Neural network model for designing automotive devices using SMD LED

The advantages offered by the electronic component LED (Light Emitting Diode) have resulted in a quick and extensive application of this device in the replacement of incandescent lights. In this combined application, however, the relationship between the design variables and the desired effect or result is very complex and renders it difficult to model using conventional techniques. This paper consists of the development of a technique using artificial neural networks that makes it possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. This technique can be utilized to design any automotive device that uses groups of SMD LEDs. The results of industrial applications using SMD LED are presented to validate the proposed technique.

Neural network-based H(infinity) control for fully actuated and underactuated cooperative manipulators

This paper develops H(infinity) control designs based on neural networks for fully actuated and underactuated cooperative manipulators. The neural networks proposed in this paper only adapt the uncertain dynamics of the robot manipulators. They work as a complement of the nominal model. The H(infinity) performance index includes the position errors as well the squeeze force errors between the manipulator end-effectors and the object, which represents a complete disturbance rejection scenario. For the underactuated case, the squeeze force control problem is more difficult to solve due to the loss of some degrees of manipulator actuation. Results obtained from an actual cooperative manipulator, which is able to work as a fully actuated and an underactuated manipulator, are presented. (C) 2008 Elsevier Ltd. All rights reserved.

Bond strength and transversal deformation aging on cement-polymer adhesive mortar

Polymer-modified mortar is widely used to set ceramic tiles used as external finishing for high rise buildings in countries such as Brazil, Israel, Singapore and Portugal, mainly because it shows better bond strength and flexibility as compared to the traditional ones. Despite this, the results in the literature already published concerning the long-term performance of those composite mortars are is not conclusive. This paper, based on a laboratory program, compared the performance over time of four commercial polymer-modified adhesive mortars exposed to a typical Brazilian outdoor aging environment and to an indoor environment in terms of mortar flexibility and the bond strength to porcelain tiles. The results show that under laboratory condition, the mortars are more flexible and have higher bond strength than under external condition, and that there is an important correlation between the transversal deformability and the bond strength. (C) 2008 Elsevier Ltd. All rights reserved.

The influence of moisture on the deformability of cement-polymer adhesive mortar

Adhesive mortars are widely used to set porcelain stoneware tiles on buildings because their bond strength and flexibility properties increase the cladding serviceability. However, their long-term performance is not well understood, mainly the degradation of the polymeric matrix. The influence of moisture content on the flexibility of six adhesive mortars is investigated, based on standard EN 12002. Four of them have defined formulations and the other two are commercial and are widely used to set porcelain stoneware tiles on building facades in Brazil. The results show that moisture content above 6% is sufficient to reduce 50% of the mortar deformability, but that the drying process allows it to recover to a value similar to that prior to saturation; a logarithmic function best fits the correlation between moisture content and flexibility; water immersion increases matrix rigidity. It is suggested that standards should consider flexibility tests on both dried and wet samples as a requirement for polymer-modified mortars. (C) 2010 Elsevier Ltd. All rights reserved.

Implementation of a Control Loop Experiment in a Network-Based Control System With LonWorks Technology and IP Networks

Considering the increasing popularity of network-based control systems and the huge adoption of IP networks (such as the Internet), this paper studies the influence of network quality of service (QoS) parameters over quality of control parameters. An example of a control loop is implemented using two LonWorks networks (CEA-709.1) interconnected by an emulated IP network, in which important QoS parameters such as delay and delay jitter can be completely controlled. Mathematical definitions are provided according to the literature, and the results of the network-based control loop experiment are presented and discussed.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

Polymer toughening using residue of recycled windshields: PVB film as impact modifier

