Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

Remediation of soils combining soil vapor extraction and bioremediation: benzene

This work reports the study of the combination of soil vapor extraction (SVE) with bioremediation (BR) to remediate soils contaminated with benzene. Soils contaminated with benzene with different water and natural organic matter contents were studied. The main goals were: (i) evaluate the performance of SVE regarding the remediation time and the process efficiency; (ii) study the combination of both technologies in order to identify the best option capable to achieve the legal clean up goals; and (iii) evaluate the influence of soil water content (SWC) and natural organic matter (NOM) on SVE and BR. The remediation experiments performed in soils contaminated with benzene allowed concluding that: (i) SVE presented (a) efficiencies above 92% for sandy soils and above 78% for humic soils; (b) and remediation times from 2 to 45 h, depending on the soil; (ii) BR showed to be an efficient technology to complement SVE; (iii) (a) SWC showed minimum impact on SVE when high airflow rates were used and led to higher remediation times for lower flow rates; (b) NOM as source of microorganisms and nutrients enhanced BR but hindered the SVE due the limitation on the mass transfer of benzene from the soil to the gas phase.

Combining RTSJ with Fork/Join: a priority-based model

This paper discusses the increased need to support dynamic task-level parallelism in embedded real-time systems and proposes a Java framework that combines the Real-Time Specification for Java (RTSJ) with the Fork/Join (FJ) model, following a fixed priority-based scheduling scheme. Our work intends to support parallel runtimes that will coexist with a wide range of other complex independently developed applications, without any previous knowledge about their real execution requirements, number of parallel sub-tasks, and when those sub-tasks will be generated.

Combining global tabu search with local search for solving systems of equalities and inequalities

This papers aims at providing a combined strategy for solving systems of equalities and inequalities. The combined strategy uses two types of steps: a global search step and a local search step. The global step relies on a tabu search heuristic and the local step uses a deterministic search known as Hooke and Jeeves. The choice of step, at each iteration, is based on the level of reduction of the l2-norm of the error function observed in the equivalent system of equations, compared with the previous iteration.

Combining sparse and dense methods in 6D Visual Odometry

13th International Conference on Autonomous Robot Systems (Robotica), 2013, Lisboa

The prominence of social responsibility disclosure in Portuguese companies’ web pages

This study investigates Portuguese companies’ use of the Internet to communicate social responsibility information, and the factors that affect this use. It examines the characteristics of companies that influence the prominence of social responsibility information on the Internet. Firm-specific factors that explain SRD by companies operating in a European country in which capital market fund raising is not regarded to be an important source of financing are analysed. The results are interpreted through the lens of a “political economy” framework which combines stakeholder and legitimacy theories perspectives, according to which companies disclose social responsibility information to present a socially responsible image so that they can legitimise their behaviours to their stakeholder groups and influence the external perception of reputation. Results suggest that a theoretical framework combining stakeholder and legitimacy theories may provide an explanatory basis for SRD by Portuguese companies. However, this study does not provide us with enough evidence to determine that the prominence given to CSR activities by Portuguese companies in their websites is linked to relationships with their stakeholders

Creativity and digital spaces in the intercultural society

In Permanent Transit: Discourses and Maps of the Intercultural Experience builds interdisciplinary approaches to the study of migrations, traffics, globalization, communication, regulations, arts, literature, and other intercultural processes, in the context of past and present times. The book offers a convergence of perspectives, combining conceptual and empirical work by sociologists, anthropologists, historians, linguists, educators, lawyers, media, specialists, and literary studies writers, in their shared attempt to understand the many routes of the intercultural experience. In Permanent Transit: Discourses and Maps of the Intercultural Experience builds interdisciplinary approaches to the study of migrations, traffics, globalization, communication, regulations, arts, literature, and other intercultural processes, in the context of past and present times. The book offers a convergence of perspectives, combining conceptual and empirical work by sociologists, anthropologists, historians, linguists, educators, lawyers, media, specialists, and literary studies writers, in their shared attempt to understand the many routes of the intercultural experience.

