Search results for "computer and information sciences"

showing 10 items of 1328 documents

Bayesian subcohort selection for longitudinal covariate measurements in follow-up studies

2016

We consider planning longitudinal covariate measurements in follow-up studies where covariates are time-varying. We assume that the entire cohort cannot be selected for longitudinal measurements due to financial limitations and study how a subset of the cohort should be selected optimally in order to obtain precise estimates of covariate effects in a survival model. In our approach, the study will be designed sequentially utilizing the data collected in previous measurements of the individuals as prior information. We propose using a Bayesian optimality criterion in the subcohort selections, which is compared with simple random sampling using simulated and real follow-up data. This study ex…

Methodology (stat.ME)FOS: Computer and information sciencesStatistics - Methodology
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Spatial noise-aware temperature retrieval from infrared sounder data

2020

In this paper we present a combined strategy for the retrieval of atmospheric profiles from infrared sounders. The approach considers the spatial information and a noise-dependent dimensionality reduction approach. The extracted features are fed into a canonical linear regression. We compare Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) for dimensionality reduction, and study the compactness and information content of the extracted features. Assessment of the results is done on a big dataset covering many spatial and temporal situations. PCA is widely used for these purposes but our analysis shows that one can gain significant improvements of the error rates when using…

Signal Processing (eess.SP)FOS: Computer and information sciencesComputer Science - Machine Learningbusiness.industryComputer scienceDimensionality reductionFeature extraction0211 other engineering and technologiesWord error ratePattern recognitionRegression analysis02 engineering and technologyMachine Learning (cs.LG)Principal component analysisLinear regression0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceElectrical Engineering and Systems Science - Signal ProcessingbusinessSpatial analysis021101 geological & geomatics engineering
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How Do Software Companies Deal with Artificial Intelligence Ethics? : A Gap Analysis

2022

The public and academic discussion on Artificial Intelligence (AI) ethics is accelerating and the general public is becoming more aware AI ethics issues such as data privacy in these systems. To guide ethical development of AI systems, governmental and institutional actors, as well as companies, have drafted various guidelines for ethical AI. Though these guidelines are becoming increasingly common, they have been criticized for a lack of impact on industrial practice. There seems to be a gap between research and practice in the area, though its exact nature remains unknown. In this paper, we present a gap analysis of the current state of the art by comparing practices of 39 companies that …

järjestelmäsuunnitteluohjelmistotuotantosoftware companiestekoälyetiikka113 Computer and information sciencesartificial intelligenceohjelmistokehitysethicstietotekniikkayritykset
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The Average State Complexity of the Star of a Finite Set of Words Is Linear

2008

We prove that, for the uniform distribution over all sets Xof m(that is a fixed integer) non-empty words whose sum of lengths is n, $\mathcal{D}_X$, one of the usual deterministic automata recognizing X*, has on average $\mathcal{O}(n)$ states and that the average state complexity of X*is i¾?(n). We also show that the average time complexity of the computation of the automaton $\mathcal{D}_X$ is $\mathcal{O}(n\log n)$, when the alphabet is of size at least three.

Uniform distribution (continuous)ComputationStar (game theory)0102 computer and information sciences02 engineering and technology[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]01 natural sciencesCombinatoricsInteger0202 electrical engineering electronic engineering information engineeringTime complexityFinite setMathematicsstar operationDiscrete mathematicsaverage case analysistate complexity16. Peace & justiceBinary logarithm[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]automatonState complexity010201 computation theory & mathematicsfinite language020201 artificial intelligence & image processingComputer Science::Formal Languages and Automata Theory
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Disentangling Derivatives, Uncertainty and Error in Gaussian Process Models

2020

Gaussian Processes (GPs) are a class of kernel methods that have shown to be very useful in geoscience applications. They are widely used because they are simple, flexible and provide very accurate estimates for nonlinear problems, especially in parameter retrieval. An addition to a predictive mean function, GPs come equipped with a useful property: the predictive variance function which provides confidence intervals for the predictions. The GP formulation usually assumes that there is no input noise in the training and testing points, only in the observations. However, this is often not the case in Earth observation problems where an accurate assessment of the instrument error is usually a…

FOS: Computer and information sciencesComputer Science - Machine Learning010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesMachine Learning (stat.ML)02 engineering and technology01 natural sciencesMachine Learning (cs.LG)symbols.namesakeStatistics - Machine LearningGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesVariance functionPropagation of uncertaintyVariance (accounting)Function (mathematics)Confidence intervalNonlinear systemNoiseKernel method13. Climate actionKernel (statistics)symbolsAlgorithmIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Text Compression Using Antidictionaries

1999

International audience; We give a new text compression scheme based on Forbidden Words ("antidictionary"). We prove that our algorithms attain the entropy for balanced binary sources. They run in linear time. Moreover, one of the main advantages of this approach is that it produces very fast decompressors. A second advantage is a synchronization property that is helpful to search compressed data and allows parallel compression. Our algorithms can also be presented as "compilers" that create compressors dedicated to any previously fixed source. The techniques used in this paper are from Information Theory and Finite Automata.

