A network of integrate and fire neurons for visual selection

Biological systems have facility to capture salient object(s) in a given scene, but it is still a difficult task to be accomplished by artificial vision systems. In this paper a visual selection mechanism based on the integrate and fire neural network is proposed. The model not only can discriminate objects in a given visual scene, but also can deliver focus of attention to the salient object. Moreover, it processes a combination of relevant features of an input scene, such as intensity, color, orientation, and the contrast of them. In comparison to other visual selection approaches, this model presents several interesting features. It is able to capture attention of objects in complex forms, including those linearly nonseparable. Moreover, computer simulations show that the model produces results similar to those observed in natural vision systems.

Three Bartlett-type corrections for score statistics in symmetric nonlinear regression models

We present simple matrix formulae for corrected score statistics in symmetric nonlinear regression models. The corrected score statistics follow more closely a chi (2) distribution than the classical score statistic. Our simulation results indicate that the corrected score tests display smaller size distortions than the original score test. We also compare the sizes and the powers of the corrected score tests with bootstrap-based score tests.

Developing and Facilitating a Successful Hybrid Statistics Course

This presentation will outline an effective model for a Hybrid Statistics course. The course continues to be very successful, incorporating on-line instruction, testing, blogs, and above all, a data analysis project driven trajectory motivating students to engage more aggressively in the class and rise up to the challenge of writing an original research paper. Obstacles, benefits and successes of this endeavor will be addressed.

Fire Incidences, Water Bodies, and Population in Maine

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FIRE HAZARD IN COCONINO COUNTY, ARIZONA

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Fire Hazard in Coconino County, Arizona

Fire is a major management issue in the southwestern United States. Three spatial models of fire risk for Coconino County, Northern Arizona. These models were generated using thematic data layers depicting vegetation, elevation, wind speed and direction, and precipitation for January (winter), June (summer), and July (start of monsoon season). ArcGIS 9.0 was used to weight attributes in raster layers to reflect their influence on fire risk and to interpolate raster data layers from point data. Final models were generated using the raster calculator in the Spatial Analyst extension of ArcGIS 9.0. Ultimately, the unique combinations of variables resulted in three different models illustrating the change in fire risk during the year.

An analysis of quit and dismissal determinants between 1988 and 1999 using the bivariate probit model

Excessive labor turnover may be considered, to a great extent, an undesirable feature of a given economy. This follows from considerations such as underinvestment in human capital by firms. Understanding the determinants and the evolution of turnover in a particular labor market is therefore of paramount importance, including policy considerations. The present paper proposes an econometric analysis of turnover in the Brazilian labor market, based on a partial observability bivariate probit model. This model considers the interdependence of decisions taken by workers and firms, helping to elucidate the causes that lead each of them to end an employment relationship. The Employment and Unemployment Survey (PED) conducted by the State System of Data Analysis (SEADE) and by the Inter-Union Department of Statistics and Socioeconomic Studies (DIEESE) provides data at the individual worker level, allowing for the estimation of the joint probabilities of decisions to quit or stay on the job on the worker’s side, and to maintain or fire the employee on the firm’s side, during a given time period. The estimated parameters relate these estimated probabilities to the characteristics of workers, job contracts, and to the potential macroeconomic determinants in different time periods. The results confirm the theoretical prediction that the probability of termination of an employment relationship tends to be smaller as the worker acquires specific skills. The results also show that the establishment of a formal employment relationship reduces the probability of a quit decision by the worker, and also the firm’s firing decision in non-industrial sectors. With regard to the evolution of quit probability over time, the results show that an increase in the unemployment rate inhibits quitting, although this tends to wane as the unemployment rate rises.

