Search results for "Algorithm"

showing 10 items of 4887 documents

"Table 2" of "Backward electroproduction of pi0 mesons on protons in the region of nucleon resonances at four momentum transfer squared Q**2 = 1.0-Ge…

2005

Cross section SIG(T) + EPSILON*SIG(L) for COS(THETA*) = -0.925.

PhotoproductionComputingMilieux_THECOMPUTINGPROFESSIONElectron productionTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYE- P --> E- P PI0ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION1.11-1.77MathematicsofComputing_NUMERICALANALYSISExclusiveInformationSystems_MISCELLANEOUSD2SIG/DOMEGADouble Differential Cross SectionGAMMA* P --> P PI0
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"Table 4" of "Backward electroproduction of pi0 mesons on protons in the region of nucleon resonances at four momentum transfer squared Q**2 = 1.0-Ge…

2005

Cross section SIG(T) + EPSILON*SIG(L) for COS(THETA*) = -0.825.

PhotoproductionComputingMilieux_THECOMPUTINGPROFESSIONElectron productionTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYE- P --> E- P PI0ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONMathematicsofComputing_NUMERICALANALYSIS1.11-1.45ExclusiveInformationSystems_MISCELLANEOUSD2SIG/DOMEGADouble Differential Cross SectionGAMMA* P --> P PI0
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"Table 3" of "Backward electroproduction of pi0 mesons on protons in the region of nucleon resonances at four momentum transfer squared Q**2 = 1.0-Ge…

2005

Cross section SIG(T) + EPSILON*SIG(L) for COS(THETA*) = -0.875.

PhotoproductionComputingMilieux_THECOMPUTINGPROFESSIONElectron productionTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYE- P --> E- P PI0ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONMathematicsofComputing_NUMERICALANALYSISExclusiveInformationSystems_MISCELLANEOUSD2SIG/DOMEGADouble Differential Cross Section1.11-1.61GAMMA* P --> P PI0
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Enhanced electron-transfer properties of cofacial porphyrin dimers through pi-pi interactions

2009

pi-pi assisted: Photoinduced electron transfer from cofacial porphyrin dimers to electron acceptors is prominently accelerated, whereas the back electron transfer is decelerated, relative to the corresponding porphyrin monomer (see figure).The radical cation of zinc tetrapentylporphyrin is dimerized with an excess of the neutral counterpart to form the dimer radical cation in which the unpaired electron is delocalized over both porphyrin rings. The dimeric radical cation exhibits an NIR absorption spectrum characteristic of weak pi-bond formation between the porphyrin rings. When cofacial porphyrin dimers, linked by different spacers, are oxidized such pi-bond formation between the porphyri…

Photosynthetic reaction centrePorphyrinsPhotosynthetic Reaction Center Complex ProteinsElectron donorpi interactionsPhotochemistry010402 general chemistry01 natural sciencesPhotoinduced electron transferCatalysisElectron Transportchemistry.chemical_compoundElectron transferredox chemistrypolycyclic compoundsComputingMilieux_MISCELLANEOUSchemistry.chemical_classificationphotosynthesisphotochemistryMolecular StructureChemistry010405 organic chemistryOrganic ChemistryGeneral ChemistryElectron acceptorelectron transferPorphyrinMarcus theory0104 chemical sciences[CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistryZincUnpaired electronModels Chemical[ CHIM.THEO ] Chemical Sciences/Theoretical and/or physical chemistryThermodynamicsOxidation-ReductionAlgorithms
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Syntax Error Handling

1990

In the previous chapters we have seen that the various parsers discussed, at least whenever they are deterministic, detect an error in any nonsentence. This means, that on any nonsentence there is a computation ending with an error configuration. For practical parsers, mere error detection is not enough; the parser should also emit a meaningful error message and recover from the error. A recovery means that the error configuration is transformed into a non-error configuration at which normal parsing can be resumed. Moreover, the transformation should be done so that as few input symbols as possible will be discarded. The goal of the error recovery is to maximize the amount of input text tha…

PhraseParsingComputer sciencemedia_common.quotation_subjectComputationAmbiguitycomputer.software_genreTransformation (function)Quality (business)Syntax errorError detection and correctionAlgorithmcomputermedia_common
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New Algorithms for Computing Phylogenetic Biodiversity

2014

A common problem that appears in many case studies in ecology is the following: given a rooted phylogenetic tree \(\mathcal{T}\) and a subset R of its leaf nodes, we want to compute the distance between the elements in R. A very popular distance measure that can be used for this reason is the Phylogenetic Diversity (PD), which is defined as the cost of the minimum weight Steiner tree in \(\mathcal{T}\) that spans the nodes in R. To analyse the value of the PD for a given set R it is important also to calculate the variance of this measure. However, the best algorithm known so far for computing the variance of the PD is inefficient; for any input tree \(\mathcal{T}\) that consists of n nodes…

Phylogenetic diversitysymbols.namesakeTree (descriptive set theory)Phylogenetic treeOpen problemsymbolsMinimum weightOrder (ring theory)Steiner tree problemMeasure (mathematics)AlgorithmMathematics
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EUDAQ $-$ A Data Acquisition Software Framework for Common Beam Telescopes

