A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

Risk Aversion in a Mixed-Integer Nonlinear Approach to Support Decision-Making for a Hydro Power Producer

In this paper, a mixed-integer nonlinear approach is proposed to support decision-making for a hydro power producer, considering a head-dependent hydro chain. The aim is to maximize the profit of the hydro power producer from selling energy into the electric market. As a new contribution to earlier studies, a risk aversion criterion is taken into account, as well as head-dependency. The volatility of the expected profit is limited through the conditional value-at-risk (CVaR). The proposed approach has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems.

Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to eat her studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement.

A comparative benchmarking analysis of main Iberian container terminals: a DEA approach

Benchmarking is an important tool to organisations to improve their productivity, product quality, process efficiency or services. From Benchmarking the organisations could compare their performance with competitors and identify their strengths and weaknesses. This study intends to do a benchmarking analysis on the main Iberian Sea ports with a special focus on their container terminals efficiency. To attain this, the DEA (data envelopment analysis) is used since it is considered by several researchers as the most effective method to quantify a set of key performance indicators. In order to reach a more reliable diagnosis tool the DEA is used together with the data mining in comparing the sea ports operational data of container terminals during 2007.Taking into account that sea ports are global logistics networks the performance evaluation is essential to an effective decision making in order to improve their efficiency and, therefore, their competitiveness.

Projecto timecloud: software de gestão de tempo laboral numa plataforma cloud

O presente projecto tem como objectivo a disponibilização de uma plataforma de serviços para gestão e contabilização de tempo remunerável, através da marcação de horas de trabalho, férias e faltas (com ou sem justificação). Pretende-se a disponibilização de relatórios com base nesta informação e a possibilidade de análise automática dos dados, como por exemplo excesso de faltas e férias sobrepostas de trabalhadores. A ênfase do projecto está na disponibilização de uma arquitectura que facilite a inclusão destas funcionalidades. O projecto está implementado sobre a plataforma Google App Engine (i.e. GAE), de forma a disponibilizar uma solução sob o paradigma de Software as a Service, com garantia de disponibilidade e replicação de dados. A plataforma foi escolhida a partir da análise das principais plataformas cloud existentes: Google App Engine, Windows Azure e Amazon Web Services. Foram analisadas as características de cada plataforma, nomeadamente os modelos de programação, os modelos de dados disponibilizados, os serviços existentes e respectivos custos. A escolha da plataforma foi realizada com base nas suas características à data de iniciação do presente projecto. A solução está estruturada em camadas, com as seguintes componentes: interface da plataforma, lógica de negócio e lógica de acesso a dados. A interface disponibilizada está concebida com observação dos princípios arquitecturais REST, suportando dados nos formatos JSON e XML. A esta arquitectura base foi acrescentada uma componente de autorização, suportada em Spring-Security, sendo a autenticação delegada para os serviços Google Acounts. De forma a permitir o desacoplamento entre as várias camadas foi utilizado o padrão Dependency Injection. A utilização deste padrão reduz a dependência das tecnologias utilizadas nas diversas camadas. Foi implementado um protótipo, para a demonstração do trabalho realizado, que permite interagir com as funcionalidades do serviço implementadas, via pedidos AJAX. Neste protótipo tirou-se partido de várias bibliotecas javascript e padrões que simplificaram a sua realização, tal como o model-view-viewmodel através de data binding. Para dar suporte ao desenvolvimento do projecto foi adoptada uma abordagem de desenvolvimento ágil, baseada em Scrum, de forma a implementar os requisitos do sistema, expressos em user stories. De forma a garantir a qualidade da implementação do serviço foram realizados testes unitários, sendo também feita previamente a análise da funcionalidade e posteriormente produzida a documentação recorrendo a diagramas UML.

