Rotatividade do mercado de trabalho no corede sul: uma análise ex-ante e ex-post a implementação do polo naval no munícipio de Rio Grande

A presente monografia tem como objetivo analisar a dinâmica do mercado de trabalho do Corede Sul, e avaliar a rotatividade dos trabalhadores a partir do impacto que o polo naval de Rio Grande trouxe para a região sul do estado do Rio Grande do Sul. As metodologias utilizadas foram dados em painel e modelos de diferenças em diferenças, nos períodos de 2003 a 2010 e 2003 a 2013 respectivamente, com o intuito de estimar os determinantes da rotatividade e analisar os impactos posteriores à implementação do polo na região. Foram estimados dois modelos, primeiramente um painel, mas o mesmo demonstrou problemas de endogenia entre as variáveis, e posteriormente um modelo de diferenças em diferenças, que foi estimado para melhor captar os efeitos para as cidades consideradas como tratadas no modelo, obtendo alguns coeficientes significativos. Foram gerados resultados estatisticamente representativos para as cidades de Rio Grande, Pelotas e São José do Norte, tendo a cidade de Rio Grande o maior resultado encontrado um aumento de 132% na rotatividade após 2006. Além disso, foi descoberto um processo de antecipação no mercado de trabalho no município de Rio Grande, em que a população já almejava uma melhor oportunidade de emprego, à medida que a construção do polo se consolidava.

Deep convolutional neural networks for semantic video object segmentation

In this thesis, we propose to infer pixel-level labelling in video by utilising only object category information, exploiting the intrinsic structure of video data. Our motivation is the observation that image-level labels are much more easily to be acquired than pixel-level labels, and it is natural to find a link between the image level recognition and pixel level classification in video data, which would transfer learned recognition models from one domain to the other one. To this end, this thesis proposes two domain adaptation approaches to adapt the deep convolutional neural network (CNN) image recognition model trained from labelled image data to the target domain exploiting both semantic evidence learned from CNN, and the intrinsic structures of unlabelled video data. Our proposed approaches explicitly model and compensate for the domain adaptation from the source domain to the target domain which in turn underpins a robust semantic object segmentation method for natural videos. We demonstrate the superior performance of our methods by presenting extensive evaluations on challenging datasets comparing with the state-of-the-art methods.

Determinantes da sustentabilidade financeira em diversos níveis de governo

Dissertação de Mestrado, Ciências Económicas e Empresariais, 18 de Julho de 2016, Universidade dos Açores.

EFFECT OF ISOTHERMAL AGING ON SAC305 HARMONIC VIBRATION DURABILITY

The effect of isothermal aging on the harmonic vibration durability of Sn3.0Ag0.5Cu solder interconnects is examined. Printed wiring assemblies with daisy-chained leadless chip resistors (LCRs) are aged at 125°C for 0, 100, and 500 hours. These assemblies are instrumented with accelerometers and strain gages to maintain the same harmonic vibration profile in-test, and to characterize PWB behavior. The tested assemblies are excited at their first natural frequencies until LCRs show a resistance increase of 20%. Dynamic finite element models are employed to generate strain transfer functions, which relate board strain levels observed in-test to respective solder strain levels. The transfer functions are based on locally averaged values of strains in critical regions of the solder and in appropriate regions of the PWB. The vibration test data and the solder strains from FEA are used to estimate lower-bound material fatigue curves for SAC305 solder materials, as a function of isothermal pre-aging.

POSTDATA – Towards publishing European poetry as linked open data

POSTDATA is a 5 year's European Research Council (ERC) Starting Grant Project that started in May 2016 and is hosted by the Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain. The context of the project is the corpora of European Poetry (EP), with a special focus on poetic materials from different languages and literary traditions. POSTDATA aims to offer a standardized model in the philological field and a metadata application profile (MAP) for EP in order to build a common classification of all these poetic materials. The information of Spanish, Italian and French repertoires will be published in the Linked Open Data (LOD) ecosystem. Later we expect to extend the model to include additional corpora. There are a number of Web Based Information Systems in Europe with repertoires of poems available to human consumption but not in an appropriate condition to be accessible and reusable by the Semantic Web. These systems are not interoperable; they are in fact locked in their databases and proprietary software, not suitable to be linked in the Semantic Web. A way to make this data interoperable is to develop a MAP in order to be able to publish this data available in the LOD ecosystem, and also to publish new data that will be created and modeled based on this MAP. To create a common data model for EP is not simple since the existent data models are based on conceptualizations and terminology belonging to their own poetical traditions and each tradition has developed an idiosyncratic analytical terminology in a different and independent way for years. The result of this uncoordinated evolution is a set of varied terminologies to explain analogous metrical phenomena through the different poetic systems whose correspondences have been hardly studied – see examples in González-Blanco & Rodríguez (2014a and b). This work has to be done by domain experts before the modeling actually starts. On the other hand, the development of a MAP is a complex task though it is imperative to follow a method for this development. The last years Curado Malta & Baptista (2012, 2013a, 2013b) have been studying the development of MAP's in a Design Science Research (DSR) methodological process in order to define a method for the development of MAPs (see Curado Malta (2014)). The output of this DSR process was a first version of a method for the development of Metadata Application Profiles (Me4MAP) (paper to be published). The DSR process is now in the validation phase of the Relevance Cycle to validate Me4MAP. The development of this MAP for poetry will follow the guidelines of Me4MAP and this development will be used to do the validation of Me4MAP. The final goal of the POSTDATA project is: i) to be able to publish all the data locked in the WIS, in LOD, where any agent interested will be able to build applications over the data in order to serve final users; ii) to build a Web platform where: a) researchers, students and other final users interested in EP will be able to access poems (and their analyses) of all databases; b) researchers, students and other final users will be able to upload poems, the digitalized images of manuscripts, and fill in the information concerning the analysis of the poem, collaboratively contributing to a LOD dataset of poetry.

