Adsorção de cobre e cromo utilizando fibra de sisal visando o tratamento da água produzida pela indústria petrolífera

Currently, the oil industry is the biggest cause of environmental pollution. The objective was to reduce the concentration of copper and chromium in the water produced by the oil industry. It was used as adsorbent natural sisal fiber Agave sp treated with nitric acid and sodium hydroxide. All vegetable fibers have physical and morphological properties that enablies the adsorption of pollutants. The basic composition of sisal is cellulose, hemicellulose and lignin. The features are typically found in the characterization of vegetable fibers, except the surface area that was practically zero. In the first stage of adsorption, it was evaluated the effect of temperature and time skeeking to optimize the execution of the factorial design. The results showed that the most feasible fiber was the one treated with acid in five hours (30°C). The second phase was a factorial design, using acid and five hours, this time was it determined in the first phase. The tests were conducted following the experimental design and the results were analyzed by statistical methods in order to optimize the main parameters that influence the process: pH, concentration (mol / L) and fiber mass/ metal solution volume. The volume / mass ratio factor showed significant interference in the adsorption process of chromium and copper. The results obtained after optimization showed that the highest percentages of extraction (98%) were obtained on the following operating conditions: pH: 5-6, Concentration: 100 ppm and mass/ volume: 1 gram of fiber/50mL solution. The results showed that the adsorption process was efficient to remove chromium and copper using sisal fibers, however, requiring further studies to optimize the process.

Análise de desempenho de vendas em telecomunicações utilizando técnicas de mineração de dados

Nowadays, telecommunications is one of the most dynamic and strategic areas in the world. Organizations are always seeking to find new management practices within an ever increasing competitive environment where resources are getting scarce. In this scenario, data obtained from business and corporate processes have even greater importance, although this data is not yet adequately explored. Knowledge Discovery in Databases (KDD) appears then, as an option to allow the study of complex problems in different areas of management. This work proposes both a systematization of KDD activities using concepts from different methodologies, such as CRISP-DM, SEMMA and FAYYAD approaches and a study concerning the viability of multivariate regression analysis models to explain corporative telecommunications sales using performance indicators. Thus, statistical methods were outlined to analyze the effects of such indicators on the behavior of business productivity. According to business and standard statistical analysis, equations were defined and fit to their respective determination coefficients. Tests of hypotheses were also conducted on parameters with the purpose of validating the regression models. The results show that there is a relationship between these development indicators and the amount of sales

Importância do gerenciamento com base em dados estudo de caso : farmácias de manipulação do Estado do Rio Grande do Norte

Last century Six Sigma Strategy has been the focus of study for many scientists, between the discoveries we have the importance of data process for the free of error product manufactory. So, this work focuses on data quality importance in an enterprise. For this, a descriptive-exploratory study of seventeen pharmacies of manipulations from Rio Grande do Norte was undertaken with the objective to be able to create a base structure model to classify enterprises according to their data bases. Therefore, statistical methods such as cluster and discriminant analyses were used applied to a questionnaire built for this specific study. Data collection identified four group showing strong and weak characteristics for each group and that are differentiated from each other

A influência da responsabilidade social empresarial na satisfação e fidelidade do cliente : um estudo com compradores de automóveis

This study presents an investigation of the influence of Corporate Social Responsibility (CSR) in customer s satisfaction and loyalty through a study with car s buyers, besides that, it aims to contribute to conceptual models of satisfaction and loyalty analysis by applying the model of Johnson et al. (2001), adapted for the introduction of variables of CSR and conscious consumption, in a car dealership in Natal / RN. The methodology has a descriptive quantitative approach and for the analysis results were applied statistical methods of simple and multiple linear regression analysis, descriptive analysis and exploratory analysis. The field research provided 90 valid forms. The results show that CSR affects the image of the company studied and is also one of the elements of the compound of satisfaction and loyalty. This study concludes that CSR should be considered in the strategic and marketing actions of firms

Sistema inteligente para detecção de vazamentos em dutos de petróleo usando transformada Wavelet e redes neurais

This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaks

Otimização do processo de recuperação do cromo de efluentes de curtumes por microemulsões no extrator Morris