Learning techniques for automatic email message tagging

A organização automática de mensagens de correio electrónico é um desafio actual na área da aprendizagem automática. O número excessivo de mensagens afecta cada vez mais utilizadores, especialmente os que usam o correio electrónico como ferramenta de comunicação e trabalho. Esta tese aborda o problema da organização automática de mensagens de correio electrónico propondo uma solução que tem como objectivo a etiquetagem automática de mensagens. A etiquetagem automática é feita com recurso às pastas de correio electrónico anteriormente criadas pelos utilizadores, tratando-as como etiquetas, e à sugestão de múltiplas etiquetas para cada mensagem (top-N). São estudadas várias técnicas de aprendizagem e os vários campos que compõe uma mensagem de correio electrónico são analisados de forma a determinar a sua adequação como elementos de classificação. O foco deste trabalho recai sobre os campos textuais (o assunto e o corpo das mensagens), estudando-se diferentes formas de representação, selecção de características e algoritmos de classificação. É ainda efectuada a avaliação dos campos de participantes através de algoritmos de classificação que os representam usando o modelo vectorial ou como um grafo. Os vários campos são combinados para classificação utilizando a técnica de combinação de classificadores Votação por Maioria. Os testes são efectuados com um subconjunto de mensagens de correio electrónico da Enron e um conjunto de dados privados disponibilizados pelo Institute for Systems and Technologies of Information, Control and Communication (INSTICC). Estes conjuntos são analisados de forma a perceber as características dos dados. A avaliação do sistema é realizada através da percentagem de acerto dos classificadores. Os resultados obtidos apresentam melhorias significativas em comparação com os trabalhos relacionados.

New insights into host-parasite ubiquitin proteome dynamics in P. falciparum infected red blood cells using a TUBEs-MS approach

Malaria, caused by Plasmodium falciparum (P. falciparum), ranks as one of the most baleful infectious diseases worldwide. New antimalarial treatments are needed to face existing or emerging drug resistant strains. Protein degradation appears to play a significant role during the asexual intraerythrocytic developmental cycle (IDC) of P. falciparum. Inhibition of the ubiquitin proteasome system (UPS), a major intracellular proteolytic pathway, effectively reduces infection and parasite replication. P. falciparum and erythrocyte UPS coexist during IDC but the nature of their relationship is largely unknown. We used an approach based on Tandem Ubiquitin-Binding Entities (TUBEs) and 1D gel electrophoresis followed by mass spectrometry to identify major components of the TUBEs-associated ubiquitin proteome of both host and parasite during ring, trophozoite and schizont stages. Ring-exported protein (REX1), a P. falciparum protein located in Maurer's clefts and important for parasite nutrient import, was found to reach a maximum level of ubiquitylation in trophozoites stage. The Homo sapiens (H. sapiens) TUBEs associated ubiquitin proteome decreased during the infection, whereas the equivalent P. falciparum TUBEs-associated ubiquitin proteome counterpart increased. Major cellular processes such as DNA repair, replication, stress response, vesicular transport and catabolic events appear to be regulated by ubiquitylation along the IDC P. falciparum infection.

A hybrid approach to multi-agent decision-making

In the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement

A practical approach for profit-based unit commitment with emission limitations

This paper proposes a practical approach for profit-based unit commitment (PBUC) with emission limitations. Under deregulation, unit commitment has evolved from a minimum-cost optimisation problem to a profit-based optimisation problem. However, as a consequence of growing environmental concern, the impact of fossil-fuelled power plants must be considered, giving rise to emission limitations. The simultaneous address of the profit with the emission is taken into account in our practical approach by a multiobjective optimisation (MO) problem. Hence, trade-off Curves between profit and emission are obtained for different energy price profiles, in a way to aid decision-makers concerning emission allowance trading. Moreover, a new parameter is presented, ratio of change, and the corresponding gradient angle, enabling the proper selection of a compromise commitment for the units. A case study based on the standard IEEE 30-bus system is presented to illustrate the proficiency Of Our practical approach for the new competitive and environmentally constrained electricity supply industry.

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach

This paper is on the problem of short-term hydro, scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach.

