Optimization of yogurt production using demineralized whey

The effect of three independent fermentation variables: demineralized whey powder (0.0; 1.5 and 3.0%), lactic culture concentration (1.0; 2.0 and 3.0%) and mix treatment temperature (85; 90 and 95°C) was studied. Fermentation time to reach pH 4.3, instrumental consistency and appearance, visual consistency and taste of the product were evaluated. Product consistency increased as mix treatment temperature increased and demineralized whey powder decreased. The powder had a stronger influence on instrumental consistency than did temperature. Appearance was better when whey powder was used at 1.4 to 1.6%. Visual consistency decreased as whey powder increased but addition of demineralized whey powder did not negatively affect yogurt flavor.

Comparative studies on non-convex optimization methods for transmission network expansion planning

We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

Combining genetic algorithm and simulated annealing: A molecular geometry optimization study

We introduce a new hybrid approach to determine the ground state geometry of molecular systems. Firstly, we compared the ability of genetic algorithm (GA) and simulated annealing (SA) to find the lowest energy geometry of silicon clusters with six and 10 atoms. This comparison showed that GA exhibits fast initial convergence, but its performance deteriorates as it approaches the desired global extreme. Interestingly, SA showed a complementary convergence pattern, in addition to high accuracy. Our new procedure combines selected features from GA and SA to achieve weak dependence on initial parameters, parallel search strategy, fast convergence and high accuracy. This hybrid algorithm outperforms GA and SA by one order of magnitude for small silicon clusters (Si6 and Si10). Next, we applied the hybrid method to study the geometry of a 20-atom silicon cluster. It was able to find an original geometry, apparently lower in energy than those previously described in literature. In principle, our procedure can be applied successfully to any molecular system. © 1998 Elsevier Science B.V.

Optimization procedures in the design of continuous induction hardening and tempering installations for magnetic steel bars

An inverse problem concerning the industrial process of steel bars hardening and tempering is considered. The associated optimization problem is formulated in terms of membership functions and, for the sake of comparison, also in terms of quadratic residuals; both geometric and electromagnetic design variables have been considered. The numerical solution is achieved by coupling a finite difference procedure for the calculation of the electromagnetic and thermal fields to a deterministic strategy of minimization based on modified Flctcher and Reeves method. © 1998 IEEE.

Global optimization approach for the H2-norm model reduction problem

A branch and bound algorithm is proposed to solve the H2-norm model reduction problem for continuous-time linear systems, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through Linear Matrix Inequalities formulations. Examples illustrate the results.

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.

Optimization of the mechanical properties of low-carbon steels by formation of a multiphase microstructure

In this work five methods of heat treatments are investigated in order to obtained convenient volume fractions of ferrite, bainite, martensite and retained austenite, starting with a low carbon steel and seeking the distinction of the phases, through optical microscopy. Specific chemical etching is improved. The results in tensile and fatigue tests were accomplished and the results were related with the microstructural parameters. The results show that the mechanical properties are closely related with the phases, grains size and the phases morphology. Copyright © 2001 Society of Automotive Engineers, Inc.

Bound constrained smooth optimization for solving variational inequalities and related problems

Variational inequalities and related problems may be solved via smooth bound constrained optimization. A comprehensive discussion of the important features involved with this strategy is presented. Complementarity problems and mathematical programming problems with equilibrium constraints are included in this report. Numerical experiments are commented. Conclusions and directions of future research are indicated.

Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning

In this article we describe a feature extraction algorithm for pattern classification based on Bayesian Decision Boundaries and Pruning techniques. The proposed method is capable of optimizing MLP neural classifiers by retaining those neurons in the hidden layer that realy contribute to correct classification. Also in this article we proposed a method which defines a plausible number of neurons in the hidden layer based on the stem-and-leaf graphics of training samples. Experimental investigation reveals the efficiency of the proposed method. © 2002 IEEE.

