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Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

Bignardi, A. B.; El Faro, L.; Rosa, G. J. M.; Cardoso, V. L.; Machado, Paulo Fernando; Albuquerque, L. G.
Fonte: ELSEVIER SCIENCE INC; NEW YORK Publicador: ELSEVIER SCIENCE INC; NEW YORK
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
45.87%
A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.; Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP); Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP); Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (Capes)...

Análise de risco de crédito com o uso de modelos de regressão logística, redes neurais e algoritmos genéticos; Credit risk analysis applying logistic regression, neural networks models and genetic algorithms

Gonçalves, Eric Bacconi
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 29/07/2005 PT
Relevância na Pesquisa
45.87%
Praticamente todas as grandes instituições brasileiras que trabalham com concessão de crédito utilizam-se de modelos para avaliar o risco de inadimplência dos potenciais contratantes de produtos de crédito. Qualquer avanço nas técnicas, que resulte no aumento da precisão de um modelo de previsão, acarreta ganhos financeiros para a instituição. Neste trabalho são apresentados, em um primeiro momento, conceitos de crédito e risco. Posteriormente, a partir de uma amostra de dados, fornecida por uma grande instituição financeira brasileira, estão desenvolvidos três modelos, aplicando-se três técnicas para a classificação de clientes: Regressão Logística, Redes Neurais e Algoritmos Genéticos. Em uma etapa final, são avaliadas e comparadas a qualidade e performance dos modelos desenvolvidos, onde é apontado qual o modelo que melhor se ajusta aos dados. Os resultados obtidos pelos modelos de regressão logística e rede neural são satisfatórios e bastante próximos, sendo o primeiro ligeiramente superior. O modelo embasado por algoritmos genéticos apresenta também bons resultados embora num patamar inferior aos dois já citados. Este trabalho ilustra os procedimentos a serem adotados por uma empresa para identificar o melhor modelo de concessão de crédito que tenha boa aderência aos seus dados. A adoção do melhor modelo detectado permite o direcionamento da estratégia da instituição...

Genetic parameters for milk yield analyzed by test-day models in Murrah buffaloes in Brazil

Aspilcueta-Borquis, Rusbel R.; Bignardi, Annaiza B.; Seno, Leonardo de O.; Camargo, Gregorio M. F. de; Munoz-Berrocal, Milthon H.; Albuquerque, Lucia Galvão de; Di Palo, Rossella; Tonhati, Humberto
Fonte: Pagepress Publ Publicador: Pagepress Publ
Tipo: Artigo de Revista Científica Formato: 179-182
ENG
Relevância na Pesquisa
45.89%
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); New statistical models for genetic parameters estimation based on longitudinal data have been proposed. In this study, we considered the data of 47,614 test-day milk yields from 1,578 buffaloes, with 4,757 complete lactations, calving from 1985 to 2006. Single- ,two-and multiple trait analyses were used and variance components were estimated by Restricted Maximum Likelihood. The model used to evaluate the milk yield trait at 305 days (MY305) included: i) herd-year-calving season (contemporary group) and milking number as fixed effects; ii) buffalo age at calving as covariate (linear and quadratic effect); iii) additive genetic, permanent environmental, residual and the animal as random effects. The same effects were included in the test-day milk yield model except the contemporary group, defined as herd-year-test day. The heritability estimations for TDMY vary from 0.13 to 0.23 for single-trait analyses, from 0.13 to 0.24 for two-trait analyses and from 0.15 to 0.24 for the multiple-trait analyses. The results obtained for each of the three models showed that the higher heritability estimations were always obtained in the third test month. The genetic correlations between the TDMY and MY305 were high and positive. In conclusion...

A Bayesian approach for constructing genetic maps when markers are miscoded

Rosa, Guilherme J. M.; Yandell, Brian S.; Gianola, Daniel
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 353-369
ENG
Relevância na Pesquisa
45.78%
The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Pereira, R. J.; Bignardi, A. B.; El Faro, L.; Verneque, R. S.; Vercesi Filho, A. E.; Albuquerque, L. G.
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 565-574
ENG
Relevância na Pesquisa
45.91%
Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that...

