Qualidade do serviço em organização do terceiro setor: um estudo na casa de apoio à criança com câncer

The research aimed identify how the quality of services provided by Casa de Apoio à Criança com Câncer Durval Paiva is perceived by its users, giving an opportunity of improve their performance in social services provision pointing out the failures experienced, the institution will have the user as a important partner in fails identification, serving as a subsidy to the actions of correction and improvement to such situations demands. With this work implementation will be observed contributions that will permeate to the fields of theory and practice, enabling progress and enrichment on the subject. The theoretical contribution is observed as this work execution will provide greater advance about the models developed for the third sector. The proposed work will raise awareness issues about the full potential of the social economy, with regard to the quality of services provided by organizations, allowing a better definition of priorities on their development. The study addressed three issues: identifying the people that receive support of the Casa Durval Paiva, identifying what is the level of satisfaction of families served and evaluate the services provided by Casa Durval Paiva that demand improvements in the perception of families assisted. Found a demand for services has been found that the institution has a multidisciplinary team with a high level of professionalism, and supervised with students of various educational institutions and many volunteers to complement the actions of individual professionals. Was measured a high satisfaction of users of the services provided by Casa Durval Paiva

Modelo de covariância bayesiana para seleção de protfólios de investimentos

The portfolio theory is a field of study devoted to investigate the decision-making by investors of resources. The purpose of this process is to reduce risk through diversification and thus guarantee a return. Nevertheless, the classical Mean-Variance has been criticized regarding its parameters and it is observed that the use of variance and covariance has sensitivity to the market and parameter estimation. In order to reduce the estimation errors, the Bayesian models have more flexibility in modeling, capable of insert quantitative and qualitative parameters about the behavior of the market as a way of reducing errors. Observing this, the present study aimed to formulate a new matrix model using Bayesian inference as a way to replace the covariance in the MV model, called MCB - Covariance Bayesian model. To evaluate the model, some hypotheses were analyzed using the method ex post facto and sensitivity analysis. The benchmarks used as reference were: (1) the classical Mean Variance, (2) the Bovespa index's market, and (3) in addition 94 investment funds. The returns earned during the period May 2002 to December 2009 demonstrated the superiority of MCB in relation to the classical model MV and the Bovespa Index, but taking a little more diversifiable risk that the MV. The robust analysis of the model, considering the time horizon, found returns near the Bovespa index, taking less risk than the market. Finally, in relation to the index of Mao, the model showed satisfactory, return and risk, especially in longer maturities. Some considerations were made, as well as suggestions for further work

Analise SWOT do gerenciamento de resíduos do coco verde em duas agroindústrias do estado do Rio Grande do Norte

In the current conjuncture, the environmental factor has been changing the position of companies that are practicing or minimally adopting environmental management. Such tool has been used by companies to face the problems caused by solid waste, in particular green coconut waste, which is constantly among the material discarded by society (companies/ consumer). It is a typical tropical fruit whose fresh water is very benefic for human health, and its popularization has caused a progressive increase of its consumption. Following this stream of thought, this present work came up with an analysis of strengths, weaknesses, threats, and opportunities SWOT analysis on green coconut solid waste management at two agribusiness companies in the state of Rio Grande do Norte (RN), Brazil, aiming to know the challenges and the potentials of this kind of waste. According to the approach of the problem, this work fits a descriptive, exploratory, and qualitative research. The data collection was obtained by a questionnaire and a structured interview, in order to evaluate the strategic posture of agribusiness companies through SWOT analysis, which is an English acronym for Strengths, Weaknesses, Opportunities and Threats. The SWOT analysis is an effective tool to analyze the internal and external environment of an organization. This tool contributes to locate the company at the environment in question and when well applied it enables the detection of mistakes, the strengthening of correct procedures, the avoidance of threats, and the bet on opportunities. The studied agribusiness industries have very similar profiles, such as a long business life span, and a strategy that extends the useful life of the fruit, by using its waste for the manufacturing of new subproducts. In both, the daily quantity of waste resulted of this process reaches approximately 20 thousand units of the fruit in high season, being necessary a focus directed at use and/or treatment of these waste. Further to SWOT analysis, it was ascertained that the agribusiness company A works through a defensive marketing strategy and acts vulnerably, in other words, unable of acting before this market segment, for it has decided to stop using the waste due to a lack of equipment and technology. On the other hand, the agribusiness company B has incorporated an offensive marketing strategy because even not possessing equipments, technology, and appropriated internal installations, it still insists on use and benefits of green coconut waste in its agribusiness. Thus, it is considered that the potential of green coconut waste management for the production of several subproducts reduces the impacts produced by inappropriate placement and generates profits in a short, medium and long term. Such profits being tangible and intangible, as the interest for sustainability actions is not only a matter of obtaining return on capital, but it is an important question in order to move on into business, since it is not enough to have quality on products and process nowadays. It is necessary to establish socio-environmental practices aiming the image of the company as the prevailing role on consumers buying decision

Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column

Um sistema para estimação da vazão de gás de poços produzindo por Plunger Lift para vaso separador de teste em plataformas de petróleo

This work intends to analyze the behavior of the gas flow of plunger lift wells producing to well testing separators in offshore production platforms to aim a technical procedure to estimate the gas flow during the slug production period. The motivation for this work appeared from the expectation of some wells equipped with plunger lift method by PETROBRAS in Ubarana sea field located at Rio Grande do Norte State coast where the produced fluids measurement is made in well testing separators at the platform. The oil artificial lift method called plunger lift is used when the available energy of the reservoir is not high enough to overcome all the necessary load losses to lift the oil from the bottom of the well to the surface continuously. This method consists, basically, in one free piston acting as a mechanical interface between the formation gas and the produced liquids, greatly increasing the well s lifting efficiency. A pneumatic control valve is mounted at the flow line to control the cycles. When this valve opens, the plunger starts to move from the bottom to the surface of the well lifting all the oil and gas that are above it until to reach the well test separator where the fluids are measured. The well test separator is used to measure all the volumes produced by the well during a certain period of time called production test. In most cases, the separators are designed to measure stabilized flow, in other words, reasonably constant flow by the use of level and pressure electronic controllers (PLC) and by assumption of a steady pressure inside the separator. With plunger lift wells the liquid and gas flow at the surface are cyclical and unstable what causes the appearance of slugs inside the separator, mainly in the gas phase, because introduce significant errors in the measurement system (e.g.: overrange error). The flow gas analysis proposed in this work is based on two mathematical models used together: i) a plunger lift well model proposed by Baruzzi [1] with later modifications made by Bolonhini [2] to built a plunger lift simulator; ii) a two-phase separator model (gas + liquid) based from a three-phase separator model (gas + oil + water) proposed by Nunes [3]. Based on the models above and with field data collected from the well test separator of PUB-02 platform (Ubarana sea field) it was possible to demonstrate that the output gas flow of the separator can be estimate, with a reasonable precision, from the control signal of the Pressure Control Valve (PCV). Several models of the System Identification Toolbox from MATLAB® were analyzed to evaluate which one better fit to the data collected from the field. For validation of the models, it was used the AIC criterion, as well as a variant of the cross validation criterion. The ARX model performance was the best one to fit to the data and, this way, we decided to evaluate a recursive algorithm (RARX) also with real time data. The results were quite promising that indicating the viability to estimate the output gas flow rate from a plunger lift well producing to a well test separator, with the built-in information of the control signal to the PCV

Software inteligente embarcado aplicado à correção de erro na medição de vazão em gás natural

This study developed software rotines, in a system made basically from a processor board producer of signs and supervisory, wich main function was correcting the information measured by a turbine gas meter. This correction is based on the use of an intelligent algorithm formed by an artificial neural net. The rotines were implemented in the habitat of the supervisory as well as in the habitat of the DSP and have three main itens: processing, communication and supervision

Um método para determinação da profundidade combinando visão estéreo e autocalibração para aplicação em robótica móvel

This work proposes a method to determine the depth of objects in a scene using a combination between stereo vision and self-calibration techniques. Determining the rel- ative distance between visualized objects and a robot, with a stereo head, it is possible to navigate in unknown environments. Stereo vision techniques supply a depth measure by the combination of two or more images from the same scene. To achieve a depth estimates of the in scene objects a reconstruction of this scene geometry is necessary. For such reconstruction the relationship between the three-dimensional world coordi- nates and the two-dimensional images coordinates is necessary. Through the achievement of the cameras intrinsic parameters it is possible to make this coordinates systems relationship. These parameters can be gotten through geometric camera calibration, which, generally is made by a correlation between image characteristics of a calibration pattern with know dimensions. The cameras self-calibration allows the achievement of their intrinsic parameters without using a known calibration pattern, being possible their calculation and alteration during the displacement of the robot in an unknown environment. In this work a self-calibration method based in the three-dimensional polar coordinates to represent image features is presented. This representation is determined by the relationship between images features and horizontal and vertical opening cameras angles. Using the polar coordinates it is possible to geometrically reconstruct the scene. Through the proposed techniques combination it is possible to calculate a scene objects depth estimate, allowing the robot navigation in an unknown environment

Otimizações da transmissão de imagens em redes de sensores visuais sem fio explorando a relevância de monitoramento dos nós fontes e codificação DWT

The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, covering since communication aspects to issues related with energy efficiency. When source sensors are endowed with cameras for visual monitoring, a new scope of challenges is raised, as transmission and monitoring requirements are considerably changed. Particularly, visual sensors collect data following a directional sensing model, altering the meaning of concepts as vicinity and redundancy but allowing the differentiation of source nodes by their sensing relevancies for the application. In such context, we propose the combined use of two differentiation strategies as a novel QoS parameter, exploring the sensing relevancies of source nodes and DWT image coding. This innovative approach supports a new scope of optimizations to improve the performance of visual sensor networks at the cost of a small reduction on the overall monitoring quality of the application. Besides definition of a new concept of relevance and the proposition of mechanisms to support its practical exploitation, we propose five different optimizations in the way images are transmitted in wireless visual sensor networks, aiming at energy saving, transmission with low delay and error recovery. Putting all these together, the proposed innovative differentiation strategies and the related optimizations open a relevant research trend, where the application monitoring requirements are used to guide a more efficient operation of sensor networks

Máquina de vetores-suporte intervalar

The Support Vector Machines (SVM) has attracted increasing attention in machine learning area, particularly on classification and patterns recognition. However, in some cases it is not easy to determinate accurately the class which given pattern belongs. This thesis involves the construction of a intervalar pattern classifier using SVM in association with intervalar theory, in order to model the separation of a pattern set between distinct classes with precision, aiming to obtain an optimized separation capable to treat imprecisions contained in the initial data and generated during the computational processing. The SVM is a linear machine. In order to allow it to solve real-world problems (usually nonlinear problems), it is necessary to treat the pattern set, know as input set, transforming from nonlinear nature to linear problem. The kernel machines are responsible to do this mapping. To create the intervalar extension of SVM, both for linear and nonlinear problems, it was necessary define intervalar kernel and the Mercer s theorem (which caracterize a kernel function) to intervalar function

Correspondência estéreo usando imagens em multiresolução com profundidade variável

We propose a multi-resolution, coarse-to-fine approach for stereo matching, where the first matching happens at a different depth for each pixel. The proposed technique has the potential of attenuating several problems faced by the constant depth algorithm, making it possible to reduce the number of errors or the number of comparations needed to get equivalent results. Several experiments were performed to demonstrate the method efficiency, including comparison with the traditional plain correlation technique, where the multi-resolution matching with variable depth, proposed here, generated better results with a smaller processing time

Análise de desempenho de estratégias de retransmissão para o mecanismo HCCA do padrão de redes sem fio IEEE 802.11e

This paper presents the performanee analysis of traffie retransmission algorithms pro¬posed to the HCCA medium aeeess meehanism of IEEE 802.11 e standard applied to industrial environmen1. Due to the nature of this kind of environment, whieh has eleetro¬magnetic interferenee, and the wireless medium of IEEE 802.11 standard, suseeptible to such interferenee, plus the lack of retransmission meehanisms, refers to an impraetieable situation to ensure quality of service for real-time traffic, to whieh the IEEE 802.11 e stan¬dard is proposed and this environment requires. Thus, to solve this problem, this paper proposes a new approach that involves the ereation and evaluation of retransmission al-gorithms in order to ensure a levei of robustness, reliability and quality of serviee to the wireless communication in such environments. Thus, according to this approaeh, if there is a transmission error, the traffie scheduler is able to manage retransmissions to reeo¬ver data 10s1. The evaluation of the proposed approaeh is performed through simulations, where the retransmission algorithms are applied to different seenarios, whieh are abstrae¬tions of an industrial environment, and the results are obtained by using an own-developed network simulator and compared with eaeh other to assess whieh of the algorithms has better performanee in a pre-defined applieation

Proposta de algoritmo para detecção de vazamentos em oleodutos utilizando análise freqüencial de sinais de pressão

