Projeto estrutural e parametrização de uma comporta segmento utilizando o método dos elementos finitos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A Learning Function for Parameter Reduction in Spiking Neural Networks with Radial Basis Function

Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

Perfil radial e uniformidade de precipitação do aspersor NaanDanJain 427, em função da regulagem do defletor

The study aimed to evaluate the radial profile and the uniformity of water distribution of sprinkler manufactured by the company NaanDanJain, model 427 1/2 '' M and nozzle with 2.8 mm of internal diameter, operating at pressures of 150, 200, 300 and 400 kPa and five positions of the deflector (0, 20, 50, 80 and 100%). For the determination of the parameters evaluated, the grid method was used and with the help of computer application CATCH 3D, overlapping layers of water depths was calculated with ten spacing. The results show that the deflector adjustment influences the radius of wetness and the distribution profile while the uniformity of water application showed as an important mechanism, since it permits different behavior for the sprinkler, ensuring wide track of utilization of the equipment.

Avaliação mesoscópica da origem, distribuição e ramificação do nervo radial no braço do gato doméstico (Felis catus domesticus, Linnaeus, 1758)

The present study evaluated the origin, distribution and ramification of the radial nerves were studied in 30 adult domestic cats. The sample included 15 females and 15 males of unknown breed. The specimens were fixed in 10% formaldehyde solution. The radial nerve showed many fascicles from the origin also your ramification in superficial and deep branches. Radial nerves were observed to originate, in 16 cases (26.7%), from the ventral branch of the sixth cervical spinal nerve; in 60 cases (100%), from the ventral branch of the seventh cervical spinal nerve; in 60 cases (100%), from the ventral branch of the eight cervical nerve and in 60 cases (100%), from the ventral branch of the first thoracic nerve. The radial nerves branched out, in all of the animals studied (100.0%), to the tensor fasciae antebrachii, long, accessory, medial and lateral heads of the triceps branchii and anconeus muscles. The radial nerve emits of 14 to 25 nervous branches in this region. However, the branch of the sixth cervical spinal nerve and the nervous fascicles reveal significant differences (p <= 0.05), respectively, in or with relation to sex of the animals and the studied region.

Comparative study between RBF and radial-PPS neural networks

The study of function approximation is motivated by the human limitation and inability to register and manipulate with exact precision the behavior variations of the physical nature of a phenomenon. These variations are referred to as signals or signal functions. Many real world problem can be formulated as function approximation problems and from the viewpoint of artificial neural networks these can be seen as the problem of searching for a mapping that establishes a relationship from an input space to an output space through a process of network learning. Several paradigms of artificial neural networks (ANN) exist. Here we will be investigated a comparative of the ANN study of RBF with radial Polynomial Power of Sigmoids (PPS) in function approximation problems. Radial PPS are functions generated by linear combination of powers of sigmoids functions. The main objective of this paper is to show the advantages of the use of the radial PPS functions in relationship traditional RBF, through adaptive training and ridge regression techniques.

Radial Plasma Dynamic in Sequential Pinches

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multinodal Load Forecasting in Power Electric Systems using a Neural Network with Radial Basis Function

In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.

A model to predict R134a refrigerant leakage through the radial clearance of rolling piston compressors

In this paper a non-isothermal two-phase model for oil-R134a refrigerant mixture flow is presented to predict the R134a leakage through the radial clearance of rolling piston compressors. The flow is divided in a liquid single-phase region and in a two-phase region, in which the homogeneous model is used to simulate the flow. The refrigerant leakage is determined using the mixture mass flow rate and the refrigerant mass fraction variation along the flow. The results are obtained for inlet pressures varying from 200 to 700 kPa, inlet temperatures ranging from 40 to 60 degrees C, and minimal clearances between 10 and 60 mu m. The results are firstly compared to existing isothermal model data, showing that there is a significant difference between the leakage flow rates predicted by isothermal and non-isothermal models. Finally, a useful general equation for compressor designers is proposed to calculate the refrigerant leakage for a large range of operation conditions. (C) 2012 Elsevier Ltd and IIR. All rights reserved.

Postfeeding radial dispersal in larvae of Chrysomya albiceps (Diptera : Calliphoridae): implications for forensic entomology

Blowflies utilize discrete and ephemeral breeding sites for larval nutrition. After the exhaustion of food, larvae begin dispersing in search of sites to pupate or additional food sources, a process referred as postfeeding larval dispersal. Some of the most important aspects of this process were investigated in the blowfly Chrysomya albiceps, employing a circular arena to allow radial dispersion of larvae from the center. The results showed a positive correlation between burial depth and distance, and a negative correlation between distance and pupal weight. These results can be used in forensic entomology for the postmortem interval estimation of human corpses in medico-criminal investigations. (c) 2004 Elsevier B.V.. All rights reserved.

Study of the combined radial post-feeding dispersion of the blowflies Chrysomya megacephala (Fabricius) and C. albiceps (Wiedemann) (Diptera, Calliphoridae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudo da dispersão larval radial pós-alimentar em Chrysomya megacephala (Fabricius) (Diptera, Calliphoridae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Dispersão larval radial pós-alimentar em Lucilia cuprina (Diptera, Calliphoridae): profundidade, peso e distância de enterramento para pupação

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Behavior of the combined radial post-feeding larval dispersal of the blowflies Chrysomya megacephala and Chrysomya albiceps (Diptera, Calliphoridae) and implications for forensic entomology

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Numerical simulation of a radial diffuser turbulent airflow

In the present work are presented results from numerical simulations performed with the ANSYS-CFX (R) code. We have studied a radial diffuser flow case, which is the main academic problem used to study the flow behavior on flat plate valves. The radial flow inside the diffuser has important behavior such as the turbulence decay downstream and recirculation regions inside the valve flow channel due to boundary layer detachment. These flow structures are present in compressor reed valve configurations, influencing to a greater extent the compressor efficiency. The main target of the present paper was finding the simulation set-up (computational domain, boundary conditions and turbulence model) that better fits with experimental data published by Tabatabai and Pollard. The local flow turbulence and velocity profiles were investigated using four different turbulence models, two different boundary conditions set-up, two different computational domains and three different flow conditions (Re-in - Reynolds number at the diffuser inlet). We used the Reynolds stress (BSL); the k-epsilon; the RNG k-epsilon; and the shear stress transport (SST) k-omega turbulence models. The performed analysis and comparison of the computational results with experimental data show that the choice of the turbulence model, as well as the choice of the other computational conditions, plays an important role in the results physical quality and accuracy. (c) 2007 Elsevier B.V. All rights reserved.

Blocking Radial Diffusion in a Double-Waved Hamiltonian Model

A non-twist Hamiltonian system perturbed by two waves with particular wave numbers can present Robust Tori, barriers created by the vanishing of the perturbing Hamiltonian at some defined positions. When Robust Tori exist, any trajectory in phase space passing close to them is blocked by emergent invariant curves that prevent the chaotic transport. We analyze the breaking up of the RT as well the transport dependence on the wave numbers and on the wave amplitudes. Moreover, we report the chaotic web formation in the phase space and how this pattern influences the transport.