizadora do crescimento económico de 47,37% e 22,17% do PIB, quando avaliada pelas despesas públicas totais e o consumo público, respectivamente.

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The aim of this contribution is to extend the techniques of composite materials design to non-linear material behaviour and apply it for design of new materials for passive vibration control. As a first step a computational tool allowing determination of macroscopic optimized one-dimensional isolator behaviour was developed. Voigt, Maxwell, standard and more complex material models can be implemented. Objective function considers minimization of the initial reaction and/or displacement peak as well as minimization of the steady-state amplitude of reaction and/or displacement. The complex stiffness approach is used to formulate the governing equations in an efficient way. Material stiffness parameters are assumed as non-linear functions of the displacement. The numerical solution is performed in the complex space. The steady-state solution in the complex space is obtained by an iterative process based on the shooting method which imposes the conditions of periodicity with respect to the known value of the period. Extension of the shooting method to the complex space is presented and verified. Non-linear behaviour of material parameters is then optimized by generic probabilistic meta-algorithm, simulated annealing. Dependence of the global optimum on several combinations of leading parameters of the simulated annealing procedure, like neighbourhood definition and annealing schedule, is also studied and analyzed. Procedure is programmed in MATLAB environment.

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In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.