Aspectos sócio-econômicos dos códigos de conduta de responsabilidade social (CRS) do setor de gás e petróleo

A presença de uma empresa internacionalmente significa também a disseminação mundial de seu Código de Conduta de Responsabilidade Social (Código de CRS). É portanto necessário um certo controle do conteúdo desses Códigos. As regras e padrões internacionais podem desempenhar este papel. O setor de gás e petróleo causa grande impacto nas comunidades em que as empresas exercem suas atividades. O mesmo se pode afirmar em relação aos seus Códigos de CRS. Este estudo examina, então, duas vertentes distintas mas convergentes. De um lado, o estudo comparativo de como os Códigos de CRS das empresas do setor de gás e petróleo tratam dos aspectos sócio-econômicos. De outro, examina-se a conformidade – ou falta de conformidade – dos Códigos de CRS com os tratados, convenções, normas e padrões internacionais. Estratégias podem então ser propostas ao setor de gás e petróleo, para a melhoria dos padrões sócio-econômicos de seus Códigos de CRS. Com isso atende-se às necessidades das comunidades envolvidas e, também, cria-se valor para as empresas do setor de gás e petróleo.

Assessing interdependence among countries' fundamentals and its implications for exchange rate misalignment estimates: An empirical exercise based on GVAR

Exchange rates are important macroeconomic prices and changes in these rates a ect economic activity, prices, interest rates, and trade ows. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that the global vector autoregressions model (GVAR) proposed by Pesaran and co-authors can add relevant information to the literature on measuring exchange rate misalignment. Our empirical exercise suggests that the estimate exchange rate misalignment obtained from GVAR can be quite di erent to that using the traditional cointegrated time series techniques, which treat countries as detached entities. The di erences between the two approaches are more pronounced for small and developing countries. Our results also suggest a strong interdependence among eurozone countries, as expected

Supply chain turbulence: the impact of a mid-range event in multi-tier, multi-dimension supply chains

Nota: A autora agradece à Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) pela concessão de bolsa de estudos para o desenvolvimento deste projeto de pesquisa.

The combination of neural estimates in prediction and decision problems

In this dissertation, different ways of combining neural predictive models or neural-based forecasts are discussed. The proposed approaches consider mostly Gaussian radial basis function networks, which can be efficiently identified and estimated through recursive/adaptive methods. Two different ways of combining are explored to get a final estimate – model mixing and model synthesis –, with the aim of obtaining improvements both in terms of efficiency and effectiveness. In the context of model mixing, the usual framework for linearly combining estimates from different models is extended, to deal with the case where the forecast errors from those models are correlated. In the context of model synthesis, and to address the problems raised by heavily nonstationary time series, we propose hybrid dynamic models for more advanced time series forecasting, composed of a dynamic trend regressive model (or, even, a dynamic harmonic regressive model), and a Gaussian radial basis function network. Additionally, using the model mixing procedure, two approaches for decision-making from forecasting models are discussed and compared: either inferring decisions from combined predictive estimates, or combining prescriptive solutions derived from different forecasting models. Finally, the application of some of the models and methods proposed previously is illustrated with two case studies, based on time series from finance and from tourism.

Motivating sustainable goal choices and providing effective feedback

Overconsumption of natural resources and the associated environmental hazards are one of today’s most pressing global issues. In the western world, individual consumption in homes and workplaces is a key contributor to this problem. Reflecting the importance of individual action in this domain, this thesis focuses on studying and influencing choices related to sustainability and energy consumption made by people in their daily lives. There are three main components to this work. Firstly, this thesis asserts that people frequently make ineffective consumption reduction goal choices and attempts to understand the rationale for these poor choices by fitting them to goalsetting theory, an established theoretical model of behavior change. Secondly, it presents two approaches that attempt to influence goal choice towards more effective targets, one of which deals with mechanisms for goal priming and the other of which explores the idea that carefully designed toys can exert influence on children’s long term consumption behavior patterns. The final section of this thesis deals with the design of feedback to support the performance of environmentally sound activities. Key contributions surrounding goals include the finding that people choose easy sustainable goals despite immediate feedback as to their ineffectiveness and the discussion and study of goal priming mechanisms that can influence this choice process. Contributions within the design of value instilling toys include a theoretically grounded framework for the design of such toys and a completed and tested prototype toy. Finally, contributions in designing effective and engaging energy consumption feedback include the finding that negative feedback is best presented verbally compared with visually and this is exemplified and presented within a working feedback system. The discussions, concepts, prototypes and empirical findings presented in this work will be useful for both environmental psychologists and for HCI researchers studying eco-feedback.

