A Data-mining-based Methodology to support MV Electricity Customers' Characterization

This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

Conservation GIS: Ontology and spatial reasoning for commonsense knowledge.

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

Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Migration and urban schistosomiasis. The case of São Lourenço da Mata, Northeast of Brazil

A population-based case-control design was used to investigate the association between migration, urbanisation and schistosomiasis in the Metropolitan Region of Recife, Northeast of Brazil. 1022 cases and 994 controls, aged 10 to 25, were selected. The natives and the migrants who come from endemic areas have a similar risk of infection. On the other hand, the risk of infection of migrants from nonendemic areas seems to be related with the time elapsed since their arrival in São Lourenço da Mata; those who have been living in that urban area for 5 or more years have a risk of infection similar to that of the natives. Those arriving in the metropolitan region of Recife mostly emigrate from "zona da mata" and "zona do agreste" in the state of Pernambuco. Due to the changes in the sugar agro-industry and to the increase in the area used for cattle grazing these workers were driven to villages and cities. The pattern of urbanisation created the conditions for the establishment of foci of transmission in São Lourenço da Mata.

Are societal changes new? Questions or trends and future perceptions on knowledge-based economy

With the emergence of a global division of labour, the internationalisation of markets and cultures, the growing power of supranational organisations and the spread of new information technologies to every field of life, it starts to appear a different kind of society, different from the industrial society, and called by many as ‘the knowledge-based economy’, emphasizing the importance of information and knowledge in many areas of work and organisation of societies. Despite the common trends of evolution, these transformations do not necessarily produce a convergence of national and regional social and economic structures, but a diversity of realities emerging from the relations between economic and political context on one hand and the companies and their strategies on the other. In this sense, which future can we expect to the knowledge economy? How can we measure it and why is it important? This paper will present some results from the European project WORKS – Work organisation and restructuring in the knowledge society (6th Framework Programme), focusing the future visions and possible future trends in different countries, sectors and industries, given empirical evidences of the case studies applied in several European countries, underling the importance of foresight exercises to design policies, prevent uncontrolled risks and anticipate alternatives, leading to different ‘knowledge economies’ and not to the ‘knowled

Innovation assessment in a local branch of a rail transport manufacture industry - A case study

Based on a poster submitted to CONCORD 2011 - Conference on Corporate R&D: The dynamics of Europe's industrial structure and the growth of innovative firms, Sevilla, IPTS, 6 Out. 2011, Seville, http://www.eventisimo.com/concord2011/recibido.html

Combining open and closed world reasoning for the semantic web

Dissertação para obtenção do Grau de Doutor em Informática

A retrospective evaluation of a score system adopted by the Ministry of Health, Brazil in the diagnosis of pulmonary tuberculosis in childhood: a case control study

Based on a retrospective case-control study we evaluated the score system adopted by the Ministry of Health of Brazil (Ministério da Saúde - MS), to diagnose pulmonary tuberculosis (PTB) in childhood. This system is independent of bacteriological or histopathological data to define a very likely (> or = 40 points), possible (30-35 points) or unlikely (< or = 25 points) diagnosis of tuberculosis. Records of hospitalized non-infected HIV children at the Instituto de Puericultura e Pediatria Martagão Gesteira of Federal University of Rio de Janeiro (IPPMG-UFRJ), were reviewed. Patients were adjusted for age and divided in two different groups: 45 subjects in the case group (culture-positive) [mean of age = 10.64 mo; SD 9.66]; and 96 in the control group (culture-negative and clinic criteria that dismissed the disease) [mean of age = 11.79 mo.; SD 11.31]. Among the variables analyzed, the radiological status had the greater impact into the diagnosis (OR = 25.39), followed by exposure to adult with tuberculosis (OR = 10.67), tuberculin skin test >10mm (OR = 8.23). The best cut-off point to the diagnosis of PTB was 30 points, where the score system was more accurate, with sensitivity of 88.9% and specificity of 86.5%.

Larva migrans: a case report and review

A case of massive Ancylostoma sp. larval infestation is presented in a patient who had received systemic corticosteroid therapy. What attracts attention in this case is the exuberance and rarity of clinical manifestation. Based on the pertinent literature, we discuss the mechanisms of parasital infection, the natural history of the disease and its treatment.

Towards Certifiable Multicore-based Platforms for Avionics

Work in Progress Session, 21st IEEE Real-Time and Embedded Techonology and Applications Symposium (RTAS 2015). 13 to 16, Apr, 2015, pp 27-28. Seattle, U.S.A..

Bringing Context Awareness to IoT-Based Wireless Sensor Networks

IEEE International Conference on Pervasive Computing and Communications (PerCom). 23 to 26, Mar, 2015, PhD Forum. Saint Louis, U.S.A..

Introducing numerical analysis tools in engineering: a Scilab user case in electronics course

Software tools in education became popular since the widespread of personal computers. Engineering courses lead the way in this development and these tools became almost a standard. Engineering graduates are familiar with numerical analysis tools but also with simulators (e.g. electronic circuits), computer assisted design tools and others, depending on the degree. One of the main problems with these tools is when and how to start use them so that they can be beneficial to students and not mere substitutes for potentially difficult calculations or design. In this paper a software tool to be used by first year students in electronics/electricity courses is presented. The growing acknowledgement and acceptance of open source software lead to the choice of an open source software tool – Scilab, which is a numerical analysis tool – to develop a toolbox. The toolbox was developed to be used as standalone or integrated in an e-learning platform. The e-learning platform used was Moodle. The first approach was to assess the mathematical skills necessary to solve all the problems related to electronics and electricity courses. Analysing the existing circuit simulators software tools, it is clear that even though they are very helpful by showing the end result they are not so effective in the process of the students studying and self learning since they show results but not intermediate steps which are crucial in problems that involve derivatives or integrals. Also, they are not very effective in obtaining graphical results that could be used to elaborate reports and for an overall better comprehension of the results. The developed tool was based on the numerical analysis software Scilab and is a toolbox that gives their users the opportunity to obtain the end results of a circuit analysis but also the expressions obtained when derivative and integrals calculations, plot signals, obtain vector diagrams, etc. The toolbox runs entirely in the Moodle web platform and provides the same results as the standalone application. The students can use the toolbox through the web platform (in computers where they don't have installation privileges) or in their personal computers by installing both the Scilab software and the toolbox. This approach was designed for first year students from all engineering degrees that have electronics/electricity courses in their curricula.

Passive Fault-Tolerance Management in Component-based Embedded Systems

It is imperative to accept that failures can and will occur, even in meticulously designed distributed systems, and design proper measures to counter those failures. Passive replication minimises resource consumption by only activating redundant replicas in case of failures, as typically providing and applying state updates is less resource demanding than requesting execution. However, most existing solutions for passive fault tolerance are usually designed and configured at design time, explicitly and statically identifying the most critical components and their number of replicas, lacking the needed flexibility to handle the runtime dynamics of distributed component-based embedded systems. This paper proposes a cost-effective adaptive fault tolerance solution with a significant lower overhead compared to a strict active redundancy-based approach, achieving a high error coverage with the minimum amount of redundancy. The activation of passive replicas is coordinated through a feedback-based coordination model that reduces the complexity of the needed interactions among components until a new collective global service solution is determined, improving the overall maintainability and robustness of the system.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.