Search results for " Computer Software"

showing 4 items of 4 documents

OpenMolcas: From Source Code to Insight

2019

In this article we describe the OpenMolcas environment and invite the computational chemistry community to collaborate. The open-source project already includes a large number of new developments realized during the transition from the commercial MOLCAS product to the open-source platform. The paper initially describes the technical details of the new software development platform. This is followed by brief presentations of many new methods, implementations, and features of the OpenMolcas program suite. These developments include novel wave function methods such as stochastic complete active space self-consistent field, density matrix renormalization group (DMRG) methods, and hybrid multico…

Wave functionSource codeField (physics)Computer sciencemedia_common.quotation_subjectInterfacesSemiclassical physics010402 general chemistry0601 Biochemistry and Cell Biology01 natural sciencesComputational scienceNOChemical calculationsMathematical methodschemical calculations ; electron correlation ; interfaces ; mathematical methods ; wave function0103 physical sciences0307 Theoretical and Computational ChemistryPhysical and Theoretical ChemistryWave functionWave function Interfaces Chemical calculations Mathematical methods Electron correlationComputingMilieux_MISCELLANEOUSmedia_commonChemical Physics010304 chemical physicsBasis (linear algebra)business.industryDensity matrix renormalization groupElectron correlationSoftware development0803 Computer Software0104 chemical sciencesComputer Science ApplicationsVisualization[CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistrybusiness
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Efficacy and cost-effectiveness of guided and unguided internet- and mobile-based indicated transdiagnostic prevention of depression and anxiety (ICa…

2019

Background Depression and anxiety are highly prevalent and often co-occur. Several studies indicate the potential of disorder-specific psychological interventions for the prevention of each of these disorders. To treat comorbidity, transdiagnostic treatment concepts seem to be a promising approach, however, evidence for transdiagnostic concepts of prevention remains inconclusive. Internet- and mobile-based interventions (IMIs) may be an effective means to deliver psychological interventions on a large scale for the prevention of common mental disorders (CMDs) such as depression and anxiety. IMIs have been shown to be effective in treating CMDs, e.g. in reducing symptoms of depression and an…

Transdiagnosticlcsh:T58.5-58.64lcsh:Information technologyDepressionPreventionlcsh:BF1-990610 Medicine & healthInternet-basedAnxietyArticlelcsh:PsychologyQA76 Computer softwareSDG 3 - Good Health and Well-beingRandomized controlled trial/dk/atira/pure/core/keywords/600089002/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingPsychologyddc:158150 PsychologyPrevention Transdiagnostic Depression Anxiety Internet-based Randomized controlled trialRC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
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DYNAMIC SEMANTIC USER PROFILING FROM IMPLICIT WEB NAVIGATION DATA

2014

International audience; On the Web, pages are often dynamically generated and allow publishers to individually adapt contents to each viewer. Underlying systems must correctly understand the user's context - crucial especially in the case of online advertisement placement. The article at hand describes our proposition of a novel profiling system, adapted to the special needs of digital advertising. Based on Semantic Web Technologies, the MindMinings system relies on an ontology to enable thorough understanding of each user's context and needs. The underlying ontology structure also provides enhanced interoperability with semantically annotated knowledge resources, notably vocabularies from …

JEL classification: M37 Advertising; L86 Information and Internet Services Computer Software; D80 General (Information Knowledge Uncertainty)Web Analysis[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL]Rule-based reasoningOntologiesUser Profiling[ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]Semantic Web
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KFAS : Exponential Family State Space Models in R

2017

State space modelling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes an R package KFAS for state space modelling with the observations from an exponential family, namely Gaussian, Poisson, binomial, negative binomial and gamma distributions. After introducing the basic theory behind Gaussian and non-Gaussian state space models, an illustrative example of Poisson time series forecasting is provided. Finally, a comparison to alternative R packages suitable for non-Gaussian time series modelling is presented.

FOS: Computer and information sciencesStatistics and ProbabilityaikasarjatGaussianNegative binomial distributionforecastingPoisson distribution01 natural sciencesStatistics - ComputationMethodology (stat.ME)010104 statistics & probability03 medical and health sciencessymbols.namesake0302 clinical medicineExponential familyexponential familyGamma distributionStatistical inferenceState spaceApplied mathematicsSannolikhetsteori och statistik030212 general & internal medicine0101 mathematicsProbability Theory and Statisticslcsh:Statisticslcsh:HA1-4737Computation (stat.CO)Statistics - MethodologyMathematicsR; exponential family; state space models; time series; forecasting; dynamic linear modelsta112state space modelsSeries (mathematics)RStatistics; Computer softwaresymbolsStatistics Probability and Uncertaintytime seriesSoftwaredynamic linear models
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