Unidade de Investigação - CIIC - Computer Science and Communication Research Centre
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Percorrer Unidade de Investigação - CIIC - Computer Science and Communication Research Centre por Domínios Científicos e Tecnológicos (FOS) "Ciências Naturais::Matemáticas"
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- Automatic Transcription of Polyphonic Piano Music Using Genetic Algorithms, Adaptive Spectral Envelope Modeling, and Dynamic Noise Level EstimationPublication . Reis, Gustavo; Fernandez de Vega, Francisco; Ferreira, AníbalThis paper presents a new method for multiple fundamental frequency (F0) estimation on piano recordings. We propose a framework based on a genetic algorithm in order to analyze the overlapping overtones and search for the most likely F0 combination. The search process is aided by adaptive spectral envelope modeling and dynamic noise level estimation: while the noise is dynamically estimated, the spectral envelope of previously recorded piano samples (internal database) is adapted in order to best match the piano played on the input signals and aid the search process for the most likely combination of F0s. For comparison, several state-of-the-art algorithms were run across various musical pieces played by different pianos and then compared using three different metrics. The proposed algorithm ranked first place on Hybrid Decay/Sustain Score metric, which has better correlation with the human hearing perception and ranked second place on both onset-only and onset–offset metrics. A previous genetic algorithm approach is also included in the comparison to show how the proposed system brings significant improvements on both quality of the results and computing time.
- Discrete Compound Tests and Dorfman’s Methodology in the Presence of MisclassificationPublication . Santos, Rui; Martins, João Paulo; Felgueiras, MiguelCompound tests can be used to save resources for classification or estimation purposes in clinical trials and quality control. Nevertheless, the methodologies that are usually applied are restricted to qualitative group tests. Moreover, when quantitative compound tests are applied the problem is to ascertain whether the amount of some substance of any individual in the group is greater or lower than a prefixed threshold. An overview of the applications of the discrete compound tests highlights the advantages (to save resources) and disadvantages (higher probability of misclassification), and suggests criteria to assess the suitability of applying Dorfman’s methodology.
- Evolution of Artificial Terrains for Video Games Based on AccessibilityPublication . Frade, Miguel; Vega, Francisco Fernandez de; Cotta, CarlosDiverse methods have been developed to generate terrains under constraints to control terrain features, but most of them use strict restrictions. However, there are situations were more flexible restrictions are sufficient, such as ensuring that terrains have enough accessible area, which is an important trait for video games. The Genetic Terrain Program technique, based on genetic programming, was used to automatically evolve Terrain Programs (TPs - which are able to generate terrains procedurally) for the desired accessibility parameters. Results showed that the accessibility parameters have negligible influence on the evolutionary system and that the terminal set has a major role on the terrain look. TPs produced this way are already being used on Chapas video game.
- Exploring Pareto scale mixturesPublication . Felgueiras, Miguel; Santos, RuiPareto scale mixtures can be used to obtain distributions with heavier tails. An explanation of this model properties is provided, together with a discussion about the parameters estimation. Finally, a real data application is presented, consisting in the larger earthquakes seismic moment modeling.
- Hybrid population-based incremental learning to assign terminals to concentratorsPublication . Bernardino, Eugénia Moreira; Bernardino, Anabela Moreira; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelIn the last decade, we have seen a significant growth in communication networks. In centralised communication networks, a central computer serves several terminals or workstations. In large networks, some concentrators are used to increase the network efficiency. A collection of terminals is connected to a concentrator and each concentrator is connected to the central computer. In this paper we propose a Hybrid Population-based Incremental Learning (HPBIL) to assign terminals to concentrators. We use this algorithm to determine the minimum cost to form a network by connecting a given collection of terminals to a given collection of concentrators. We show that HPBIL is able to achieve good solutions, improving the results obtained by previous approaches.
- A Hybrid Scatter Search algorithm to assign terminals to concentratorsPublication . Bernardino, Eugénia Moreira; Bernardino, Anabela Moreira; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelThe last few years have seen a significant growth in communication networks. With the growth of data traffic, network operators seek network-engineering tools to extract the maximum benefits out of the existing infrastructure. This has suggested a number of new optimisation problems, most of them in the field of combinatorial optimisation. We address here the Terminal Assignment problem. The main objective is to assign a collection of terminals to a collection of concentrators. In this paper, we propose a Hybrid Scatter Search (HSS) algorithm to assign terminals to concentrators. Coupled with the Scatter Search algorithm we use a Tabu Search algorithm to locate the global minimum. We show that HSS is able to achieve feasible solutions to Terminal Assignment instances, improving the results obtained by previous approaches.
- Indicator-based multi objective evolutionary algorithms and an application in filament winding processPublication . Yevseyeva, Iryna; de Melo, Francisco Queirós; Grácio, José; Basto-Fernandes, VitorThis work presents recent developments on multi objective evolutionary algorithms, so-called set-based evolutionary algorithms. These techniques are shown to approximate a Pareto front of efficient solutions taking into account both quality of the approximation and its diversity, both important in the design of these methods. Set-based evolutionary algorithms outperform their predecessors on a variety of benchmark problems and are suggested as tools to be used for solving complex mechanical engineering problems, such as filament winding process discussed in this work.
- Pseudo-convex mixturesPublication . Felgueiras, Miguel; Martins, João; Santos, RuiAllowing weights w∈]−1;1]\{0}, pseudo-convex mixtures increase usual mixtures flexibility. The finite mixtures with negative components are investigated for distribution families closed under minimization. The main purpose is to define these mixtures and to study their properties.
- Quality Management: Concepts and Approaches for Software ProjectsPublication . Gonçalves, Dulce; Varajão, João; Martinho, Ricardo; Cruz, José BulasIn a world of growing competitiveness, “quality” is a main subject. On recent years, there has been a trend towards the improvement of software projects’ quality. This means improving not only the final software products, but especially the quality of leadership and of project management. It is now recognized that the quality of software products and services can be improved if quality management is accomplished according to the unique characteristics and complexity of each project. In this paper we present the main concepts of quality management, as also some approaches of software quality assurance. We then gather them around and, using the Deming’s philosophy, present the Total Quality Management paradigm. We also discuss the rules and standards of Quality Management Systems (ISO 9000 and CMMI), and identify some misfits regarding the specific context of software development.
- Solving large-scale SONET network design problems using bee-inspired algorithmsPublication . Bernardino, Eugénia Moreira; Bernardino, Anabela Moreira; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelIn the past years, the number of users of Internet-based applications has exponentially increased and consequently the request for transmission capacity or bandwidth has significantly augmented. When managed properly, the ring networks are uniquely suited to deliver a large amount of bandwidth in a reliable and inexpensive way. In this paper, we consider two problems that arise in the design of optical telecommunication networks, namely the SONET Ring Assignment Problem (SRAP) and the Intraring Synchronous Optical Network Design Problem (IDP), known to be NP-hard. In SRAP, the objective is to minimise the number of rings (i.e., DXCs). In IDP, the objective is to minimise the number of ADMs. Both problems are subject to a ring capacity constraint. To solve these problems, we propose two bee-inspired algorithms: Hybrid Artificial Bee Colony and Hybrid Bees Algorithm. We hybridise the basic form of these algorithms with local search, in order to refine newly constructed solutions. We also perform comparisons with other algorithms from the literature and use larger instances. The simulation results verify the effectiveness and robustness of the proposed algorithms.