Capacidade de modificar parâmetros espaço-temporais do ciclo da marcha após modificação de componentes intrínsecas ao membro inferior em indivíduos com sequelas de acidente vascular encefálico - intervenção na reeducação da marcha em treadmill

Objectivo: A realização deste estudo tem como objectivo identificar a capacidade de modificação dos parâmetros do ciclo da marcha após intervenção a nível dos componentes do membro inferior e uma abordagem na reeducação da marcha no tapete rolante (treadmill). Métodos: Este estudo é um estudo de série de casos, constituído por três indivíduos com sequelas de Acidente Vascular Encefálico (AVE), com comprometimento a nível do membro inferior, capazes de realizar marcha. Os instrumentos de avaliação foram o teste de marcha de 10 metros (10-M), o teste de marcha de 6 minutos (6-Min) e o Time Up and Go (TUG). Os indivíduos receberam intervenção da fisioterapia baseada no conceito de Bobath e na reeducação de marcha no treadmill. Resultados: Após a intervenção verificou-se um aumento da velocidade e cadência da marcha, assim como uma maior tolerância e resistência na capacidade da sua realização. Conclusão: A intervenção realizada a nível dos componentes do membro inferior e na reeducação da marcha utilizando o treadmill permitiu modificar alguns parâmetros espaço-temporais do ciclo da marcha, aumentando a velocidade e cadência da marcha. A utilização conjunta de diferentes abordagens na intervenção ao indivíduo com sequelas de AVE deve ser sempre considerada uma vez que pode trazer benefícios na sua independência e qualidade de vida.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

Research on evaluation system of emergency disposal plan for power plant incidents

This paper starts with the analysis of the unusual inherence mechanism, from two aspects: accumulating and human error. We put forward twelve factors affected the decision of the emergency treatment plan in practice and summarized the evaluation index system combining with literature data. Then we screened out eighteen representative indicators by used the FDM expert questionnaire in the first phase. Hereafter, we calculated the weight of evaluation index and sorted them by the FAHP expert questionnaire, and came up with the frame of the evaluation rule by combined with the experience. In the end, the evaluation principles are concluded.

Multi-dimensional scaling applied to histogram-based DNA analysis

This paper aims to study the relationships between chromosomal DNA sequences of twenty species. We propose a methodology combining DNA-based word frequency histograms, correlation methods, and an MDS technique to visualize structural information underlying chromosomes (CRs) and species. Four statistical measures are tested (Minkowski, Cosine, Pearson product-moment, and Kendall τ rank correlations) to analyze the information content of 421 nuclear CRs from twenty species. The proposed methodology is built on mathematical tools and allows the analysis and visualization of very large amounts of stream data, like DNA sequences, with almost no assumptions other than the predefined DNA “word length.” This methodology is able to produce comprehensible three-dimensional visualizations of CR clustering and related spatial and structural patterns. The results of the four test correlation scenarios show that the high-level information clusterings produced by the MDS tool are qualitatively similar, with small variations due to each correlation method characteristics, and that the clusterings are a consequence of the input data and not method’s artifacts.

Self-optimizing through CBR learning

In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

Autonomic computing for scheduling in manufacturing systems

We describe a novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm aiming at embedding applications with a management structure similar to a central nervous system. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. In this paper we envisage the use of Multi-Agent Systems paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with Autonomic properties, in order to reduce the complexity of managing systems and human interference. Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems.

VirtualECare: group decision supported by idea generation and argumentation

In the last years there has been a considerable increase in the number of people in need of intensive care, especially among the elderly, a phenomenon that is related to population ageing (Brown 2003). However, this is not exclusive of the elderly, as diseases as obesity, diabetes, and blood pressure have been increasing among young adults (Ford and Capewell 2007). As a new fact, it has to be dealt with by the healthcare sector, and particularly by the public one. Thus, the importance of finding new and cost effective ways for healthcare delivery are of particular importance, especially when the patients are not to be detached from their environments (WHO 2004). Following this line of thinking, a VirtualECare Multiagent System is presented in section 2, being our efforts centered on its Group Decision modules (Costa, Neves et al. 2007) (Camarinha-Matos and Afsarmanesh 2001).On the other hand, there has been a growing interest in combining the technological advances in the information society - computing, telecommunications and knowledge – in order to create new methodologies for problem solving, namely those that convey on Group Decision Support Systems (GDSS), based on agent perception. Indeed, the new economy, along with increased competition in today’s complex business environments, takes the companies to seek complementarities, in order to increase competitiveness and reduce risks. Under these scenarios, planning takes a major role in a company life cycle. However, effective planning depends on the generation and analysis of ideas (innovative or not) and, as a result, the idea generation and management processes are crucial. Our objective is to apply the GDSS referred to above to a new area. We believe that the use of GDSS in the healthcare arena will allow professionals to achieve better results in the analysis of one’s Electronically Clinical Profile (ECP). This attainment is vital, regarding the incoming to the market of new drugs and medical practices, which compete in the use of limited resources.