Factors that influence entrepreneurship activity by gender in the European Union

This research work aims to discuss the gender issue concerning entrepreneurship in European Union countries in a period of nine years, from 2007 to 2015, identifying the factors which drive individuals to be entrepreneurs. The study mainly concentrates on identifying and quantifying the personal, social, political and economic features which are motivating individuals, especially women, to be entrepreneurs, as well as the main difficulties they feel during the process of business creation. In order to explore the entrepreneurial activity across a set of developed countries the econometric methodology of panel data (in particular the fixed effects and random effects models) is applied to a data set of entrepreneurial statistical indicators calculated and made available by the Global Entrepreneurship Monitor. The results show that the knowledge of other start-up entrepreneurs, a desired career choice, the governmental support and the existence of public policies that promote entrepreneurship (specially within the framework of small and medium sized firms) and the transfer of R&D are factors influencing negatively on the rate of female entrepreneurship. None of the observed variables are barriers for male entrepreneurs. The perceived capabilities and opportunities, the entrepreneurial intention, the policies to lower taxes and bureaucracy and the social and cultural norms are identified drives for women for engaging in a process of running their own ventures. These findings offer a set of valid knowledge to understand which measures could be implemented or should be changed and improved at a political and managerial level for stimulating entrepreneurship, especially for women.

US Antidumping Petitions and Revealed Comparative Advantage of Shrimp Exporting Countries

The paper explores the trade competitiveness of seven major shrimp exporting countries, namely Vietnam, China, Thailand, Ecuador, India, Indonesia and Mexico, to the USA. Specifically, we investigate whether the United States (US) antidumping petitions impact upon the bilateral revealed comparative advantage (RCA) indexes for each of the seven shrimp exporting countries with the USA. Monthly data from January 2003 to December 2014 and the panel data model are used to examine the determinants of the RCA for the shrimp exporting countries. The empirical results show the shrimp exporting countries have superior competitiveness against the shrimp market in the USA. Moreover, the RCA indexes are significantly negatively influenced by shrimp prices, and are positively affected by US income per capita. However, the EMS (Early Mortality Syndrome) shrimp disease, domestic US shrimp quantity, exchange rate, and US antidumping laws are found to have no significant impacts on the RCA indexes. In terms of policy implications, the USA should try to reduce production costs of shrimp in the US market instead of imposing antidumping petitions, and the shrimp exporting countries should maintain their comparative advantage and diversify into new markets.

A Corrupção burocrática inibe o empreendedorismo? uma análise empírica dos estados brasileiros

This work aims to investigate the relationship between the entrepreneurship and the incidence of bureaucratic corruption in the states of Brazil and Federal District. The main hypothesis of this study is that the opening of a business in Brazilian states is negatively affected by the incidence of corruption. The theoretical reference is divided into Entrepreneurship and bureaucratic corruption, with an emphasis on materialistic perspective (objectivist) of entrepreneurship and the effects of bureaucratic corruption on entrepreneurial activity. By the regression method with panel data, we estimated the models with pooled data and fixed and random effects. To measure corruption, I used the General Index of Corruption for the Brazilian states (BOLL, 2010), and to represent entrepreneurship, firm entry per capita by state. Tests (Chow, Hausman and Breusch-Pagan) indicate that the random effects model is more appropriate, and the preliminary results indicate a positive impact of bureaucratic corruption on entrepreneurial activity, contradicting the hypothesis expected and found in previous articles to Brazil, and corroborating the proposition of Dreher and Gassebner (2011) that, in countries with high regulation, bureaucratic corruption can be grease in the wheels of entrepreneurship

Tensões e contradições do processo de construção das diretrizes para a politica pública de educação infantil do campo

Tese (doutorado)—Universidade de Brasília, Faculdade de Educação, Programa de Pós-Graduação em Educação, 2016.

