Search results for "Information Science"

showing 10 items of 3627 documents

Popularity of patterns over $d$-equivalence classes of words and permutations

2020

Abstract Two same length words are d-equivalent if they have same descent set and same underlying alphabet. In particular, two same length permutations are d-equivalent if they have same descent set. The popularity of a pattern in a set of words is the overall number of copies of the pattern within the words of the set. We show the far-from-trivial fact that two patterns are d-equivalent if and only if they are equipopular over any d-equivalence class, and this equipopularity does not follow obviously from a trivial equidistribution.

FOS: Computer and information sciencesClass (set theory)General Computer ScienceDiscrete Mathematics (cs.DM)010102 general mathematics0102 computer and information sciences01 natural sciencesPopularityTheoretical Computer ScienceCombinatoricsSet (abstract data type)010201 computation theory & mathematicsIf and only if[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]FOS: MathematicsMathematics - CombinatoricsCombinatorics (math.CO)0101 mathematicsAlphabetComputingMilieux_MISCELLANEOUSComputer Science::Formal Languages and Automata TheoryMathematicsDescent (mathematics)Computer Science - Discrete Mathematics
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Probabilistic entailment in the setting of coherence: The role of quasi conjunction and inclusion relation

2013

In this paper, by adopting a coherence-based probabilistic approach to default reasoning, we focus the study on the logical operation of quasi conjunction and the Goodman-Nguyen inclusion relation for conditional events. We recall that quasi conjunction is a basic notion for defining consistency of conditional knowledge bases. By deepening some results given in a previous paper we show that, given any finite family of conditional events F and any nonempty subset S of F, the family F p-entails the quasi conjunction C(S); then, given any conditional event E|H, we analyze the equivalence between p-entailment of E|H from F and p-entailment of E|H from C(S), where S is some nonempty subset of F.…

FOS: Computer and information sciencesClass (set theory)Goodman–Nguyen’s inclusion relationQAND ruleSettore MAT/06 - Probabilita' E Statistica MatematicaComputer Science - Artificial IntelligenceMathematics - Statistics TheoryStatistics Theory (math.ST)Logical consequencegoodman-nguyen's inclusion relationTheoretical Computer ScienceArtificial IntelligenceQuasi conjunctionFOS: MathematicsEquivalence (measure theory)MathematicsEvent (probability theory)Discrete mathematicsSettore INF/01 - InformaticaApplied MathematicsProbability (math.PR)quasi conjunction; goodman-nguyen inclusion relation; qand rule; coherence; probabilistic default reasoning; p-entailment; goodman-nguyen's inclusion relationProbabilistic logicCoherence (statistics)Conjunction (grammar)Greatest elementArtificial Intelligence (cs.AI)Probabilistic default reasoninggoodman-nguyen inclusion relationp-EntailmentCoherenceSoftwareMathematics - Probability
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On the Number of Closed Factors in a Word

2015

A closed word (a.k.a. periodic-like word or complete first return) is a word whose longest border does not have internal occurrences, or, equivalently, whose longest repeated prefix is not right special. We investigate the structure of closed factors of words. We show that a word of length $n$ contains at least $n+1$ distinct closed factors, and characterize those words having exactly $n+1$ closed factors. Furthermore, we show that a word of length $n$ can contain $\Theta(n^{2})$ many distinct closed factors.

FOS: Computer and information sciencesClosed wordCombinatorics on wordsComplete returnFormal Languages and Automata Theory (cs.FL)Computer scienceComputer Science (all)Structure (category theory)Computer Science - Formal Languages and Automata TheoryCombinatorics on words Closed word Complete return Rich word Bitonic word68R15Theoretical Computer ScienceCombinatoricsPrefixCombinatorics on wordsRich wordBitonic wordFOS: MathematicsMathematics - CombinatoricsCombinatorics (math.CO)ArithmeticWord (computer architecture)Combinatorics on word
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The Personal Software Process, Experiences from Denmark

2003

Software process improvement (SPI) research and practice is transforming from the traditional large-scale assessment based improvement initiatives into smaller sized, tailored initiatives where the emphasis is set on the development personnel and their personal abilities. The personal software process (PSPSM) is a method for improving the personal capabilities of a single software engineer. This paper contributes to the body of knowledge within this area by reporting experiences from Denmark. The results indicate an improvement in the effort estimation skills and a significant increase in the resulting product quality in terms of reduced total defect density. The data shows that with relati…

FOS: Computer and information sciencesCode reviewProcess managementbusiness.industryComputer sciencemedia_common.quotation_subjectcomputer.software_genreBody of knowledgeSoftware development processSoftware Engineering (cs.SE)Computer Science - Software EngineeringSoftwarePersonal software processQuality (business)Product (category theory)Set (psychology)businesscomputermedia_common
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Color image quality assessment measure using multivariate generalized Gaussian distribution

2014

This paper deals with color image quality assessment in the reduced-reference framework based on natural scenes statistics. In this context, we propose to model the statistics of the steer able pyramid coefficients by a Multivariate Generalized Gaussian distribution (MGGD). This model allows taking into account the high correlation between the components of the RGB color space. For each selected scale and orientation, we extract a parameter matrix from the three color components sub bands. In order to quantify the visual degradation, we use a closed-form of Kullback-Leibler Divergence (KLD) between two MGGDs. Using "TID 2008" benchmark, the proposed measure has been compared with the most i…

