Procura distribuída de soluções com restrições locais e globais

Esta dissertação aborda a procura distribuída de soluções baseando-se em cenários cuja informação não esteja totalmente disponível, por não ser possível ou mesmo porque não é desejável. Os dois tipos de problemas abordados neste trabalho são: i) o problema de atribuição de tarefas, e ii) o problema de agendamento de eventos. O problema de atribuição de tarefas é ilustrado num cenário de catástrofe (atribuição de incêndios a bombeiros) cujos agentes tentam encontrar a melhor solução global de acordo com as capacidades de cada um. O problema do agendamento de eventos com múltiplos recursos, ocorre numa organiza- ção que pretende maximizar o valor do tempo dos seus empregados, enquanto preserva o valor individual (privacidade) atribuído ao evento (valor da importância relativa do evento). Estes problemas são explorados para confrontar os dois tipos de abordagem na sua resolução: centralizada e distribuída. Os problemas são formulados para resolução de maneira distribuída e centralizada, de modo a evidenciar as suas características e as situações em que fará mais sentido a utilização de cada abordagem. O desempenho a nível de tempo de execução e consumo de memória, bem como o conceito de privacidade são os pontos considerados no comparativo das abordagens centralizada e distribuída. Para analisar o problema de atribuição de tarefas e o problema de agendamento de eventos, é proposto um modelo que integra dois tipos de formulação de problemas distribuídos, e que utiliza um algoritmo distribuído para a resolução dos mesmos.

Cape Verde hotspot from the upper crust to the top of the lower mantle

We investigate the crust, upper mantle and mantle transition zone of the Cape Verde hotspot by using seismic P and S receiver functions from several tens of local seismograph stations. We find a strong discontinuity at a depth of similar to 10 km underlain by a similar to 15-km thick layer with a high (similar to 1.9) Vp/Vs velocity ratio. We interpret this discontinuity and the underlying layer as the fossil Moho, inherited from the pre-hotspot era, and the plume-related magmatic underplate. Our uppermost-mantle models are very different from those previously obtained for this region: our S velocity is much lower and there are no indications of low densities. Contrary to previously published arguments for the standard transition zone thickness our data indicate that this thickness under the Cape Verde islands is up to similar to 30 km less than in the ambient mantle. This reduction is a combined effect of a depression of the 410-km discontinuity and an uplift of the 660-km discontinuity. The uplift is in contrast to laboratory data and some seismic data on a negligible dependence of depth of the 660-km discontinuity on temperature in hotspots. A large negative pressure-temperature slope which is suggested by our data implies that the 660-km discontinuity may resist passage of the plume. Our data reveal beneath the islands a reduction of S velocity of a few percent between 470-km and 510-km depths. The low velocity layer in the upper transition zone under the Cape Verde archipelago is very similar to that previously found under the Azores and a few other hotspots. In the literature there are reports on a regional 520-km discontinuity, the impedance of which is too large to be explained by the known phase transitions. Our observations suggest that the 520-km discontinuity may present the base of the low-velocity layer in the transition zone. (C) 2011 Elsevier B.V. All rights reserved.

Water quality in lakes and reservoirs in China

Dissertation elaborated for the partial fulfilment of the requirements of the Master Degree in Civil Engineering in the Speciality Area of Hydarulics

Risk Analysis and Behavior of Electricity Portfolio Aggregator

The scope of this paper is to adapt the standard mean-variance model of Henry Markowitz theory, creating a simulation tool to find the optimal configuration of the portfolio aggregator, calculate its profitability and risk. Currently, there is a deep discussion going on among the power system society about the structure and architecture of the future electric system. In this environment, policy makers and electric utilities find new approaches to access the electricity market; this configures new challenging positions in order to find innovative strategies and methodologies. Decentralized power generation is gaining relevance in liberalized markets, and small and medium size electricity consumers are also become producers (“prosumers”). In this scenario an electric aggregator is an entity that joins a group of electric clients, customers, producers, “prosumers” together as a single purchasing unit to negotiate the purchase and sale of electricity. The aggregator conducts research on electricity prices, contract terms and conditions in order to promote better energy prices for their clients and allows small and medium customers to benefit improved market prices.

A Spatial Econometrics Analysis for Road Accidents in Lisbon

This paper presents a spatial econometrics analysis for the number of road accidents with victims in the smallest administrative divisions of Lisbon, considering as a baseline a log-Poisson model for environmental factors. Spatial correlation on data is investigated for data alone and for the residuals of the baseline model without and with spatial-autocorrelated and spatial-lagged terms. In all the cases no spatial autocorrelation was detected.

Generalized models from Beta(p,2) densities with strong allee effect: dynamical approach

A dynamical approach to study the behaviour of generalized populational growth models from Bets(p, 2) densities, with strong Allee effect, is presented. The dynamical analysis of the respective unimodal maps is performed using symbolic dynamics techniques. The complexity of the correspondent discrete dynamical systems is measured in terms of topological entropy. Different populational dynamics regimes are obtained when the intrinsic growth rates are modified: extinction, bistability, chaotic semistability and essential extinction.

