Path integral approach to the full Dicke model

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

Distribution line models analysis for loss calculation within three-phase three-wire power flow algorithms

Three-phase three-wire power flow algorithms, as any tool for power systems analysis, require reliable impedances and models in order to obtain accurate results. Kron's reduction procedure, which embeds neutral wire influence into phase wires, has shown good results when three-phase three-wire power flow algorithms based on current summation method were used. However, Kron's reduction can harm reliabilities of some algorithms whose iterative processes need loss calculation (power summation method). In this work, three three-phase three-wire power flow algorithms based on power summation method, will be compared with a three-phase four-wire approach based on backward-forward technique and current summation. Two four-wire unbalanced medium-voltage distribution networks will be analyzed and results will be presented and discussed. © 2004 IEEE.

Planning accelerated life tests under Exponentiated-Weibull-Arrhenius model

Purpose - The purpose of this paper is to present designs for an accelerated life test (ALT). Design/methodology/approach - Bayesian methods and simulation Monte Carlo Markov Chain (MCMC) methods were used. Findings - In the paper a Bayesian method based on MCMC for ALT under EW distribution (for life time) and Arrhenius models (relating the stress variable and parameters) was proposed. The paper can conclude that it is a reasonable alternative to the classical statistical methods since the implementation of the proposed method is simple, not requiring advanced computational understanding and inferences on the parameters can be made easily. By the predictive density of a future observation, a procedure was developed to plan ALT and also to verify if the conformance fraction of the manufactured process reaches some desired level of quality. This procedure is useful for statistical process control in many industrial applications. Research limitations/implications - The results may be applied in a semiconductor manufacturer. Originality/value - The Exponentiated-Weibull-Arrhenius model has never before been used to plan an ALT. © Emerald Group Publishing Limited.

On the determination of epsilon during discriminative GMM training

Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. In this letter, we derive an equation to adaptively determine ε, by showing that the second-order Newton-Raphson iterative method to find roots of equations is equivalent to the gradient descent algorithm. © 2010 IEEE.

A useful empirical bayesian method to analyse industrial data from saturated factorial designs

The use of saturated two-level designs is very popular, especially in industrial applications where the cost of experiments is too high. Standard classical approaches are not appropriate to analyze data from saturated designs, since we could only get the estimates of the main factor effects and we would not have degrees of freedom to estimate the variance of the error. In this paper, we propose the use of empirical Bayesian procedures to get inferences for data obtained from saturated designs. The proposed methodology is illustrated assuming a simulated data set. © 2013 Growing Science Ltd. All rights reserved.

Estimativas de componentes de (CO) variância de características de crescimentos na raça Nelore, utilizando inferência bayesiana

Pós-graduação em Genética e Melhoramento Animal - FCAV

Utilizações de informações genômicas para o melhoramento genético de características de crescimento em bovinos da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

A Comparison of Induction Motor Starting Methods Being Powered by a Diesel-Generator Set

Starting induction motors on isolated or weak systems is a highly dynamic process that can cause motor and load damage as well as electrical network fluctuations. Mechanical damage is associated with the high starting current drawn by a ramping induction motor. In order to compensate the load increase, the voltage of the electrical system decreases. Different starting methods can be applied to the electrical system to reduce these and other starting method issues. The purpose of this thesis is to build accurate and usable simulation models that can aid the designer in making the choice of an appropriate motor starting method. The specific case addressed is the situation where a diesel-generator set is used as the electrical supplied source to the induction motor. The most commonly used starting methods equivalent models are simulated and compared to each other. The main contributions of this thesis is that motor dynamic impedance is continuously calculated and fed back to the generator model to simulate the coupling of the electrical system. The comparative analysis given by the simulations has shown reasonably similar characteristics to other comparative studies. The diesel-generator and induction motor simulations have shown good results, and can adequately demonstrate the dynamics for testing and comparing the starting methods. Further work is suggested to refine the equivalent impedance presented in this thesis.

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. (C) 2012 Elsevier B.V. All rights reserved.

A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

Income inequality and elderly self-rated health in Sao Paulo, Brazil

Purpose: To test the association between income inequality and elderly self-rated health and to propose a pathway to explain the relationship. Methods: We analyzed a sample of 2143 older individuals (60 years of age and over) from 49 distritos of the Municipality of Sao Paulo, Brazil. Bayesian multilevel logistic models were performed with poor self-rated health as the outcome variable. Results: Income inequality (measured by the Gini coefficient) was found to be associated with poor self-rated health after controlling for age, sex, income and education (odds ratio, 1.19; 95% credible interval, 1.01-1.38). When the practice of physical exercise and homicide rate were added to the model, the Gini coefficient lost its statistical significance (P>.05). We fitted a structural equation model in which income inequality affects elderly health by a pathway mediated by violence and practice of physical exercise. Conclusions: The health of older individuals may be highly susceptible to the socioeconomic environment of residence, specifically to the local distribution of income. We propose that this association may be mediated by fear of violence and lack of physical activity. (C) 2012 Elsevier Inc. All rights reserved.

