Enabling Global Experiments With Interactive Reconfiguration And Steering By Multiple Users

In global scientific experiments with collaborative scenarios involving multinational teams there are big challenges related to data access, namely data movements are precluded to other regions or Clouds due to the constraints on latency costs, data privacy and data ownership. Furthermore, each site is processing local data sets using specialized algorithms and producing intermediate results that are helpful as inputs to applications running on remote sites. This paper shows how to model such collaborative scenarios as a scientific workflow implemented with AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic), a decentralized framework offering a feasible solution to run the workflow activities on distributed data centers in different regions without the need of large data movements. The AWARD workflow activities are independently monitored and dynamically reconfigured and steering by different users, namely by hot-swapping the algorithms to enhance the computation results or by changing the workflow structure to support feedback dependencies where an activity receives feedback output from a successor activity. A real implementation of one practical scenario and its execution on multiple data centers of the Amazon Cloud is presented including experimental results with steering by multiple users.

Logarithmically proportional objective function for planar surfaces recognition in 3D point cloud

3D laser scanning is becoming a standard technology to generate building models of a facility's as-is condition. Since most constructions are constructed upon planar surfaces, recognition of them paves the way for automation of generating building models. This paper introduces a new logarithmically proportional objective function that can be used in both heuristic and metaheuristic (MH) algorithms to discover planar surfaces in a point cloud without exploiting any prior knowledge about those surfaces. It can also adopt itself to the structural density of a scanned construction. In this paper, a metaheuristic method, genetic algorithm (GA), is used to test this introduced objective function on a synthetic point cloud. The results obtained show the proposed method is capable to find all plane configurations of planar surfaces (with a wide variety of sizes) in the point cloud with a minor distance to the actual configurations. © 2014 IEEE.

The extended unsymmetric frontal solution for multiple-point constraints

The purpose of this paper is to discuss the linear solution of equality constrained problems by using the Frontal solution method without explicit assembling. Design/methodology/approach - Re-written frontal solution method with a priori pivot and front sequence. OpenMP parallelization, nearly linear (in elimination and substitution) up to 40 threads. Constraints enforced at the local assembling stage. Findings - When compared with both standard sparse solvers and classical frontal implementations, memory requirements and code size are significantly reduced. Research limitations/implications - Large, non-linear problems with constraints typically make use of the Newton method with Lagrange multipliers. In the context of the solution of problems with large number of constraints, the matrix transformation methods (MTM) are often more cost-effective. The paper presents a complete solution, with topological ordering, for this problem. Practical implications - A complete software package in Fortran 2003 is described. Examples of clique-based problems are shown with large systems solved in core. Social implications - More realistic non-linear problems can be solved with this Frontal code at the core of the Newton method. Originality/value - Use of topological ordering of constraints. A-priori pivot and front sequences. No need for symbolic assembling. Constraints treated at the core of the Frontal solver. Use of OpenMP in the main Frontal loop, now quantified. Availability of Software.

Data analytics in the cloud with flexible mapreduced workflows

Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

A stochastic programming approach for the development of offering strategies for a wind power producer

A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

O contributo da expressão plástica para o desenvolvimentodas múltiplas linguagens da criança

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

Quality indicators in the education of children with profound Intellectual and multiple disabilities

Todas as crianças, independentemente das suas necessidades, deveriam ter acesso a uma educação de qualidade e a serem incluídas nas suas famílias e comunidades. Esta afirmação inclui as crianças mais vulneráveis, em particular as crianças com dificuldades intelectuais e multideficiência. Os resultados da investigação sobre a educação de crianças com dificuldades intelectuais e multideficiência ainda não produziram até ao momento informação suficiente que possa ser usada para desenvolver indicadores de qualidade para a avaliação das práticas e dos serviços. A investigação nesta área é limitada por constrangimentos éticos, dificuldades na determinação de amostras e desafios metodológicos, sendo reduzido o número de estudos capaz de produzir a informação necessária. Este artigo tem como objetivo discutir fatores que contribuam para a qualidade do envolvimento de crianças com dificuldades intelectuais e multideficiência em atividades educativas, com base na experiência das autoras e na informação disponível que tem sido publicada sobre este assunto. Com base nesta discussão é sugerido um conjunto de indicadores que poderão ajudar os profissionais a dirigir as suas observações para a qualidade da oferta educativa e para aspetos significativos dos desempenhos das crianças quando envolvidas em atividades curriculares.

