Males of Neotropical social wasps (Vespidae, Polistinae, Epiponini) recognize colonies with virgin females

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

Métodos de otimização aplicados no ajuste de ESPS e controladores de amortecimento inseridos no FACTS TCSC em sistemas elétricos de potência

Pós-graduação em Engenharia Elétrica - FEIS

Seleção de características utilizando algoritmos evolucionistas e suas aplicações em reconhecimento de padrões

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Harmony Search applied for Support Vector Machines Training Optimization

Since the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation.

Investigação sobre deformação neotectônica no lineamento Guapiara, região de Ourinhos, Fartura-SP e Santo Antonio da Platina - PR

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Investigação sobre deformação neotectônica no lineamento Guapiara, região de Guapiara e Jacupiranga

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

On the optical flow model selection through metaheuristics

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

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.

Caracterização da produção e qualidade físico-química de méis produzidos no Estado de Pernambuco

The present study had as objective contribute to the characterization of beekeeping in the Pernambuco State and evaluate the physical-chemical quality of the honeys produced in the region. For this, was applied a directed formulary to the representative organ of beekeeping class aboutthe productives and technicals aspects of beekeepers. Was obtained 14 samples of honey by Apis mellifera africanized, stored in sterile plastic vessels was sent to the Beekeeping Products Quality Control Laboratory (CEA-UNITAU). Was observed that the most of beekeepers have of 50 to 100 hives (57,14%), 28,57% of 100 to 200 hives and 14,28% more than 500 hives, being that 85,71% produce 30 to 50 kg honey/hives/flowering. All use the standard hive Langstroth and 85,71% obtain their swarm by capture. About the physical-chemical quality of the honey, was observed that moisture content varied from 18,2% to 22,0%, with mean value of 19,80±1,11; the water activity varied from 0,70 to 0,84 aw, with mean value of 0,79±0,05 aw; the total acidity was 24,91±8,99 meq/kg and the average index of hydroxymethylfurfural was 16,32±17,88 meq/kg. The results obtained are according to the quality limits established by the brazilian legislation, excepted the water activity that exceeded the maximum limit of 0,65 aw. The datasobtained in this paper shows the development of beekeeping in Pernambuco State and the honey presents nice quality.

Phylogeographic analysis in populations of Protonectarina sylveirae (Saussure, 1854) (Hymenoptera, Vespidae, Polistinae)

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

Phylogeographic analysis in populations of Protonectarina sylveirae (Saussure, 1854) (Hymenoptera, Vespidae, Polistinae)

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

Consensus Statement on Standard of Care for Congenital Myopathies

Recent progress in scientific research has facilitated accurate genetic and neuropathological diagnosis of congenital myopathies. However, given their relatively low incidence, congenital myopathies remain unfamiliar to the majority of care providers, and the levels of patient care are extremely variable. This consensus statement aims to provide care guidelines for congenital myopathies. The International Standard of Care Committee for Congenital Myopathies worked through frequent e-mail correspondences, periodic conference calls, 2 rounds of online surveys, and a 3-day workshop to achieve a consensus for diagnostic and clinical care recommendations. The committee includes 59 members from 10 medical disciplines. They are organized into 5 working groups: genetics/diagnosis, neurology, pulmonology, gastroenterology/nutrition/speech/oral care, and orthopedics/rehabilitation. In each care area the authors summarize the committee's recommendations for symptom assessments and therapeutic interventions. It is the committee's goal that through these recommendations, patients with congenital myopathies will receive optimal care and improve their disease outcome.

Isolation and characterisation of microsatellite loci in the wasp Mischocyttarus cassununga

Mischocyttarus cassununga, a primitively eusocial Brazilian wasp, commonly found in urban environments, is an interesting model for studies on the evolution of social behaviour in hymenopteran insects. In this study, we constructed a microsatellite-enriched genomic library and presented primers for 18 microsatellite loci. For the analysis, 20 unrelated females were screened and all loci obtained were polymorphic. PCR amplification revealed from 3 (Mcas5b) to 17 (Mcas53b) alleles per locus (). We detected the levels of observed (H (o)) and expected (H (e)) heterozygosities ranging from 0.150 to 0.950 and 0.261 to 0.920, respectively. The polymorphic information content ranged from 0.238 to 0.915, averaging 0.680. All loci were in Hardy-Weinberg equilibrium and linkage disequilibrium was not detected after sequential Bonferroni correction (P > 0.05). These molecular markers will allow further studies on sociogenetic structure, extensive population genetic analysis and diversity of M. cassununga and other Mischocyttarini species.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

Hybrid heuristic-waterfilling game theory approach in MC-CDMA resource allocation

This paper discusses the power allocation with fixed rate constraint problem in multi-carrier code division multiple access (MC-CDMA) networks, that has been solved through game theoretic perspective by the use of an iterative water-filling algorithm (IWFA). The problem is analyzed under various interference density configurations, and its reliability is studied in terms of solution existence and uniqueness. Moreover, numerical results reveal the approach shortcoming, thus a new method combining swarm intelligence and IWFA is proposed to make practicable the use of game theoretic approaches in realistic MC-CDMA systems scenarios. The contribution of this paper is twofold: (i) provide a complete analysis for the existence and uniqueness of the game solution, from simple to more realist and complex interference scenarios; (ii) propose a hybrid power allocation optimization method combining swarm intelligence, game theory and IWFA. To corroborate the effectiveness of the proposed method, an outage probability analysis in realistic interference scenarios, and a complexity comparison with the classical IWFA are presented. (C) 2011 Elsevier B.V. All rights reserved.