Electronic Notes in Theoretical Computer Science最新文献

This paper presents an architecture for a parallel programming environment designed to assist the process of writing parallel programs. The proposed architecture allows the integration of several tools such as parallel programming skeletons and parallelizing compilers, among others. On the one hand, parallel programming skeletons simplify the design of parallel algorithms. On the other hand, parallelizing compilers rely on compiler capabilities to translate sequential programs into ones capable of using multiple processing units (CPU/GPU) found in personal computers (PCs). The technological solution presented in this work follows a microservices-oriented approach. This approach eases the integration of new parallel programming tools in the existing deployment through well-known protocols and existing services. We show how the aforementioned parallel programming tools were integrated to support the coding and parallelization of a general purpose cellular automata. Since the parallelization rely on the capabilities underlying to each tool, the focus of this work is not to deal with an efficient cellular automata parallelization. Instead, a promising microservice approach to the development of an extensible and scalable parallel programming environment is presented.

Center-based clustering is a set of clustering problems that require finding a single element, a center, to represent an entire cluster. The algorithms that solve this type of problems are very efficient for clustering large and high-dimensional datasets. In this paper, we propose a similar heuristic used in Lloyd's algorithm to approximately solve (EMAX algorithm) a more robust variation of the k-means problem, namely the EMAX problem. Also, a new center-based clustering algorithm (SSO-C) is proposed, which is based on a swarm intelligence technique called Social Spider Optimization. This algorithm minimizes a multi-objective optimization function defined as a weighted combination of the objective functions of the k-means and EMAX problems. Also, an approximation algorithm for the discrete k-center problem is used as a local search strategy for initializing the population. Results of the experiments showed that SSO-C algorithm is suitable for finding maximum best values, however EMAX algorithm is better in finding median and mean values.

A bracket abstraction is a syntactic operator to abstract variables in combinatory logic. There are different algorithms for different combinator systems. In this paper we present a recursive algorithm scheme, which generates a family of brackets abstractions, in which all the bracket abstractions referenced here are found. In addition, theorems with certain hypotheses are enunciated about the scheme, which state that the resulting abstraction operators, has one property or another. Thus forming a criteria for designing bracket abstractions that comply with a given property.

Several histogram equalization methods focus on enhancing the contrast as one of their main objectives, but usually without considering the details of the input image. Other methods seek to keep the brightness while improving the contrast, causing distortion. Among the multi-objective algorithms, the classical optimization (a priori) techniques are commonly used given their simplicity. One of the most representative method is the weighted sum of metrics used to enhance the contrast of an image. These type of techniques, beside just returning a single image, have problems related to the weight assignment for each selected metric. To avoid the pitfalls of the algorithms just mentioned, we propose a new method called MOPHE (Multi-Objective Pareto Histogram Equalization) which is based on Multi-objective Particle Swarm Optimization (MOPSO) approach combining different metrics in a posteriori selection criteria context. The goal of this method is three-fold: (1) improve the contrast (2) without losing important details, (3) avoiding an excessive distortion. MOPHE, is a pure multi-objective optimization algorithm, consequently a set of trade-off optimal solutions are generated, thus providing alternative solutions to the decision-maker, allowing the selection of one or more resulting images, depending on the application needs. Experimental results indicate that MOPHE is a promising approach, as it calculates a set of trade-off optimal solutions that are better than the results obtained from representative algorithms from the state-of-the-art regarding visual quality and metrics measurement.

Medical imaging help medical doctors provide faster and more efficient diagnoses to their patients. Medical image quality directly influences diagnosis. However, when medical images are acquired, they often present degradations such as poor detail or low contrast. This work presents an algorithm that improves contrast and detail, preserving the natural brightness of medical images. The proposed method is based on multiscale top-hat transform by reconstruction. It extracts multiple features from the image that are then used to enhance the medical image. To quantify the performance of the proposed method, 100 medical images from a public database were used. Experiments show that the proposal improves contrast, introducing less distortion and preserving the average brightness of medical images.

This paper introduces a sort of automata and associated languages, often arising in modelling natural phenomena, in which both vagueness and simultaneity are taken as first class citizens. This requires a fuzzy semantics assigned to transitions and a precise notion of a synchronous product to enforce the simultaneous occurrence of actions. The expected relationships between automata and languages are revisited in this setting; in particular it is shown that any subset of a fuzzy synchronous language with the suitable signature forms a synchronous Kleene algebra.

This paper proposes an extension of first-order disunification problems by taking into account binding operators according to the nominal approach. In this approach, bindings are implemented through atom abstraction, and renaming of atoms is implemented via atom permutations. In the nominal setting, unification problems consist of equational questions ($s{\approx }_{\alpha }^{?}t$) considered under freshness constraints ($a{\#}^{?}t$) that restrict solutions by forbidding free occurrences of atoms in the instantiation of variables. In addition to equational and freshness constraints, nominal disunification problems include also nominal disunification constraints ($s{\not\approx }_{\alpha }^{?}t$), and their solutions consist of a substitution and additional freshness constraints such that under these constraints the instantiation of the equations, disequations and freshness constraints with the substitution hold. By re-using nominal unification techniques, this paper shows how to decide whether two nominal terms can be made different modulo α-equivalence. This is done by extending previous results on first-order disunification, and defining the notion of solutions with exceptions in the nominal syntax. A discussion on the semantics of disunification constraints is also given.

We present a proof of the equivalence between two deductive systems for the constructive modal logic S4. On one side, an axiomatic characterization inspired by Hakli and Negri's Hilbert-style system of derivations from assumptions for modal logic K. On the other side, the judgmental reconstruction given by Pfenning and Davies by means of a so-called dual natural deduction approach that makes a distinction between valid, true and possible formulas. Both systems and the proof of their equivalence are formally verified using the Coq proof assistant.

This work deals with the definability problem by quantifier-free first-order formulas over a finite algebraic structure. We show the problem to be coNP-complete and present a decision algorithm based on a semantical characterization of definable relations as those preserved by isomorphisms of substructures. Our approach also includes the design of an algorithm that computes the isomorphism type of a tuple in a finite algebraic structure. Proofs of soundness and completeness of the algorithms are presented, as well as empirical tests assessing their performances.

This paper intends to contribute with a new fuzzy modal logic to model and reason about transition systems involving uncertainty in behaviours. Our formalism supports fuzziness at transitions and on the proposition symbols assignment levels.

Against of other approaches in the literature, our bisimulation and bisimilarity notions generalise the analogous standard notions of classic modal logic and of process algebras. Moreover, the outcome of our logic is also fuzzy, with the semantic interpretation of connectives supported by the Gödel algebra.