Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Fine root isotropy in Eucalyptus grandis plantations. Towards the prediction of root length densities from root counts on trench walls

The objectives of the study were to assess changes in fine root anisotropy and specific root lengths throughout the development of Eucalyptus grandis ( W. Hill ex Maiden) plantations and to establish a predictive model of root length density (RLD) from root intercept counts on trench walls. Fine root densities (<1 mm in diameter) were studied in 6-, 12-, 22-, 28-, 54-, 68- and 72-month-old E. grandis plantations established on deep Ferralsols in southern Brazil. Fine root intercepts were counted on 3 faces of 90-198 soil cubes (1 dm(3) in volume) in each stand and fine root lengths (L) were measured inside 576 soil cubes, sampled between the depths of 10 cm and 290 cm. The number of fine root intercepts was counted on one vertical face perpendicular to the planting row (N(t)), one vertical face parallel to the planting row (N(l)) and one horizontal face (N(h)), for each soil cube sampled. An overall isotropy of fine roots was shown by paired Student's t-tests between the numbers of fine roots intersecting each face of soil cubes at most stand ages and soil depths. Specific root lengths decreased with stand age in the upper soil layers and tended to increase in deep soil layers at the end of the rotation. A linear regression established between N(t) and L for all the soil cubes sampled accounted for 36% of the variability of L. Such a regression computed for mean Nt and L values at each sampling depth and stand age explained only 55% of the variability, as a result of large differences in the relationship between L and Nt depending on stand productivity. The equation RLD=1.89*LAI*N(t), where LAI was the stand leaf area index (m(2) m(-2)) and Nt was expressed as the number of root intercepts per cm(2), made it possible to predict accurately (R(2)=0.84) and without bias the mean RLDs (cm cm(-3)) per depth in each stand, for the whole data set of 576 soil cubes sampled between 2 years of age and the end of the rotation.

Desidratação de polpas de frutas pelo método foam-mat

This study aimed to investigate the foam mat drying process of pineapple and mango pulp, as well as to evaluate the final product quality. Initially, the selection of fruit and additives was conducted based on density and stability determinations of mango, seriguela, umbu and pineapple foams. After selecting pineapple and mango for further studies, the fruit pulps and fruit foams were characterized in regard to their physicochemical composition. The temperature (60oC or 70oC) and the foam thickness (4 and 11 mm) were evaluated in accordance to the obtained drying curves and after model adjustment. Mango and pineapple powders obtained at the best process conditions were characterized in regard to their physicochemical composition, solubility, reconstitution time. Yoghurts were prepared with the addition of pineapple and mango powders and they were evaluated for their sensory acceptance. Results show that the best drying rates were achieved by using 70o C and layers 4mm thick for both fruits. The Page model successfully fitted the drying experimental data and it can be used as a predictive model. Pineapple and mango powders showed acid pH, high soluble solids content, low water activity (approx. 0.25), lipids between 1.46% and 2.03%, protein around 2.00%, and ascorbic acid content of 17,73 mg/100g and 14.32 mg/100g, for mango and pineapple, respectively. It was observed higher ascorbic acid retention for pineapple and mango powders processed at 70o C, which would be explained by the lower drying time applied. The fruit powders exhibited high solubility and fast reconstitution in water. The sensory acceptance indexes for yoghurts with the addition of both fruit powders were higher than 70%, which reflect the satisfactory product acceptance

Estudo do equilíbrio líquido-vapor do sistema água+etanol+líquido iônico visando a separação do álcool anidro

Anhydrous ethanol is used in chemical, pharmaceutical and fuel industries. However, current processes for obtaining it involve high cost, high energy demand and use of toxic and pollutant solvents. This problem occurs due to the formation of an azeotropic mixture of ethanol + water, which does not allow the complete separation by conventional methods such as simple distillation. As an alternative to currently used processes, this study proposes the use of ionic liquids as solvents in extractive distillation. These are organic salts which are liquids at low temperatures (under 373,15 K). They exhibit characteristics such as low volatility (almost zero/ low vapor ), thermal stability and low corrosiveness, which make them interesting for applications such as catalysts and as entrainers. In this work, experimental data for the vapor pressure of pure ethanol and water in the pressure range of 20 to 101 kPa were obtained as well as for vapor-liquid equilibrium (VLE) of the system ethanol + water at atmospheric pressure; and equilibrium data of ethanol + water + 2-HDEAA (2- hydroxydiethanolamine acetate) at strategic points in the diagram. The device used for these experiments was the Fischer ebulliometer, together with density measurements to determine phase compositions. The experimental data were consistent with literature data and presented thermodynamic consistency, thus the methodology was properly validated. The results were favorable, with the increase of ethanol concentration in the vapor phase, but the increase was not shown to be pronounced. The predictive model COSMO-SAC (COnductor-like Screening MOdels Segment Activity Coefficient) proposed by Lin & Sandler (2002) was studied for calculations to predict vapor-liquid equilibrium of systems ethanol + water + ionic liquids at atmospheric pressure. This is an alternative for predicting phase equilibrium, especially for substances of recent interest, such as ionic liquids. This is so because no experimental data nor any parameters of functional groups (as in the UNIFAC method) are needed

