Search results for "COD"

showing 10 items of 2985 documents

Semantics of UML 2.0 Activity Diagram for Business Modeling by Means of Virtual Machine

2005

The paper proposes a more formalized definition of UML 2.0 Activity Diagram semantics. A subset of activity diagram constructs relevant for business process modeling is considered. The semantics definition is based on the original token flow methodology, but a more constructive approach is used. The Activity Diagram Virtual machine is defined by means of a metamodel, with operations defined by a mix of pseudocode and OCL pre- and postconditions. A formal procedure is described which builds the virtual machine for any activity diagram. The relatively complicated original token movement rules in control nodes and edges are combined into paths from an action to action. A new approach is the us…

FOS: Computer and information sciencesComputer Science - Programming LanguagesSemantics (computer science)Computer scienceProgramming languageActivity diagramBusiness process modelingSecurity tokencomputer.software_genreMetamodelingComputational Engineering Finance and Science (cs.CE)Unified Modeling LanguageVirtual machineComputer Science - Computational Engineering Finance and SciencePseudocodecomputercomputer.programming_languageProgramming Languages (cs.PL)
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Nash codes for noisy channels

2012

This paper studies the stability of communication protocols that deal with transmission errors. We consider a coordination game between an informed sender and an uninformed decision maker, the receiver, who communicate over a noisy channel. The sender's strategy, called a code, maps states of nature to signals. The receiver's best response is to decode the received channel output as the state with highest expected receiver payoff. Given this decoding, an equilibrium or "Nash code" results if the sender encodes every state as prescribed. We show two theorems that give sufficient conditions for Nash codes. First, a receiver-optimal code defines a Nash code. A second, more surprising observati…

FOS: Computer and information sciencesComputer Science::Computer Science and Game TheoryTheoretical computer scienceComputer scienceInformation Theory (cs.IT)Computer Science - Information TheoryStochastic gamejel:C72jel:D82Stability (learning theory)Data_CODINGANDINFORMATIONTHEORYManagement Science and Operations Researchsender-receiver game communication noisy channel91A28Computer Science ApplicationsComputer Science - Computer Science and Game TheoryBest responseCode (cryptography)Coordination gameQA MathematicsDecoding methodsCommunication channelComputer Science and Game Theory (cs.GT)Computer Science::Information Theory
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Quantum autoencoders via quantum adders with genetic algorithms

2017

The quantum autoencoder is a recent paradigm in the field of quantum machine learning, which may enable an enhanced use of resources in quantum technologies. To this end, quantum neural networks with less nodes in the inner than in the outer layers were considered. Here, we propose a useful connection between quantum autoencoders and quantum adders, which approximately add two unknown quantum states supported in different quantum systems. Specifically, this link allows us to employ optimized approximate quantum adders, obtained with genetic algorithms, for the implementation of quantum autoencoders for a variety of initial states. Furthermore, we can also directly optimize the quantum autoe…

FOS: Computer and information sciencesComputer Science::Machine Learning0301 basic medicineComputer Science - Machine LearningAdderPhysics and Astronomy (miscellaneous)Quantum machine learningField (physics)Computer scienceMaterials Science (miscellaneous)Computer Science::Neural and Evolutionary ComputationFOS: Physical sciencesData_CODINGANDINFORMATIONTHEORYTopology01 natural sciencesMachine Learning (cs.LG)Statistics::Machine Learning03 medical and health sciencesQuantum state0103 physical sciencesNeural and Evolutionary Computing (cs.NE)Electrical and Electronic Engineering010306 general physicsQuantumQuantum PhysicsArtificial neural networkComputer Science - Neural and Evolutionary ComputingTheoryofComputation_GENERALAutoencoderAtomic and Molecular Physics and OpticsQuantum technology030104 developmental biologyComputerSystemsOrganization_MISCELLANEOUSQuantum Physics (quant-ph)
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Improving table compression with combinatorial optimization