Efeitos organizacionais da implantação de metas e remuneração variável por desempenho: o caso da segurança pública em Minas Gerais

Quais os efeitos práticos que a cobrança de metas provoca nas instituições e nos servidores públicos? E quando se vincula premiações financeiras a elas, qual o resultado? O Brasil vive uma onda recente de implantação de modelos de remuneração variável por desempenho no setor público. Minas Gerais universalizou o sistema em 2008, implantando o Acordo de Resultados e o Prêmio por Produtividade, já tendo gasto 1,3 bilhão de reais com o programa. Mas o otimismo dos gestores não encontra fundamento na teoria. A literatura mostra que sistemas de remuneração variável no setor público fracassam ou têm sucesso muito limitado (OCDE, 2005; Perry, Engbergs e Jun, 2009; Bowman, 2010; Weibel, Rost e Osterloh 2010). Conflitos, dificuldade de mensuração do desempenho, fraude e incapacidade de motivar servidores públicos têm direcionado experiências de incentivo ao fracasso. Alguns poucos estudos mostram que, sob certas condições, a remuneração variável por desempenho pode gerar resultados positivos (Marsden, 2010). Seria o sistema mineiro capaz de superar o pessimismo dos especialistas e alcançar resultados positivos? Quais mecanismos de fato operam quando se implementa metas e remuneração variável em instituições públicas? Este trabalho busca responder estas questões a partir do estudo de caso de três organizações da segurança pública em Minas Gerais: Polícia Militar, Polícia Civil e Corpo de Bombeiros Militar. Foram feitas 46 entrevistas com policiais, bombeiros e com a cúpula das instituições, analisados dados estatísticos – que avaliam a evolução do desempenho, observação participante e monitoramento da percepção da mídia sobre tais efeitos. O resultado mostra que metas e incentivos financeiros geraram profundas mudanças nas instituições pesquisadas. Na Polícia Civil houve crescimento da produtividade, aumento do controle e melhoria de processos internos. Entretanto, o foco na produção quantitativa de inquéritos gerou incentivos para a redução de sua qualidade. Na Polícia Militar observou-se impacto menor, uma vez que esta já havia auferido no passado recente ganhos que o uso de indicadores e metas poderia proporcionar. Ainda assim, observou-se aumento da cobrança interna de resultados. Esse fato foi um dos fatores que contribuiu para um efeito negativo importante: a reclassificação de crimes. Uma estrutura de incentivos e a ausência de obstáculos levaram alguns policiais a reclassificar crimes que tinham natureza próxima para melhorar as estatísticas de suas unidades. No Corpo de Bombeiros o impacto foi altamente positivo, levando a instituição a conceber novas estratégias, gerando ganhos importantes de produtividade e melhoria de resultados para o cidadão. O resultado mostra que metas e incentivos financeiros são muito poderosos e podem gerar resultados positivos ou negativos, dependendo da forma como são implementados. As evidências contradizem, em parte, o pessimismo dos acadêmicos e descortinam o funcionamento dos mecanismos que fazem metas e remuneração variável interferirem no resultado de organizações públicas.

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

Log smoldering after an Amazonian deforestation fire

The characteristics of log smoldering after an Amazonian deforestation fire are described. The experiment was carried out in 2001 at the Caiabi farm, near the city of Alta Floresta, state of Mato Grosso, Brazil, as part of a set of tests that have been performed in the same area since 1997. A 200 x 200m(2) test area was slashed in the beginning of June and burned on 20 August. The area contained 507 logs with diameter at breast height (DBH) higher than 10 cm, per hectare. In the day following the main burn 59 logs were found to remain smoldering, a number that corresponds to 2.9% of the total in the area. We chose 11 of the 59 logs to have their smoldering process monitored. Their diameter, moisture content and CHN dry biomass composition after the plot burn and before smoldering were determined. Other parameters such as temperature distribution while smoldering, porosity, density and mass volatilized during thermogravimetric test were also determined. Average smoldering speeds were in the range from 0.8 to 1.5 cm h(-1) for logs that smoldered without transition to the flaming regime. The average speed increased to 2.1 cm h(-1) for those logs that oscillated between smoldering and flaming. The speeds were lower overnight as compared to values determined during daytime for the same log. Higher log moisture contents were found to produce decreased speeds. Micro-porous biomass was not observed in the set of the 11 selected logs. Smoldering was observed to occur at substantial intensity in crossing of logs, with no longitudinal propagation. (C) 2003 Elsevier Ltd. All rights reserved.

Biomass consumption and CO2, CO and main hydrocarbon gas emissions in an Amazonian forest clearing fire

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