884 resultados para random preference
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This paper presents a new approach to the LU decomposition method for the simulation of stationary and ergodic random fields. The approach overcomes the size limitations of LU and is suitable for any size simulation. The proposed approach can facilitate fast updating of generated realizations with new data, when appropriate, without repeating the full simulation process. Based on a novel column partitioning of the L matrix, expressed in terms of successive conditional covariance matrices, the approach presented here demonstrates that LU simulation is equivalent to the successive solution of kriging residual estimates plus random terms. Consequently, it can be used for the LU decomposition of matrices of any size. The simulation approach is termed conditional simulation by successive residuals as at each step, a small set (group) of random variables is simulated with a LU decomposition of a matrix of updated conditional covariance of residuals. The simulated group is then used to estimate residuals without the need to solve large systems of equations.
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Fiji disease (FD) of sugar cane caused by Fiji disease virus (FDV) is transmitted by the planthopper Perkinsiella saccharicida Kirkaldy (Hemiptera: Delphacidae). FD is effectively managed by using resistant cultivars, but whether the resistance is for the vector or for the Virus is Unknown. This knowledge would help develop a rapid and reliable glasshouse-based screening method for disease resistance. Sugar cane cultivars resistant, intermediate, and susceptible to FD were screened in a glasshouse, and the relationship between vector preferences and FD incidence was studied. Cultivar preference by nymphs increased with an increase in cultivar susceptibility to FD, but the relationship between adult preference and FD resistance was not significant. There was a positive correlation between the vector population and FD incidence, and the latent period for symptom expression declined with the increase in the vector populations. FD incidence in the glasshouse trial reflected the field-resistance status of sugar cane cultivars with known FD-resistance scores. The results suggest that resistance to FD in sugar cane is mediated by cultivar preference of the plant-hopper vector.
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We investigated the oviposition preference and larval performance of Helicoverpa armigera under laboratory conditions to determine if the oviposition preference of individual females on maize, cowpea and cotton correlates with offspring performance on the leaves of the same host plants. The host-plant preference hierarchy of females did not correlate with their offspring performance. Female moths chose host plants that contributed less to their offspring fitness. Plant effects accounted for the largest amount of variation in offspring performance, while the effects of female (family) was low. The offspring of most females (80%, n = 10) were broadly similar, but 20% (two out of 10), showed marked difference in their offspring performance across the host-plant species. Similarly, there was no relation between larval feeding preference and performance. However, like most laboratory experiments, our experi-mental design does not allow the evaluation of ecological factors (for example, natural enemies, host abundance, etc.) that can play an important role in larval performance in the field. Overall, the results highlight the importance of carrying out preference performance analysis on the individual or family level, rather than pooling individuals to obtain average population data.
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Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a≥0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields.
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This article represents the proceedings of a symposium at the 2002 joint RSA/ISBRA Conference in San Francisco, California. The organizer was Paula L. Hoffman and the co-chairs were Paula L. Hoffman and Michael Miles. The presentations were (1) Introduction and overview of the use of DNA microarrays, by Michael Miles; (2) DNA microarray analysis of gene expression in brains of P and NP rats, by Howard J. Edenberg; (3) Gene expression patterns in brain regions of AA and ANA rats, by Wolfgang Sommer; (4) Patterns of gene expression in brains of selected lines of mice that differ in ethanol tolerance, by Boris Tabakoff; (5) Gene expression profiling related to initial sensitivity and tolerance in gamma-protein kinase C mutants, by Jeanne Wehner; and (6) Gene expression patterns in human alcoholic brain: from microarrays to protein profiles, by Joanne Lewohl.
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The associations of physical activity and sedentary behavior with barriers, enjoyment, and preferences were examined in a population-based mail survey of 1,332 adults. Respondents reporting high enjoyment and preference for physical activity were more likely to report high levels of activity. Those reporting cost, the weather, and personal barriers to physical activity were less likely to be physically active. Preference for sedentary behavior was associated with the decreased likelihood of being physically active, and the weather as a barrier to physical activity was associated with the increased likelihood of sedentary behavior. These constructs can be used to examine individual and environmental influences on physical activity and sedentary behavior in specific populations and could inform the development of targeted interventions.
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Larvae of the genus Spodoptera spp. are highly polyphagous and can cause economical losses in several agricultural crops. Given their growing importance in the tomato crop, especially for industry, this work aimed to evaluate the feeding non-preference by larvae of Spodoptera frugiperda (J. E. Smith, 1797) and Spodoptera eridania (Cramer, 1782) on tomato genotypes and classify them by the levels of resistance. The commercial cultivar Santa Clara was set as the susceptible standard and line PI 134417 as the resistant standard to evaluate the lines PI 134418, PI 126931, LA 462 and LA 716. Feeding non-preference tests were performed under non-choice and free-choice conditions to evaluate the genotype attractiveness to larvae at predetermined times after their release, as well as the leaf area consumed. Overall, the genotypes LA 716 and PI 126931 were the least attractive to S. frugiperda, whereas Santa Clara was the most attractive and consumed. For S. eridania, the genotypes PI 126931, LA 462, LA 716 and PI 134418 were the least preferred for feeding, and Santa Clara and PI 134417 were the most attractive and consumed. The genotypes LA 716 and PI 126931 are moderately resistant to S. frugiperda and S. eridania; PI 134418 and LA 462 are moderately resistant to S. eridania; PI 134417 is susceptible to S. frugiperda and S. eridania; and Santa Clara is highly susceptible to both S. frugiperda and S. eridania.
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Topology optimization consists in finding the spatial distribution of a given total volume of material for the resulting structure to have some optimal property, for instance, maximization of structural stiffness or maximization of the fundamental eigenfrequency. In this paper a Genetic Algorithm (GA) employing a representation method based on trees is developed to generate initial feasible individuals that remain feasible upon crossover and mutation and as such do not require any repairing operator to ensure feasibility. Several application examples are studied involving the topology optimization of structures where the objective functions is the maximization of the stiffness and the maximization of the first and the second eigenfrequencies of a plate, all cases having a prescribed material volume constraint.
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We have studied, in particular under normality of the implied random variables, the connections between different measures of risk such as the standard deviation, the W-ruin probability and the p-V@R. We discuss conditions granting the equivalence of these measures with respect to risk preference relations and the equivalence of dominance and efficiency of risk-reward criteria involving these measures. Then more specifically we applied these concepts to rigorously face the problem of finding the efficient set of de Finetti’s variable quota share proportional reinsurance.
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Mestrado em Contabilidade
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Este estudo enquadra-se no âmbito do Marketing e Comportamento do Consumidor e tem como tema Promoção no Ponto de Venda. Esta investigação tem como objectivo conhecer a percepção e comportamento de grupos de consumidores face a promoções no ponto de venda. O desenvolvimento deste projecto procurou encontrar resposta para os objectivos de investigação propostos através da realização de um inquérito por questionário. Toda a investigação empírica teve por base os resultados obtidos através de 156 questionários online a consumidores, maiores de 18 anos, de super e hipermercados e centros comerciais. Foi utilizada uma amostra por conveniência, para a qual foi enviado questionário online através de email e redes sociais. Realizou-se então este estudo e os resultados demonstraram que as promoções continuam a motivar o consumo e a despoletar a compra imediata e em maior quantidade. Estas conclusões são diferenciadas face às categorias de produto, com maior interesse por parte do consumidor em relação às promoções nos bens essenciais e moda, e face às tipologias de promoção, cuja preferência de promoção são as que têm incidência no preço. No nosso estudo encontramos quatro segmentos de consumidores, que de uma forma global registam auto percepção de consumidores inteligentes, que procuram com a promoções optimizar a relação qualidade preço, e que são pouco impulsivos no consumo. Concluímos que as promoções no ponto de venda são técnicas de marketing em que os gestores de marketing devem continuar a apostar pois é um factor critico de sucesso no incremento de vendas.
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Epidemiological studies have shown the effect of diet on the incidence of chronic diseases; however, proper planning, designing, and statistical modeling are necessary to obtain precise and accurate food consumption data. Evaluation methods used for short-term assessment of food consumption of a population, such as tracking of food intake over 24h or food diaries, can be affected by random errors or biases inherent to the method. Statistical modeling is used to handle random errors, whereas proper designing and sampling are essential for controlling biases. The present study aimed to analyze potential biases and random errors and determine how they affect the results. We also aimed to identify ways to prevent them and/or to use statistical approaches in epidemiological studies involving dietary assessments.
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This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.
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Applied Mathematical Modelling, Vol.33