2002

We study the problem of compressing massive tables within the partition-training paradigm introduced by Buchsbaum et al. [SODA'00], in which a table is partitioned by an off-line training procedure into disjoint intervals of columns, each of which is compressed separately by a standard, on-line compressor like gzip. We provide a new theory that unifies previous experimental observations on partitioning and heuristic observations on column permutation, all of which are used to improve compression rates. Based on the theory, we devise the first on-line training algorithms for table compression, which can be applied to individual files, not just continuously operating sources; and also a new, …

FOS: Computer and information sciencesComputer scienceHeuristic (computer science)E.4G.2.1Data_CODINGANDINFORMATIONTHEORYDisjoint setsTravelling salesman problemPermutationArtificial IntelligenceCompression (functional analysis)Computer Science - Data Structures and AlgorithmsH.1.8H.2.7Data Structures and Algorithms (cs.DS)E.4; F.1.3; F.2.2; G.2.1; H.1.1; H.1.8; H.2.7H.1.1Dynamic programmingHardware and ArchitectureControl and Systems EngineeringCombinatorial optimizationTable (database)F.1.3F.2.2AlgorithmSoftwareInformation SystemsJournal of the ACM
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On Combinatorial Generation of Prefix Normal Words

2014

A prefix normal word is a binary word with the property that no substring has more 1s than the prefix of the same length. This class of words is important in the context of binary jumbled pattern matching. In this paper we present an efficient algorithm for exhaustively listing the prefix normal words with a fixed length. The algorithm is based on the fact that the language of prefix normal words is a bubble language, a class of binary languages with the property that, for any word w in the language, exchanging the first occurrence of 01 by 10 in w results in another word in the language. We prove that each prefix normal word is produced in O(n) amortized time, and conjecture, based on expe…

FOS: Computer and information sciencesDiscrete Mathematics (cs.DM)Computer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)Data_CODINGANDINFORMATIONTHEORYComputer Science - Discrete Mathematics
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Normal, Abby Normal, Prefix Normal

2014

A prefix normal word is a binary word with the property that no substring has more 1s than the prefix of the same length. This class of words is important in the context of binary jumbled pattern matching. In this paper we present results about the number $pnw(n)$ of prefix normal words of length $n$, showing that $pnw(n) =\Omega\left(2^{n - c\sqrt{n\ln n}}\right)$ for some $c$ and $pnw(n) = O \left(\frac{2^n (\ln n)^2}{n}\right)$. We introduce efficient algorithms for testing the prefix normal property and a "mechanical algorithm" for computing prefix normal forms. We also include games which can be played with prefix normal words. In these games Alice wishes to stay normal but Bob wants t…

FOS: Computer and information sciencesDiscrete Mathematics (cs.DM)Formal Languages and Automata Theory (cs.FL)Computer Science - Data Structures and AlgorithmsFOS: MathematicsMathematics - CombinatoricsData Structures and Algorithms (cs.DS)Computer Science - Formal Languages and Automata TheoryCombinatorics (math.CO)Data_CODINGANDINFORMATIONTHEORYComputer Science - Discrete Mathematics
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Monoids and Maximal Codes

2011

In recent years codes that are not Uniquely Decipherable (UD) are been studied partitioning them in classes that localize the ambiguities of the code. A natural question is how we can extend the notion of maximality to codes that are not UD. In this paper we give an answer to this question. To do this we introduce a partial order in the set of submonoids of a monoid showing the existence, in this poset, of maximal elements that we call full monoids. Then a set of generators of a full monoid is, by definition, a maximal code. We show how this definition extends, in a natural way, the existing definition concerning UD codes and we find a characteristic property of a monoid generated by a maxi…

FOS: Computer and information sciencesDiscrete mathematicsMonoidCode (set theory)Formal Languages and Automata Theory (cs.FL)lcsh:MathematicsComputer Science - Formal Languages and Automata TheoryAstrophysics::Cosmology and Extragalactic Astrophysicslcsh:QA1-939lcsh:QA75.5-76.95Set (abstract data type)chemistry.chemical_compoundchemistryFOS: MathematicsMathematics - CombinatoricsOrder (group theory)High Energy Physics::ExperimentCombinatorics (math.CO)lcsh:Electronic computers. Computer scienceCharacteristic propertyPartially ordered setMaximal elementMathematicsElectronic Proceedings in Theoretical Computer Science
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Fast MATLAB assembly of FEM matrices in 2D and 3D: Edge elements

2014

We propose an effective and flexible way to assemble finite element stiffness and mass matrices in MATLAB. We apply this for problems discretized by edge finite elements. Typical edge finite elements are Raviart-Thomas elements used in discretizations of H(div) spaces and Nedelec elements in discretizations of H(curl) spaces. We explain vectorization ideas and comment on a freely available MATLAB code which is fast and scalable with respect to time.