Influence of palatoplasty on occlusion of patients with isolated cleft palate

OBJECTIVE: This study compared the dental arch morphology of adult patients with isolated cleft palate in order to verify the influence of palatoplasty on occlusion. METHODS: Cast models of 77 patients, 30 males and 47 females, with an average age of 21 years and no syndromes were taken. They were in the permanent dentition and had not undergone orthodontic treatment. The sample was divided into non-operated and operated patients, the latter having been submitted to palatoplasty at a mean age of 2.2 years. RESULTS: Almost 80% of the sample exhibited sagittal discrepancies in the inter-arch relationship, with a Class II malocclusion prevailing (59.74%) followed by Class III (20,78%), regardless of palatoplasty. Transverse analysis showed a 23% incidence of posterior crossbite also not influenced by palatoplasty. Intra-arch relationship indicated that constriction and crowding on the upper arch were more frequent in the operated group (p=0.0238 and p=0.0002, respectively), showing an influence of palatoplasty on its morphology. The predominant morphological characteristics in patients with isolated cleft palate were a Class II malocclusion, upper dental arch constriction and upper and lower anterior crowding. CONCLUSION: The influence of palatoplasty was restricted to constriction and crowding of the upper dental arch, with no interference from the extension of the cleft, except for the upper crowding, which occurred more in patients with complete cleft palates.

Customer Evolution in Sales Channel Migration

This research has been triggered by an emergent trend in customer behavior: customers have rapidly expanded their channel experiences and preferences beyond traditional channels (such as stores) and they expect the company with which they do business to have a presence on all these channels. This evidence has produced an increasing interest in multichannel customer behavior and it has motivated several researchers to study the customers’ channel choices dynamics in multichannel environment. We study how the consumer decision process for channel choice and response to marketing communications evolves for a cohort of new customers. We assume a newly acquired customer’s decisions are described by a “trial” model, but the customer’s choice process evolves to a “post-trial” model as the customer learns his or her preferences and becomes familiar with the firm’s marketing efforts. The trial and post-trial decision processes are each described by different multinomial logit choice models, and the evolution from the trial to post-trial model is determined by a customer-level geometric distribution that captures the time it takes for the customer to make the transition. We utilize data for a major retailer who sells in three channels – retail store, the Internet, and via catalog. The model is estimated using Bayesian methods that allow for cross-customer heterogeneity. This allows us to have distinct parameters estimates for a trial and an after trial stages and to estimate the quickness of this transit at the individual level. The results show for example that the customer decision process indeed does evolve over time. Customers differ in the duration of the trial period and marketing has a different impact on channel choice in the trial and post-trial stages. Furthermore, we show that some people switch channel decision processes while others don’t and we found that several factors have an impact on the probability to switch decision process. Insights from this study can help managers tailor their marketing communication strategy as customers gain channel choice experience. Managers may also have insights on the timing of the direct marketing communications. They can predict the duration of the trial phase at individual level detecting the customers with a quick, long or even absent trial phase. They can even predict if the customer will change or not his decision process over time, and they can influence the switching process using specific marketing tools

Mortality from road traffic accidents in Switzerland: longitudinal and spatial analyses

Road traffic accidents (RTA) are an important cause of premature death. We examined socio-demographic and geographical determinants of RTA mortality in Switzerland by linking 2000 census data to RTA mortality records 2000-2005 (ICD-10 codes V00-V99). Data from 5.5 million residents aged 18-94 years, 1744 study areas, and 1620 RTA deaths were analyzed, including 978 deaths (60.4%) in motor vehicle occupants, 254 (15.7%) in motorcyclists, 107 (6.6%) in cyclists, and 259 (16.0%) in pedestrians. Weibull survival models and Bayesian methods were used to calculate hazard ratios (HR), and standardized mortality ratios (SMR) across study areas. Adjusted HR comparing women with men ranged from 0.04 (95% CI 0.02-0.07) in motorcyclists to 0.43 (95% CI 0.32-0.56) in pedestrians. There was a u-shaped relationship with age in motor vehicle occupants and motorcyclists. In cyclists and pedestrians, mortality increased after age 55 years. Mortality was higher in individuals with primary education (HR 1.53; 95% CI 1.29-1.81), and higher in single (HR 1.24; 95% CI 1.05-1.46), widowed (HR 1.31; 95% CI 1.05-1.65) and divorced individuals (HR 1.62; 95% CI 1.33-1.97), compared to persons with tertiary education or married persons. The association with education was particularly strong for pedestrians (HR 1.87; 95% CI 1.20-2.91). RTA mortality increased with decreasing population density of study areas for motor vehicle occupants (test for trend p<0.0001) and motorcyclists (p=0.0021) but not for cyclists (p=0.39) or pedestrians (p=0.29). SMR standardized for socio-demographic and geographical variables ranged from 82 to 190. Prevention efforts should aim to reduce inequities across socio-demographic and educational groups, and across geographical areas, with interventions targeted at high-risk groups and areas, and different traffic users, including pedestrians.

Additive Hazards Models with Latent Treatment Effectiveness Lag Time

In many clinical trials to evaluate treatment efficacy, it is believed that there may exist latent treatment effectiveness lag times after which medical procedure or chemical compound would be in full effect. In this article, semiparametric regression models are proposed and studied to estimate the treatment effect accounting for such latent lag times. The new models take advantage of the invariance property of the additive hazards model in marginalizing over random effects, so parameters in the models are easy to be estimated and interpreted, while the flexibility without specifying baseline hazard function is kept. Monte Carlo simulation studies demonstrate the appropriateness of the proposed semiparametric estimation procedure. Data collected in the actual randomized clinical trial, which evaluates the effectiveness of biodegradable carmustine polymers for treatment of recurrent brain tumors, are analyzed.