9 resultados para Field trip
em Universidade do Minho
Resumo:
Devido à elevada dimensão espacial e temporal da maior parte dos fenómenos geológicos, não é possível reproduzir no laboratório os fenómenos a estudar, pelo que, se o professor de Geologia pretender colocar os alunos em contato com esses fenómenos, terá que organizar uma saída de campo para que as necessárias e adequadas atividades sejam realizadas no lugar onde esses fenómenos ocorrem. Contudo, e apesar de professores e alunos reconhecerem diversas potencialidades didáticas das saídas de campo, os professores raramente as organizam e justificam isso com base em diversos impedimentos. Neste artigo relatam-se os resultados de um estudo em que 233 professores portugueses de Biologia e Geologia foram inquiridos acerca de formas ideais de integrar as atividades de campo na componente de Geologia, no 3º ciclo do Ensino Básico (n=102) e no Ensino Secundário (n=131). Os resultados sugerem que as práticas que os professores gostariam de implementar, caso não houvesse constrangimentos à realização de atividades de campo, não seriam, na maior parte dos casos, muito diferentes das práticas implementadas que são relatadas na literatura. Esta falta de exigência e de ousadia por parte dos professores, no que concerne ao modo como as atividades de campo deveriam ser utilizadas, sugere a necessidade de a formação inicial e contínua de professores contemplar uma abordagem adequada das saídas de campo e de as escolas se reorganizarem para facilitarem a organização, fundamentada, das mesmas.
Resumo:
This paper presents the design and the prototype implementation of a three-phase power inverter developed to drive a motor-in-wheel. The control system is implemented in a FPGA (Field Programmable Gate Array) device. The paper describes the Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique that were implemented. The control platform uses a Spartan-3E FPGA board, programmed with Verilog language. Simulation and experimental results are presented to validate the developed system operation under different load conditions. Finally are presented conclusions based on the experimental results.
Resumo:
Electric Vehicles (EVs) are increasingly used nowadays, and different powertrain solutions can be adopted. This paper describes the control system of an axial flux Permanent Magnet Synchronous Motor (PMSM) for EVs powertrain. It is described the implemented Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique. Also, the mathematical model of the PMSM is presented. Both, simulation and experimental, results with different types of mechanical load are presented. The experimental results were obtained using a laboratory test bench. The obtained results are discussed.
Resumo:
One of the most popular approaches to path planning and control is the potential field method. This method is particularly attractive because it is suitable for on-line feedback control. In this approach the gradient of a potential field is used to generate the robot's trajectory. Thus, the path is generated by the transient solutions of a dynamical system. On the other hand, in the nonlinear attractor dynamic approach the path is generated by a sequence of attractor solutions. This way the transient solutions of the potential field method are replaced by a sequence of attractor solutions (i.e., asymptotically stable states) of a dynamical system. We discuss at a theoretical level some of the main differences of these two approaches.
Resumo:
Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.
Resumo:
We summarise recent results about the evolution of linear density perturbations in scalar field cosmologies with an exponential potential. We use covariant and gauge invariant perturbation variables and a dynamical systems' approach. We establish under what conditions do the perturbations decay to the future in agreement with the cosmic no-hair conjecture.
Resumo:
The computation of the optical conductivity of strained and deformed graphene is discussed within the framework of quantum field theory in curved spaces. The analytical solutions of the Dirac equation in an arbitrary static background geometry for one dimensional periodic deformations are computed, together with the corresponding Dirac propagator. Analytical expressions are given for the optical conductivity of strained and deformed graphene associated with both intra and interbrand transitions. The special case of small deformations is discussed and the result compared to the prediction of the tight-binding model.
Resumo:
We study the longitudinal and transverse spin dynamical structure factors of the spin-1/2 XXX chain at finite magnetic field h, focusing in particular on the singularities at excitation energies in the vicinity of the lower thresholds. While the static properties of the model can be studied within a Fermi-liquid like description in terms of pseudoparticles, our derivation of the dynamical properties relies on the introduction of a form of the ‘pseudofermion dynamical theory’ (PDT) of the 1D Hubbard model suitably modified for the spin-only XXX chain and other models with two pseudoparticle Fermi points. Specifically, we derive the exact momentum and spin-density dependences of the exponents ζτ(k) controlling the singularities for both the longitudinal  and transverse (τ = t) dynamical structure factors for the whole momentum range  , in the thermodynamic limit. This requires the numerical solution of the integral equations that define the phase shifts in these exponents expressions. We discuss the relation to neutron scattering and suggest new experiments on spin-chain compounds using a carefully oriented crystal to test our predictions.
Resumo:
Inspired by natural structures, great attention has been devoted to the study and development of surfaces with extreme wettable properties. The meticulous study of natural systems revealed that the micro/nano-topography of the surface is critical to obtaining unique wettability features, including superhydrophobicity. However, the surface chemistry also has an important role in such surface characteristics. As the interaction of biomaterials with the biological milieu occurs at the surface of the materials, it is expected that synthetic substrates with extreme and controllable wettability ranging from superhydrophilic to superhydrophobic regimes could bring about the possibility of new investigations of cellâ material interactions on nonconventional surfaces and the development of alternative devices with biomedical utility. This first part of the review will describe in detail how proteins and cells interact with micro/nano-structured surfaces exhibiting extreme wettabilities.