Uma Abordagem para a Geração de Casos de Teste Baseada em Modelos

Abstract — The analytical methods based on evaluation models of interactive systems were proposed as an alternative to user testing in the last stages of the software development due to its costs. However, the use of isolated behavioral models of the system limits the results of the analytical methods. An example of these limitations relates to the fact that they are unable to identify implementation issues that will impact on usability. With the introduction of model-based testing we are enable to test if the implemented software meets the specified model. This paper presents an model-based approach for test cases generation from the static analysis of source code.

Dense motion field estimation from myocardial boundary displacements

Minimally invasive cardiovascular interventions guided by multiple imaging modalities are rapidly gaining clinical acceptance for the treatment of several cardiovascular diseases. These images are typically fused with richly detailed pre-operative scans through registration techniques, enhancing the intra-operative clinical data and easing the image-guided procedures. Nonetheless, rigid models have been used to align the different modalities, not taking into account the anatomical variations of the cardiac muscle throughout the cardiac cycle. In the current study, we present a novel strategy to compensate the beat-to-beat physiological adaptation of the myocardium. Hereto, we intend to prove that a complete myocardial motion field can be quickly recovered from the displacement field at the myocardial boundaries, therefore being an efficient strategy to locally deform the cardiac muscle. We address this hypothesis by comparing three different strategies to recover a dense myocardial motion field from a sparse one, namely, a diffusion-based approach, thin-plate splines, and multiquadric radial basis functions. Two experimental setups were used to validate the proposed strategy. First, an in silico validation was carried out on synthetic motion fields obtained from two realistic simulated ultrasound sequences. Then, 45 mid-ventricular 2D sequences of cine magnetic resonance imaging were processed to further evaluate the different approaches. The results showed that accurate boundary tracking combined with dense myocardial recovery via interpolation/ diffusion is a potentially viable solution to speed up dense myocardial motion field estimation and, consequently, to deform/compensate the myocardial wall throughout the cardiac cycle. Copyright © 2015 John Wiley & Sons, Ltd.

BRAND EQUITY OF LAHORE FORT AS A TOURISM DESTINATION BRAND

ABSTRACTStudies that measure the brand equity of destination brands by using the Customer-Based Brand Equity (CBBE) model in a developing country context are scarce. The present study investigates the destination brand equity of the Lahore Fort by employing the CBBE model in a developing country context of Pakistan. Following the positivist tradition, we adopted a survey-based approach to collect data from 237 tourists visiting the Lahore Fort. Data were collected through a questionnaire developed to explain the relationship of brand awareness, brand image, brand association, and brand loyalty with Lahore Fort’s overall brand equity. We used various robust statistical techniques such as correlation, regression and confirmatory factor analysis (using PLS method) to reach meaningful conclusions and found that brand image and brand associations positively contribute to brand loyalty. Furthermore, brand loyalty significantly contributes towards overall brand equity. Pragmatically, this study measures the customer based brand equity of the Lahore Fort, a destination brand. The results are useful as they suggest a few strategies that can help policy makers to enhance Lahore Fort’s brand performance.

Delineamento do papel profissional dos especialistas em Educação em Saúde: uma proposta técnica

Objetivou-se apreciar as responsabilidades, competências e subcompetências dos especialistas em Educação em Saúde da Secretaria da Saúde do Estado de São Paulo, Brasil, e verificar se há ou não convergência na proposta da atuação técnica desses profissionais de saúde no Brasil e nos Estados Unidos. Utilizou-se, como base para as perguntas incluídas em questionários respondidos por educadores em saúde, o documento intitulado, "A Framework for the Development of Competency - based Curricula for Entry - Level Health Education". Os resultados descrevem o grau de importância atribuída às responsabilidades técnicas e à freqüência com que estas se realizam na rede de serviços estudada.