A formação e o desenvolvimento de arranjos cooperativos sob a ótica da imersão social e da economia dos custos de transação: um estrudo de caso na Coopercam e na Unipesca

The current study analyzes the birth and development of two strategic alliances established between shrimp producers in Rio Grande do Norte: the Unipesca and the Coopercam. To achieve this aim, two approaches which, at first sight, could be considered contradictory were used: the Transactional Costs Economy and Embeddedness. The first approach is fundamentally based in the studies of Williamson (1985; 1991; 1996; 1999; 2000; 2002). Embededness, on the other hand, went through the review of a series of authors, such as Burt (1992), Granovetter (1973; 1985), Uzzi (1997), Gulati (1994; 1995; 1997; 1998; 1999; 2000), Nielsen (2005), Ring (2002), Ring and Van de Ven (1994), Zafirovski (2002), among others. To analyze the birth and development of the cooperatives in this study, Gulati s work (1998) was used. This study shows the steps to be studied for a better comprehension of an alliance: the decision of starting an alliance and the choice of the partners, the decision about the governance structure, the evolution of the alliance and the development of the companies which established this partnership. To carry this study out, a study case accordingly to Yin s proposal (2001) was adopted. Semi-structured interviews with pre-defined plots were conducted in two phases: in the beginning of 2006 and in the beginning of 2007. The subjects from the research were, in 2006, representative members of the main associations and corporations, besides the shrimp producers from the state, when the context of the activity was set. In the second phase, in 2007, representative members from the two cooperatives that were listed above were interviewed the president from Coopercam and the marketing manager from Unipesca. Besides these two members, directors from two important organizations in each of these cooperatives were also interviewed, giving out the necessary information for the research. Secondary data was also collected from the Brazilian Association of Crab producers website, as well as from news from important newspapers in RN, such as Tribuna do Norte. The primary data was analyzed in terms of quality, accordingly to the documental analysis technique. Thus, through the data that was collected, it can be concluded that the reasons that motivated the companies to cooperate can be explained in terms of the transactional costs economy. However, the choice of partners is more connected to aspects approached by the social embededness. When aspects related to development and evolution were analyzed, it could be seen that both aspects from TCE and Embededness were vital to explain the development of the cooperatives mentioned

Prevalência da infecção pelo Papilomavírus humano, Chlamydia Trachomatis e Herpes Simples do tipo 2 em adolescentes atendidas em unidades de saúde pública de Natal

This study assessed the level of knowledge, attitude and practice of Pap smear and human papillomavirus (HPV), in addition to analyzing the prevalence of genital HPV infection, Herpes Simplex Type 2 (HSV-2) and Chlamydia trachomatis in teenagers. The study consisted of two approaches, one based only on interviews conducted with adolescents enrolled in public schools or in public health facilities in the city of Natal. The other approach involved only a group of 132 adolescents enrolled among those admitted to two health units in Natal-RN. This second group of participants two specimens were collected for laboratory analysis: one was directed to prepare the blade for the Pap test, and other processed for DNA extraction for molecular analysis, focusing on the detection of HPV, HSV-2 and C . trachomatis. The presence of DNA of the three pathogens was investigated by the technique of polymerase chain reaction (PCR). The presence of each of the three pathogens was analyzed in terms of socio-demographic characteristics, as well as sexual and reproductive activity to identify risk factors for infection and development of lesions of the uterine cervix. The results show that the adolescents in this study had levels of knowledge and attitude very low, both in relation to cytology to HPV as though they have made a reasonable percentage of adequate practice exam and prevention of HPV infection. The overall prevalence of HPV infection was 54.5% and 48.2% in adolescents with normal cytology and 86.4% in those with abnormal cytology. We observed a higher proportion of cases of infection in the age group of 18 to 21. The prevalence of HPV infection was slightly higher among pregnant teenagers. The overall prevalence of HSV-2 infection was 13.6% and 11.8% in women with normal cytology and 22.7% in those with abnormal cytology. A higher proportion of cases of infection was found in the age group from 14 to 17, with a slightly higher prevalence among pregnant women. The C. trachomatis was found with an overall prevalence of 19.7% and 21.8% in adolescents with normal cytology and 9.1% in those with abnormal cytology. The prevailing rate was highest in the age group 18 to 21 years and in nonpregnant

Association of an insulin-like growth factor 1 gene microsatellite with phenotypic variation and estimated breeding values of growth traits in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evaluation of an average numerator relationship matrix model and a Bayesian hierarchical model for growth traits in Nellore cattle with uncertain paternity

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

Detecção e isolamento de falhas em sistemas dinâmicos baseados em redes neurais

This master dissertation presents the development of a fault detection and isolation system based in neural network. The system is composed of two parts: an identification subsystem and a classification subsystem. Both of the subsystems use neural network techniques with multilayer perceptron training algorithm. Two approaches for identifica-tion stage were analyzed. The fault classifier uses only residue signals from the identification subsystem. To validate the proposal we have done simulation and real experiments in a level system with two water reservoirs. Several faults were generated above this plant and the proposed fault detection system presented very acceptable behavior. In the end of this work we highlight the main difficulties found in real tests that do not exist when it works only with simulation environments

Algoritmos inteligentes para auto-correção, auto-verificação e auto-validação de medidas em sensores

