Search results for " minimization"

showing 10 items of 107 documents

Representation of Autonomous Automata

2001

An autonomous automaton is a finite automaton with output in which the input alphabet has cardinality one when special reduced. We define the transition from automata to semigroups via a representation successful if given two incomparable automata (neither simulate the other), the semigroups representing the automata are distinct. We show that representation by the transition semigroup is not successful. We then consider a representation of automata by semigroups of partial transformations. We show that in general transition from automata to semigroups by this representation is not successful either. In fact, the only successful transition presented is the transiton to this semigroup of par…

Krohn–Rhodes theoryDiscrete mathematicsNested wordFinite-state machineMathematics::Operator AlgebrasComputer scienceSemigroupTimed automatonω-automatonNonlinear Sciences::Cellular Automata and Lattice GasesMobile automatonAutomatonNondeterministic finite automaton with ε-movesStochastic cellular automatonDeterministic finite automatonDFA minimizationDeterministic automatonContinuous spatial automatonSpecial classes of semigroupsQuantum finite automataAutomata theoryTwo-way deterministic finite automatonNondeterministic finite automatonComputer Science::Formal Languages and Automata Theory
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Quantile Regression Coefficients Modeling: a Penalized Approach

2018

Modeling quantile regression coefficients functions permits describing the coefficients of a quantile regression model as parametric functions of the order of the quantile. This approach has numerous advantages over standard quantile regression, in which different quantiles are estimated one at the time: it facilitates estimation and inference, improves the interpretation of the results, and is statistically efficient. On the other hand, it poses new challenges in terms of model selection. We describe a penalized approach that can be used to identify a parsimonious model that can fit the data well. We describe the method, and analyze the dataset that motivated the present paper. The propose…

Lasso penalty Penalized integrated loss minimization Penalized quantile regression coefficients modeling Inspiratory capacity
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Experimental Comparison of Efficiency Enhancement Algorithms for Three-Phase Induction Motors

2019

This paper presents an experimental comparison of two efficiency improvement algorithms for three-phase induction motors by adopting Loss Model Algorithms (LMAs). The efficiency enhancement is evaluated starting from several simulations for different conditions of load and speed and, then, validated by comparing the experimental results obtained by applying the two control strategies and the traditional Field Oriented Control (FOC). Significant results in terms of efficiency enhancement are presented and discussed.

Loss Model AlgorithmVector controlThree-phaseComputer scienceField Oriented ControlInduction motorSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciAlgorithmInduction motorPower losses minimization2019 Fourteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)
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Membrane bioreactors sludge: From production to disposal

2020

Abstract This chapter reviews the MBR activated sludge from production to disposal. Starting from sludge characterization, the chapter first presents the features of MBR sludge (morphology and EPS chemical composition), also in terms of differences with the activated sludge from conventional activated sludge plants. Sludge dewaterability is then discussed, focusing on the differences between aerobically and anaerobically digested sludge. An analysis of the costs related to MBR sludge treatment and disposal also is presented in order to provide a framework for a sustainable MBR sludge management.

MBRActivated sludgeSettore ICAR/03 - Ingegneria Sanitaria-AmbientaleSludge disposalSludge minimization strategiesBioreactorEnvironmental scienceSewage sludge treatmentPulp and paper industrySludge productionActivated sludge dewaterability
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Gradient-enhanced model and its micromorphic regularization for simulation of Lüders-like bands in shape memory alloys

2018

Abstract Shape memory alloys, notably NiTi, often exhibit softening pseudoelastic response that results in formation and propagation of Luders-like bands upon loading, for instance, in uniaxial tension. A common approach to modelling softening and strain localization is to resort to gradient-enhanced formulations that are capable of restoring well-posedness of the boundary-value problem. This approach is also followed in the present paper by introducing a gradient-enhancement into a simple one-dimensional model of pseudoelasticity. In order to facilitate computational treatment, a micromorphic-type regularization of the gradient-enhanced model is subsequently performed. The formulation empl…

