44 resultados para Genetic Algorithms and Simulated Annealing
Resumo:
When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009
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This paper analyzes the complexity-performance trade-off of several heuristic near-optimum multiuser detection (MuD) approaches applied to the uplink of synchronous single/multiple-input multiple-output multicarrier code division multiple access (S/MIMO MC-CDMA) systems. Genetic algorithm (GA), short term tabu search (STTS) and reactive tabu search (RTS), simulated annealing (SA), particle swarm optimization (PSO), and 1-opt local search (1-LS) heuristic multiuser detection algorithms (Heur-MuDs) are analyzed in details, using a single-objective antenna-diversity-aided optimization approach. Monte- Carlo simulations show that, after convergence, the performances reached by all near-optimum Heur-MuDs are similar. However, the computational complexities may differ substantially, depending on the system operation conditions. Their complexities are carefully analyzed in order to obtain a general complexity-performance framework comparison and to show that unitary Hamming distance search MuD (uH-ds) approaches (1-LS, SA, RTS and STTS) reach the best convergence rates, and among them, the 1-LS-MuD provides the best trade-off between implementation complexity and bit error rate (BER) performance.
Resumo:
In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
Variation among natural populations of Culex (Culex) quinquefasciatus Say is associated with different vectorial capacities. The species Cx. quinquefasciatus is present in the equatorial, tropical and subtropical zones in the Brazilian territory, with intermediate forms between Cx. quinquefasciatus and Culex pipiens occurring in regions of latitudes around 33°-35°S. Herein, we studied geographically distinct populations of Cx. quinquefasciatus by genetic characterization and analysis of intra-specific wing morphometrics. After morphological analysis, molecular characterization of Cx. quinquefasciatus and intermediate forms was performed by polymerase chain reaction of the polymorphic nuclear region of the second intron of the acetylcholinesterase locus. Additionally, the morphology of adult female wings collected from six locations was analyzed. Wing centroid sizes were significantly different between some geographical pairs. Mean values of R2/R2+3 differed significantly after pairwise comparisons. The overall wing shape represented by morphometric characters could be divided into two main groupings. Our data suggest that Brazilian samples are morphologically and genetically distinct from the Argentinean samples and also indicated a morphological distinction between northern and southern populations of Brazilian Cx. quinquefasciatus. We suggest that wing morphology may be used for preliminary assessment of population structure of Cx. quinquefasciatusin Brazil
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Survival or longevity is an economically important trait in beef cattle. The main inconvenience for its inclusion in selection criteria is delayed recording of phenotypic data and the high computational demand for including survival in proportional hazard models. Thus, identification of a longevity-correlated trait that could be recorded early in life would be very useful for selection purposes. We estimated the genetic relationship of survival with productive and reproductive traits in Nellore cattle, including weaning weight (WW), post-weaning growth (PWG), muscularity (MUSC), scrotal circumference at 18 months (SC18), and heifer pregnancy (HP). Survival was measured in discrete time intervals and modeled through a sequential threshold model. Five independent bivariate Bayesian analyses were performed, accounting for cow survival and the five productive and reproductive traits. Posterior mean estimates for heritability (standard deviation in parentheses) were 0.55 (0.01) for WW, 0.25 (0.01) for PWG, 0.23 (0.01) for MUSC, and 0.48 (0.01) for SC18. The posterior mean estimates (95% confidence interval in parentheses) for the genetic correlation with survival were 0.16 (0.13-0.19), 0.30 (0.25-0.34), 0.31 (0.25-0.36), 0.07 (0.02-0.12), and 0.82 (0.78-0.86) for WW, PWG, MUSC, SC18, and HP, respectively. Based on the high genetic correlation and heritability (0.54) posterior mean estimates for HP, the expected progeny difference for HP can be used to select bulls for longevity, as well as for post-weaning gain and muscle score.