Efeito de uma intervenção em crianças com hemiparésia espástica ao nível dos ajustes posturais anticipatórios no início da marcha

Objectivos: Verificar o efeito de uma intervenção baseada na abordagem segundo o Conceito de Bobath nos Ajustes Posturais Anticipatórios no Início da Marcha em duas crianças com hemiparésia espástica. Pretendeu-se ainda, verificar o efeito desta abordagem nas actividades e participação, bem como comparar os aspectos individuais das duas crianças com a capacidade de mudança após a intervenção. Metodologia: A avaliação foi realizada antes e três meses após a intervenção através da Electromiografia, da Plataforma de Forças, de um sistema de Câmaras de Vídeo, de uma Máquina Fotográfica e da Classificação Internacional de Funcionalidade para Crianças e Jovens. Resultados: A sequência de activação muscular alterou-se apenas na criança A. A postura na posição de pé, a actividade muscular, o deslocamento do centro de pressão e as actividades e participação modificaram-se em ambas as crianças, sendo que a criança A apresentou maior capacidade de mudança. Conclusão: A intervenção com base numa abordagem segundo o conceito de Bobath induziu mudanças positivas nos Ajustes Posturais Anticipatórios e nas actividades e participação dos casos em estudo.

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

Metamorfoses identitárias em contexto institucional

Dissertação de Mestrado, Sociologia, 4 de Abril de 2014, Universidade dos Açores.

Long-term modifications of coastal defences enhance marine biodiversity

Realization that hard coastal infrastructures support lower biodiversity than natural habitats has prompted a wealth of research seeking to identify design enhancements offering ecological benefits. Some studies showed that artificial structures could be modified to increase levels of diversity. Most studies, however, only considered the short-term ecological effects of such modifications, even though reliance on results from short-term studies may lead to serious misjudgements in conservation. In this study, a sevenyear experiment examined how the addition of small pits to otherwise featureless seawalls may enhance the stocks of a highly-exploited limpet. Modified areas of the seawall supported enhanced stocks of limpets seven years after the addition of pits. Modified areas of the seawall also supported a community that differed in the abundance of littorinids, barnacles andmacroalgae compared to the controls. Responses to different treatments (numbers and size of pits) were speciesspecific and, while some species responded directly to differences among treatments, others might have responded indirectly via changes in the distribution of competing species. This type of habitat enhancement can have positive long-lasting effects on the ecology of urban seascapes.Understanding of species interactions could be used to develop a rule-based approach to enhance biodiversity.

Hyperspectral subspace identification

Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.

Orchestration of e-learning services for automatic evaluation of programming exercises

Managing programming exercises require several heterogeneous systems such as evaluation engines, learning objects repositories and exercise resolution environments. The coordination of networks of such disparate systems is rather complex. These tools would be too specific to incorporate in an e-Learning platform. Even if they could be provided as pluggable components, the burden of maintaining them would be prohibitive to institutions with few courses in those domains. This work presents a standard based approach for the coordination of a network of e-Learning systems participating on the automatic evaluation of programming exercises. The proposed approach uses a pivot component to orchestrate the interaction among all the systems using communication standards. This approach was validated through its effective use on classroom and we present some preliminary results.

A framework for programming sensor networks with scheduling and resource-sharing optimizations

Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

Virtual laboratory for educational environments

In this paper a new simulation environment for a virtual laboratory to educational proposes is presented. The Logisim platform was adopted as the base digital simulation tool, since it has a modular implementation in Java. All the hardware devices used in the laboratory course was designed as components accessible by the simulation tool, and integrated as a library. Moreover, this new library allows the user to access an external interface. This work was motivated by the needed to achieve better learning times on co-design projects, based on hardware and software implementations, and to reduce the laboratory time, decreasing the operational costs of engineer teaching. Furthermore, the use of virtual laboratories in educational environments allows the students to perform functional tests, before they went to a real laboratory. Moreover, these functional tests allow to speed-up the learning when a problem based approach methodology is considered. © 2014 IEEE.

A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.