Poverty Dynamics: Empirical Evidence for Canada (Working Paper 29)

Poverty (low income) dynamics are explored using tax filer data covering the period 1992 to 1996. The distributions of short-and long-term episodes are identified, and reveal substantial differences by sex and family type. Entry and exit models explore the relationships between poverty transitions and sex, family status and other personal and situational attributes. Duration effects on exiting and re-entering poverty are found to be important, and models including past poverty experiences point to strong "occurrence dependence" for poverty entry and incidence. Fixed-effect panel data models confirm the above, and reveal asymmetries in the impacts of household transitions on poverty.

Diversity and path coefficient analysis of Southern African maize hybrids

Detailed knowledge on genetic diversity among germplasm is important for hybrid maize ( Zea mays L.) breeding. The objective of the study was to determine genetic diversity in widely grown hybrids in Southern Africa, and compare effectiveness of phenotypic analysis models for determining genetic distances between hybrids. Fifty hybrids were evaluated at one site with two replicates. The experiment was a randomized complete block design. Phenotypic and genotypic data were analyzed using SAS and Power Marker respectively. There was significant (p < 0.01) variation and diversity among hybrid brands but small within brand clusters. Polymorphic Information Content (PIC) ranged from 0.07 to 0.38 with an average of 0.34 and genetic distance ranged from 0.08 to 0.50 with an average of 0.43. SAH23 and SAH21 (0.48) and SAH33 and SAH3 (0.47) were the most distantly related hybrids. Both single nucleotide polymorphism (SNP) markers and phenotypic data models were effective for discriminating genotypes according to genetic distance. SNP markers revealed nine clusters of hybrids. The 12-trait phenotypic analysis model, revealed eight clusters at 85%, while the five-trait model revealed six clusters. Path analysis revealed significant direct and indirect effects of secondary traits on yield. Plant height and ear height were negatively correlated with grain yield meaning shorter hybrids gave high yield. Ear weight, days to anthesis, and number of ears had highest positive direct effects on yield. These traits can provide good selection index for high yielding maize hybrids. Results confirmed that diversity of hybrids is small within brands and also confirm that phenotypic trait models are effective for discriminating hybrids.

Uma arquitetura de referência para o processamento distribuído de stream de dados em soluções analíticas de near real-time

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

A influência do conselho de administração na lucratividade das empresas listadas na BM&FBOVESPA

Dissertação (mestrado)—UnB/UFPB/UFRN, Programa MultiInstitucional e Inter-Regional de Pós-Graduação em Ciências Contábeis, 2016.

Obesidad, sobrepeso y condiciones socioeconómicas. El caso argentino

Obesity has been classified by the World Health Organization as a worldwide epidemic -- This issue is a growing field in economics due to pathologies associated with overweight, the significant impact on healthcare costs and consequent deterioration of welfare -- This paper shows the analysis of the results from the National Survey of Risk Factors in order to identify the role of socioeconomic conditions of obesity and overweight based on panel data models -- The results indicate that the income level and sedentary lifestyle have positively influenced obesity and overweight, whereas the education and medical coverage are not relevant when explaining the differences between provinces in overweight prevalence, but become significant in the obesity rates variations

Apoio geoespacial a uma operação NEO

No âmbito das obrigações que o Estado Português tem em garantir a segurança dos seus cidadãos, é efetuada, em países ou regiões onde há comunidades nacionais, uma avaliação quanto ao risco de vida para os cidadãos nacionais que aí residam ou aí se encontrem, entendendo-se, à luz do direito internacional consuetudinário, que é legítima a eventual execução de intervenção militar de extração de nacionais não combatentes dessas zonas de risco. Este trabalho pretende contribuir para uma reflexão sobre o apoio geoespacial a uma operação de extração de cidadãos nacionais não combatentes, que se denomina NEO (non-combatant evacuation operation). Dada a importância do conhecimento holístico do ambiente operacional para os comandantes militares, os Sistemas de Informação Geográfica desempenham um papel fundamental em termos da análise, contextualização e visualização da informação geoespacial, sendo um precioso sistema de apoio à decisão. A tomada de decisão é efetuada com os contributos de várias áreas de conhecimento, sendo fundamental que o planeamento seja efetuado com base na mesma informação geoespacial, evitando a existência de uma multitude de dados geoespaciais nem sempre coerentes, atualizados e acessíveis a todos os que deles necessitam, pretendendo-se com este trabalho fornecer um contributo para resolver este problema. Aborda-se também a escassez dos dados geográficos nas zonas em que este tipo de operações se poderá desenrolar, a pertinência e a adequabilidade de utilização de dados espaciais abertos, os modelos de dados, bem como a forma como a informação pode ser disponibilizada.

Macroeconomic determinants of contingent protection:the case of the European Union

Contingent Protection has grown to become an important trade restricting device. In the European Union, protection instruments like antidumping are used extensively. This paper analyses whether macroeconomic pressures may contribute to explain the variations in the intensity of antidumping protectionism in the EU. The empirical analysis uses count data models, applying various specification tests to derive the most appropriate specification. Our results suggest that the filing activity is inversely related to the macroeconomic conditions. Moreover, they confirm existing evidence for the US suggesting that domestic macroeconomic pressures are a more important determinant of contingent protection policy than external pressures.

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.

Bringing forward semantic relations: Issues and proposals

Semantic relations are an important element in the construction of ontologies and models of problem domains. Nevertheless, they remain fuzzy or under-specified. This is a pervasive problem in software engineering and artificial intelligence. Thus, we find semantic links that can have multiple interpretations in wide-coverage ontologies, semantic data models with abstractions that are not enough to capture the relation richness of problem domains, and improperly structured taxonomies. However, if relations are provided with precise semantics, some of these problems can be avoided, and meaningful operations can be performed on them. In this paper we present some insightful issues about the modeling, representation and usage of relations including the available taxonomy structuring methodologies as well as the initiatives aiming to provide relations with precise semantics. Moreover, we explain and propose the control of relations as a key issue for the coherent construction of ontologies.

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.

Contribution to the diffuse radiation modelling in Évora, Portugal

Solar radiation data is crucial for the design of energy systems based on the solar resource. Since diffuse radiation measurements are not always available in the archive data series, either due to the inexistence of measuring equipment, shading device misplacement or missing data, models to generate these data are needed. In this work, one year of hourly and daily horizontal solar global and diffuse irradiation measurements in Évora are used to establish a new relation between the diffuse radiation and the clearness index. The proposed model includes a fitting parameter, which was adjusted through a simple optimization procedure to minimize the Least Square Error as compared to measurements. A comparison against several other fitting models presented in the literature was also carried out using the Root Mean Square Error as statistical indicator, and it was found that the present model is more accurate than the previous fitting models for the diffuse radiation data in Évora.