Dossiê os livreiros e o seu património

Este dossiê representa a continuidade de um projecto que tem procurado debater publi­camente o património dos agentes ligados à produção e circulação do livro. Centrando-se nos espólios dos livreiros, a introdução problematizante e os depoimentos procuram dis­cutir o seu carácter invisível enquanto objecto de pesquisa, salvaguarda e divulgação. Há, então, uma reflexão que urge fazer, à semelhança do que ocorre com o património dos edi­tores (arquivos históricos e não só), no sentido de reconhecer o estatuto patrimonial e histó­rico dos acervos dos livreiros e das livrarias enquanto espaços fundamentais da construção da cultura impressa e da história do livro e da edição. Mas é também urgente conferir ao debate um cunho de acção e de cooperação inter-institucional que suscitem uma sensibili­dade política e o aparecimento de possibilidades concretas de salvamento, recolha e depó­sito sistemático de um dos mais fundamentais elementos da memória colectiva escrita. Os depoimentos referidos são de Fátima Ribeiro de Medeiros e dos Livreiros da Sá da Costa.

On performance of distributed model predictive control in power system frequency regulation

This paper describes the implementation of a distributed model predictive approach for automatic generation control. Performance results are discussed by comparing classical techniques (based on integral control) with model predictive control solutions (centralized and distributed) for different operational scenarios with two interconnected networks. These scenarios include variable load levels (ranging from a small to a large unbalance generated power to power consumption ratio) and simultaneously variable distance between the interconnected networks systems. For the two networks the paper also examines the impact of load variation in an island context (a network isolated from each other).

Hydraulic binders

Hydraulic binders play a vital role in the economic and social development because they are essential components of concrete, the most widely used construction material. Nowadays, Portland cement is the most predominantly used hydraulic binder due to its properties and widespread availability. Cement manufacture consumes large amount of non-renewable raw materials and energy, and it is a carbon-intensive process. Many efforts are, therefore, being undertaken towards the developing “greener” hydraulic binders. Concomitantly, binders must also correspond to market demand in terms of performance and aesthetic as well as fulfill mandatory regulations. In order to pursue these goals, different approaches have been followed including the improvement of the cement manufacturing process, production of blended cements, and testing innovative hydraulic binders with a different chemistry. This chapter presents a brief history of hydraulic binder’s discovery and use as well as the environmental and economic context of cement industry. It, then, describes the chemistry and properties of currently most used hydraulic binders—common cements and hydraulic limes—and that of the more promising binders for future applications, namely special Portland cements, aluminous cements, calcium sulfoaluminate cements, and alkali-activated cements.

Bacterial enzymes and multi-enzymatic systems for cleaning-up dyes from the environment

Synthetic dyes are xenobiotic compounds that are being increasingly used in several industries, with special emphasis in the paper, textile and leather industries. Over 100,000 commercial dyes exist today and more than 7 × 105 tons of dyestuff is produced annually, of which 1–1.5 × 105 tons is released into the wastewaters (Rai et al in Crit Rev Environ Sci Tecnhol 35:219–238, 2005). Among these, azo dyes, characterized by the presence of one or more azo groups (–N=N–), and anthraquinonic dyes represent the largest and most versatile groups.

Feature Discretization with Relevance and Mutual Information Criteria

Feature discretization (FD) techniques often yield adequate and compact representations of the data, suitable for machine learning and pattern recognition problems. These representations usually decrease the training time, yielding higher classification accuracy while allowing for humans to better understand and visualize the data, as compared to the use of the original features. This paper proposes two new FD techniques. The first one is based on the well-known Linde-Buzo-Gray quantization algorithm, coupled with a relevance criterion, being able perform unsupervised, supervised, or semi-supervised discretization. The second technique works in supervised mode, being based on the maximization of the mutual information between each discrete feature and the class label. Our experimental results on standard benchmark datasets show that these techniques scale up to high-dimensional data, attaining in many cases better accuracy than existing unsupervised and supervised FD approaches, while using fewer discretization intervals.

An adaptive IoT management infrastructure for eco transport networks

The complexity associated with fast growing of B2B and the lack of a (complete) suite of open standards makes difficulty to maintain the underlying collaborative processes. Aligned to this challenge, this paper aims to be a contribution to an open architecture of logistics and transport processes management system. A model of an open integrated system is being defined as an open computational responsibility from the embedded systems (on-board) as well as a reference implementation (prototype) of a host system to validate the proposed open interfaces. Embedded subsystem can, natively, be prepared to cooperate with other on-board units and with IT-systems in an infrastructure commonly referred to as a center information system or back-office. In interaction with a central system the proposal is to adopt an open framework for cooperation where the embedded unit or the unit placed somewhere (land/sea) interacts in response to a set of implemented capabilities.

Exploiting the bin-class histograms for feature selection on discrete data

In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.

Risk assessment in open innovation networks

Innovation is considered crucial for enterprises survival and current economic environment demands the best ways of achieving it. However, the development of complex products and services require the utilization of diverse know-how and technology, which enterprises may not hold. An effective strategy for achieving them is to rely in open innovation. Still, open innovation projects may fail for many causes, e.g. due to the dynamics of collaboration between partners. To effectively benefit from open innovation, it is recommended the utilization of adequate risk models. For achieving such models, a preliminary conceptualization of open innovation and risk is necessary, which includes modeling experiments with existing risk models, such as the FMEA.

Innovation from Academia-Industry symbiosis

Anchored on a systemic perspective of innovation and particularly on the triple helix model, which highlights the state, university and companies as central players, this paper aims to discuss the factors that enable or constrain the processes of innovation, using the system thinking approach to understand the academia-industry symbiosis. The paper's empirical section is based on a case study on Portugal's major highway management concessionaire. In order to ensure a "healthy" co-innovation environment, the archetype studied emphasizes the need to implement coordination mechanisms such as communication routines and metrics to monitor collaborative behavior in addition to the need to develop global goals that align the efforts of the partners.