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.

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.

Collaboration intensity in the Brazilian supermarket retail chain

Purpose - This paper seeks to identify collaboration elements and evaluate their intensity in the Brazilian supermarket retail chain, especially the manufacturer-retailer channel. Design/methodology/approach - A structured questionnaire was elaborated and applied to 125 representatives from suppliers of large supermarket chains. Statistical methods including multivariate analysis were employed. Variables were grouped and composed into five indicators (joint actions, information sharing, interpersonal integration, gains and cost sharing, and strategic integration) to assess the degree of collaboration. Findings - The analyses showed that the interviewees considered interpersonal integration to be of greater importance to collaboration intensity than the other integration factors, such as gain or cost sharing or even strategic integration. Research limitations/implications - The research was conducted solely from the point of view of the industries that supply the large retail networks. The interviews were not conducted in pairs; that is, there was no application of one questionnaire to the retail network and another to the partner industry. Practical implications - Companies should invest in conducting periodic meetings with their partners to increase collaboration intensity, and should carry out technical visits to learn about their partners` logistic reality and thus make better operational decisions. Originality/value - The paper reveals which indicators produce greater collaboration intensity, and thus those that are more relevant to more efficient logistics management.

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.

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.

Route to chaos in a third-order phase-locked loop network

Phase-locked loops (PLLs) are widely used in applications related to control systems and telecommunication networks. Here we show that a single-chain master-slave network of third-order PLLs can exhibit stationary, periodic and chaotic behaviors, when the value of a single parameter is varied. Hopf, period-doubling and saddle-saddle bifurcations are found. Chaos appears in dissipative and non-dissipative conditions. Thus, chaotic behaviors with distinct dynamical features can be generated. A way of encoding binary messages using such a chaos-based communication system is suggested. (C) 2009 Elsevier B.V. All rights reserved.

Optimized network structure for full-synchronization

A network of Kuramoto oscillators with different natural frequencies is optimized for enhanced synchronizability. All node inputs are normalized by the node connectivity and some important properties of the network Structure are determined in this case: (i) optimized networks present a strong anti-correlation between natural frequencies of adjacent nodes: (ii) this anti-correlation should be as high as possible since the average path length between nodes is maintained as small as in random networks: and (iii) high anti-correlation is obtained without any relation between nodes natural frequencies and the degree of connectivity. We also propose a network construction model with which it is shown that high anti-correlation and small average paths may be achieved by randomly rewiring a fraction of the links of a totally anti-correlated network, and that these networks present optimal synchronization properties. (C) 2008 Elsevier B.V. All rights reserved.

On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata

We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.

Reachability of the synchronous state in a mutually connected PLL network

Second-order phase locked loops (PLLs) are devices that are able to provide synchronization between the nodes in a network even under severe quality restrictions in the signal propagation. Consequently, they are widely used in telecommunication and control. Conventional master-slave (M-S) clock-distribution systems are being, replaced by mutually connected (MC) ones due to their good potential to be used in new types of application such as wireless sensor networks, distributed computation and communication systems. Here, by using an analytical reasoning, a nonlinear algebraic system of equations is proposed to establish the existence conditions for the synchronous state in an MC PLL network. Numerical experiments confirm the analytical results and provide ideas about how the network parameters affect the reachability of the synchronous state. The phase-difference oscillation amplitudes are related to the node parameters helping to design PLL neural networks. Furthermore, estimation of the acquisition time depending on the node parameters allows the performance evaluation of time distribution systems and neural networks based on phase-locked techniques. (c) 2008 Elsevier GmbH. All rights reserved.

Synaptic compensation on Hopfield network: implications for memory rehabilitation

The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.

