Maintenance of fire sprinkler systems based on the dynamic assessment of its condition

Safety is one of the major concerns of process safety engineers in most industrial facilities all over the world. To this scope, some events play an important role once the effect of their consequences can be assumed as totally undesirable. One of these events refers to the occurrence of a fire. Such event can result in catastrophic consequences for life, equipment, and continuity of activities or even leading to environmental damage. A fire protection equipment with low reliability means that this equipment are often unavailable and thus the risk of a fire increases. Maintenance of fire protection equipment is very important because this kind of systems is mostly in a dormant mode, which gives uncertainty about their operability when demanded in a real situation of fire. This article outlines the importance of tests, inspection, and maintenance operations in the context of a fire sprinkler system and proposes a methodology based on international standards and supported by test/inspection reports to correct the frequency of these actions according to the level of degradation of the components and regarding safety purposes. © 2015 American Institute of Chemical Engineers.

Service-oriented mobility of java code in web services-based architectures

Dissertação apresentada na Faculdade de Ciências e Tecnologias da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Text classification using compression-based dissimilarity measures

Arguably, the most difficult task in text classification is to choose an appropriate set of features that allows machine learning algorithms to provide accurate classification. Most state-of-the-art techniques for this task involve careful feature engineering and a pre-processing stage, which may be too expensive in the emerging context of massive collections of electronic texts. In this paper, we propose efficient methods for text classification based on information-theoretic dissimilarity measures, which are used to define dissimilarity-based representations. These methods dispense with any feature design or engineering, by mapping texts into a feature space using universal dissimilarity measures; in this space, classical classifiers (e.g. nearest neighbor or support vector machines) can then be used. The reported experimental evaluation of the proposed methods, on sentiment polarity analysis and authorship attribution problems, reveals that it approximates, sometimes even outperforms previous state-of-the-art techniques, despite being much simpler, in the sense that they do not require any text pre-processing or feature engineering.

Media Brokerage: Agent-Based SLA Negotiation

Media content personalisation is a major challenge involving viewers as well as media content producer and distributor businesses. The goal is to provide viewers with media items aligned with their interests. Producers and distributors engage in item negotiations to establish the corresponding service level agreements (SLA). In order to address automated partner lookup and item SLA negotiation, this paper proposes the MultiMedia Brokerage (MMB) platform, which is a multiagent system that negotiates SLA regarding media items on behalf of media content producer and distributor businesses. The MMB platform is structured in four service layers: interface, agreement management, business modelling and market. In this context, there are: (i) brokerage SLA (bSLA), which are established between individual businesses and the platform regarding the provision of brokerage services; and (ii) item SLA (iSLA), which are established between producer and distributor businesses about the provision of media items. In particular, this paper describes the negotiation, establishment and enforcement of bSLA and iSLA, which occurs at the agreement and negotiation layers, respectively. The platform adopts a pay-per-use business model where the bSLA define the general conditions that apply to the related iSLA. To illustrate this process, we present a case study describing the negotiation of a bSLA instance and several related iSLA instances. The latter correspond to the negotiation of the Electronic Program Guide (EPG) for a specific end viewer.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

Demand Response Design and Use Based on Network Locational Marginal Prices

Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper proposes a methodology to support VPPs in the DR programs’ management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific programs in the LMP values supports the manager decision concerning the DR use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 33-bus network with intensive use of DG.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

The role of lifelong learning (LLL) in the creation of a european knowledge- based society

This chapter appears in Encyclopaedia of Human Resources Information Systems: Challenges in e-HRM edited by Torres-Coronas, T. and Arias-Oliva, M. Copyright 2009, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL:http://www.igi-pub.com/reference/details.asp?id=7737

Human capital in the knowledge-based society: comparative analysis: Romania-Portugal

The current economic crisis has rushed even more the economists’ concerns to identify new directions for the sustainable development of the society. In this context, the human capital is crystallised as the key variable of the creative economy and of the knowledge-based society. As such, we have directed the research underlying this paper to identifying the most eloquent indicators of human capital to meet the demands of the knowledge-based society and sustainable development as well as towards achieving a comprehensive analysis of the human capital in the EU countries, respectively of a comparative analysis: Romania - Portugal. To carry out this paper, the methodology used is based on the interdisciplinary triangulation involving approaches from the perspective of human resource management, economy and economic statistics. The research techniques used consist of the content analysis and investigation of secondary data of international organisations accredited in the field of this research, such as: the United Nation Development Programme - Human Development Reports, World Bank - World Development Reports, International Labour Organisation, Eurostat, European Commission’s Eurobarometer surveys and reports on human capital. The research results emphasise both similarities and differences between the two countries under the comparative analysis and the main directions in which one has to invest for the development of human capital.

Constraint-based modeling of minimum set covering: application to species differentation

Work presented in the context of the European Master in Computational Logics, as partial requisit for the graduation as Master in Computational Logics

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

CANDi: context-aware node discovery for short-range cooperation

Multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the benefits gained from multiple interfaces come at an expense—that being higher energy consumption in an era where mobile devices need to be energy compliant. One promising solution is the usage of short-range cooperative communication as an overlay for infrastructure-based networks taking advantage of its context information. However, the node discovery mechanism, which is pivotal to the bearer establishment process, still represents a major burden in terms of the total energy budget. In this paper, we propose a technology agnostic approach towards enhancing the MAC energy ratings by presenting a context-aware node discovery (CANDi) algorithm, which provides a priori knowledge towards the node discovery mechanism by allowing it to search nodes in the near vicinity at the ‘right time and at the right place’. We describe the different beacons required for establishing the cooperation, as well as the context information required, including battery level, modes, location and so on. CANDi uses the long-range network (WiMAX and WiFi) to distribute the context information about cooperative clusters (Ultra-wideband-based) in the vicinity. The searching nodes can use this context in locating the cooperative clusters/nodes, which facilitates the establishing of short-range connections. Analytical and simulation results are obtained, and the energy saving gains are further demonstrated in the laboratory using a customised testbed. CANDi saves up to 50% energy during the node discovery process, while the demonstrative testbed shows up to 75% savings in the total energy budget, thus validating the algorithm, as well as providing viable evidence to support the usage of short-range cooperative communications for energy savings.

A framework for robustness assessment in the context of corroded RC structures

Structural robustness is an emergent concept related to the structural response to damage. At the present time, robustness is not well defined and much controversy still remains around this subject. Even if robustness has seen growing interest as a consequence of catastrophic consequences due to extreme events, the fact is that the concept can also be very useful when considered on more probable exposure scenarios such as deterioration, among others. This paper intends to be a contribution to the definition of structural robustness, especially in the analysis of reinforced concrete structures subjected to corrosion. To achieve this, first of all, several proposed robustness definitions and indicators and misunderstood concepts will be analyzed and compared. From this point and regarding a concept that could be applied to most type of structures and dam-age scenarios, a robustness definition is proposed. To illustrate the proposed concept, an example of corroded reinforced concrete structures will be analyzed using nonlinear analysis numerical methods based on a contin-uum strong discontinuities approach and isotropic damage models for concrete. Finally the robustness of the presented example will be assessed.

A disposable glass-based immunosensor for monitoring the cancer biomarker CEA in urine

NanoPT 2014 International Conference, in Portugal, on February 12-14. Poster presentation based on topic Nanobio/Nanomedicine