The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

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

Spatial evaluation of larvae of Culicidae (Diptera) from different breeding sites: application of a geospatial method and implications for vector control

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Smart structures health monitoring using artificial neural network

This paper presents a non-model based technique to detect and locate structural damage with the use of artificial neural networks. This method utilizes high frequency structural excitation (typically greater than 30 kHz) through a surface-bonded piezoelectric sensor/actuator to detect changes in structural point impedance due to the presence of damage. Two sets of artificial neural networks were developed in order to detect, locate and characterize structural damage by examining changes in the measured impedance curves. A simulation beam model was developed to verify the proposed method. An experiment was successfully performed in detecting damage on a 4-bay structure with bolted-joints, where the bolts were progressively released.

Potentiometric determination of saccharin in commercial artificial sweeteners using a silver electrode

A simple, precise, rapid and low-cost potentiometric method for saccharin determination in commercial artificial sweeteners is proposed. Saccharin present in several samples of artificial sweeteners is potentiometrically titrated with silver nitrate solution using a silver wire as the indicator electrode, coupled to a titroprocessor. The best pH range was from 3.0 to 3.5 and the detection limit of sodium saccharin was 2.5 mg/ml. Substances normally found along with saccharin in several commercial artificial sweeteners such as maltodextrin, glucose, sucrose, fructose, aspartame, cyclamate, caffeine, sorbitol, lactose, nitrate, methyl- and n-propyl-p-hydroxybenzoate, benzoic, citric and ascorbic acids do not interfere even in significant amounts (e.g. 20 excess relative to saccharin). Chloride ion interferes when present in concentrations larger than 10 mg l(-1); this interference is eliminated with previous extraction of the sweetener from the aqueous medium with ethyl acetate. The results obtained by applying the proposed method compared very favorably with those given by the HPLC method recommended by the FDA. (C) 2003 Elsevier Ltd. All rights reserved.

A barrier method for constrained nonlinear optimization using a modified Hopfield network

The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel barrier method using artificial neural networks to solve robust parameter estimation problems for nonlinear model with unknown-but-bounded errors and uncertainties. This problem can be represented by a typical constrained optimization problem. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach.

Using artificial intelligence for the control of medium voltage substations

This paper introduces a method for the supervision and control of devices in electric substations using fuzzy logic and artificial neural networks. An automatic knowledge acquisition process is included which allows the on-line processing of operator actions and the extraction of control rules to replace gradually the human operator. Some experimental results obtained by the application of the implemented software in a simulated environment with random signal generators are presented.

Surface electromyography of facial muscles during natural and artificial feeding of infants

Objective: To measure and compare the activity of the masseter, temporalis and buccinator muscles in different infant feeding methods. Method: Cross-sectional study of 60 full-term infants with no intercurrent diseases, aged between two and three months, classified into the following groups: 1) exclusive breastfeeding; 2) breastfeeding plus bottle-feeding; and 3) exclusive breastfeeding plus cup feeding. Surface electromyography was performed during infant feeding. The Krushal-Wallis test was used, complemented by multiple paired comparisons of the groups. A 5% significance level was chosen for the tests. Results: Statistically higher results were verified in the breastfeeding group in relation to the bottle-feeding one, both in the range of movement and the mean contraction of the masseter. With regard to the temporalis muscle, statistically higher results were found in the breastfeeding group comparatively to the bottle-feeding one. As to the buccinator muscle, statistically higher results were observed in the breastfeeding group in relation to the bottle-feeding one, although in this case, the difference concerned only the range of contraction. Conclusion: The similarities between the muscle activity in the breastfeeding and in the cup-feeding groups suggests that cup-feeding can be used as an alternative infant feeding method, being better than bottle-feeding, due to the hyperactivity of the buccinator muscle, which could result in changes to the structural growth and development of the stomatognathic system functions. Copyright © 2006 by Sociedade Brasileira de Pediatria.

Cryopreservation of dog spermatozoa: Effect of bovine serum albumin on acrosomal integrity and pregnancy rates after artificial insemination

The objective of the present study was to compare the in vitro and in vivo profile of frozen dog semen with Tris-bovine serum albumin (TB) and Tris-egg yolk (TE) extenders. Twenty dogs were used as donors. Each dog was stimulated by penile massage and only the sperm-rich fraction was collected weekly until 40 ejaculates were obtained. After macroscopic and microscopic analysis, equal parts of each ejaculate were diluted with TB and TE by the one-step method at 37 °C. The semen was added to 0.5-mL French straws which presented normal characteristics before freezing and after thawing. Acrosomal integrity was evaluated by double Trypan blue-Giemsa staining, in which alive intact (LI), alive reacted (LR), dead intact (DI) and dead reacted (DR) spermatozoa, were identified by the time of thawing and up to 4 h of incubation at 39 °C, the TE being significantly superior to TB (P<0,01) in the LI and LR variables. The TB being significantly superior to TE (P<0,01) in the DR variable. Female dogs in natural heat were submitted to artificial insemination, 20 receiving TE-semen and 20 receiving TB-semen with the Osiris probe (IMV, L'Aigle, France) and the numbers indicate that TE was significantly better than TB (P<0,01) to pregnancy rate and number of puppies/delivery. We concluded from this study, that TE was better than TB, because this, induced an eady acrossome reaction in dog's sperm.

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.