Integrando problem frames com aspectos

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

A new approach to the initial value problem

5th Portuguese Conference on Automatic Control, September, 5-7, 2002, Aveiro, Portugal

Modeling assembly program with constraints. A contribution to WCET problem

Dissertação para obtenção do Grau de Mestre em Lógica Computacional

Maximum likelihood detection for OFDM signals with strong nonlinear distortion effects

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Linear amplification with multiple nonlinear devices

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e Computadores

GIS capacity building for risk management to help developing countries:Case of climate change problem in Amhara rural region (Ethiopia)

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

Probabilistic constraint reasoning

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Factorization of elliptic boundary value problems by invariant embedding and application to overdetermined problems

Dissertação para obtenção do Grau de Doutor em Matemática

Business model analysis of Mobitto: How to solve the chicken and egg problem of a multi-sided platform?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Characterization of an OPCPA laser amplifier based on the nonlinear crystal YCOB

The work described in this thesis was performed at the Laboratory for Intense Lasers (L2I) of Instituto Superior Técnico, University of Lisbon (IST-UL). Its main contribution consists in the feasibility study of the broadband dispersive stages for an optical parametric chirped pulse amplifier based on the nonlinear crystal yttrium calcium oxi-borate (YCOB). In particular, the main goal of this work consisted in the characterization and implementation of the several optical devices involved in pulse expansion and compression of the amplified pulses to durations of the order of a few optical cycles (20 fs). This type of laser systems find application in fields such as medicine, telecommunications and machining, which require high energy, ultrashort (sub-100 fs) pulses. The main challenges consisted in the preliminary study of the performance of the broadband amplifier, which is essential for successfully handling pulses with bandwidths exceeding 100 nm when amplified from the μJ to 20 mJ per pulse. In general, the control, manipulation and characterization of optical phenomena on the scale of a few tens of fs and powers that can reach the PW level are extremely difficult and challenging due to the complexity of the phenomena of radiation-matter interaction and their nonlinearities, observed at this time scale and power level. For this purpose the main dispersive components were characterized in detail, specifically addressing the demonstration of pulse expansion and compression. The tested bandwidths are narrower than the final ones, in order to confirm the parameters of these elements and predict the performance for the broadband pulses. The work performed led to additional tasks such as a detailed characterization of laser oscillator seeding the laser chain and the detection and cancelling of additional sources of dispersion.

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.