Genetic associations among average annual productivity, growth traits, and stayability: A parallel between Nelore and composite beef cattle

Santana, M. L.; Eler, J. P.; Bignardi, A. B.; Ferraz, J. B S
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 2566-2574
ENG
Relevância na Pesquisa
45.77%
This study was conducted to examine the relationship among average annual productivity of the cow (PRODAM), yearling weight (YW), postweaning BW gain (PWG), scrotal circumference (SC), and stayability in the herd for at least 6 yr (STAY) of Nelore and composite beef cattle. Measurements were taken on animals born between 1980 and 2010 on 70 farms located in 7 Brazilian states. Estimates of heritability and genetic and environmental correlations were obtained by Bayesian approach with 5-trait animal models. Genetic trends were estimated by regressing means of estimated breeding values by year of birth. The heritability estimates were between 0.14 and 0.47. Estimates of genetic correlation among female traits (PRODAM and STAY) and growth traits ranged from-0.02 to 0.30. Estimates of genetic correlations ranged from 0.23 to 0.94 among growth traits indicating that selection for these traits could be successful in tropical breeding programs. Genetic correlations among all traits were favorable and simultaneous selection for growth, productivity, and stayability is therefore possible. Genetic correlation between PRODAM and STAY was 0.99 and 0.85 for Nelore and composite cattle, respectively. Therefore, PRODAM and STAY might be influenced by many of the same genes. The inclusion of PRODAM instead of STAY as a selection criterion seems to be more advantageous for tropical breeding programs because the generation interval required to obtain accurate estimates of genetic merit for PRODAM is shorter. Average annual genetic changes were greater in Nelore than in composite cattle. This was not unexpected because the breeding program of composite cattle included a large number of farms...

Ajuste de modelos não lineares e estimativas de parâmetros genéticos para produção de ovos de uma linhagem de poedeiras White Leghorn

Savegnago, Rodrigo Pelicioni
Fonte: Universidade Estadual Paulista (UNESP) Publicador: Universidade Estadual Paulista (UNESP)
Tipo: Dissertação de Mestrado Formato: vi, 69 f. : grafs.
POR
Relevância na Pesquisa
45.92%
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES); Pós-graduação em Genética e Melhoramento Animal - FCAV; Modelos não lineares são úteis para ajustar curvas de produção de ovos de aves, facilitando o estudo do desempenho dessa característica ao longo do tempo. As estimativas de parâmetros genéticos da produção de ovos e de outras características associadas auxiliam no processo de seleção. O objetivo do trabalho foi: (1) utilizar modelos não lineares para ajustar curvas de produção de ovos aos dados de uma população de aves selecionada para postura e uma controle e verificar as mudanças ocorridas entre estas curvas preditas em função do processo de seleção, por meio do ganho genético e pelas diferenças entre as estimativas dos parâmetros dos modelos; (2) estimar parâmetros genéticos para características relacionadas à postura de ovos da população selecionada, avaliar a associação genética entre estas e determinar quais as melhores características que podem ser utilizadas para melhorar a produção de ovos. Foram estudados os ajustes de 10 modelos não lineares aplicados aos registros da produção de ovos de 54 semanas de postura de 1693 aves de uma população selecionada para taxa de postura e 282 aves de uma população controle. Foi utilizado o PROC NLIN do SAS com o algoritmo de Gauss-Newton para efetuar os ajustes dos modelos. Os parâmetros genéticos...

Modelagem de sistemas dinamicos não lineares utilizando sistemas fuzzy, algoritmos geneticos e funções de base ortonormal; Modeling of nonlinear dynamics systems using fuzzy systems, genetic algorithms and orthonormal basis functions

Anderson Vinicius de Medeiros
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 23/01/2006 PT
Relevância na Pesquisa
45.94%
Esta dissertação apresenta uma metodologia para a geração e otimização de modelos fuzzy Takagi-Sugeno (TS) com Funções de Base Ortonormal (FBO) para sistemas dinâmicos não lineares utilizando um algoritmo genético. Funções de base ortonormal têm sido utilizadas por proporcionarem aos modelos propriedades como ausência de recursão da saída e possibilidade de se alcançar uma razoável capacidade de representação com poucos parâmetros. Modelos fuzzy TS agregam a essas propriedades as características de interpretabilidade e facilidade de representação do conhecimento. Enfim, os algoritmos genéticos se apresentam como um método bem estabelecido na literatura na tarefa de sintonia de parâmetros de modelos fuzzy TS. Diante disso, desenvolveu-se um algoritmo genético para a otimização de duas arquiteturas, o modelo fuzzy TS FBO e sua extensão, o modelo fuzzy TS FBO Generalizado. Foram analisados modelos locais lineares e não lineares nos conseqüentes das regras fuzzy, assim como a diferença entre a estimação local e a global (utilizando o estimador de mínimos quadrados) dos parâmetros desses modelos locais. No algoritmo genético, cada arquitetura contou com uma representação cromossômica específica. Elaborou-se para ambas uma função de fitness baseada no critério de Akaike. Em relação aos operadores de reprodução...

