Genetic algorithm to design logical topologies in reconfigurable WDM networks

A new method to design logical topologies based on genetic algorithms is presented. Not only does the algorithm determine which nodes should be connected by means of lightpaths with the aim of minimizing congestion, but it also solves the routing and wavelength assignment problem. In this way, the algorithm guarantees that the logical topology obtained can be embedded in the optical network subject to the available set of resources. The algorithm is effective in terms of both congestion and fairness. For instance, when compared with other work, the congestion is significantly reduced (from 20% to 75% depending on the matrix of traffic considered), and the fairness, when evaluated in terms of the Jain index, is generally higher than 0.94. Moreover, the algorithm brings advantages when employed in dynamic scenarios where the logical topology is frequently reconfigured, as it is fast and, in contrast to other algorithms previously proposed, the calculation process can be stopped at any time (if required) in order to give the best virtual topology found up to the moment.

Automatic texture feature selection for image pixel classification

Pixel-based texture classifiers and segmenters are typically based on the combination of texture feature extraction methods that belong to a single family (e.g., Gabor filters). However, combining texture methods from different families has proven to produce better classification results both quantitatively and qualitatively. Given a set of multiple texture feature extraction methods from different families, this paper presents a new texture feature selection scheme that automatically determines a reduced subset of methods whose integration produces classification results comparable to those obtained when all the available methods are integrated, but with a significantly lower computational cost. Experiments with both Brodatz and real outdoor images show that the proposed selection scheme is more advantageous than well-known general purpose feature selection algorithms applied to the same problem.     

A Practical Case Study: Face Recognition on Low Quality Images Using Gabor Wavelet and Support Vector Machines

Image segmentation is accepted to be one of the most important problems in image analysis. The good performance of any recognition system strongly depends on the results provided by the segmentation module. According to many researchers, segmentation finishes when the goal of observer is satisfied. Experience has shown that the most effective methods continue to be the iterative algorithms. However, a problem with these algorithms is the stopping criterion. In this work, we present a strategy for image segmentation through a new algorithm based on recursively applying the mean shift filtering, where entropy is used as a stopping criterion. The main feature of the proposed algorithm is to carry out segmentation in an only step. In other words, with the new algorithm is not necessary to carry out additionally the segmentation step, where in many occasions (mainly in complex applications), it can be computationally expensive. The effectiveness of the proposed algorithm is shown through several experimental results. The obtained results proved that the proposed segmentation algorithm is a straightforward extension of the filtering process. In this paper a comparison between our algorithm and so called EDISON System was carried out.     

Design of an electronic system and its application to electronic tongues using variable amplitude pulse voltammetry and impedance spectroscopy

Electronic equipment (IDM-1) especially designed for the application of voltammetric and impedometric electronic tongues is described. For impedance spectroscopy the equipment permits the generation of sinusoidal signals with a frequency in the range of 1 Hz to 1 MHz and programmable amplitude up to 1 Vpp. For voltammetry the IDM-1 equipment generates a sequence of up to 32 pulses with an amplitude that can be configured for each of the pulses in the range [−0.5; +0.5 V]. Voltammetric studies were performed using a total of eight working electrodes (i.e. Au, Pt, Ir, Rh, Ag, Cu, Ni, and Co) which were housed in a stainless steel cylinder used at the same time as both the body of the electronic tongue system and the counter/reference electrode. The width of the pulses can also be configured with a maximum value of 40 ms. The system consists of a software application that runs on a PC and electronic equipment. In order to test the capabilities of the designed system, impedometric and voltammetric measurements were carried out on five different commercial cola drinks (brands I–V). Three different waveforms were used in the voltammetric study (i.e. staircase, ascendant SAPV and descendant SAPV). The voltammetric response and the impedance phase and module values obtained were processed using PCA. A remarkable discrimination between all cola drinks was seen using the descendant waveform and a group of metal electrodes (Ni, Co, Cu, Ag). In contrast, impedance spectroscopy technique discriminated one brand (brand I) from the others.     

Numerical and experimental parametric analysis of anomalous enhanced transmission through subwavelength apertures

Here, we present a numerical and experimental parametric analysis of anomalous enhanced transmission supported by dielectric-loaded holey metals. We focus the study on circular and square subwavelength hole apertures (arranged in a rectangular lattice) both under normal and oblique incidence within the millimetre-wave regime. It is experimentally confirmed that the thickness of the dielectric slab plays a role: the thicker the slab is, the higher the transmission is, which is in good agreement with the interpretation founded on grounded dielectric slab mode and circuit models. Also, from the experimental results, it is shown that finiteness effects arisen in the real experiments have significant consequences. Among them, it is outstanding the considerable penalty on the transmission through circular holes, which can be explained intuitively by the smaller clear aperture per unit area with respect to the square holes. In addition to transmission results, the TE nature of the grounded dielectric slab mode is stressed by the field distribution calculated numerically. The results presented here enlarge the knowledge about anomalous enhanced transmission and establish a platform from which polarization- and frequency-dependent devices can be foreseen.     

Computer method for kinematic analysis of lower-pair mechanisms—II position problemsEine neue methode zur analyse von mechanismen teil 2: Positionsprobleme

In the first part of this study, a new method for solving the problem of kinematic analysis was presented, based on the concepts of “basic coordinates” and “link constraint equations”. In this second part, these same concepts are used to solve the problems of initial position, finite displacements and static equilibrium position of a mechanism with springs between its links. The proposed algorithms are elementary in their formulation and of exceptional efficiency in their performance. The methods describes are based on the solution of a problem of mathematical programming. Several examples are presented, giving an idea of the potential of said algorithms.     

Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.     

Multi-reservoir Operation Rules: Multi-swarm PSO-based Optimization Approach

Reservoir operation rules are intended to help an operator so that water releases and storage capacities are in the best interests of the system objectives. In multi-reservoir systems, a large number of feasible operation policies may exist. System engineering and optimization techniques can assist in identifying the most desirable of those feasible operation policies. This paper presents and tests a set of operation rules for a multi-reservoir system, employing a multi-swarm version of particle swarm optimization (MSPSO) in connection with the well-known HEC-ResPRM simulation model in a parameterization–simulation–optimization (parameterization SO) approach. To improve the performance of the standard particle swarm optimization algorithm, this paper incorporates a new strategic mechanism called multi-swarm into the algorithm. Parameters of the rule are estimated by employing a parameterization–simulation–optimization approach, in which a full-scale simulation model evaluates the objective function value for each trial set of parameter values proposed with an efficient version of the particle swarm optimization algorithm. The usefulness of the MSPSO in developing reservoir operation policies is examined by using the existing three-reservoir system of Mica, Libby, and Grand Coulee as part of the Columbia River Basin development. Results of the rule-based reservoir operation are compared with those of HEC-ResPRM. It is shown that the real-time operation of the three reservoir system with the proposed approach may significantly outperform the common implicit stochastic optimization approach.