A Graph-Theoretical Approach to the Selection of the Minimum Tiling Path from a Physical Map

The problem of computing the minimum tiling path (MTP) from a set of clones arranged in a physical map is a cornerstone of hierarchical (clone-by-clone) genome sequencing projects. We formulate this problem in a graph theoretical framework, and then solve by a combination of minimum hitting set and minimum spanning tree algorithms. The tool implementing this strategy, called FMTP, shows improved performance compared to the widely used software FPC. When we execute FMTP and FPC on the same physical map, the MTP produced by FMTP covers a higher portion of the genome, and uses a smaller number of clones. For instance, on the rice genome the MTP produced by our tool would reduce by about 11 percent the cost of a clone-by-clone sequencing project. Source code, benchmark data sets, and documentation of FMTP are freely available at \u3ehttp://code.google.com/p/fingerprint-based-minimal-tiling-path/ under MIT license

Exploring search space trees using an adapted version of Monte Carlo tree search for combinatorial optimization problems

In this article, a novel approach to solve combinatorial optimization problems is proposed. This approach makes use of a heuristic algorithm to explore the search space tree of a problem instance. The algorithm is based on Monte Carlo tree search, a popular algorithm in game playing that is used to explore game trees. By leveraging the combinatorial structure of a problem, several enhancements to the algorithm are proposed. These enhancements aim to efficiently explore the search space tree by pruning subtrees, using a heuristic simulation policy, reducing the domains of variables by eliminating dominated value assignments and using a beam width. They are demonstrated for two specific combinatorial optimization problems: the quay crane scheduling problem with non-crossing constraints and the 0-1 knapsack problem. Computational results show that the algorithm achieves promising results for both problems and eight new best solutions for a benchmark set of instances are found for the former problem. These results indicate that the algorithm is competitive with the state-of-the-art. Apart from this, the results also show evidence that the algorithm is able to learn to correct the incorrect choices made by constructive heuristics

The Emergence of Sparse Spanners and Greedy Well-Separated Pair Decomposition

A spanner graph on a set of points in $R^d$ contains a shortest path between any pair of points with length at most a constant factor of their Euclidean distance. In this paper we investigate new models and aim to interpret why good spanners 'emerge' in reality, when they are clearly built in pieces by agents with their own interests and the construction is not coordinated. Our main result is to show that if edges are built in an arbitrary order but an edge is built if and only if its endpoints are not 'close' to the endpoints of an existing edge, the graph is a (1 + \eps)-spanner with a linear number of edges, constant average degree, and the total edge length as a small logarithmic factor of the cost of the minimum spanning tree. As a side product, we show a simple greedy algorithm for constructing optimal size well-separated pair decompositions that may be of interest on its own

Constant-Delay Enumeration for Nondeterministic Document Spanners

We consider the information extraction framework known as document spanners, and study the problem of efficiently computing the results of the extraction from an input document, where the extraction task is described as a sequential variable-set automaton (VA). We pose this problem in the setting of enumeration algorithms, where we can first run a preprocessing phase and must then produce the results with a small delay between any two consecutive results. Our goal is to have an algorithm which is tractable in combined complexity, i.e., in the sizes of the input document and the VA; while ensuring the best possible data complexity bounds in the input document size, i.e., constant delay in the document size. Several recent works at PODS'18 proposed such algorithms but with linear delay in the document size or with an exponential dependency in size of the (generally nondeterministic) input VA. In particular, Florenzano et al. suggest that our desired runtime guarantees cannot be met for general sequential VAs. We refute this and show that, given a nondeterministic sequential VA and an input document, we can enumerate the mappings of the VA on the document with the following bounds: the preprocessing is linear in the document size and polynomial in the size of the VA, and the delay is independent of the document and polynomial in the size of the VA. The resulting algorithm thus achieves tractability in combined complexity and the best possible data complexity bounds. Moreover, it is rather easy to describe, in particular for the restricted case of so-called extended VAs. Finally, we evaluate our algorithm empirically using a prototype implementation.Comment: 29 pages. Extended version of arXiv:1807.09320. Integrates all corrections following reviewer feedback. Outside of some minor formatting differences and tweaks, this paper is the same as the paper to appear in the ACM TODS journa

Creative Support Musical Composition System: a study on Multiple Viewpoints Representations in Variable Markov Oracle

Em meados do século XX, assistiu-se ao surgimento de uma área de estudo focada na geração au-tomática de conteúdo musical por meios computacionais. Os primeiros exemplos concentram-se no processamento offline de dados musicais mas, recentemente, a comunidade tem vindo a explorar maioritariamente sistemas musicais interativos e em tempo-real. Além disso, uma tendência recente enfatiza a importância da tecnologia assistiva, que promove uma abordagem centrada em escolhas do utilizador, oferecendo várias sugestões para um determinado problema criativo. Nesse contexto, a minha investigação tem como objetivo promover novas ferramentas de software para sistemas de suporte criativo, onde algoritmos podem participar colaborativamente no fluxo de composição. Em maior detalhe, procuro uma ferramenta que aprenda com dados musicais de tamanho variável para fornecer feedback em tempo real durante o processo de composição. À luz das características de multi-dimensionalidade e hierarquia presentes nas estruturas musicais, pretendo estudar as representações que abstraem os seus padrões temporais, para promover a geração de múltiplas soluções ordenadas por grau de optimização para um determinado contexto musical. Por fim, a natureza subjetiva da escolha é dada ao utilizador, ao qual é fornecido um número limitado de soluções 'ideais'. Uma representação simbólica da música manifestada como Modelos sob múltiplos pontos de vista, combinada com o autómato Variable Markov Oracle (VMO), é usada para testar a interação ideal entre a multi-dimensionalidade da representação e a idealidade do modelo VMO, fornecendo soluções coerentes, inovadoras e estilisticamente diversas. Para avaliar o sistema, foram realizados testes para validar a ferramenta num cenário especializado com alunos de composição, usando o modelo de testes do índice de suporte à criatividade.The mid-20th century witnessed the emergence of an area of study that focused on the automatic generation of musical content by computational means. Early examples focus on offline processing of musical data and recently, the community has moved towards interactive online musical systems. Furthermore, a recent trend stresses the importance of assistive technology, which pro-motes a user-in-loop approach by offering multiple suggestions to a given creative problem. In this context, my research aims to foster new software tools for creative support systems, where algorithms can collaboratively participate in the composition flow. In greater detail, I seek a tool that learns from variable-length musical data to provide real-time feedback during the composition process. In light of the multidimensional and hierarchical structure of music, I aim to study the representations which abstract its temporal patterns, to foster the generation of multiple ranked solutions to a given musical context. Ultimately, the subjective nature of the choice is given to the user to which a limited number of 'optimal' solutions are provided. A symbolic music representation manifested as Multiple Viewpoint Models combined with the Variable Markov Oracle (VMO) automaton, are used to test optimal interaction between the multi-dimensionality of the representation with the optimality of the VMO model in providing both style-coherent, novel, and diverse solutions. To evaluate the system, an experiment was conducted to validate the tool in an expert-based scenario with composition students, using the creativity support index test

Review of Optimization Problems in Wireless Sensor Networks

International audienc