Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

Dynamic and interaction of cytochrome c with Pf1 virus

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em BioOrgânica

Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

Selection Constructive based Hyper-heuristic for Dynamic Scheduling

A função de escalonamento desempenha um papel importante nos sistemas de produção. Os sistemas de escalonamento têm como objetivo gerar um plano de escalonamento que permite gerir de uma forma eficiente um conjunto de tarefas que necessitam de ser executadas no mesmo período de tempo pelos mesmos recursos. Contudo, adaptação dinâmica e otimização é uma necessidade crítica em sistemas de escalonamento, uma vez que as organizações de produção têm uma natureza dinâmica. Nestas organizações ocorrem distúrbios nas condições requisitos de trabalho regularmente e de forma inesperada. Alguns exemplos destes distúrbios são: surgimento de uma nova tarefa, cancelamento de uma tarefa, alteração na data de entrega, entre outros. Estes eventos dinâmicos devem ser tidos em conta, uma vez que podem influenciar o plano criado, tornando-o ineficiente. Portanto, ambientes de produção necessitam de resposta imediata para estes eventos, usando um método de reescalonamento em tempo real, para minimizar o efeito destes eventos dinâmicos no sistema de produção. Deste modo, os sistemas de escalonamento devem de uma forma automática e inteligente, ser capazes de adaptar o plano de escalonamento que a organização está a seguir aos eventos inesperados em tempo real. Esta dissertação aborda o problema de incorporar novas tarefas num plano de escalonamento já existente. Deste modo, é proposta uma abordagem de otimização – Hiper-heurística baseada em Seleção Construtiva para Escalonamento Dinâmico- para lidar com eventos dinâmicos que podem ocorrer num ambiente de produção, a fim de manter o plano de escalonamento, o mais robusto possível. Esta abordagem é inspirada em computação evolutiva e hiper-heurísticas. Do estudo computacional realizado foi possível concluir que o uso da hiper-heurística de seleção construtiva pode ser vantajoso na resolução de problemas de otimização de adaptação dinâmica.

Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid Network

IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Embedded Multi-Core systems for Mixed Criticality applications in dynamic and changeable real-time environments

EMC2 finds solutions for dynamic adaptability in open systems. It provides handling of mixed criticality multicore applications in r eal-time conditions, withscalability and utmost flexibility, full-scale deployment and management of integrated tool chains, through the entire lifecycle.

Asymmetric dynamic price competition with uncertainty

We consider a dynamic setting-price duopoly model in which a dominant (leader) firm moves first and a subordinate (follower) firm moves second. We suppose that each firm has two different technologies, and uses one of them according to a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We analyse the effect of the production costs uncertainty on the profits of the firms, for different values of the intercept demand parameters.

Dynamic stability metrics for the container loading problem

The Container Loading Problem (CLP) literature has traditionally evaluated the dynamic stability of cargo by applying two metrics to box arrangements: the mean number of boxes supporting the items excluding those placed directly on the floor (M1) and the percentage of boxes with insufficient lateral support (M2). However, these metrics, that aim to be proxies for cargo stability during transportation, fail to translate real-world cargo conditions of dynamic stability. In this paper two new performance indicators are proposed to evaluate the dynamic stability of cargo arrangements: the number of fallen boxes (NFB) and the number of boxes within the Damage Boundary Curve fragility test (NB_DBC). Using 1500 solutions for well-known problem instances found in the literature, these new performance indicators are evaluated using a physics simulation tool (StableCargo), replacing the real-world transportation by a truck with a simulation of the dynamic behaviour of container loading arrangements. Two new dynamic stability metrics that can be integrated within any container loading algorithm are also proposed. The metrics are analytical models of the proposed stability performance indicators, computed by multiple linear regression. Pearson’s r correlation coefficient was used as an evaluation parameter for the performance of the models. The extensive computational results show that the proposed metrics are better proxies for dynamic stability in the CLP than the previous widely used metrics.

Organising interoperability information on highly dynamic and heterogeneous environments

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Focal Malignant Liver Lesions: Diagnosis by Dynamic Incremental CT, Early Phase

The purpose of our study was to evaluate the accuracy of dynamic incremental bolus-enhanced conventional CT (DICT) with intravenous contrast administration, early phase, in the diagnosis of malignancy of focal liver lesions. A total of 122 lesions were selected in 74 patients considering the following criteria: lesion diameter 10 mm or more, number of lesions less than six per study, except in multiple angiomatosis and the existence of a valid criteria of definitive diagnosis. Lesions were categorized into seven levels of diagnostic confidence of malignancy compared with the definitive diagnosis for acquisition of a receiver-operator-characteristic (ROC) curve analysis and to determine the sensitivity and specificity of the technique. Forty-six and 70 lesions were correctly diagnosed as malignant and benign, respectively; there were 2 false-positive and 4 false-negative diagnoses of malignancy and the sensitivity and specificity obtained were 92 and 97%. The DICT early phase was confirmed as a highly accurate method in the characterization and diagnosis of malignancy of focal liver lesions, requiring an optimal technical performance and judicious analysis of existing semiological data.

Muscarinic antibodies and heart rate responses to dynamic exercise and to the Valsalva maneuver in chronic chagasic patients

We have studied the cardiac chronotropic responses to the Valsalva maneuver and to dynamic exercise of twenty chronic chagasic patients with normal left ventricular function and no segmental wall abnormalities by two-dimensional echocardiogram. The absolute increase in heart rate of the patients (Δ = 21.5 ± 10 bpm, M±SD) during the maneuver was significantly diminished when compared to controls (Δ = 31.30 ± 70, M±SD, p = 0.03). The minimum heart rate (58.24 ± 8.90 vs. 62.80 ± 10, p = 0.68) and the absolute decrease in heart rate at the end of the maneuver (Δ = 38.30 ± 13 vs. Δ = 31.47 ± 17, p = 0.10) were not different from controls. The initial heart rate acceleration during dynamic exercise (Δ = 12 ± 7.55 vs. Δ = 19 ± 7.27, M±SD, p = 0.01) was also diminished, but the heart rate recovery during the first ten seconds was more prominent in the sero-positive patients (Median: 14, Interquartile range: (9.75-17.50 vs. 5(0-8.75, p = 0.001). The serum levels of muscarinic cardiac auto-antibodies were significantly higher in the chagasic patients (Median: 34.58, Interquartile Range: 17-46.5, Optical Density) than in controls (Median: 0, Interquartile Range: 0-22.25, p = 0.001) and correlated significantly and directly (r = 0.68, p = 0.002) with early heart rate recovery during dynamic exercise. The results of this investigation indirectly suggest that, the cardiac muscarinic auto-antibodies may have positive agonist effects on parasympathetic heart rate control of chagasic patients.

Sustainability of systems interoperability in dynamic business networks

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

Evaluating Dynamic Signage for Emergency Evacuation using an Immersive Video Environment

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.