On the parameters of performance of combined refrigeration and power plants

Combined Refrigeration and Power (CRP) plants generate power and refrigerate a thermal load simultaneously from the same fuel. The overall efficiency is a parameter based on the first law generally used to quantify the fuel saving, in the sense that a plant that has greater overall efficiency saves more fuel than others to generate the same useful energy. However, the literature shows that the overall efficiency and other parameters of performance are defined in several different ways. This heterogeneity is not desirable when considering a coherent and universally accepted parameter of performance based on the first law. In this work, some parameters found in the literature are critically analyzed in order to indicate the most proper one. The indicated parameter is then formally analyzed in order to verify its mathematical consistency. The primary energy rate is considered the most well-suited parameter based on the first law to characterize the performance of a CRP plant. © 2013 Elsevier Ltd and IIR.

Evolutionary optimization applied for fine-tuning parameter estimation in optical flow-based environments

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.

Genetic parameter estimates for live weight and daily live weight gain obtained for Nellore bulls in a test station using different models

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

Milk yield persistency in Brazilian Gyr cattle based on a random regression model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A framework for monitoring and runtime recovery of web service-based applications

Service provisioning is a challenging research area for the design and implementation of autonomic service-oriented software systems. It includes automated QoS management for such systems and their applications. Monitoring, Diagnosis and Repair are three key features of QoS management. This work presents a self-healing Web service-based framework that manages QoS degradation at runtime. Our approach is based on proxies. Proxies act on meta-level communications and extend the HTTP envelope of the exchanged messages with QoS-related parameter values. QoS Data are filtered over time and analysed using statistical functions and the Hidden Markov Model. Detected QoS degradations are handled with proxies. We experienced our framework using an orchestrated electronic shop application (FoodShop).

A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest

Nowadays, fraud detection is important to avoid nontechnical energy losses. Various electric companies around the world have been faced with such losses, mainly from industrial and commercial consumers. This problem has traditionally been dealt with using artificial intelligence techniques, although their use can result in difficulties such as a high computational burden in the training phase and problems with parameter optimization. A recently-developed pattern recognition technique called optimum-path forest (OPF), however, has been shown to be superior to state-of-the-art artificial intelligence techniques. In this paper, we proposed to use OPF for nontechnical losses detection, as well as to apply its learning and pruning algorithms to this purpose. Comparisons against neural networks and other techniques demonstrated the robustness of the OPF with respect to commercial losses automatic identification.

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. 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. Copyright (C) 2000 IFAC.

Neural network based estimation of torque in induction motors for real-time applications

Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

Crystallization kinetics in phosphate sodium-based glass studied by DSC technique

In this work, differential scanning calorimetry (DSC) was used to study the mechanism of crystallization of 5OP(2)O(5-)27.8Na(2)O-16ZnO-6.2Al(2)O(3) glass. DSC measurements were performed on bulk and powdered glasses with different particle size. The curve for bulk glass shows one crystallization peak while powdered glasses presented two distinct crystallization peaks. Based on DSC studies, the activation energies obtained were 336 +/- 6 and 213 +/- 3 U mol(-1), associated with first and second crystallization peaks, respectively. Analyzing the DSC parameters as a function of particle size, the Avrami n parameter suggests that the peak at low temperature may be associated with surface crystallization while the peak at high temperature is associated with bulk crystallization. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

Ground annatto seeds (Bixa orellana L.) in sorghum-based commercial layer diets and their effects on performance, egg quality, and yolk pigmentation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

EMG amplitude and frequency parameters of muscular activity: Effect of resistance training based on electromyographic fatigue threshold

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efficient robust optimization based on polynomial chaos and tabu search algorithm

The study of robust design methodologies and techniques has become a new topical area in design optimizations in nearly all engineering and applied science disciplines in the last 10 years due to inevitable and unavoidable imprecision or uncertainty which is existed in real word design problems. To develop a fast optimizer for robust designs, a methodology based on polynomial chaos and tabu search algorithm is proposed. In the methodology, the polynomial chaos is employed as a stochastic response surface model of the objective function to efficiently evaluate the robust performance parameter while a mechanism to assign expected fitness only to promising solutions is introduced in tabu search algorithm to minimize the requirement for determining robust metrics of intermediate solutions. The proposed methodology is applied to the robust design of a practical inverse problem with satisfactory results.

Asymmetry parameter for the nonmesonic decay of 5LHe

We report the preliminary result of an exact calculation of the asymmetry parameter, alambda, in the nonmesonic hypernuclear decay, based on a one-meson-exchange (OME) model. For the case of He and including one-pion-exchange only, the result is shown not to differ considerably from the one obtained with the approximate formula widely used in the literature. In particular, the sign of alambda remains negative, in disagreement with its most recent experimental determination. Whether these facts remain true for heavier hypernuclei and in a more complete OME model is still under investigation.

Parameter space for a dissipative Fermi-Ulam model

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

An improved tabu-based vector optimal algorithm for design optimizations of electromagnetic devices

This paper introduces an improved tabu-based vector optimal algorithm for multiobjective optimal designs of electromagnetic devices. The improvements include a division of the entire search process, a new method for fitness assignment, a novel scheme for the generation and selection of neighborhood solutions, and so forth. Numerical results on a mathematical function and an engineering multiobjective design problem demonstrate that the proposed method can produce virtually the exact Pareto front, in both parameter and objective spaces, even though the iteration number used by it is only about 70% of that required by its ancestor.