An integer programming model for the minimum interval graph completion problem

The minimum interval graph completion problem consists of, given a graph G = ( V, E ), finding a supergraph H = ( V, E ∪ F ) that is an interval graph, while adding the least number of edges |F| . We present an integer programming formulation for solving the minimum interval graph completion problem recurring to a characteri- zation of interval graphs that produces a linear ordering of the maximal cliques of the solution graph.

Da transcrição à legendagem em busca da perda mínima de conteúdo

Como projeto final do Mestrado em Tradução e Interpretação Especializadas foi proposta a legendagem de um excerto de uma apresentação oral, em ambiente de debate, de um discurso do ator Stephen Fry. Inseriu-se o trabalho no âmbito do mestrado e no seguimento da licenciatura na mesma área, possibilitando o exercício de três das principais áreas do curso: transcrição, tradução e legendagem, por esta ordem. Procurou-se inovar no sentido de aproximar a transcrição à legendagem, com a menor supressão possível de texto e consequentemente da mensagem, enquanto se cumpriram na íntegra as normas e sugestões dos autores-chave da área. Como elementos técnicos do trabalho estão inseridos no corpo do texto a transcrição, a tradução e a legendagem, pois estes são os objetos práticos do trabalho e o grande desafio proposto foi o seguinte: manter a fidelidade entre estes três modos de transferência – obedecer a todo o procedimento distinto a que estes modos obrigam, mas mantendo entre eles uma similaridade que os torne praticamente iguais, no sentido de transmissão da mensagem. Apresentaram-se também uma breve história da tradução audiovisual, os diferentes tipos da mesma, uma abordagem à realidade da área em Portugal, uma contextualização do excerto e do seu conteúdo e a vertente técnica na sua globalidade.

Bioatividade da quinoxalina 1,4-dióxido e seus derivados

O objetivo deste estudo consiste em avaliar a atividade antimicrobiana da quinoxalina 1,4-dióxido e alguns dos seus derivados em estirpes bacterianas e leveduras. Os compostos estudados foram a quinoxalina 1,4-dióxido (QNX), 2-metilquinoxalina-1,4-dióxido (2MQNX), 2-metil-3-Benzoilquinoxalina-1,4-dióxido (2M3BenzoilQNX), 2-metil-3-benzilquinoxalina-1,4-dióxido (2M3BQNX), 2-amino-3-cianoquinoxalina-1,4-dióxido (2A3CQNX), 3-metil-2-quinoxalinacarboxamida-1,4-dióxido (3M2QNXC), 2-hidroxifenazina–N-dióxido (2HF) e 3-metil-N-(2-metilphenil)quinoxalinacarboxamida-1,4-dioxido (3MN(2MF)QNXC). Os modelos procariotas selecionados para este estudo foram o Staphylococcus aureus ATCC 6538, Staphylococcus aureus ATCC 6538P, Staphylococcus aureus ATCC 29213, Escherichia coli ATCC 25922, Escherichia coli S3R9, Escherichia coli S3R22, Escherichia coli TEM CTX-M9, Escherichia coli TEM-1, Escherichia coli AmpC MOX-2, Escherichia coli CTX-M2 e Escherichia coli CTX-M9. A Candida albicans ATCC 10231 e a Saccharomyces cerevisiae PYCC 4072 constituíram os modelos eucariotas deste estudo. Para os compostos químicos que apresentem atividade pelo método de difusão em disco, será determinada a Concentração Mínima Inibitória (CMI), bem como a viabilidade e o crescimento (na presença e na ausência dos compostos químicos). Os resultados deste estudo mostram atividade antimicrobiana para a maioria dos compostos estudados em todos os modelos procariotas Gram negativos, à exceção da E.coli CTX-M2 e CTX-M9 e nenhuma atividade nos modelos eucariotas. O estudo da viabilidade/curvas de morte em bactérias e num modelo eucariota (S.cerevisiae) sugerem que alguns destes compostos constituem potenciais drogas para a quimioterapia antibacteriana.

Os Crimes fiscais: em especial, o crime de abuso de confiança (fiscal)

Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientador: Professor Dr. António da Costa Oliveira

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Meta-heuristics self-configuration for scheduling

Scheduling resolution requires the intervention of highly skilled human problemsolvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. This paper addresses the resolution of complex scheduling problems using cooperative negotiation. A Multi-Agent Autonomic and Meta-heuristics based framework with self-configuring capabilities is proposed.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

This paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, balancing load among feeders and subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. The Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages; the first one is the Master problem and is formulated as a mixed integer non-linear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a non-linear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS. The effectiveness of the proposal is demonstrated through two examples extracted from the literature.

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.

Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.

Entrepreneurship Strategies in a Portuguese and in a Polish Region

In the present paper we will consider strategies of innovation, risk and proactivity as entre/ intrapreneurship strategies. This study was done in a Portuguese and in a Polish region. In Portugal the region was Vale do Sousa, located in the northern Portugal. The Polish region was Lublin Voivodeship and it is situated in the south-eastern part of the country. The study focused on Industrial and Construction sectors. In order to get a valid sample, a group of 251 firms were analysed in Portugal, and 215 in Poland. However, the minimum sample size in Poland should be 323. Since this is a work in progress, we are aiming for this number of questionnaires. Each strategy was analysed individually for both regions and the results pointed to a lack of culture of entrepreneurship in firms’ management. Only Proactivity presented a positive result in firms’ management. Polish firms tend to be more innovative and more risk takers, while in proactivity Portuguese ones present a slightly higher result. Combining the strategy results, it was possible to identify that 61.2% of Portuguese firms present a low level of entrepreneurship, while 60% of Polish firms present a moderate level. Considering intrapreneurship good levels, while Portugal account for 5.2% this figure is 19.1% in Poland.