Road segment delineation using active testing principle and an edge-based post-processing strategy

This paper presents a semi-automated method for extracting road segments from medium-resolution images based on active testing and edge analysis. The method is based on two sequential and independent stages. Firstly, an active testing method is used to extract an approximated road centreline which is based on a sequential and local exploitation of the image. Secondly, an iterative strategy based on edge analysis and the approximated centreline is used to measure precisely the road centreline. Based on the results obtained using medium-resolution test images, the method seems to be very promising. In general, the method proved to be very accurate whenever the roads are characterized by two well-defined anti-parallel edges and robust even in the presence of larger obstacles such as trees and shadows.

Tuning of fuzzy inference systems through unconstrained optimization techniques

This paper presents a new methodology for the adjustment of fuzzy inference systems. A novel approach, which uses unconstrained optimization techniques, is developed in order to adjust the free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through an estimation of time series. More specifically, the Mackey-Glass chaotic time series estimation is used for the validation of the proposed methodology.

Optimization of neutral hydrolysis reaction of post-consumer PET for chemical recycling

The neutral hydrolysis reaction of post-consumer poly(ethylene terephthalate) in solid state was studied through the reaction of the polymer with water at the molar ratio 1:91 with autogenous pressure. Two sizes of post-consumer PET flakes and temperatures of 135 °C, 170°C and 205°C with pressures of 4.0 atm, 7.5 atm and 13.5 atm, respectively, were considered. With reaction time equal to 6h, the method reached 99% depolymerization at 205°C, 8.2% at 170 °C and 1.7% at 135°C. The reaction extension was measured by separating the terephthalic acid formed in the process and calculating by gravimetry how much material could still be reacted. Through the viscosimetry of diluted, solutions and the counting of carboxylic end groups in the remaining material from the gravimetric assay, it was possible to suggest that the reaction occurs randomly and in the whole volume of the polymeric particle and not solely on the surface. The terephthalic acid obtained and then purified was characterized by elemental analysis, magnetic nuclear resonance, size and panicle size distribution and spectrophotometry in the visible spectrum, and it was similar to the petrochemical equivalent, with purity recorded in carbon base equal to 99.9%.

Optimization of xylanase biosynthesis by Aspergillus japonicus isolated from a Caatinga area in the Brazilian state of Bahia

The objective of this research was to investigate the potential of xylanase production by Aspergillus japonicus and to determine the effects of cultivation conditions in the process, aiming toward optimization of enzyme production. The best temperature, as well as the best carbon source, for biomass production was determined through an automated turbidimetric method (Bioscreen-C). The enzyme activity of this fungus was separately evaluated in two solid substrates (wheat and soybean bran) and in Vogel medium, adding other carbon sources. Temperature effects, cultivation time, and spore concentrations were also tested. The best temperature for enzyme and biomass production was 25°C; however, the best carbon source for growth (determined by the Bioscreen C) did not turn out to be a good inducer of xylanase production. Maximum xylanase activity was achieved when the fungus was cultivated in wheat bran (without the addition of any other carbon source) using a spore concentration of 1 × 107 spores/mL (25°C, pH 5.0, 120 h). A. japonicus is a good xylanase producer under the conditions presented in these assays. © 2006 Academic Journals.

A new implementation of Population Based Incremental Learning method for optimization studies in electromagnetics

To enhance the global search ability of Population Based Incremental Learning (PBIL) methods, It Is proposed that multiple probability vectors are to be Included on available PBIL algorithms. As a result, the strategy for updating those probability vectors and the negative learning and mutation operators are redefined as reported. Numerical examples are reported to demonstrate the pros and cons of the newly Implemented algorithm. ©2006 IEEE.

A procedure to estimate parameters of a line segment taking into account its representation through π circuits: Theoretical development

The objective of this paper is to show an alternative methodology to estimate per unit length parameters of a line segment of a transmission line. With this methodology the line segment parameters can be obtained starting from the phase currents and voltages in receiving and sending end of the line segment. If the line segment is represented as being one or more π circuits whose frequency dependent parameters are considered lumped, its impedance and admittance can be easily expressed as functions of the currents and voltages at the sending and receiving end. Because we are supposing that voltages and currents at the sending and receiving end of the line segment (in frequency domain) are known, it is possible to obtains its impedance and admittance and consequently its per unit length longitudinal and transversal parameters. The procedure will be applied to estimate the longitudinal and transversal parameters of a small segment of a single-phase line that is already built. © 2006 IEEE.