In this work, poly(vinyl butyral) (PVB) film originated from the mechanical separation of windshields was tested as all impact modifier of Polyamide-6 (PA-6). The changes undergone by PVB film during the recycling process and the blend manufacturing were evaluated by thermal analyses, infrared spectroscopy and loss oil ignition. Blends of PA-6/original PVB film and PA-6/recovered PVB film were obtained in concentrations ranging from 90/10 to 60/40. The mechanical properties of the blends were investigated and explained in light of the blends morphologies, which in turns were correlated to the changes undergone by the PVB film during the recycling process. The original film presented a plasticizer content of 33 wt.%, which decreased to as low as 20 wt.%, after the recycling and blend preparation processes. The PA-6/PVB film blends presented lower values of tensile strength and Young`s modulus than Polyamide-6, but all blends presented a dramatic increase in their toughness, with a special feature for the 40 wt.%(, blend, which resulted in a super toughened material (impact strength exceeding 500 J/m). Similar results were obtained with recovered PVB film and super tough blends were also obtained. The use of recovered PVB resulted in a smaller improvement of the impact strength due to the loss of plasticizer undergone during the recycling process. The morphological observations showed that if the interparticle distance is smaller than around 0.2 mu m (critical value), the notched Izod impact strength values increase considerably and the fracture surface of blends exhibit characteristics of tough failure. (C) 2007 Elsevier Ltd. All rights reserved.

Stress relaxation behavior of PMMA/PS polymer blends

In this work, the stress relaxation behavior of PMMA/PS blends, with or without random copolymer addition, submitted to step shear strain experiments in the linear and nonlinear regime was studied. The effect of blend composition (ranging from 10 to 30 wt.% of dispersed phase), viscosity ratio (ranging from 0.1 to 7.5), and random copolymer addition (for concentrations up to 8 wt.% with respect to the dispersed phase) was evaluated and correlated to the evolution of the morphology of the blends. All blends presented three relaxation stages: a first fast relaxation which was attributed to the relaxation of the pure phases, a second one which was characterized by the presence of a plateau, and a third fast one. The relaxation was shown to be faster for less extended and smaller droplets and to be influenced by coalescence for blends with a dispersed phase concentration larger than 20 wt.%. The relaxation of the blend was strongly influenced by the matrix viscosity. The addition of random copolymer resulted in a slower relaxation of the droplets.

Preparation and characterization of crosslinked resins containing ferrite particles

Micrometer-sized magnetic particles hosted on network material were successfully prepared by a simple chemical process (ion exchange followed by co-precipitation) from commercial styrene-divinylbenzene copolymers. Energy dispersive X-ray spectroscopy (EDS) coupled to scanning electron microscopy (SEM) allowed the observation of submicron particles. All the produced spherical beads have presented metallic particles (NiFe2O4, CuFe2O4, CoFe2O4, or MnFe2O4), either as isolated particles or agglomerates, located on their external and internal (within pores) The thermal stability of the composites, evaluated by thermogravimetric techniques, were found to be dependent on the amount of ferrite particles incorporated into them.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Ultra-thin films of alternating semi-interpenetrating layers of a conducting polymer with thermosetting phenolic resins for sensor application

In this work a new method for crosslinking ultra-thin films with potential applications in sensor systems is proposed. The films were produced by layer-by-layer (LbL) assembly using a conducting polymer, poly(o-ethoxyaniline) (POEA), alternated with a thermosetting resin, novolac-type phenolformaldehyde (PF), crosslinked by a simple thermal treatment. The PF resin served as both alternating and crosslinking agents. The films were characterized by Fourier transform infrared (FTIR) and ultraviolet-visible (UV-Vis) spectroscopy, thermogravimetry (TG), desorption, doping/dedoping cycling and electrical measurements. The results showed that film architecture and crosslinking degree can be controlled by the conditions used for film deposition (number of bilayers, polymer concentration, pH, and deposition time), and crosslinking time. Moreover, this approach offers several advantages such as fast curing time and low cost, indicating that these films can be used to produce sensors with improved stability.

Who should wear mask against airborne infections? Altering the contact network for controlling the spread of contagious diseases

There are several ways of controlling the propagation of a contagious disease. For instance, to reduce the spreading of an airborne infection, individuals can be encouraged to remain in their homes and/or to wear face masks outside their domiciles. However, when a limited amount of masks is available, who should use them: the susceptible subjects, the infective persons or both populations? Here we employ susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations and probabilistic cellular automata in order to investigate how the deletion of links in the random complex network representing the social contacts among individuals affects the dynamics of a contagious disease. The inspiration for this study comes from recent discussions about the impact of measures usually recommended by health public organizations for preventing the propagation of the swine influenza A (H1N1) virus. Our answer to this question can be valid for other eco-epidemiological systems. (C) 2010 Elsevier BM. All rights reserved.

Network of phase-locking oscillators and a possible model for neural synchronization

In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state. (C) 2011 Elsevier B.V. All rights reserved.