2019

EUDAQ is a generic data acquisition software developed for use in conjunction with common beam telescopes at charged particle beam lines. Providing high-precision reference tracks for performance studies of new sensors, beam telescopes are essential for the research and development towards future detectors for high-energy physics. As beam time is a highly limited resource, EUDAQ has been designed with reliability and ease-of-use in mind. It enables flexible integration of different independent devices under test via their specific data acquisition systems into a top-level framework. EUDAQ controls all components globally, handles the data flow centrally and synchronises and records the data…

Physics - Instrumentation and DetectorsDetector control systems (detector and experiment monitoring and slow-control systems architecture hardware algorithms databases)data acquisitionData management01 natural sciences7. Clean energyHigh Energy Physics - Experiment030218 nuclear medicine & medical imagingHigh Energy Physics - Experiment (hep-ex)0302 clinical medicineData acquisitionbeam [charged particle]Particle tracking detectors[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]hardwareDetectors and Experimental Techniquesphysics.ins-detInstrumentationMathematical PhysicsData processingData stream miningPhysicsDetectorInstrumentation and Detectors (physics.ins-det)control systemCharged particle beamdatabases)Particle Physics - ExperimentComputer hardwareperformancearchitectureData acquisition system for beam tests [5]FOS: Physical sciencesalgorithmsprogramming03 medical and health sciencesCalorimeterscharged particle: beam0103 physical sciencesddc:530ddc:610[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]hep-ex010308 nuclear & particles physicsbusiness.industryDetector control systems (detector and experiment monitoring and slow-control systemsData acquisition conceptsData flow diagramdata managementbusinessBeam (structure)
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The distributed Slow Control System of the XENON100 experiment

2012

The XENON100 experiment, in operation at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy, was designed to search for evidence of dark matter interactions inside a volume of liquid xenon using a dual-phase time projection chamber. This paper describes the Slow Control System (SCS) of the experiment with emphasis on the distributed architecture as well as on its modular and expandable nature. The system software was designed according to the rules of Object-Oriented Programming and coded in Java, thus promoting code reusability and maximum flexibility during commissioning of the experiment. The SCS has been continuously monitoring the XENON100 detector since mid 2008, remotely recordi…

Physics - Instrumentation and Detectorsarchitecture[PHYS.ASTR.IM]Physics [physics]/Astrophysics [astro-ph]/Instrumentation and Methods for Astrophysic [astro-ph.IM]JavaComputer scienceReal-time computingFOS: Physical scienceschemistry.chemical_elementControl and monitor systems online; Control systems; Detector control systems (detector and experiment monitoring and slow-control systems architecture hardware algorithms databases)algorithms01 natural sciencesXenon0103 physical scienceshardwareDETECTOR CONTROL SYSTEMS[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]CONTROL SYSTEMS010306 general physicsInstrumentation and Methods for Astrophysics (astro-ph.IM)InstrumentationMathematical Physicscomputer.programming_languageTime projection chamber010308 nuclear & particles physicsbusiness.industryControl and monitor systems onlineDetector control systems (detector and experiment monitoring and slow-control systemsEmphasis (telecommunications)Volume (computing)Instrumentation and Detectors (physics.ins-det)Modular design[SDU.ASTR.IM]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Instrumentation and Methods for Astrophysic [astro-ph.IM]chemistryControl systemAstrophysics - Instrumentation and Methods for Astrophysicsdatabases)businesscomputerSystem software
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A tool for filtering information in complex systems

2005

We introduce a technique to filter out complex data-sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation based graphs giving filtered graphs which preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0) triangular loops and 4 element cliques are formed. The application of this filtering procedure to 100 stocks in the USA equity markets shows that such loops and cliqu…

Physics - Physics and SocietyComputer scienceComplex systemFOS: Physical sciencesPhysics and Society (physics.soc-ph)Minimum spanning treecomputer.software_genrePlanarHierarchical organizationINTERNETCondensed Matter - Statistical MechanicsComplex data typeMultidisciplinarySmall-world networkStatistical Mechanics (cond-mat.stat-mech)SMALL-WORLD NETWORKSFilter (signal processing)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComplex networkWEBDYNAMIC ASSET TREESPhysical SciencesGRAPHData miningAlgorithmcomputerMathematicsofComputing_DISCRETEMATHEMATICS
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Kullback-Leibler distance as a measure of the information filtered from multivariate data

2007

We show that the Kullback-Leibler distance is a good measure of the statistical uncertainty of correlation matrices estimated by using a finite set of data. For correlation matrices of multivariate Gaussian variables we analytically determine the expected values of the Kullback-Leibler distance of a sample correlation matrix from a reference model and we show that the expected values are known also when the specific model is unknown. We propose to make use of the Kullback-Leibler distance to estimate the information extracted from a correlation matrix by correlation filtering procedures. We also show how to use this distance to measure the stability of filtering procedures with respect to s…

Physics - Physics and SocietyKullback–Leibler divergenceStatistical Finance (q-fin.ST)Covariance matrixEXPRESSION DATAFOS: Physical sciencesQuantitative Finance - Statistical FinanceMultivariate normal distributionPhysics and Society (physics.soc-ph)Measure (mathematics)Stability (probability)Hierarchical clusteringDistance correlationFOS: Economics and businessPhysics - Data Analysis Statistics and ProbabilityStatisticsTime seriesAlgorithmData Analysis Statistics and Probability (physics.data-an)MATRICESMathematics
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