Pipeline leak detection is a matter of great interest for companies who transport petroleum and its derivatives, in face of rising exigencies of environmental policies in industrialized and industrializing countries. However, existing technologies are not yet fully consolidated and many studies have been accomplished in order to achieve better levels of sensitivity and reliability for pipeline leak detection in a wide range of flowing conditions. In this sense, this study presents the results obtained from frequency spectrum analysis of pressure signals from pipelines in several flowing conditions like normal flowing, leakages, pump switching, etc. The results show that is possible to distinguish between the frequency spectra of those different flowing conditions, allowing recognition and announce of liquid pipeline leakages from pressure monitoring. Based upon these results, a pipeline leak detection algorithm employing frequency analysis of pressure signals is proposed, along with a methodology for its tuning and calibration. The proposed algorithm and its tuning methodology are evaluated with data obtained from real leakages accomplished in pipelines transferring crude oil and water, in order to evaluate its sensitivity, reliability and applicability to different flowing conditions

Otimização de modelos de predição da perda de propagação aplicáveis em 3,5GHZ utilizando algoritmos genéticos

The telecommunications industry has experienced recent changes, due to increasing quest for access to digital services for data, video and multimedia, especially using the mobile phone networks. Recently in Brazil, mobile operators are upgrading their networks to third generations systems (3G) providing to users broadband services such as video conferencing, Internet, digital TV and more. These new networks that provides mobility and high data rates has allowed the development of new market concepts. Currently the market is focused on the expansion of WiMAX technology, which is gaining increasingly the market for mobile voice and data. In Brazil, the commercial interest for this technology appears to the first award of licenses in the 3.5 GHz band. In February 2003 ANATEL held the 003/2002/SPV-ANATEL bidding, where it offered blocks of frequencies in the range of 3.5 GHz. The enterprises who purchased blocks of frequency were: Embratel, Brazil Telecom (Vant), Grupo Sinos, Neovia and WKVE, each one with operations spread in some regions of Brazil. For this and other wireless communications systems are implemented effectively, many efforts have been invested in attempts to developing simulation methods for coverage prediction that is close to reality as much as possible so that they may become believers and indispensable tools to design wireless communications systems. In this work wasm developed a genetic algorithm (GA's) that is able to optimize the models for predicting propagation loss at applicable frequency range of 3.5 GHz, thus enabling an estimate of the signal closer to reality to avoid significant errors in planning and implementation a system of wireless communication

Posicionamento e movimentação de um robô humanóide utilizando imagens de uma câmera móvel externa

This work proposes a method to localize a simple humanoid robot, without embedded sensors, using images taken from an extern camera and image processing techniques. Once the robot is localized relative to the camera, supposing we know the position of the camera relative to the world, we can compute the position of the robot relative to the world. To make the camera move in the work space, we will use another mobile robot with wheels, which has a precise locating system, and will place the camera on it. Once the humanoid is localized in the work space, we can take the necessary actions to move it. Simultaneously, we will move the camera robot, so it will take good images of the humanoid. The mainly contributions of this work are: the idea of using another mobile robot to aid the navigation of a humanoid robot without and advanced embedded electronics; chosing of the intrinsic and extrinsic calibration methods appropriated to the task, especially in the real time part; and the collaborative algorithm of simultaneous navigation of the robots

Desacoplamento de um gerador síncrono através de um controle adaptativo por modelo de referência baseado em funções de Base radial

An alternative nonlinear technique for decoupling and control is presented. This technique is based on a RBF (Radial Basis Functions) neural network and it is applied to the synchronous generator model. The synchronous generator is a coupled system, in other words, a change at one input variable of the system, changes more than one output. The RBF network will perform the decoupling, separating the control of the following outputs variables: the load angle and flux linkage in the field winding. This technique does not require knowledge of the system parameters and, due the nature of radial basis functions, it shows itself stable to parametric uncertainties, disturbances and simpler when it is applied in control. The RBF decoupler is designed in this work for decouple a nonlinear MIMO system with two inputs and two outputs. The weights between hidden and output layer are modified online, using an adaptive law in real time. The adaptive law is developed by Lyapunov s Method. A decoupling adaptive controller uses the errors between system outputs and model outputs, and filtered outputs of the system to produce control signals. The RBF network forces each outputs of generator to behave like reference model. When the RBF approaches adequately control signals, the system decoupling is achieved. A mathematical proof and analysis are showed. Simulations are presented to show the performance and robustness of the RBF network