Síndrome da fragilidade e fatores associados em idosos comunitários do município de Santa Cruz RN

The frailty in the elderly is characterized by decreased physiological reserves, and is associated with increased risk of disability and high vulnerability to morbidity and mortality. This study is part of a multicentric project on Frailty in Elderly Brazilians (REDE FIBRA). Aims: to investigate characteristics, prevalence and associated factors related to frailty. Metodology: We interviewed 391 elderly patients aged 65 years, selected randomly. Data collection was performed using a multidimensional questionnaire containing information about socio-demographic and clinical variables. To characterize the frail elderly, was considered the phenotype proposed by Fried. Data were analyzed using descriptive statistics, bivariate analysis (χ ²) and binary logistic regression. Results: The prevalence of frailty was 17.1%. In the final model of multivariate analysis, was obtained as factors associated with frailty: advanced chronological age (p <0.001), have comorbidity (p <0.035), show dependence on performing basic activities of daily living (p <0.010) and instrumental (p <0.003) and have poor perception of health status (p <0030). Conclusions: The factors associated with frailty suggest a predictive model helping to understand the syndrome, guiding actions that minimize adverse effects on the aging process

The Incremental Shuttle Walk Test in Older Brazilian Adults

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

Caracterização da cobertura vegetal na equação universal de perda de solos (fator C) por meio de geotecnologias

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Caracterização da erosão hídrica laminar do solo em bacia hidrográfica com base na malha fundiária, por meio de sensoriamento remoto, geoprocessamento e modelagem

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

Estimando o desfecho no recém-nascido grave através da Lógica Fuzzy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimativa espaço-temporal da superfície potenciométrica do sistema aqüífero guarani na cidade de Ribeirão Preto (SP), Brasil

Pós-graduação em Geociências e Meio Ambiente - IGCE

Análise diagnóstica de indicadores de erosão do solo na bacia hidrográfica do Córrego João Dias, Aquidauana/MS

Pós-graduação em Geografia - IGCE

Contribuição dos impactos na saúde bucal e de variáveis sociodemográficas e clínicas na qualidade de vida relacionada à saúde

Pós-graduação em Reabilitação Oral - FOAR

Avaliação da erosão hídrica, transporte de sedimentos e qualidade da água na bacia do córrego Monjolo Grande

Understanding the linkages between the natural elements is essential for being promoted the land use, occupation and sustainable management of environmental systems. Universal Soil Loss Equation (USLE), as a predictive model of erosion, is important to allowing the prevention of possible environmental impacts which may drastically interfere in natural or anthropic environments, as well as prevent potential financial wastes and even contribute to greater efficiency of agricultural production. This research will be working some USLE parameters, emphasizing topographic factor from Ribeirão Monjolo Grande watershed. Among the factors considered by the USLE, the Topographic Factor interferes directly in the erosive dynamic of a watershed because it involves variables related to hydrological processes that occur on it. In this research, were discussed different methods for obtaining the Topographic Factor (BERTONI e LOMBARDI NETO, 1985; MOORE e BURCH, 1986; DESMET E GOVERS, 1996) in GIS environment. After comparison between the methods, was indicated that best represents the conditions of geometry strand of the study area. Finally, other factors (R, K, C, P) considered by the USLE were obtained. The attainment of these parameters were guided by the use of geotechnologies, especially in Geographic Information Systems (GIS), with the assistance of secondary data and periodic field visits. The results obtained contributed to the understanding of hydrosedimentological dynamic in this area and serve as a viable strategy for studies of soil loss, aiming at developing consistent material for future researches about environmental planning and land management

Estimativa da erosão na microbacia do Córrego do Gambá no município de Monte Alto, SP

Pós-graduação em Agronomia (Ciência do Solo) - FCAV