The tanning industries are those which transform animal hide or skin into leather. Due to the complexity of the transformation process, greater quantities of chemicals are being used which results in the generation of effluents with residual solids. The chromium in the residual waters generated by tanning tend to be a serious problem to the environment, therefore the recovery of this metal could result in the reduction of manufacturing costs. This metal is usually found in a trivalent form which can be converted into a hexavalent compound under acidic conditions and in the presence of organic matter. The present study was carried out with the objective to recover chromium through an extraction/re-extraction process using micro emulsions. Micro emulsions are transparent and thermodynamically stable system composed of two immiscible liquids, one forming the continuous phase and the other dispersed into micro bubbles, established by an interfacial membrane formed by surface active and co-surface active molecules. The process of recovering the chromium was carried out in two stages. The first, an extraction process, where the chromium was extracted in the micro emulsion phase and the aqueous phase in excess was separated. In the second stage, a concentrated acid was added to the micro emulsion phase rich in chromium in order to obtain a Winsor II system, where the water that formed in the micro emulsion phase separates into a new micro emulsion phase with a higher concentration of chromium, due to the lowering of the hydrophiles as well as the ionisation of the system. During the experimental procedure, a study was initiated with a synthetic solution of chromium sulphate passing onto the effluent. A Morris extractor was used in the extraction process. Tests were carried out according to the plan and the results were analysed by statistical methods in order to optimise the main parameters that influence the process: the total rate of flow (Q), stirring speed (w) and solvent rate (r). The results, after optimization, demonstrated that the best percentuals in relation to the chromium extraction (99 %) were obtained in the following operational conditions: Q= 2,0 l/h, w= 425 rpm and r= 0,375. The re-extraction was carried out at room temperature (28 °C), 40 °C and 50°C using hydrochloric acid (8 and 10 M) and sulphuric acid (8 M) as re-extracting agents. The results obtained demonstrate that the process was efficient enough in relation to the chromium extraction, reaching to re-extraction percentage higher than 95 %.

Efeito de diferentes divisões territoriais na flutuação aleatória de indicadores socioeconômicos relacionados à determinação social da saúde

This research aimed to analyse the effect of different territorial divisions in the random fluctuation of socio-economic indicators related to social determinants of health. This is an ecological study resulting from a combination of statistical methods including individuated and aggregate data analysis, using five databases derived from the database of the Brazilian demographic census 2010: overall results of the sample by weighting area. These data were grouped into the following levels: households; weighting areas; cities; Immediate Urban Associated Regions and Intermediate Urban Associated Regions. A theoretical model related to social determinants of health was used, with the dependent variable Household with death and as independent variables: Black race; Income; Childcare and school no attendance; Illiteracy; and Low schooling. The data was analysed in a model related to social determinants of health, using Poisson regression in individual basis, multilevel Poisson regression and multiple linear regression in light of the theoretical framework of the area. It was identified a greater proportion of households with deaths among those with at least one black resident, lower-income, illiterate, who do not attend or attended school or day-care and less educated. The analysis of the adjusted model showed that most adjusted prevalence ratio was related to Income, where there is a risk value of 1.33 for households with at least one resident with lower average personal income to R$ 655,00 (Brazilian current). The multilevel analysis demonstrated that there was a context effect when the variables were subjected to the effects of areas, insofar as the random effects were significant for all models and with different prevalence rates being higher in the areas with smaller dimensions - Weighting areas with coefficient of 0.035 and Cities with coefficient of 0.024. The ecological analyses have shown that the variable Income and Low schooling presented explanatory potential for the outcome on all models, having income greater power to determine the household deaths, especially in models related to Immediate Urban Associated Regions with a standardized coefficient of -0.616 and regions intermediate urban associated regions with a standardized coefficient of -0.618. It was concluded that there was a context effect on the random fluctuation of the socioeconomic indicators related to social determinants of health. This effect was explained by the characteristics of territorial divisions and individuals who live or work there. Context effects were better identified in the areas with smaller dimensions, which are more favourable to explain phenomena related to social determinants of health, especially in studies of societies marked by social inequalities. The composition effects were better identified in the Regions of Urban Articulation, shaped through mechanisms similar to the phenomenon under study.

Adsorção de cobre e cromo utilizando fibra de sisal visando o tratamento da água produzida pela indústria petrolífera

Currently, the oil industry is the biggest cause of environmental pollution. The objective was to reduce the concentration of copper and chromium in the water produced by the oil industry. It was used as adsorbent natural sisal fiber Agave sp treated with nitric acid and sodium hydroxide. All vegetable fibers have physical and morphological properties that enablies the adsorption of pollutants. The basic composition of sisal is cellulose, hemicellulose and lignin. The features are typically found in the characterization of vegetable fibers, except the surface area that was practically zero. In the first stage of adsorption, it was evaluated the effect of temperature and time skeeking to optimize the execution of the factorial design. The results showed that the most feasible fiber was the one treated with acid in five hours (30°C). The second phase was a factorial design, using acid and five hours, this time was it determined in the first phase. The tests were conducted following the experimental design and the results were analyzed by statistical methods in order to optimize the main parameters that influence the process: pH, concentration (mol / L) and fiber mass/ metal solution volume. The volume / mass ratio factor showed significant interference in the adsorption process of chromium and copper. The results obtained after optimization showed that the highest percentages of extraction (98%) were obtained on the following operating conditions: pH: 5-6, Concentration: 100 ppm and mass/ volume: 1 gram of fiber/50mL solution. The results showed that the adsorption process was efficient to remove chromium and copper using sisal fibers, however, requiring further studies to optimize the process.