A influência dos sistemas de recompensas sobre a satisfação no trabalho

Mestrado em Contabilidade e Gestão das Instituições Financeiras

Examination timetabling automation using hybrid meta-heuristics

Trabalho de projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Relatório de estágio

Resumo I (Prática Pedagógica) - O Estágio do Ensino Especializado realizado no presente ano lectivo foi elaborado na Academia de Música de Lisboa em três turmas. Vários foram os desafios encontrados no decorrer do ano lectivo, como por exemplo a instabilidade das turmas, a falta do quadro na sala em algumas aulas e a pouca experiência anterior na área de docência. A realização deste estágio permitiu experimentar actividades e estratégias aprendidas nas disciplinas do mestrado e estimulou uma atitude de reflexão regular sobre as escolhas pedagógicas elaboradas e sobre a resposta dos alunos. Também o feedback dos professores da Unidade Curricular de Didáctica do Ensino Especializado foi essencial na consciencialização de aspectos que teriam que ser mudados na minha abordagem do ensino: fazer actividades mais formativas e menos avaliativas, dar mais feedback, não avançar para outro nível enquanto uma tarefa ainda não estiver consolidada, não modificar as instruções tão rapidamente, ter cuidado com a apresentação visual das células rítmicas e pensar em soluções para quando os alunos estão cansados. Foi também importante reflectir sobre os planos de aula realizados ao longo do ano e sobre o que não seria realizado da mesma forma, nomeadamente na introdução de células rítmicas, introdução de funções harmónicas e cadências. Durante este ano foi feito um esforço para melhorar estes aspectos, no entanto ainda não foi possível implementar todas as mudanças. De qualquer modo, esta reflexão é um bom ponto de partida para o planeamento do próximo ano e um exemplo da atitude que deve acompanhar-me durante toda a minha actividade enquanto docente.

Multi-strand narrative structures: a filmic game of multiple players

Session 7: Playing with Roles, images and improvising New States of Awareness, 3rd Global Conference, 1st November – 3rd November, 2014, Prague, Czech Republic.

Otimização estocástica para a exploração de centrais de concentração solar considerando incerteza e risco

Dissertação para obtenção do grau de Mestre em Engenharia Eletrotécnica

Deterministic approach for multiple-source tsunami hazard assessment for Sines, Portugal

In this paper, we present a deterministic approach to tsunami hazard assessment for the city and harbour of Sines, Portugal, one of the test sites of project ASTARTE (Assessment, STrategy And Risk Reduction for Tsunamis in Europe). Sines has one of the most important deep-water ports, which has oil-bearing, petrochemical, liquid-bulk, coal, and container terminals. The port and its industrial infrastructures face the ocean southwest towards the main seismogenic sources. This work considers two different seismic zones: the Southwest Iberian Margin and the Gloria Fault. Within these two regions, we selected a total of six scenarios to assess the tsunami impact at the test site. The tsunami simulations are computed using NSWING, a Non-linear Shallow Water model wIth Nested Grids. In this study, the static effect of tides is analysed for three different tidal stages: MLLW (mean lower low water), MSL (mean sea level), and MHHW (mean higher high water). For each scenario, the tsunami hazard is described by maximum values of wave height, flow depth, drawback, maximum inundation area and run-up. Synthetic waveforms are computed at virtual tide gauges at specific locations outside and inside the harbour. The final results describe the impact at the Sines test site considering the single scenarios at mean sea level, the aggregate scenario, and the influence of the tide on the aggregate scenario. The results confirm the composite source of Horseshoe and Marques de Pombal faults as the worst-case scenario, with wave heights of over 10 m, which reach the coast approximately 22 min after the rupture. It dominates the aggregate scenario by about 60 % of the impact area at the test site, considering maximum wave height and maximum flow depth. The HSMPF scenario inundates a total area of 3.5 km2. © Author(s) 2015.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.