Materials scienceAugmented Lagrangian methodApplied MathematicsMechanical EngineeringUniaxial tension02 engineering and technologyShape-memory alloyMechanics021001 nanoscience & nanotechnologyCondensed Matter PhysicsEnergy minimization020303 mechanical engineering & transportsClassical mechanics0203 mechanical engineeringMechanics of MaterialsNickel titaniumModeling and SimulationRegularization (physics)PseudoelasticityGeneral Materials Science0210 nano-technologySofteningInternational Journal of Solids and Structures
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Atomistic modeling of crystal structure of Ca1.67SiHx

2015

The atomic structure of calcium-silicate-hydrate (C-1.67-S-H-x) has been investigated by theoretical methods in order to establish a better insight into its structure. Three models for C-S-H all derived from tobermorite are proposed and a large number of structures were created within each model by making a random distribution of silica oligomers of different size within each structure. These structures were subjected to structural relaxation by geometry optimization and molecular dynamics steps. That resulted in a set of energies within each model. Despite an energy distribution between individual structures within each model, significant energy differences are observed between the three m…

Materials scienceRelaxation (NMR)Structure (category theory)Applied ChemistryTobermoriteBuilding and ConstructionCrystal structureCalcium-Silicate-Hydrate (C-S-H) (B); Crystal Structure (B); Atomistic simulationEnergy minimizationInorganic ChemistryCrystallographyMolecular dynamicsChemical physicsTheoretical chemistryMoleculeGeneral Materials ScienceTheoretical Chemistry
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Forecasting Techniques for Energy Optimization in Buildings

2014

Mathematical optimizationComputer scienceEnergy minimization
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A challenging family of automata for classical minimization algorithms

2010

In this paper a particular family of deterministic automata that was built to reach the worst case complexity of Hopcroft's state minimization algorithm is considered. This family is also challenging for the two other classical minimization algorithms: it achieves the worst case for Moore's algorithm, as a consequence of a result by Berstel et al., and is of at least quadratic complexity for Brzozowski's solution, which is our main contribution. It therefore constitutes an interesting family, which can be useful to measure the efficiency of implementations of well-known or new minimization algorithms.

Mathematical optimizationComputer science[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS][INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]0102 computer and information sciences02 engineering and technology01 natural sciencesMeasure (mathematics)Classical Minimization AlgorithmAutomatonRegular languageDFA minimization010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringWorst-case complexity020201 artificial intelligence & image processingMinificationState (computer science)AlgorithmComputer Science::Formal Languages and Automata TheoryComputingMilieux_MISCELLANEOUS
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BMaD – A Boolean Matrix Decomposition Framework

2014

Boolean matrix decomposition is a method to obtain a compressed representation of a matrix with Boolean entries. We present a modular framework that unifies several Boolean matrix decomposition algorithms, and provide methods to evaluate their performance. The main advantages of the framework are its modular approach and hence the flexible combination of the steps of a Boolean matrix decomposition and the capability of handling missing values. The framework is licensed under the GPLv3 and can be downloaded freely at http://projects.informatik.uni-mainz.de/bmad.

Matrix (mathematics)Theoretical computer scienceAnd-inverter graphBoolean circuitDecomposition (computer science)Logical matrixCircuit minimization for Boolean functionsRepresentation (mathematics)Standard Boolean modelMathematics
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Ab initio conformational study of 2,2′:5′,2″-terthiophene

1996

Abstract The conformers of 2,2′:5′,2″-terthiophene were determined through ab initio MO full geometry optimization with a 6-31G * basis set. Different minima were found corresponding to twisted anti, anti, syn, anti and syn, syn structures. An estimate of the interconversion rate between conformers was performed.

Maxima and minimaCrystallographychemistry.chemical_compoundTerthiopheneChemistryComputational chemistryAb initioGeneral Physics and AstronomyPhysical and Theoretical ChemistryEnergy minimizationConformational isomerismBasis setChemical Physics Letters
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