FOS: Computer and information sciencesColor histogramColor imagebusiness.industryComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionPattern recognitionColor spaceRGB color spacesymbols.namesakesymbolsPyramid (image processing)Artificial intelligencebusinessDivergence (statistics)Gaussian processGeneralized normal distributionMathematics
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On color image quality assessment using natural image statistics

2014

Color distortion can introduce a significant damage in visual quality perception, however, most of existing reduced-reference quality measures are designed for gray scale images. In this paper, we consider a basic extension of well-known image-statistics based quality assessment measures to color images. In order to evaluate the impact of color information on the measures efficiency, two color spaces are investigated: RGB and CIELAB. Results of an extensive evaluation using TID 2013 benchmark demonstrates that significant improvement can be achieved for a great number of distortion type when the CIELAB color representation is used.

FOS: Computer and information sciencesColor histogrambusiness.industryColor imageComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONColor balanceFalse colorColor spaceICC profileColor depthRGB color modelComputer visionArtificial intelligencebusinessMathematics
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Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis

2016

Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical explanations that do consider both phenomena simultaneously follow parametric formulations based on empirical models. Therefore, it may be argued that the behavior does not come directly from the color statistics but from the convenient functional form adopted. In addition, many times the whole statistical analysis is based on simplified databases that disregard relevant physical effects in the input signal, as, for instance…

FOS: Computer and information sciencesColor visionComputer scienceCognitive NeuroscienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONStandard illuminantMachine Learning (stat.ML)Models BiologicalArts and Humanities (miscellaneous)Statistics - Machine LearningPsychophysicsHumansLearningComputer SimulationChromatic scaleParametric statisticsPrincipal Component AnalysisColor VisionNonlinear dimensionality reductionAdaptation PhysiologicalNonlinear systemNonlinear DynamicsFOS: Biological sciencesQuantitative Biology - Neurons and CognitionMetric (mathematics)A priori and a posterioriNeurons and Cognition (q-bio.NC)AlgorithmColor PerceptionPhotic Stimulation
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Uncommon Suffix Tries

2011

Common assumptions on the source producing the words inserted in a suffix trie with $n$ leaves lead to a $\log n$ height and saturation level. We provide an example of a suffix trie whose height increases faster than a power of $n$ and another one whose saturation level is negligible with respect to $\log n$. Both are built from VLMC (Variable Length Markov Chain) probabilistic sources; they are easily extended to families of sources having the same properties. The first example corresponds to a ''logarithmic infinite comb'' and enjoys a non uniform polynomial mixing. The second one corresponds to a ''factorial infinite comb'' for which mixing is uniform and exponential.

FOS: Computer and information sciencesCompressed suffix arrayPolynomialLogarithmGeneral MathematicsSuffix treevariable length Markov chain[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Generalized suffix treeprobabilistic source0102 computer and information sciences02 engineering and technologysuffix trie01 natural scienceslaw.inventionCombinatoricslawComputer Science - Data Structures and AlgorithmsTrieFOS: Mathematics0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)Mixing (physics)[ INFO.INFO-DS ] Computer Science [cs]/Data Structures and Algorithms [cs.DS]MathematicsDiscrete mathematicsApplied MathematicsProbability (math.PR)020206 networking & telecommunicationssuffix trie.Computer Graphics and Computer-Aided Design[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]010201 computation theory & mathematicsmixing properties60J05 37E05Suffix[ MATH.MATH-PR ] Mathematics [math]/Probability [math.PR]Mathematics - ProbabilitySoftware
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New separation between $s(f)$ and $bs(f)$

2011

In this note we give a new separation between sensitivity and block sensitivity of Boolean functions: $bs(f)=(2/3)s(f)^2-(1/3)s(f)$.

FOS: Computer and information sciencesComputational Complexity (cs.CC)
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A gap analysis of Internet-of-Things platforms

2016

We are experiencing an abundance of Internet-of-Things (IoT) middleware solutions that provide connectivity for sensors and actuators to the Internet. To gain a widespread adoption, these middleware solutions, referred to as platforms, have to meet the expectations of different players in the IoT ecosystem, including device providers, application developers, and end-users, among others. In this article, we evaluate a representative sample of these platforms, both proprietary and open-source, on the basis of their ability to meet the expectations of different IoT users. The evaluation is thus more focused on how ready and usable these platforms are for IoT ecosystem players, rather than on t…

FOS: Computer and information sciencesComputer Networks and CommunicationsComputer science02 engineering and technologyGap analysiscomputer.software_genreWorld Wide WebComputer Science - Computers and SocietyOrder (exchange)Computers and Society (cs.CY)0202 electrical engineering electronic engineering information engineeringesineiden internetIoT ecosystemIoT marketplaceta113internet of Thingsbusiness.industry020206 networking & telecommunicationsIoT platformsData sharingMiddleware (distributed applications)Middleware020201 artificial intelligence & image processingThe InternetbusinessInternet of Thingsgap analysiscomputerComputer Communications
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