Harmonic content identification based on neural method for single phase power systems

An alternative method is presented in this paper to identify the harmonic components of non-linear loads in single phase power systems based on artificial neural networks. The components are identified by analyzing the single phase current waveform in time domain in half-cycle of the ac voltage source. The proposed method is compared to the fast Fourier transform. Simulation and experimental results are presented to validate the proposed approach.

Assessment of the flexural strength of two heat-curing acrylic resins for artificial eyes

Prosthetic eyes are artificial substitutes for the eyeball, made of heat-curing acrylic resin, serving to improve the esthetic appearance of the mutilated patient and his/her inclusion in society. The aim of this study was to assess the flexural strength of two heat-curing acrylic resins used for manufacturing prosthetic eyes. Thirty-six specimens measuring 64 x 10 x 3.3 mm were obtained and divided into four groups: acrylic resin for artificial sclera N1 (Artigos Odontológicos Clássico, São Paulo, SP, Brazil), heat-cure water technique (GI) and microwave-cured (GII); colorless acrylic resin for prosthetic eyes (Artigos Odontológicos Clássico, São Paulo, SP, Brazil), heat-cure water technique (GIII) and microwave-cured (GIV). Mechanical tests using three point loads were performed in a test machine (EMIC, São José dos Pinhais, PR, Brazil). The analysis of variance and the Tukey test were used to identify significant differences (p < 0.01). Groups GII and GIV presented, respectively, the highest (98.70 ± 11.90 MPa) and lowest means (71.07 ± 8.93 MPa), with a statistically significant difference. The cure method used for the prosthetic eye resins did not interfere in their flexural strength. It was concluded that all the resins assessed presented sufficient flexural strength values to be recommended for the manufacture of prosthetic eyes.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Effects of surface treatment, hydration and application method on the bond strength of a silorane adhesive and resin system to dentine

Objectives: To evaluate the effects of surface treatment, surface hydration (SH) and application method (AM) on the tensile bond strength of the Silorane Adhesive System (SAS) to dentine. Methods: Ninety bovine teeth were used. For the control group (n = 10), each dentine surface was treated according to the manufacturer's instructions of the SAS. The remaining teeth were randomly distributed into two groups (n = 40), according to the type of dentine surface treatment (ST) - 37% phosphoric acid or Er:YAG Laser prior to the application of the SAS. Each group was further divided into 2 subgroups (n = 20), according to the SH status: dry (D) or wet (W). Each subgroup was further divided into 2 subgroups (n = 10), according to the application method [AM: Active (AC) mode or Passive (PA) mode]. A coat of resin composite (Filtek P90) was applied on the surface. Artificial ageing was performed with a thermo-mechanical cycling machine. The specimens were sectioned into 1 mm × 1 mm × 10 mm sticks and stressed to failure using a universal testing machine. The remaining teeth in each group were used for Scanning Electron Microscopy to examine the fractured area. Data were subjected to a three-way ANOVA, Tukey's test and Dunnet's test (α = 0.05). Results: The ANOVA showed significant differences for SH and AM, but not for ST. For SH, the results of Tukey's test were (in MPa): D-14.9(±3.8)a, W-17.1(±4.3)b; and for AM: PA-14. 9(±4.2)a, AC-17.1(±3.9) b. Conclusions: Acid etching, when combined with a moist dentine surface and the use of primer agitation, improves the bond strength of the SAS to dentine. Clinical Significance: According to the results of the present in vitro study, modification of the application protocols for the silorane-based adhesive system may improve its clinical performance. © 2012 Published by Elsevier Ltd.

Chlorophyll a spatial inference using artificial neural network from multispectral images and in situ measurements

Considering the importance of monitoring the water quality parameters, remote sensing is a practicable alternative to limnological variables detection, which interacts with electromagnetic radiation, called optically active components (OAC). Among these, the phytoplankton pigment chlorophyll a is the most representative pigment of photosynthetic activity in all classes of algae. In this sense, this work aims to develop a method of spatial inference of chlorophyll a concentration using Artificial Neural Networks (ANN). To achieve this purpose, a multispectral image and fluorometric measurements were used as input data. The multispectral image was processed and the net training and validation dataset were carefully chosen. From this, the neural net architecture and its parameters were defined to model the variable of interest. In the end of training phase, the trained network was applied to the image and a qualitative analysis was done. Thus, it was noticed that the integration of fluorometric and multispectral data provided good results in the chlorophyll a inference, when combined in a structure of artificial neural networks.

