997 resultados para Vehicle Dynamics


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We propose a fractional model for computer virus propagation. The model includes the interaction between computers and removable devices. We simulate numerically the model for distinct values of the order of the fractional derivative and for two sets of initial conditions adopted in the literature. We conclude that fractional order systems reveal richer dynamics than the classical integer order counterpart. Therefore, fractional dynamics leads to time responses with super-fast transients and super-slow evolutions towards the steady-state, effects not easily captured by the integer order models.

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In this paper we study a model for HIV and TB coinfection. We consider the integer order and the fractional order versions of the model. Let α∈[0.78,1.0] be the order of the fractional derivative, then the integer order model is obtained for α=1.0. The model includes vertical transmission for HIV and treatment for both diseases. We compute the reproduction number of the integer order model and HIV and TB submodels, and the stability of the disease free equilibrium. We sketch the bifurcation diagrams of the integer order model, for variation of the average number of sexual partners per person and per unit time, and the tuberculosis transmission rate. We analyze numerical results of the fractional order model for different values of α, including α=1. The results show distinct types of transients, for variation of α. Moreover, we speculate, from observation of the numerical results, that the order of the fractional derivative may behave as a bifurcation parameter for the model. We conclude that the dynamics of the integer and the fractional order versions of the model are very rich and that together these versions may provide a better understanding of the dynamics of HIV and TB coinfection.

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This paper reports on the analysis of tidal breathing patterns measured during noninvasive forced oscillation lung function tests in six individual groups. The three adult groups were healthy, with prediagnosed chronic obstructive pulmonary disease, and with prediagnosed kyphoscoliosis, respectively. The three children groups were healthy, with prediagnosed asthma, and with prediagnosed cystic fibrosis, respectively. The analysis is applied to the pressure-volume curves and the pseudophase-plane loop by means of the box-counting method, which gives a measure of the area within each loop. The objective was to verify if there exists a link between the area of the loops, power-law patterns, and alterations in the respiratory structure with disease. We obtained statistically significant variations between the data sets corresponding to the six groups of patients, showing also the existence of power-law patterns. Our findings support the idea that the respiratory system changes with disease in terms of airway geometry and tissue parameters, leading, in turn, to variations in the fractal dimension of the respiratory tree and its dynamics.

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In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

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In this paper, motivated by the interest and relevance of the study of tumor growth models, a central point of our investigation is the study of the chaotic dynamics and the bifurcation structure of Weibull-Gompertz-Fréchet's functions: a class of continuousdefined one-dimensional maps. Using symbolic dynamics techniques and iteration theory, we established that depending on the properties of this class of functions in a neighborhood of a bifurcation point PBB, in a two-dimensional parameter space, there exists an order regarding how the infinite number of periodic orbits are born: the Sharkovsky ordering. Consequently, the corresponding symbolic sequences follow the usual unimodal kneading sequences in the topological ordered tree. We verified that under some sufficient conditions, Weibull-Gompertz-Fréchet's functions have a particular bifurcation structure: a big bang bifurcation point PBB. This fractal bifurcations structure is of the so-called "box-within-a-box" type, associated to a boxe ω1, where an infinite number of bifurcation curves issues from. This analysis is done making use of fold and flip bifurcation curves and symbolic dynamics techniques. The present paper is an original contribution in the framework of the big bang bifurcation analysis for continuous maps.

