Search results for "Programming Language"
showing 10 items of 624 documents
Agent-based Social Gaming with AMUSE
2014
Abstract This paper describes the core features and the multi-agent architecture of AMUSE (Agent-based Multi-User Social Environment), a novel agent-based platform for social gaming. AMUSE is designed to offer game developers readymade solutions to many issues that are common to social games like, e.g., advanced management of matches, turns and players. AMUSE is developed on top of WADE to leverage the scalable and solid agent-based deployment environment and the PaaS approach that it provides. This paper first outlines some of the motivations that originated the development of AMUSE. Then, it presents the multi-agent architecture of AMUSE and it enumerates the major applicative features th…
Mercury$$^\mathrm{\textregistered }$$: A Software Based on Fuzzy Clustering for Computer-Assisted Composition
2019
We present Mercury, a new software for computer-assisted composition based on fuzzy clustering algorithms. This software is able to generate a big number of transitions between any two different melodies, harmonic progressions or rhythmical patterns. Mercury works with symbolic music notation. The software is, therefore, able to read music and to export the generated musical production into MusicXML format. This paper focusses on some theoretical aspects of the CFT algorithm implemented in the software in order to create those complete transitions, overviewing not only the structure of the program but the user’s interface and its music notation module. Finally, the wide variety of compositi…
A description based on languages of the final non-deterministic automaton
2014
The study of the behaviour of non-deterministic automata has traditionally focused on the languages which can be associated to the different states. Under this interpretation, the different branches that can be taken at every step are ignored. However, we can also take into account the different decisions which can be made at every state, that is, the branches that can be taken, and these decisions might change the possible future behaviour. In this case, the behaviour of the automata can be described with the help of the concept of bisimilarity. This is the kind of description that is usually obtained when the automata are regarded as labelled transition systems or coalgebras. Contrarily t…
Complexity of operations on cofinite languages
2010
International audience; We study the worst case complexity of regular operation on cofinite languages (i.e., languages whose complement is finite) and provide algorithms to compute efficiently the resulting minimal automata.
Imaginary time propagation code for large-scale two-dimensional eigenvalue problems in magnetic fields
2013
We present a code for solving the single-particle, time-independent Schr\"odinger equation in two dimensions. Our program utilizes the imaginary time propagation (ITP) algorithm, and it includes the most recent developments in the ITP method: the arbitrary order operator factorization and the exact inclusion of a (possibly very strong) magnetic field. Our program is able to solve thousands of eigenstates of a two-dimensional quantum system in reasonable time with commonly available hardware. The main motivation behind our work is to allow the study of highly excited states and energy spectra of two-dimensional quantum dots and billiard systems with a single versatile code, e.g., in quantum …
A nonlinear Chaikin-based binary subdivision scheme
2019
Abstract In this work we introduce and analyze a new nonlinear subdivision scheme based on a nonlinear blending between Chaikin’s subdivision rules and the linear 3-cell subdivision scheme. Our scheme seeks to improve the lack of convergence in the uniform metric of the nonlinear scheme proposed in Amat et al. (2012), where the authors define a cell-average version of the PPH subdivision scheme (Amat et al., 2006). The properties of the new scheme are analyzed and its performance is illustrated through numerical examples.
The Regression Tsetlin Machine: A Tsetlin Machine for Continuous Output Problems
2019
The recently introduced Tsetlin Machine (TM) has provided competitive pattern classification accuracy in several benchmarks, composing patterns with easy-to-interpret conjunctive clauses in propositional logic. In this paper, we go beyond pattern classification by introducing a new type of TMs, namely, the Regression Tsetlin Machine (RTM). In all brevity, we modify the inner inference mechanism of the TM so that input patterns are transformed into a single continuous output, rather than to distinct categories. We achieve this by: (1) using the conjunctive clauses of the TM to capture arbitrarily complex patterns; (2) mapping these patterns to a continuous output through a novel voting and n…
BANΔIT: B’‐factor Analysis for Drug Design and Structural Biology
2020
The analysis of B‐factor profiles from X‐ray protein structures can be utilized for structure‐based drug design since protein mobility changes have been associated with the quality of protein‐ligand interactions. With the BANΔIT (B’‐factor analysis and ΔB’ interpretation toolkit), we have developed a JavaScript‐based browser application that provides a graphical user interface for the normalization and analysis of B’‐factor profiles. To emphasize the usability for rational drug design applications, we have analyzed a selection of crystallographic protein‐ligand complexes and have given exemplary conclusions for further drug optimization including the development of a B’‐factor‐supported pha…
Identification of photon-tagged jets in the ALICE experiment
2007
30 pp.-- PACS numbers: 25.75.Nq, 24.10.Lx, 25.75.-q, 29.40.Vj.-- Published in: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. Volume 585, Issues 1-2, 21 January 2008, Pages 28-39.-- Final full-text version of the paper available at: http://dx.doi.org/10.1016/j.nima.2007.10.050.
Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment
2021
[EN] Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulat…