A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Multi-Stage Stochastic Non-Linear Model for Reactive Power Planning Under Contingencies

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

A genetic algorithm for the one-dimensional cutting stock problem with setups

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

Objective CT-Based Quantification of Lung Sequelae in Treated Patients With Paracoccidioidomycosis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An evolutionary approach to improve connectivity prediction in mobile wireless sensor networks

Connectivity is the basic factor for the proper operation of any wireless network. In a mobile wireless sensor network it is a challenge for applications and protocols to deal with connectivity problems, as links might get up and down frequently. In these scenarios, having knowledge of the node remaining connectivity time could both improve the performance of the protocols (e.g. handoff mechanisms) and save possible scarce nodes resources (CPU, bandwidth, and energy) by preventing unfruitful transmissions. The current paper provides a solution called Genetic Machine Learning Algorithm (GMLA) to forecast the remainder connectivity time in mobile environments. It consists in combining Classifier Systems with a Markov chain model of the RF link quality. The main advantage of using an evolutionary approach is that the Markov model parameters can be discovered on-the-fly, making it possible to cope with unknown environments and mobility patterns. Simulation results show that the proposal is a very suitable solution, as it overcomes the performance obtained by similar approaches.

Genetic gain in the selection by multi-effects index in open-pollinated progenies of Eucalyptus grandis Hill ex Maiden

In Brazil, Eucalyptus grandis Hill ex Maiden is widely used for commercial reforestation, especially for production of pulp, paper and energy. Its genetic variability is being explored in tree improvement programs for over 30 years. The objective of this work was to estimate genetic parameters and compare genetic gains by multi-effects index in a breeding population of E. grandis. Progeny tests were established using open-pollinated seeds from ten provenances ranging from 153 to 160 progenies established in a completely randomized block design in four sites of Sao Paulo State (Anhembi, Avere Itarare e Pratania). At 24 months of age the traits diameter at breast height (DBH), height (ALT) and volume (VOL) were measured. The individual site analyses indicated significant genetic differences among progenies, height genetic variability and the mean progeny heritability (> 0.70). For joint analyses of sites, significant differences in genotype x environmental interaction effects were detected, showing differences of performance of the progenies in different sites. The Itarare site gave high genetic gains, effective size and genetic diversity. The genetic diversity and low effective size are unviable factors; considering that the progeny tests studied should retain adequate levels of genetic variability in order to be transformed in future seedling seed orchards.

Locating control points in aerial images with a multi-scale approach based on terrestrial image patches

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

Geoffroy's side-necked turtle [Phrynops geoffroanus (Schweigger, 1812), Testudines: Chelidae] as a model for evolutionary ecotoxicology: relationship between environmental contamination, conditions and genetic variability

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reconfiguração de sistemas de distribuição de energia elétrica utilizando uma metodologia multipartida

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fatores que Influenciam a flexibilidade da produção de veículos comerciais

Pós-graduação em Engenharia de Produção - FEG

Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Fatores que Influenciam a flexibilidade da produção de veículos comerciais

Pós-graduação em Engenharia de Produção - FEG

Identification of multi-component trail pheromones in the most evolutionarily derived termites, the Nasutitermitinae (Termitidae)

In the present study, trail pheromone blends are identified for the first time in termites. In the phylogenetically complex Nasutitermitinae, trail-following pheromones are composed of dodecatrienol and neocembrene, the proportions of which vary according to species, although neocembrene is always more abundant than dodecatrienol (by 25-250-fold). Depending on species, termites were more sensitive to dodecatrienol or to neocembrene but the association of both components always elicited significantly higher trail following, with a clear synergistic effect in most of the studied species. A third component, trinervitatriene, was identified in the sternal gland secretion of several species, but its function remains unknown. The secretion of trail pheromone blends appears to be an important step in the evolution of chemical communication in termites. The pheromone optimizes foraging, and promotes their ecological success. (C) 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 20-27.

A comparison of CA125, HE4, risk ovarian malignancy algorithm (ROMA), and risk malignancy index (RMI) for the classification of ovarian masses

OBJECTIVE: Differentiation between benign and malignant ovarian neoplasms is essential for creating a system for patient referrals. Therefore, the contributions of the tumor markers CA125 and human epididymis protein 4 (HE4) as well as the risk ovarian malignancy algorithm (ROMA) and risk malignancy index (RMI) values were considered individually and in combination to evaluate their utility for establishing this type of patient referral system. METHODS: Patients who had been diagnosed with ovarian masses through imaging analyses (n = 128) were assessed for their expression of the tumor markers CA125 and HE4. The ROMA and RMI values were also determined. The sensitivity and specificity of each parameter were calculated using receiver operating characteristic curves according to the area under the curve (AUC) for each method. RESULTS: The sensitivities associated with the ability of CA125, HE4, ROMA, or RMI to distinguish between malignant versus benign ovarian masses were 70.4%, 79.6%, 74.1%, and 63%, respectively. Among carcinomas, the sensitivities of CA125, HE4, ROMA (pre-and post-menopausal), and RMI were 93.5%, 87.1%, 80%, 95.2%, and 87.1%, respectively. The most accurate numerical values were obtained with RMI, although the four parameters were shown to be statistically equivalent. CONCLUSION: There were no differences in accuracy between CA125, HE4, ROMA, and RMI for differentiating between types of ovarian masses. RMI had the lowest sensitivity but was the most numerically accurate method. HE4 demonstrated the best overall sensitivity for the evaluation of malignant ovarian tumors and the differential diagnosis of endometriosis. All of the parameters demonstrated increased sensitivity when tumors with low malignancy potential were considered low-risk, which may be used as an acceptable assessment method for referring patients to reference centers.