Theoretical computer scienceFinite-state machineComputer science[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]010102 general mathematicsforbidden wordData_CODINGANDINFORMATIONTHEORY0102 computer and information sciencesInformation theory01 natural sciencesfinite automatonParallel compressionpattern matching010201 computation theory & mathematicsEntropy (information theory)Pattern matching0101 mathematicsTime complexityAlgorithmdata compressioninformation theoryData compression
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Force-velocity profiling in athletes: Reliability and agreement across methods

2021

The aim of the study was to examine the test-retest reliability and agreement across methods for assessing individual force-velocity (FV) profiles of the lower limbs in athletes. Using a multicenter approach, 27 male athletes completed all measurements for the main analysis, with up to 82 male and female athletes on some measurements. The athletes were tested twice before and twice after a 2- to 6-month period of regular training and sport participation. The double testing sessions were separated by ~1 week. Individual FV-profiles were acquired from incremental loading protocols in squat jump (SJ), countermovement jump (CMJ) and leg press. A force plate, linear encoder and a flight time cal…

MalePhysiologyIntraclass correlationExtrapolationVelocitySocial Sciencesmedicine.disease_causeJumpingMathematical and Statistical TechniquesJumpingStatisticsMedicine and Health SciencesPsychologyRange of Motion ArticularLeg pressMathematicsMeasurementNumerical AnalysisMultidisciplinaryPhysicsStatisticsQRClassical MechanicsSoftware EngineeringVDP::Medisinske Fag: 700::Idrettsmedisinske fag: 850Sports ScienceLower ExtremityPhysical SciencessymbolsJumpLegsEngineering and TechnologyRegression AnalysisMedicineFemaleAnatomyResearch ArticleSportsAdultComputer and Information SciencesAdolescentCoefficient of variationScienceLinear Regression AnalysisResearch and Analysis MethodsComputer SoftwareMotionYoung Adultsymbols.namesakeLinear regressionmedicineHumansMuscle StrengthStatistical MethodsExerciseBehaviorBiological LocomotionBiology and Life SciencesReproducibility of ResultsPearson product-moment correlation coefficientStandard errorAthletesPhysical FitnessBody LimbsExercise TestRecreationMathematics
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Qualitative Comparison of Community Detection Algorithms

2011

Community detection is a very active field in complex networks analysis, consisting in identifying groups of nodes more densely interconnected relatively to the rest of the network. The existing algorithms are usually tested and compared on real-world and artificial networks, their performance being assessed through some partition similarity measure. However, artificial networks realism can be questioned, and the appropriateness of those measures is not obvious. In this study, we take advantage of recent advances concerning the characterization of community structures to tackle these questions. We first generate networks thanks to the most realistic model available to date. Their analysis r…

FOS: Computer and information sciencesPhysics - Physics and SocietyComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionFOS: Physical sciences02 engineering and technologyPhysics and Society (physics.soc-ph)Similarity measure[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Complex NetworksField (computer science)Qualitative analysis020204 information systems0202 electrical engineering electronic engineering information engineeringSocial and Information Networks (cs.SI)Algorithms ComparisonArtificial networks[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Computer Science - Social and Information Networks[ INFO.INFO-DM ] Computer Science [cs]/Discrete Mathematics [cs.DM]Complex networkPartition (database)Community Properties020201 artificial intelligence & image processingAlgorithmCommunity Detection
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Binary jumbled string matching for highly run-length compressible texts

2012

The Binary Jumbled String Matching problem is defined as: Given a string $s$ over $\{a,b\}$ of length $n$ and a query $(x,y)$, with $x,y$ non-negative integers, decide whether $s$ has a substring $t$ with exactly $x$ $a$'s and $y$ $b$'s. Previous solutions created an index of size O(n) in a pre-processing step, which was then used to answer queries in constant time. The fastest algorithms for construction of this index have running time $O(n^2/\log n)$ [Burcsi et al., FUN 2010; Moosa and Rahman, IPL 2010], or $O(n^2/\log^2 n)$ in the word-RAM model [Moosa and Rahman, JDA 2012]. We propose an index constructed directly from the run-length encoding of $s$. The construction time of our index i…

FOS: Computer and information sciencesString algorithmsStructure (category theory)Binary numberG.2.1Data_CODINGANDINFORMATIONTHEORY0102 computer and information sciences02 engineering and technologyString searching algorithm01 natural sciencesComputer Science - Information RetrievalTheoretical Computer ScienceCombinatoricsdata structuresSimple (abstract algebra)Computer Science - Data Structures and AlgorithmsString algorithms; jumbled pattern matching; prefix normal form; data structures0202 electrical engineering electronic engineering information engineeringParikh vectorData Structures and Algorithms (cs.DS)Run-length encodingMathematics68W32 68P05 68P20String (computer science)prefix normal formSubstringComputer Science Applicationsjumbled pattern matching010201 computation theory & mathematicsData structureSignal ProcessingRun-length encoding020201 artificial intelligence & image processingConstant (mathematics)Information Retrieval (cs.IR)Information SystemsInformation Processing Letters
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A Motzkin filter in the Tamari lattice

2015

The Tamari lattice of order n can be defined on the set T n of binary trees endowed with the partial order relation induced by the well-known rotation transformation. In this paper, we restrict our attention to the subset M n of Motzkin trees. This set appears as a filter of the Tamari lattice. We prove that its diameter is 2 n - 5 and that its radius is n - 2 . Enumeration results are given for join and meet irreducible elements, minimal elements and coverings. The set M n endowed with an order relation based on a restricted rotation is then isomorphic to a ranked join-semilattice recently defined in Baril and Pallo (2014). As a consequence, we deduce an upper bound for the rotation distan…

Discrete mathematicsMathematics::CombinatoricsBinary tree010102 general mathematicsLattice (group)0102 computer and information sciences[ MATH.MATH-CO ] Mathematics [math]/Combinatorics [math.CO]01 natural sciencesUpper and lower boundsTheoretical Computer ScienceCombinatoricsJoin and meet010201 computation theory & mathematics[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]Discrete Mathematics and CombinatoricsOrder (group theory)Ideal (order theory)0101 mathematicsFilter (mathematics)Tamari latticeComputingMilieux_MISCELLANEOUSMathematics
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