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No âmbito do estágio curricular realizado na DSV Transitários, surgiu a oportunidade de estar inserida em duas das áreas funcionais da empresa: durante o primeiro mês, no departamento comercial e nos restantes meses no departamento ROAD (rodoviário Internacional) no qual me foi proporcionado a oportunidade de desempenhar funções de Operacional de Tráfego Rodoviário Internacional. Desta forma, surge o desafio de integrar na equipa de operacionais ROAD da DSV, por forma a contribuir ativamente para a rotina da empresa e paralelamente analisar os processos operacionais do departamento, bem como, identificar todos os pontos que necessitem de melhoria. Após estar inserida neste sector, compreendi que a grupagem de mercadorias desempenha um papel fundamental neste departamento, na medida em que, quando desenvolvida de uma forma eficiente, pode traduzir-se numa atividade de extremo valor. A dinâmica diária desta atividade exige que os operadores de tráfego respondam de uma forma rápida e flexível aos problemas, apresentando soluções eficazes às solicitações do mercado. Para isso, é importante encontrar mecanismos capazes de os auxiliar na tomada decisões operacionais.

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Sandflies attracted by human bait were caught in an endemic focus of localized cutaneous leishmaniasis in the state of Campeche, Mexico. Catches were carried out monthly from February 1994 to January 1995 between 18:00 and 22:00 h. Lutzomyia cruciata was the only species caught. The highest population peak of Lu. cruciata was found in March with lesser peaks in February, December 1994, and January 1995. Maximum biting rate of Lu. cruciata was found between 18:00 and 19:00 h. The host-seeking females of Lu. cruciata were directly related to levels of humidity between 88 and 100%. Low and high temperature had a negative effect upon Lu. cruciata activity. The possible role of Lu. cruciata as vector of leishmaniasis in the state of Campeche, Mexico is discussed.

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This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle- To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow calculation is included in the metaheuristics approach to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

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This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

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The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

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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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For a period of 2 years, five follow-up measures of prevalence and incidence rates were estimated in a prospective study of S. mansoni infection in a group of schoolchildren who were living in a rural area of the Municipality of Itariri (São Paulo, Brazil), where schistosomiasis is transmitted by Biomphalaria tenagophila. Infection was determined by the examination of three Kato-Katz stool slides, and the parasitological findings were analyzed in comparison to serological data. In the five surveys, carried out at 6-month intervals (March-April and September-October), the prevalences were, respectively, 8.6, 6.8, 9.9, 5.8 and 17.2% by the Kato-Katz, and 56.5, 52.6, 60.8, 53.5 and 70.1% by the immunofluorescence test (IFT). Geometric mean egg counts were low: 57.8, 33.0, 35.6, 47.3 and 40.9 eggs per gram of feces, respectively. Of the total of 299 schoolchildren, who submitted five blood samples at 6-month intervals, one for each survey, 40% were IFT-positive throughout the study, and 22% were IFT-negative in all five surveys. Seroconversion from IFT negative to positive, indicating newly acquired S. mansoni infection, was observed more frequently in surveys carried out during March-April (after Summer holidays), than during September-October. Seasonal trends were not statistically significant for detection of S. mansoni eggs in stool. The results indicate that the use of IgM-IFT is superior to parasitological methods for detection of incidence of S. mansoni infection in areas with low worm burden.

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We prove that the stable holonomies of a proper codimension 1 attractor Λ, for a Cr diffeomorphism f of a surface, are not C1+θ for θ greater than the Hausdorff dimension of the stable leaves of f intersected with Λ. To prove this result we show that there are no diffeomorphisms of surfaces, with a proper codimension 1 attractor, that are affine on a neighbourhood of the attractor and have affine stable holonomies on the attractor.

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Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

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The use of unmanned marine robotic vehicles in bathymetric surveys is discussed. This paper presents recent results in autonomous bathymetric missions with the ROAZ autonomous surface vehicle. In particular, robotic surface vehicles such as ROAZ provide an efficient tool in risk assessment for shallow water environments and water land interface zones as the near surf zone in marine coast. ROAZ is an ocean capable catamaran for distinct oceanographic missions, and with the goal to fill the gap were other hydrographic surveys vehicles/systems are not compiled to operate, like very shallow water rivers and marine coastline surf zones. Therefore, the use of robotic systems for risk assessment is validated through several missions performed either in river scenario (in a very shallow water conditions) and in marine coastlines.