894 resultados para Expectation
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Mode of access: Internet.
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Mode of access: Internet.
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Direct quantile regression involves estimating a given quantile of a response variable as a function of input variables. We present a new framework for direct quantile regression where a Gaussian process model is learned, minimising the expected tilted loss function. The integration required in learning is not analytically tractable so to speed up the learning we employ the Expectation Propagation algorithm. We describe how this work relates to other quantile regression methods and apply the method on both synthetic and real data sets. The method is shown to be competitive with state of the art methods whilst allowing for the leverage of the full Gaussian process probabilistic framework.
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In recent years, hotels in Cyprus have encountered difficult economic times due to increasing customer demands and strong internal industry development competition. The hospitality industry’s main concern globally is to serve its customer S needs and desires, most of which are addressed through personal services. Hence, the hotel businesses that are able to provide quality services to its ever-demanding customers in a warm and efficient manner are those businesses which will be more likely to obtain a long term competitive advantage over their rivals. Ironically, the quality of services frequently cannot fully appreciated until something goes wrong, and then, the poor quality of services can have long lasting lingering effects on the customer base and, hence, often is translated into a loss of business. Nevertheless, since the issue of delivery of hospitality services always involves people, this issue must center around the management of the human resource factor, and in particular, on the way which interacts with itself and with guests, as service encounters. In the eyes of guests, hospitality businesses will be viewed successful or failure, depending on [he cumulative impact of the service encounters they have experienced on a personal level. Finally, since hotels are offering intangible and perishable personal service encounters, managing these services must be a paramount concern of any hotel business. As a preliminary exercise, visualize when you have last visited a hotel, or a restaurant, and then, ask yourself these questions: What did you feel about the quality of the experience? Was it a memorable one, which you would recommend it to others, or there were certain things, which could have made the difference? Thus, the way personalized services are provided can make the deference in attracting arid retaining long-term customers
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Episodic memory formation is shaped by expectation. Events that generate expectations have the capacity to influence memory. Additionally, whether subsequent events meet or violate expectations has consequences for memory. However, clarification is still required to illuminate the circumstances and direction of memory modulation. In the brain, the mechanisms by which expectation modulates memory formation also require consideration. The dopamine system has been implicated in signaling events associated with different states of expectancy; it has also been shown to modulate episodic memory formation in the hippocampus. Thus, the studies included in this dissertation utilized both functional magnetic resonance imaging (fMRI) and behavioral testing to examine when and how the dopaminergic system supports the modulation of memory by expectation. The work aimed to characterize the activation of dopaminergic circuitry in response to cues that generate expectancy, during periods of anticipation, and in response to outcomes that resolve expectancy. The studies also examined how each of these event types influenced episodic memory formation. The present findings demonstrated that novelty and expectancy violation both drive dopaminergic circuitry capable of contributing to memory formation. Consistent with elevated dopaminergic midbrain and hippocampus activation for each, expected versus expectancy violating novelty did not differentially affect memory success. We also showed that high curiosity expectancy states drive memory formation. This was supported by activation in dopaminergic circuitry that was greater for subsequently remembered information only in the high curiosity state. Finally, we showed that cues that generate high expected reward value versus high reward uncertainty differentially modulate memory formation during reward anticipation. This behavioral result was consistent with distinct temporal profiles of dopaminergic action having differential downstream effects on episodic memory formation. Integrating the present studies with previous research suggests that dopaminergic circuitry signals events that are unpredicted, whether cuing or resolving expectations. It also suggests that contextual differences change the contribution of the dopaminergic system during anticipation, depending on the nature of the expectation. And finally, this work is consistent with a model in which dopamine elevation in response to expectancy events positively modulates episodic memory formation.
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Members of the general population have high expectations of people who are asked to corroborate an alibi for the suspect of a crime. The general belief is that it is easy to provide an alibi if a person is innocent, and therefore guilt should be assumed when an alibi cannot be provided. The possibility that having to generate an alibi oneself could influence expectations was examined. Additionally, potential changes in opinion after being provided with positive or negative feedback were explored. Results showed a significant difference in expectations based on whether participants were correct or incorrect in identifying the suspect, that is, whether participants were able to provide an alibi. Those who were incorrect had lower expectations of themselves and of others than those who were correct. Making jurors aware of the difficulty in providing an alibi may lead to fairer treatment of suspects who have difficulty providing one.
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Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.
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In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.
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Human land use tends to decrease the diversity of native plant species and facilitate the invasion and establishment of exotic ones. Such changes in land use and plant community composition usually have negative impacts on the assemblages of native herbivorous insects. Highly specialized herbivores are expected to be especially sensitive to land use intensification and the presence of exotic plant species because they are neither capable of consuming alternative plant species of the native flora nor exotic plant species. Therefore, higher levels of land use intensity might reduce the proportion of highly specialized herbivores, which ultimately would lead to changes in the specialization of interactions in plant-herbivore networks. This study investigates the community-wide effects of land use intensity on the degree of specialization of 72 plant-herbivore networks, including effects mediated by the increase in the proportion of exotic plant species. Contrary to our expectation, the net effect of land use intensity on network specialization was positive. However, this positive effect of land use intensity was partially canceled by an opposite effect of the proportion of exotic plant species on network specialization. When we analyzed networks composed exclusively of endophagous herbivores separately from those composed exclusively of exophagous herbivores, we found that only endophages showed a consistent change in network specialization at higher land use levels. Altogether, these results indicate that land use intensity is an important ecological driver of network specialization, by way of reducing the local host range of herbivore guilds with highly specialized feeding habits. However, because the effect of land use intensity is offset by an opposite effect owing to the proportion of exotic host species, the net effect of land use in a given herbivore assemblage will likely depend on the extent of the replacement of native host species with exotic ones.
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A combination of the variational principle, expectation value and Quantum Monte Carlo method is used to solve the Schrödinger equation for some simple systems. The results are accurate and the simplicity of this version of the Variational Quantum Monte Carlo method provides a powerful tool to teach alternative procedures and fundamental concepts in quantum chemistry courses. Some numerical procedures are described in order to control accuracy and computational efficiency. The method was applied to the ground state energies and a first attempt to obtain excited states is described.
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The efficiency of swine production performance depends on the herd administration, such as good nutrition, sanitary control, facilities and appropriate environmental conditions. The concept of this production model is directly related with the reduction of selective losses and the process control. Each production segment is controlled to reach the optimization in the system totality, it is necessary to apply animals handling concepts, environmental control implementation, diseases control, nutrition control, information concerning in guaranteeing the animal welfare and individual identification. The present work presents as objective the development of the mathematical model to evaluate interactions among the internal atmosphere of the installation and the thermal animals preference, in the expectation of detecting a relationship among the frequency access to the drinking fountain and the atmosphere conditions - temperature, black globe temperature and relative humidity, using as tool the electronic identification. The results obtained by the mathematical model, allowed to conclude accurately the evaluation of the swine thermal preference correlating with the climatic variables in the pregnancy stage.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física