Wavelength assignment using a hybrid evolutionary computation to reduce cross-phase modulation

In this paper, we propose a hybrid methodology based on Graph-Coloring and Genetic Algorithm (GA) to solve the Wavelength Assignment (WA) problem in optical networks, impaired by physical layer effects. Our proposal was developed for a static scenario where the physical topology and traffic matrix are known a priori. First, we used fixed shortest-path routing to attend demand requests over the physical topology and the graph-coloring algorithm to minimize the number of necessary wavelengths. Then, we applied the genetic algorithm to solve WA. The GA finds the wavelength activation order on the wavelengths grid with the aim of reducing the Cross-Phase Modulation (XPM) effect; the variance due to the XPM was used as a function of fitness to evaluate the feasibility of the selected WA solution. Its performance is compared with the First-Fit algorithm in two different scenarios, and has shown a reduction in blocking probability up to 37.14% when considered both XPM and residual dispersion effects and up to 71.42% when only considered XPM effect. Moreover, it was possible to reduce by 57.14% the number of wavelengths.

Using Proteomic Strategies for Sequencing and Post-Translational Modifications Assignment of Antigen-5, a Major Allergen from the Venom of the Social Wasp Polybia paulista

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

Biological and molecular characterisation of Bidens mosaic virus supports its assignment as a member of a distinct species in the genus Potyvirus

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

O que nós sabemos? Da relação com o saber na e com a educação física em um processo educacional-escolar

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

Attribute charts for monitoring the mean vector of bivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Synthesis and total 1H- and 13C-NMR assignment of cephem derivatives for use in ADEPT approaches

We report the synthesis and total NMR characterization of 5-thia-1-azabicyclo-[4.2.0]oct-2-ene-2-carboxylic acid-3-[[[(4″- nitrophenoxy)carbonyl]oxy]-methyl]-8-oxo-7-[(2-thienyloxoacetyl)amino] -diphenylmethyl ester-5-dioxide (5), a new cephalosporin derivative. This compound can be used as the carrier of a wide range of drugs containing an amino group. The preparation of the intermediate product, 5-thia-1-azabicyclo[4.2.0] oct-2-ene-2-carboxylic acid-3-[methyl 4-(6-methoxyquinolin-8-ylamino) pentylcarbamate]-8-oxo-7-[(2-thienyloxoacetyl)amino]-diphenylmethyl ester-5-dioxide (6), as well as the synthesis of the antimalarial primaquine prodrug 5-thia-1-azabicyclo[4.2.0]oct-2-ene-2-carboxylic acid-3-[methyl 4-(6-methoxyquinolin-8-ylamino)pentylcarbamate]-8-oxo-7-[(2-thienyloxoacetyl) amino]- 5-dioxide (7) are also described, together with their total 1H- and 13C-NMR assignments. © 2008 by MDPI.

Routing and Wavelength Assignment (RWA) with Power Considerations In All- Optical Wavelength-Routed Networks

Routing and wavelength assignment (RWA) is an important problem that arises in wavelength division multiplexed (WDM) optical networks. Previous studies have solved many variations of this problem under the assumption of perfect conditions regarding the power of a signal. In this paper, we investigate this problem while allowing for degradation of routed signals by components such as taps, multiplexers, and fiber links. We assume that optical amplifiers are preplaced. We investigate the problem of routing the maximum number of connections while maintaining proper power levels. The problem is formulated as a mixed-integer nonlinear program and two-phase hybrid solution approaches employing two different heuristics are developed

Simple heuristics for the assembly line worker assignment and balancing problem

We propose simple heuristics for the assembly line worker assignment and balancing problem. This problem typically occurs in assembly lines in sheltered work centers for the disabled. Different from the well-known simple assembly line balancing problem, the task execution times vary according to the assigned worker. We develop a constructive heuristic framework based on task and worker priority rules defining the order in which the tasks and workers should be assigned to the workstations. We present a number of such rules and compare their performance across three possible uses: as a stand-alone method, as an initial solution generator for meta-heuristics, and as a decoder for a hybrid genetic algorithm. Our results show that the heuristics are fast, they obtain good results as a stand-alone method and are efficient when used as a initial solution generator or as a solution decoder within more elaborate approaches.

Detailed H-1 and C-13 NMR structural assignment and relative stereochemistry determination for three new and one known semi-synthetic sesquiterpene lactones

In this work is described a complete H-1 and C-13 NMR analysis for a group of four sesquiterpene lactones, three previously unknown. The unequivocal assignments were achieved by H-1 NMR, C-13{H-1} NMR, gCOSY. gHMQC, gHMBC and NOESY experiments and no ambiguities were left behind. All hydrogen coupling constants were measured, clarifying all hydrogen signals multiplicities. (C) 2011 Elsevier B.V. All rights reserved.

Morphological analysis of Mecosarthron Buquet and Xixuthrus Thomson and Reevaluation of Generic Assignment of Xixuthrus domingoensis Fisher (Coleoptera, Cerambycidae, Prioninae)

The characters defining Mecosarthron Buquet, 1840 and Xixuthrus Thomson 1864 are discussed, along with a historical review of the literature that described and classified these taxa. Through morphological examination of these genera and most of the included species, we addressed the systematic placement of Xixuthrus domingoensis Fisher, 1932 that was placed in Mecosarthron by Ivie (1985). We restore its placement in the genus Xixuthrus. The first description of the female of X. domingoensis is provided, along with comparative redescriptions of Mecosarthron gounellei (Lameere, 1903), and M. buphagus Buquet, 1840. We include a key to the species currently in Mecosarthron.

Evaluation of LBP and HOG descriptors for clothing attribute description

[EN]In this work an experimental study about the capability of the LBP, HOG descriptors and color for clothing attribute classification is presented. Two different variants of the LBP descriptor are considered, the original LBP and the uniform LBP. Two classifiers, Linear SVM and Random Forest, have been included in the comparison because they have been frequently used in clothing attributes classification. The experiments are carried out with a public available dataset, the clothing attribute dataset, that has 26 attributes in total. The obtained accuracies are over 75% in most cases, reaching 80% for the necktie or sleeve length attributes.

Referee Assignment Problem Case: Italian Volleyball Championships

This thesis addresses the formulation of a referee assignment problem for the Italian Volleyball Serie A Championships. The problem has particular constraints such as a referee must be assigned to different teams in a given period of times, and the minimal/maximal level of workload for each referee is obtained by considering cost and profit in the objective function. The problem has been solved through an exact method by using an integer linear programming formulation and a clique based decomposition for improving the computing time. Extensive computational experiments on real-world instances have been performed to determine the effectiveness of the proposed approach.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.