Onboard and real-time artificial satellite orbit determination using GPS

An algorithm for real-time and onboard orbit determination applying the Extended Kalman Filter (EKF) method is developed. Aiming at a very simple and still fairly accurate orbit determination, an analysis is performed to ascertain an adequacy of modeling complexity versus accuracy. The minimum set of to-be-estimated states to reach the level of accuracy of tens of meters is found to have at least the position, velocity, and user clock offset components. The dynamical model is assessed through several tests, covering force model, numerical integration scheme and step size, and simplified variational equations. The measurement model includes only relevant effects to the order of meters. The EKF method is chosen to be the simplest real-time estimation algorithm with adequate tuning of its parameters. In the developed procedure, the obtained position and velocity errors along a day vary from 15 to 20 m and from 0.014 to 0.018 m/s, respectively, with standard deviation from 6 to 10 m and from 0.006 to 0.008 m/s, respectively, with the SA either on or off. The results, as well as analysis of the final adopted models used, are presented in this work. © 2013 Ana Paula Marins Chiaradia et al.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.

Speed estimation for induction motor using neural networks method

This work presents an alternative approach based on neural network method in order to estimate speed of induction motors, using the measurement of primary variables such as voltage and current. Induction motors are very common in many sectors of the industry and assume an important role in the national energy policy. The nowadays methodologies, which are used in diagnosis, condition monitoring and dimensioning of these motors, are based on measure of the speed variable. However, the direct measure of this variable compromises the system control and starting circuit of an electric machinery, reducing its robustness and increasing the implementation costs. Simulation results and experimental data are presented to validate the proposed approach. © 2003-2012 IEEE.

Efeito da concentração espermática e da metodologia de inseminação artificial com sêmen equino congelado

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

Quantificação de citocinas no líquido amniótico de bezerros nelore oriundos de produção in vitro, tranferência de embrião e inseminação artificial colhido no momento do parto

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

Avaliação clínica, morbi-mortalidade e desenvolvimento de bezerros da raça Brahman produzidos por fertilização in vitro e inseminação artificial

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

Metodologias de avaliação de sêmen e procedimentos de fertilização artificial de surubim-do-paraíba, Steindachneridion parahybae

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Avaliação da técnica de inseminação artificial intrauterina em fêmeas caninas por videolaparoscopia com sêmen fresco e descongelado

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Cl-synch: protocolo alternativo para inseminação artificial em tempo fixo em búfalas, criadas em sistema extensivo na Amazônia

Apesar dos avanços tecnológicos alcançados no manejo de criação de búfalos e de técnicas de melhoramento genético, pouco se utilizam na prática para búfalos criados de forma extensiva. O desenvolvimento de protocolos de sincronização, que diminuam o estresse de contenção e reduzem os custos, contribuirá para o incremento da utilização da IATF nos rebanhos bubalinos. O experimento objetivou avaliar um método de sincronização e IATF econômico e pratico compatível ao tipo de criação extensiva. O experimento foi realizado em três fazendas distintas, duas em uma região de várzea, no Estado do Amapá (Local 1 e 2) conduzido na estação reprodutiva favorável. O terceiro no estado do Pará em pastagem cultivada de terra firme. Foram utilizadas 208 búfalas lactantes mestiças mediterrâneo/murrah com idades variadas de 2,5 a 10 anos com histórico de período pós parto ≥ 60 dias. As matrizes que portavam um corpo lúteo foi aplicado 2.0 ml Intra-Muscular de prostaglandina (PGF2α) (150μg/D-cloprostenol) no Dia 0 = D0. Setenta duas horas depois (Dia 3 = D3), foram realizados exame ginecológico para verificar a presença de muco e contratilidade uterina, e posterior inseminação e aplicação de 1.0 ml (100μg) IM de GnRH, com sêmen, de diferentes reprodutores. O diagnóstico de prenhez foi realizado entre 45 a 90 dias, através da palpação retal. O CL-Synch proporcionou uma taxa de prenhez media de 42,79%. Houve efeito significativo das variáveis: presença de contratilidade uterina (χ²= 10.9891; P= 0.0009), muco (χ²= 10.9891; P= 0.0009) e a condição corporal, (χ²= 20.2247; P= 0.0005). A presença do tônus uterino e do muco uterino mostraram-se como excelentes sinais indicativos de uma resposta de crescimento e diferenciação folicular e ovulação à estimulação hormonal. A relação reprodutor e taxa de prenhez não foi estatisticamente significativo (P=0,1684), sugerindo a uniformidade na qualidade do sêmen congelado proveniente da mesma central. Concluí-se que o CL-synch é promissor e suas vantagens se concentram no manejo de contenção das fêmeas e o baixo custo, pois possibilita a contenção somente duas vezes, quando comparado aos demais protocolos que necessitam de contenção de quatro vezes ou mais, diminuindo consideravelmente o estresse.

Composição bioquímica e hormonal do líquido ammniotico de fetos bovinos oriundos de inseminação artificial(IA), transferência de embriões(TE) e produção in vitro(PIV)

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