Chaos and crises in a model for cooperative hunting: A symbolic dynamics approach

In this work we investigate the population dynamics of cooperative hunting extending the McCann and Yodzis model for a three-species food chain system with a predator, a prey, and a resource species. The new model considers that a given fraction sigma of predators cooperates in prey's hunting, while the rest of the population 1-sigma hunts without cooperation. We use the theory of symbolic dynamics to study the topological entropy and the parameter space ordering of the kneading sequences associated with one-dimensional maps that reproduce significant aspects of the dynamics of the species under several degrees of cooperative hunting. Our model also allows us to investigate the so-called deterministic extinction via chaotic crisis and transient chaos in the framework of cooperative hunting. The symbolic sequences allow us to identify a critical boundary in the parameter spaces (K, C-0) and (K, sigma) which separates two scenarios: (i) all-species coexistence and (ii) predator's extinction via chaotic crisis. We show that the crisis value of the carrying capacity K-c decreases at increasing sigma, indicating that predator's populations with high degree of cooperative hunting are more sensitive to the chaotic crises. We also show that the control method of Dhamala and Lai [Phys. Rev. E 59, 1646 (1999)] can sustain the chaotic behavior after the crisis for systems with cooperative hunting. We finally analyze and quantify the inner structure of the target regions obtained with this control method for wider parameter values beyond the crisis, showing a power law dependence of the extinction transients on such critical parameters.

Is stock market volatility persistent? A fractionally integrated approach

This paper seeks to study the persistence in the G7’s stock market volatility, which is carried out using the GARCH, IGARCH and FIGARCH models. The data set consists of the daily returns of the S&P/TSX 60, CAC 40, DAX 30, MIB 30, NIKKEI 225, FTSE 100 and S&P 500 indexes over the period 1999-2009. The results evidences long memory in volatility, which is more pronounced in Germany, Italy and France. On the other hand, Japan appears as the country where this phenomenon is less obvious; nevertheless, the persistence prevails but with minor intensity.

A multifactor approach to the social discount rate

This work focuses on the appraisal of public and environmental projects and, more specifically, on the calculation of the social discount rate (SDR) for this kind of very long-term investment projects. As a rule, we can state that the instantaneous discount rate must be equal to the hazard rate of the public good or to the mortality rate of the population that the project is intended to. The hazard can be due to technical failures of the system, but, in this paper, we are going to consider different independent variables that can cause the hazard. That is, we are going to consider a multivariate hazard rate. In our empirical application, the Spanish forest surface will be the system and the forest fire will be the fail that can be caused by several factors. The aim of this work is to integrate the different variables that produce the fail in the calculation of the SDR from a multivariate hazard rate approach.

The Bambuí health and ageing study (BHAS): methodological approach and preliminary results of a population-based cohort study of the elderly in Brazil

OBJECTIVE: A cohort study has been designed to identify predictors of adverse health events in the elderly. The methodology of the study and preliminary descriptive results are presented. METHODS: The study population comprises all residents of Bambuí (Minas Gerais, Brazil), aged 60 or more years (n=1.742). From these, 92.2% were interviewed and 85.9% underwent clinical examination, consisting of haematological and biochemical tests, serology for Trypanosoma cruzi, anthropometric and blood pressure measures and electrocardiogram. Aliquots of serum, plasma and DNA were stored for future investigations. The baseline interview included sociodemographic characteristics, self-referred health condition and history of selected diseases, medication use, health service use, source of medical care, physical activities, smoking, drinking and eating habits, reproductive history, physical functioning, life events, social support and mental health. Individuals are being followed up annually. RESULTS: The following characteristics predominated among participants: women (60,0%), married (48.9%) or widowed (35.4%), people living in households with up to 2 residents (73.8%), heads of family (76.7%), people with monthly income between 1.00 and 2.99 Brazilian minimum wages (62.0%) and people with up to 4 years of schooling (89.1%). The median age was 68 years. Among the cohort members, only 1.7% were lost in the first follow-up. CONCLUSIONS: In general, the characteristics of the study population were very similar to those from other epidemiological studies of the elderly based on large Brazilian cities. The small number of losses to follow-up indicates that the choice of Bambuí was adequate, assuring the feasibility of a long term cohort study.