Previsão de carga de curto prazo usando ensembles de previsores selecionados e evoluidos por algoritmos geneticos; Short-term load forecasting using esembles of selected and evolved predictors by genetic algorithms

Marcos de Almeida Leone Filho
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 31/01/2006 PT
Relevância na Pesquisa
45.78%
Neste trabalho é proposta uma metodologia para previsão de séries temporais de carga de energia elétrica de curto prazo. Esta metodologia vem sendo muito utilizada no contexto da previsão de séries temporais e do reconhecimento de padrões. Os autores que propuseram esta metodologia a chamaram de "Ensembles". Este nome tenta explicar o é este modelo: uma combinação de partes que juntas formam um só modelo. Neste sentido, este nome expressa com relativa clareza qual é o principal aspecto desta metodologia, que no caso específico deste trabalho, é o de fazer várias previsões de uma mesma série temporal utilizando diferentes ferramentas que sozinhas são suficientemente competentes para prever a série temporal em questão, e em seguida combinar as soluções para, deste modo, tentar obter uma solução melhor do que quando é usada somente uma ferramenta. As ferramentas usadas para compor a previsão dos "Ensembles" finais são Redes Neurais Artificiais (RNAs) e Redes Neurais Nebulosas. Atualmente, estas redes são largamente utilizadas em problemas de previsão de séries temporais, principalmente quando o fator gerador destas séries é um sistema não-linear. Desta forma, isto as tornou candidatas potenciais para prever valores de uma série de cargas de energia elétrica...

Estimation of genetic parameters and verification of early selection efficiency in baru (Dipteryx alata)

Santos,Alisson Moura; Rosado,Sebastião Carlos da Silva; Oliveira,Adelson Nascimento
Fonte: Crop Breeding and Applied Biotechnology Publicador: Crop Breeding and Applied Biotechnology
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2014 EN
Relevância na Pesquisa
45.71%
This study aimed at verifying the efficiency of early selection, and estimating the genetic parameters in Dipteryx alata. The 66 half-sib families were obtained from three seed provenances at the Brazilian Savannah of the state of Minas Gerais. The experiment was carried out in a randomized block design with 3 replications and 5 plants per plot. Data diameters at breast height (DBH) and total height (TH) were taken at the ages of 64, 125 and 138 months. REML/BLUP methodology was applied in the D. alata different provenances and progenies. Analysis indicated significant genetic variability (P < 0.01) between and within provenances. Both traits, DBH and TH, presented high narrow sense heritability for the ages analyzed. High genetic correlation occurred between DBH and TH traits, and between ages (age-age); thus, it allowed indirect selection, as well as early selection with high genetics gains.

Automatic Structure Generation using Genetic Programming and Fractal Geometry

Bergen, Steve
Fonte: Brock University Publicador: Brock University
Tipo: Electronic Thesis or Dissertation
ENG
Relevância na Pesquisa
45.85%
Three dimensional model design is a well-known and studied field, with numerous real-world applications. However, the manual construction of these models can often be time-consuming to the average user, despite the advantages o ffered through computational advances. This thesis presents an approach to the design of 3D structures using evolutionary computation and L-systems, which involves the automated production of such designs using a strict set of fitness functions. These functions focus on the geometric properties of the models produced, as well as their quantifiable aesthetic value - a topic which has not been widely investigated with respect to 3D models. New extensions to existing aesthetic measures are discussed and implemented in the presented system in order to produce designs which are visually pleasing. The system itself facilitates the construction of models requiring minimal user initialization and no user-based feedback throughout the evolutionary cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented...

Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks

Medland, Michael; Medland, Michael
Fonte: Brock University Publicador: Brock University
Tipo: Electronic Thesis or Dissertation
ENG
Relevância na Pesquisa
45.92%
Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models...

Genetic covariance structure of incisor crown size in twins

Dempsey, P.; Townsend, G.; Martin, N.; Neale, M.
Fonte: International Association for Dental Research Publicador: International Association for Dental Research
Tipo: Artigo de Revista Científica
Publicado em //1995 EN
Relevância na Pesquisa
45.9%
Previous studies of tooth size in twins and their families have suggested a high degree of genetic control, although there have been difficulties separating the various genetic and environmental effects. A genetic analysis of variation in crown size of the permanent incisors of South Australian twins was carried out, with structural equation modeling used to determine the relative contributions of genetic and environmental factors. Maximum mesiodistal crown dimensions of maxillary and mandibular permanent incisors were recorded from dental models of 298 pairs of twins, including 149 monozygous (MZ) and 149 dizygous (DZ) pairs. The analysis revealed that: (i) an adequate fit required additive genetic and unique environmental components; (ii) augmenting the model with non-additive genetic variation did not lead to a significant improvement in fit; (iii) there was evidence of shared environmental influences in the upper central incisors of males; (iv) the additive genetic component constituted a general factor loading on all eight teeth, with group factors loading on antimeric pairs of teeth; (v) unique environmental effects were mostly variable-specific; (vi) most factor loadings on antimeric tooth pairs could be constrained to be equal...