FOS: Computer and information sciencesDiscretizationfinite element method97N80 65M60Matlab codeComputational scienceMathematics::Numerical AnalysisMATLAB code vectorizationmedicineFOS: MathematicsMathematics - Numerical AnalysisMATLABMathematicscomputer.programming_languageCurl (mathematics)ta113Nédélec elementApplied Mathematicsta111StiffnessRaviart–Thomas elementMixed finite element methodNumerical Analysis (math.NA)Finite element methodComputational Mathematicsedge elementScalabilityComputer Science - Mathematical Softwaremedicine.symptomcomputerMathematical Software (cs.MS)
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Generating a Gray code for prefix normal words in amortized polylogarithmic time per word

2020

A prefix normal word is a binary word with the property that no substring has more $1$s than the prefix of the same length. By proving that the set of prefix normal words is a bubble language, we can exhaustively list all prefix normal words of length $n$ as a combinatorial Gray code, where successive strings differ by at most two swaps or bit flips. This Gray code can be generated in $\Oh(\log^2 n)$ amortized time per word, while the best generation algorithm hitherto has $\Oh(n)$ running time per word. We also present a membership tester for prefix normal words, as well as a novel characterization of bubble languages.

FOS: Computer and information sciencesGeneral Computer ScienceFormal Languages and Automata Theory (cs.FL)Property (programming)combinatorial Gray codeComputer Science - Formal Languages and Automata TheoryData_CODINGANDINFORMATIONTHEORY0102 computer and information sciences02 engineering and technologyCharacterization (mathematics)01 natural sciencesTheoretical Computer ScienceCombinatoricsSet (abstract data type)Gray codeComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)MathematicsAmortized analysisSettore INF/01 - Informaticaprefix normal wordsSubstringcombinatorial generationPrefixjumbled pattern matching010201 computation theory & mathematics020201 artificial intelligence & image processingbinary languagesprefix normal words binary languages combinatorial Gray code combinatorial generation jumbled pattern matchingWord (computer architecture)Theoretical Computer Science
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Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations

2019

Abstract Satellite remote sensing has been widely used in the last decades for agricultural applications, both for assessing vegetation condition and for subsequent yield prediction. Existing remote sensing-based methods to estimate gross primary productivity (GPP), which is an important variable to indicate crop photosynthetic function and stress, typically rely on empirical or semi-empirical approaches, which tend to over-simplify photosynthetic mechanisms. In this work, we take advantage of all parallel developments in mechanistic photosynthesis modeling and satellite data availability for an advanced monitoring of crop productivity. In particular, we combine process-based modeling with …

FOS: Computer and information sciencesLandsat 8Earth observation010504 meteorology & atmospheric sciencesComputer Vision and Pattern Recognition (cs.CV)0208 environmental biotechnologyComputer Science - Computer Vision and Pattern RecognitionSoil Science02 engineering and technologyGross primary productivity (GPP)Sentinel-2 (S2)Machine learningcomputer.software_genre01 natural sciencesRadiative transfer modeling (RTM)Atmospheric radiative transfer codesSoil-canopy-observation of photosynthesis and the energy balance (SCOPE)Computers in Earth SciencesC3 crops0105 earth and related environmental sciencesRemote sensing2. Zero hungerArtificial neural networkbusiness.industryEmpirical modellingNeural networks (NN)GeologyVegetationMachine learning (ML)15. Life on landHybrid approach22/4 OA procedure020801 environmental engineeringVariable (computer science)ITC-ISI-JOURNAL-ARTICLEEnvironmental scienceSatelliteArtificial intelligenceScale (map)businesscomputerRemote sensing of environment
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