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This paper addresses the use of optimization techniques in the design of a steel riser. Two methods are used: the genetic algorithm, which imitates the process of natural selection, and the simulated annealing, which is based on the process of annealing of a metal. Both of them are capable of searching a given solution space for the best feasible riser configuration according to predefined criteria. Optimization issues are discussed, such as problem codification, parameter selection, definition of objective function, and restrictions. A comparison between the results obtained for economic and structural objective functions is made for a case study. Optimization method parallelization is also addressed. [DOI: 10.1115/1.4001955]
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Titanium oxide (TiO(2)) has been extensively applied in the medical area due to its proved biocompatibility with human cells [1]. This work presents the characterization of titanium oxide thin films as a potential dielectric to be applied in ion sensitive field-effect transistors. The films were obtained by rapid thermal oxidation and annealing (at 300, 600, 960 and 1200 degrees C) of thin titanium films of different thicknesses (5 nm, 10 nm and 20 nm) deposited by e-beam evaporation on silicon wafers. These films were analyzed as-deposited and after annealing in forming gas for 25 min by Ellipsometry, Fourier Transform Infrared Spectroscopy (FTIR), Raman Spectroscopy (RAMAN), Atomic Force Microscopy (AFM), Rutherford Backscattering Spectroscopy (RBS) and Ti-K edge X-ray Absorption Near Edge Structure (XANES). Thin film thickness, roughness, surface grain sizes, refractive indexes and oxygen concentration depend on the oxidation and annealing temperature. Structural characterization showed mainly presence of the crystalline rutile phase, however, other oxides such Ti(2)O(3), an interfacial SiO(2) layer between the dielectric and the substrate and the anatase crystalline phase of TiO(2) films were also identified. Electrical characteristics were obtained by means of I-V and C-V measured curves of Al/Si/TiO(x)/Al capacitors. These curves showed that the films had high dielectric constants between 12 and 33, interface charge density of about 10(10)/cm(2) and leakage current density between 1 and 10(-4) A/cm(2). Field-effect transistors were fabricated in order to analyze I(D) x V(DS) and log I(D) x Bias curves. Early voltage value of -1629 V, R(OUT) value of 215 M Omega and slope of 100 mV/dec were determined for the 20 nm TiO(x) film thermally treated at 960 degrees C. (C) 2009 Elsevier B.V. All rights reserved.
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Eucalyptus camaldulensis has great importance in Brazil because of their phenotypic plasticity for different environmental conditions, as soils, altitudes and rainfall. This study is an investigation of a base population of E. camaldulensis from Australia through a progeny test implanted in Selviria, MS. The trial was established in a randomized block design, with 25 families and 60 replications of single tree plots. Genetic parameters for anatomic traits and volume shrinkage were estimated, as well as their correlations with wood basic density. No significant differences among progenies were observed for the traits studied. The additive genetic variation coefficient at individual and among progeny levels ranged from low (0.26%) to high (16.98%). The narrow sense heritability at individual and family means levels also ranged from low (0.01) to high (0.87). This indicates that some traits are under strong genetic control and can be improved by selection. In the present situation, in order to attain the highest genetic gains, the sequential selection among and within progeny would be recommended.
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This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.
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Ficus arpazusa Casaretto is a fig tree native to the Atlantic Rain Forest sensu lato. High levels of genetic diversity and no inbreeding were observed in Ficus arpazusa. This genetic pattern is due to the action of its pollinator, Pegoscapus sp., which disperses pollen an estimated distance of 5.6 km, and of Ficus arpazusa`s mating system which, in the study area, is allogamous. This study highlights the importance of adding both ecological and genetic data into population studies, allowing a better understanding of evolutionary processes and in turn increasing the efficacy of forest management and revegetation projects, as well as species conservation.
Resumo:
Objective: Hantaviruses are rodent-borne RNA viruses that have caused hantavirus cardiopulmonary syndrome in several Brazilian regions. In the present study, geographical distribution, seroprevalence, natural host range, and phylogenetic relations of rodent-associated hantaviruses collected from seven counties of Southeastern Brazil were evaluated. Methods: ELISA, RT-PCR and phylogenetic analysis were used in this study. Results: Antibodies to hantavirus were detected in Bolomys lasiurus, Akodon sp. and Oligoryzomys sp., performing an overall seroprevalence of 5.17%. All seropositive rodents were associated with grasslands or woods surrounded by sugar cane fields. Phylogenetic analysis of partial S- and M-segment sequences showed that viral sequences isolated from B. lasiurus specimens clustered with Araraquara virus. However, a sequence from Akodon sp. shared 100% similarity with Argentinian/Chilean viruses based on the partial S- segment amino acid sequence. Conclusion: These results indicate that there are associations between rodent reservoirs and hantaviruses in some regions of Southeastern Brazil, and suggest the existence of additional hantavirus genetic diversity and host ecology in these areas. Copyright (C) 2008 S. Karger AG, Basel
Resumo:
With the availability of a large amount of genomic data it is expected that the influence of single nucleotide variations (SNVs) in many biological phenomena will be elucidated. Here, we approached the problem of how SNVs affect alternative splicing. First, we observed that SNVs and exonic splicing regulators (ESRs) independently show a biased distribution in alternative exons. More importantly, SNVs map more frequently in ESRs located in alternative exons than in ESRs located in constitutive exons. By looking at SNVs associated with alternative exon/intron borders (by their common presence in the same cDNA molecule), we observed that a specific type of ESR, the exonic splicing silencers (ESSs), are more frequently modified by SNVs. Our results establish a clear association between genetic diversity and alternative splicing involving ESSs.
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In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.