Real-coded genetic algorithm parameter setting for water distribution system optimisation.

Gibbs, Matthew S.
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2008
Relevância na Pesquisa
45.73%
The management of Water Distribution Systems (WDSs) involves making decisions about various operations in the network, including the scheduling of pump operations and setting of disinfectant dosing rates. There are often conflicting objectives in making these operational decisions, such as minimising costs while maximising the quality of the water supplied. Hence, the operation of WDSs can be very difficult, and there is generally considerable scope to improve the operational efficiency of these systems by improving the associated decision making process. In order to achieve this goal, optimisation methods known as Genetic Algorithms (GAs) have been successfully adopted to assist in determining the best possible solutions to WDS optimisation problems for a number of years. Even though there has been extensive research demonstrating the potential of GAs for improving the design and operation of WDSs, the method has not been widely adopted in practice. There are a number of reasons that may contribute to this lack of uptake, including the following difficulties: (a) developing an appropriate fitness function that is a suitable description of the objective of the optimisation including all constraints, (b) making decisions that are required to select the most appropriate variant of the algorithm...

Modelling BMI trajectories in children for genetic association studies

Warrington, N.; Wu, Y.; Pennell, C.; Marsh, J.; Beilin, L.; Palmer, L.; Lye, S.; Briollais, L.
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em //2013 EN
Relevância na Pesquisa
45.93%
Background: The timing of associations between common genetic variants and changes in growth patterns over childhood may provide insight into the development of obesity in later life. To address this question, it is important to define appropriate statistical models to allow for the detection of genetic effects influencing longitudinal childhood growth. Methods and Results: Children from The Western Australian Pregnancy Cohort (Raine; n = 1,506) Study were genotyped at 17 genetic loci shown to be associated with childhood obesity (FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, SEC16B, LYPLAL1, TFAP2B, MTCH2, BCDIN3D, NRXN3, SH2B1, MRSA) and an obesity-risk-allele-score was calculated as the total number of ‘risk alleles’ possessed by each individual. To determine the statistical method that fits these data and has the ability to detect genetic differences in BMI growth profile, four methods were investigated: linear mixed effects model, linear mixed effects model with skew-t random errors, semi-parametric linear mixed models and a non-linear mixed effects model. Of the four methods, the semi-parametric linear mixed model method was the most efficient for modelling childhood growth to detect modest genetic effects in this cohort. Using this method...

Genetic architecture of idiopathic generalized epilepsy: Clinical genetic analysis of 55 multiplex families

Marini, C.; Scheffer, I.; Crossland, K.; Grinton, B.; Phillips, F.; McMahon, J.; Turner, S.; Dean, J.; Kivity, S.; Mazarib, A.; Neufeld, M.; Korczyn, A.; Harkin, L.; Dibbens, L.; Wallace, R.; Mulley, J.; Berkovic, S.
Fonte: Blackwell Publishing Inc Publicador: Blackwell Publishing Inc
Tipo: Artigo de Revista Científica
Publicado em //2004 EN
Relevância na Pesquisa
45.76%
Summary: Purpose: In families with idiopathic generalized epilepsy (IGE), multiple IGE subsyndromes may occur. We performed a genetic study of IGE families to clarify the genetic relation of the IGE subsyndromes and to improve understanding of the mode(s) of inheritance. Methods: Clinical and genealogic data were obtained on probands with IGE and family members with a history of seizures. Families were grouped according to the probands' IGE subsyndrome: childhood absence epilepsy (CAE), juvenile absence epilepsy (JAE), juvenile myoclonic epilepsy (JME), and IGE with tonic–clonic seizures only (IGE-TCS). The subsyndromes in the relatives were analyzed. Mutations in genes encoding α1 and γ2 γ-aminobutyric acid (GABA)-receptor subunits, α1 and β1 sodium channel subunits, and the chloride channel CLC-2 were sought. Results: Fifty-five families were studied. 122 (13%) of 937 first- and second-degree relatives had seizures. Phenotypic concordance within families of CAE and JME probands was 28 and 27%, respectively. JAE and IGE-TCS families had a much lower concordance (10 and 13%), and in the JAE group, 31% of relatives had CAE. JME was rare among affected relatives of CAE and JAE probands and vice versa. Mothers were more frequently affected than fathers. No GABA-receptor or sodium or chloride channel gene mutations were identified. Conclusions: The clinical genetic analysis of this set of families suggests that CAE and JAE share a close genetic relation...