This work presents a set of intelligent algorithms with the purpose of correcting calibration errors in sensors and reducting the periodicity of their calibrations. Such algorithms were designed using Artificial Neural Networks due to its great capacity of learning, adaptation and function approximation. Two approaches willbe shown, the firstone uses Multilayer Perceptron Networks to approximate the many shapes of the calibration curve of a sensor which discalibrates in different time points. This approach requires the knowledge of the sensor s functioning time, but this information is not always available. To overcome this need, another approach using Recurrent Neural Networks was proposed. The Recurrent Neural Networks have a great capacity of learning the dynamics of a system to which it was trained, so they can learn the dynamics of a sensor s discalibration. Knowingthe sensor s functioning time or its discalibration dynamics, it is possible to determine how much a sensor is discalibrated and correct its measured value, providing then, a more exact measurement. The algorithms proposed in this work can be implemented in a Foundation Fieldbus industrial network environment, which has a good capacity of device programming through its function blocks, making it possible to have them applied to the measurement process

Estratégias baseadas em aprendizado para coordenação de uma frota de robôs em tarefas cooperativas

In multi-robot systems, both control architecture and work strategy represent a challenge for researchers. It is important to have a robust architecture that can be easily adapted to requirement changes. It is also important that work strategy allows robots to complete tasks efficiently, considering that robots interact directly in environments with humans. In this context, this work explores two approaches for robot soccer team coordination for cooperative tasks development. Both approaches are based on a combination of imitation learning and reinforcement learning. Thus, in the first approach was developed a control architecture, a fuzzy inference engine for recognizing situations in robot soccer games, a software for narration of robot soccer games based on the inference engine and the implementation of learning by imitation from observation and analysis of others robotic teams. Moreover, state abstraction was efficiently implemented in reinforcement learning applied to the robot soccer standard problem. Finally, reinforcement learning was implemented in a form where actions are explored only in some states (for example, states where an specialist robot system used them) differently to the traditional form, where actions have to be tested in all states. In the second approach reinforcement learning was implemented with function approximation, for which an algorithm called RBF-Sarsa($lambda$) was created. In both approaches batch reinforcement learning algorithms were implemented and imitation learning was used as a seed for reinforcement learning. Moreover, learning from robotic teams controlled by humans was explored. The proposal in this work had revealed efficient in the robot soccer standard problem and, when implemented in other robotics systems, they will allow that these robotics systems can efficiently and effectively develop assigned tasks. These approaches will give high adaptation capabilities to requirements and environment changes.

Spin-Stabilized Spacecrafts: Analytical Attitude Propagation Using Magnetic Torques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Violência nas escolas: Um novo olhar ante as relações sociais

The most varied ways of manifestation of the violence phenomenon in the contemporary society are each time more found in the media spaces and among society discussions. It makes think about procedures to be taken before the growth and new outbreaks of such phenomenon. The violences manifestations in schools reveal themselves as a reflection of what happens in the scope of social violence. Its dynamics originates in society and reflects itself in scholl, that is, the violences in schools combine internal and external elements to school enviroment of many fields and spheres of which the individuals participate. To reflect about the violences in the schools requires, over all, to make a bridge with the categories: youth and violence. Violences in schools: A new look to the social relations, is a Ms. Sc. Dissertation that has as main objective: to analyze the main existing forms of violence in the school space. For its achievement, it was made a bibliographical survey, questionnaires application (annexed) and observation. Thus, this research articulated the two approaches: qualitative and quantitative. The questionnaires application happened in a state school of the Natal city and amongst yhe criteria for this choice there was the fact of the school had more than 500 pupils, to be located on a strategical place of the city, providing a subjects heterogeneity to be researched, deyond the limitations of available resources financial and material and the available time for the research accomplishment. The scool congregates objective conditions, specifically in what concerns the criteria previously defined: age range, socioenomical level and number of pupils. Amongst the main results obtained, it can be detached that the violence is a phenomenon seen, for the great majority of the research subjects, as a phenomenon connected to the most visible violence forms: the agressions. And a question always present in the public education institutions: infrastructures precariousness, high scool evasion índex and vulnerability among the pupils that makes possible to the pupil to see school as an home extension. Such dissertation concludes that the phenomenon of the violence in scools demands and requires of the most varied subjects involved in the processes na understanding of its determinants so that thus, one can intervene in such phenomenon that does not restrains itself to the physical acts of aggression, but that it is, over all, on a non respecting the different

Seleção de atributos em comitês de classificadores utilizando algoritmos genéticos

Classifier ensembles are systems composed of a set of individual classifiers and a combination module, which is responsible for providing the final output of the system. In the design of these systems, diversity is considered as one of the main aspects to be taken into account since there is no gain in combining identical classification methods. The ideal situation is a set of individual classifiers with uncorrelated errors. In other words, the individual classifiers should be diverse among themselves. One way of increasing diversity is to provide different datasets (patterns and/or attributes) for the individual classifiers. The diversity is increased because the individual classifiers will perform the same task (classification of the same input patterns) but they will be built using different subsets of patterns and/or attributes. The majority of the papers using feature selection for ensembles address the homogenous structures of ensemble, i.e., ensembles composed only of the same type of classifiers. In this investigation, two approaches of genetic algorithms (single and multi-objective) will be used to guide the distribution of the features among the classifiers in the context of homogenous and heterogeneous ensembles. The experiments will be divided into two phases that use a filter approach of feature selection guided by genetic algorithm