Corporate governance : value creation and performance in credit unions

In this study, we examine the relationship between good corporate governance practices and the creation of value/performance of credit unions from 2010 to 2012. The objective was to create and validate a corporate governance index for credit unions, and to then analyse the relationship between good governance practices and the creation of value/performance. The problem question is: do good corporate governance practices provide value creation for credit unions? The research started by creating indices from factor analysis to identify latent dependent variables related to value creation and performance; next indices were created from the principal component analysis for the creation of independent latent variables related to corporate governance. Finally, based on panel data from regression models, the influence of the variables and indices related to corporate governance on the indices of value creation and performance was verified. Based on the research, it became evident that the Corporate Governance Index (IGC) is mainly impacted by Executive Management, with 40.31% of the IGC value, followed by the Representation and Participation dimension, with 34.07% of the IGC value. The contribution for academics was the creation of the Corporate Governance Index (IGC) applied for credit unions. As for the contribution to the system of credit unions, the highlight was the effectiveness of the mechanisms for economic-financial and asset management adopted by BACEN, credit unions and OCEMG.

Three Essays on a Longitudinal Analysis of Business Start-ups using the Kauffman Firm Survey

This dissertation focused on the longitudinal analysis of business start-ups using three waves of data from the Kauffman Firm Survey. The first essay used the data from years 2004-2008, and examined the simultaneous relationship between a firm’s capital structure, human resource policies, and its impact on the level of innovation. The firm leverage was calculated as, debt divided by total financial resources. Index of employee well-being was determined by a set of nine dichotomous questions asked in the survey. A negative binomial fixed effects model was used to analyze the effect of employee well-being and leverage on the count data of patents and copyrights, which were used as a proxy for innovation. The paper demonstrated that employee well-being positively affects the firm's innovation, while a higher leverage ratio had a negative impact on the innovation. No significant relation was found between leverage and employee well-being. The second essay used the data from years 2004-2009, and inquired whether a higher entrepreneurial speed of learning is desirable, and whether there is a linkage between the speed of learning and growth rate of the firm. The change in the speed of learning was measured using a pooled OLS estimator in repeated cross-sections. There was evidence of a declining speed of learning over time, and it was concluded that a higher speed of learning is not necessarily a good thing, because speed of learning is contingent on the entrepreneur's initial knowledge, and the precision of the signals he receives from the market. Also, there was no reason to expect speed of learning to be related to the growth of the firm in one direction over another. The third essay used the data from years 2004-2010, and determined the timing of diversification activities by the business start-ups. It captured when a start-up diversified for the first time, and explored the association between an early diversification strategy adopted by a firm, and its survival rate. A semi-parametric Cox proportional hazard model was used to examine the survival pattern. The results demonstrated that firms diversifying at an early stage in their lives show a higher survival rate; however, this effect fades over time.

A next application prediction service using the BaranC framework

Predicting user behaviour enables user assistant services provide personalized services to the users. This requires a comprehensive user model that can be created by monitoring user interactions and activities. BaranC is a framework that performs user interface (UI) monitoring (and collects all associated context data), builds a user model, and supports services that make use of the user model. A prediction service, Next-App, is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts, based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic, reflecting the current context, and is also dynamic in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

A service-oriented user interaction analysis framework supporting adaptive applications

A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.

Integration of process planning and scheduling using mobile-agent based approach in a networked manufacturing environment

Effective and efficient implementation of intelligent and/or recently emerged networked manufacturing systems require an enterprise level integration. The networked manufacturing offers several advantages in the current competitive atmosphere by way to reduce, by shortening manufacturing cycle time and maintaining the production flexibility thereby achieving several feasible process plans. The first step in this direction is to integrate manufacturing functions such as process planning and scheduling for multi-jobs in a network based manufacturing system. It is difficult to determine a proper plan that meets conflicting objectives simultaneously. This paper describes a mobile-agent based negotiation approach to integrate manufacturing functions in a distributed manner; and its fundamental framework and functions are presented. Moreover, ontology has been constructed by using the Protégé software which possesses the flexibility to convert knowledge into Extensible Markup Language (XML) schema of Web Ontology Language (OWL) documents. The generated XML schemas have been used to transfer information throughout the manufacturing network for the intelligent interoperable integration of product data models and manufacturing resources. To validate the feasibility of the proposed approach, an illustrative example along with varied production environments that includes production demand fluctuations is presented and compared the proposed approach performance and its effectiveness with evolutionary algorithm based Hybrid Dynamic-DNA (HD-DNA) algorithm. The results show that the proposed scheme is very effective and reasonably acceptable for integration of manufacturing functions.

Essays on employment / education, investment in education and student achievement

Méthodologie: Modèle de régression quantile de variable instrumentale pour données de Panel utilisant la fonction de production partielle