A heterogeneity test for fine-scale genetic structure

Smouse, Peter E; Peakall, Rodney; Gonzales, Eva
Fonte: Blackwell Publishing Ltd Publicador: Blackwell Publishing Ltd
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.74%
For organisms with limited vagility and/or occupying patchy habitats, we often encounter nonrandom patterns of genetic affinity over relatively small spatial scales, labelled fine-scale genetic structure. Both the extent and decay rate of that pattern can

IIR modeling of interpositional transfer functions with a genetic algorithm aided by an adaptive filter for the purpose of altering free-field sound localization

Padden, Dereck
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
EN_US
Relevância na Pesquisa
45.73%
The psychoacoustic process of sound localization is a system of complex analysis. Scientists have found evidence that both binaural and monaural cues are responsible for determining the angles of elevation and azimuth which represent a sound source. Engineers have successfully used these cues to build mathematical localization systems. Research has indicated that spectral cues play an important role in 3-d localization. Therefore, it seems conceivable to design a filtering system which can alter the localization of a sound source, either for correctional purposes or listener preference. Such filters, known as Interpositional Transfer Functions, can be formed from division in the z-domain of Head-related Transfer Functions. HRTF’s represent the free-field response of the human body to sound processed by the ears. In filtering applications, the use of IIR filters is often favored over that of FIR filters due to their preservation of resolution while minimizing the number of required coefficients. Several methods exist for creating IIR filters from their representative FIR counterparts. For complicated filters, genetic algorithms (GAs) have proven effective. The research summarized in this thesis combines the past efforts of researchers in the fields of sound localization...

Genetic structure, conservation genetics and evidence of speciation by range expansion in shy and white-capped albatrosses

Abbott, Cathryn; Double, Michael
Fonte: Blackwell Publishing Ltd Publicador: Blackwell Publishing Ltd
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.75%
Six variable microsatellite loci were used to examine genetic structuring in the closely related shy albatross (Thalassarche cauta) and white-capped albatross (T. steadi). First, levels of genetic differentiation between the species, and among three populations within each species, were analysed using AMOVA, FST and RST. We found high levels of genetic structuring and detected many unshared alleles between the species, which provide strong evidence against any contemporary gene flow between them. Within each species, shy albatross populations were found to be genetically distinct whereas white-capped albatross populations were undifferentiated, which implies that dispersal events are much rarer in the former than in the latter. These results formed the basis for the recommendation that the three white-capped albatross populations (as a whole) and each shy albatross population be treated as separate units for conservation. Second, levels of genetic diversity and allelic patterns in shy and white-capped albatrosses were assessed for whether they support earlier mtDNA results suggesting that shy albatrosses arose through range expansion of white-capped albatrosses. All measures indicated lower genetic diversity within shy albatrosses than within white-capped albatrosses and upheld the hypothesis that shy albatrosses were founded by white-capped albatrosses.

Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure

Smouse, P; Peakall, Rodney
Fonte: Blackwell Publishing Ltd Publicador: Blackwell Publishing Ltd
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.75%
Population genetic theory predicts that plant populations will exhibit internal spatial autocorrelation when propagule flow is restricted, but as an empirical reality, spatial structure is rarely consistent across loci or sites, and is generally weak. A lack of sensitivity in the statistical procedures may explain the discrepancy. Most work to date, based on allozymes, has involved pattern analysis for individual alleles, but new PCR-based genetic markers are coming into vogue, with vastly increased numbers of alleles. The field is badly in need of an explicitly multivariate approach to autocorrelation analysis, and our purpose here is to introduce a new approach that is applicable to multiallelic codominant, multilocus arrays. The procedure treats the genetic data set as a whole, strengthening the spatial signal and reducing the stochastic (allele-to-allele, and locus-to-locus) noise. We (i) develop a very general multivariate method, based on genetic distance methods, (ii) illustrate it for multiallelic codominant loci, and (iii) provide nonparametric permutational testing procedures for the full correlogram. We illustrate the new method with an example data set from the orchid Caladenia tentaculata, for which we show (iv) how the multivariate treatment compares with the single-allele treatment...