Mapping the Contemporary Studies on Alliances and Strategic Networks

The competition among the companies depends on the velocity and efficience they can create and commercialize knowledge in a timely and cost-efficient manner. In this context, collaboration emerges as a reaction to the environmental changes. Although strategic alliances and networks have been exploited in the strategic literature for decades, the complexity and continuous usage of these cooperation structures, in a world of growing competition, justify the continuous interest in both themes. This article presents a scanning of the contemporary academic production in strategic alliances and networks, covering the period from January 1997 to august 2007, based on the top five journals accordingly to the journal of Citation Report 2006 in the business and management categories simultaneously. The results point to a retraction in publications about strategic alliances and a significant growth in the area of strategic. networks. The joint view of strategic alliances and networks, cited by some authors a the evolutionary path of study, still did not appear salient. The most cited topics found in the alliance literature are the governance structure, cooperation, knowledge transfer, culture, control, trust, alliance formation,,previous experience, resources, competition and partner selection. The theme network focuses mainly on structure, knowledge transfer and social network, while the joint vision is highly concentrated in: the subjects of alliance formation and the governance choice.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Podzolization as a deferralitization process: dynamics and chemistry of ground and surface waters in an Acrisol-Podzol sequence of the upper Amazon Basin

Hydrochemical processes involved in the development of hydromorphic Podzols are a major concern for the upper Amazon Basin because of the extent of the areas affected by such processes and the large amounts of organic carbon and associated metals exported to the rivers. The dynamics and chemical composition of ground and surface waters were studied along an Acrisol-Podzol sequence lying in an open depression of a plateau. Water levels were monitored along the sequence over a period of 2 years by means of piezometers. Water was sampled in zero-tension lysimeters for groundwater and for surface water in the drainage network of the depression. The pH and concentrations of organic carbon and major elements (Si, Fe and Al) were determined. The contrasted changes reported for concentrations of Si, organic carbon and metals (Fe, Al) mainly reflect the dynamics of the groundwater and the weathering conditions that prevail in the soils. Iron is released by the reductive dissolution of Fe oxides, mostly in the Bg horizons of the upslope Acrisols. It moves laterally under the control of hydraulic gradients and migrates through the iron-depleted Podzols where it is exported to the river network. Aluminium is released from the dissolution of Al-bearing minerals (gibbsite and kaolinite) at the margin of the podzolic area but is immobilized as organo-Al complexes in spodic horizons. In downslope positions, the quick recharge of the groundwater and large release of organic compounds lead to acidification and a loss of metals (mainly Al), previously stored in the Podzols.

Thermal Behavior, Microstructure, Polymorphism, and Crystallization Properties of Zero Trans Fats from Soybean Oil and Fully Hydrogenated Soybean Oil

Blends of soybean oil (SO) and fully hydrogenated soybean oil (FHSBO), with 10, 20, 30, 40, and 50% (w/w) FHSBO content were interesterified under the following conditions: 20 min reaction time, 0.4% sodium methoxide catalyst, and 500 rpm stirring speed, at 100 A degrees C. The original and interesterified blends were examined for triacylglycerol composition, thermal behavior, microstructure, crystallization kinetics, and polymorphism. Interesterification produced substantial rearrangement of the triacylglycerol species in all the blends, reduction of trisaturated triacylglycerol content and increase in monounsaturated-disaturated and diunsaturated-monosaturated triacylglycerols. Evaluation of thermal behavior parameters showed linear relations with FHSBO content in the original blends. Blend melting and crystallization thermograms were significantly modified by the randomization. Interesterification caused significant reductions in maximum crystal diameter in all blends, in addition to modifying crystal morphology. Characterization of crystallization kinetics revealed that crystal formation induction period (tau (SFC)) and maximum solid fat content (SFC(max)) were altered according to FHSBO content in the original blends and as a result of the random rearrangement. Changes in Avrami constant (k) and exponent (n) indicated, respectively, that-as compared with the original blends-interesterification decreased crystallization velocities and modified crystallization processes, altering crystalline morphology and nucleation mechanism. X-ray diffraction analyses revealed that interesterification altered crystalline polymorphism. The interesterified blends showed a predominance of the beta` polymorph, which is of more interest for food applications.