Search results for "algorithm."

showing 10 items of 4617 documents

Calcification is not the Achilles' heel of cold-water corals in an acidifying ocean

2015

Ocean acidification is thought to be a major threat to coral reefs: laboratory evidence and CO2 seep research has shown adverse effects on many coral species, although a few are resilient. There are concerns that cold-water corals are even more vulnerable as they live in areas where aragonite saturation (?ara) is lower than in the tropics and is falling rapidly due to CO2 emissions. Here, we provide laboratory evidence that net (gross calcification minus dissolution) and gross calcification rates of three common cold-water corals, Caryophyllia smithii, Dendrophyllia cornigera, and Desmophyllum dianthus, are not affected by pCO2 levels expected for 2100 (pCO2 1058 ?atm, ?ara 1.29), and nor a…

CnidariaSettore BIO/07 - EcologiaCaryophyllia smithiiCoralcold-water coralsocean acidificationengineering.materialCaryophyllia smithiiDendrophyllia cornigeraCold-water coralcalcification and dissolutionCalcification PhysiologicAnthozoaTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONMediterranean SeaAnimalsEnvironmental ChemistrySeawaterGlobal ChangeReefDesmophyllum dianthuGeneral Environmental ScienceGlobal and Planetary ChangegeographyDesmophyllum dianthusgeography.geographical_feature_categorybiologyEcology2300EcologyAragoniteOcean acidificationfungiCalcification and dissolutionOcean acidificationCoral reefbiochemical phenomena metabolism and nutritionCarbon DioxideHydrogen-Ion Concentrationbiology.organism_classificationAnthozoaOceanographyengineeringCold-water coralsgeographic locationsMathematicsofComputing_DISCRETEMATHEMATICS
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Genome-wide detection of signatures of selection in three Valdostana cattle populations

2020

International audience; The Valdostana is a local dual purpose cattle breed developed in Italy. Three populations are recognized within this breed, based on coat colour, production level, morphology and temperament: Valdostana Red Pied (VPR), Valdostana Black Pied (VPN) and Valdostana Chestnut (VCA). Here, we investigated putative genomic regions under selection among these three populations using the Bovine 50K SNP array by combining three different statistical methods based either on allele frequencies (F-ST) or extended haplotype homozygosity (iHS and Rsb). In total, 8, 5 and 8 chromosomes harbouring 13, 13 and 16 genomic regions potentially under selection were identified by at least tw…

CoatCandidate geneMeatGenotypelocal cattle population[SDV]Life Sciences [q-bio]Quantitative Trait LociBovine BeadChip 50K; candidate genes; local cattle populations; selection signaturesRuns of HomozygosityBiologyBreedingGenomePolymorphism Single Nucleotideselection signatures03 medical and health sciencesFood AnimalsGene FrequencyAnimalsSelection GeneticGeneAllele frequencySelection (genetic algorithm)Genetic Association Studies030304 developmental biology2. Zero hungerGenetics0303 health sciencesGenomeBehavior AnimalHomozygote0402 animal and dairy sciencecandidate geneBovine BeadChip 50K04 agricultural and veterinary sciencesGeneral Medicine040201 dairy & animal sciencelocal cattle populationsMilkPhenotypeHaplotypesAnimal Science and ZoologyCattlecandidate genesSNP array
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Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality

2015

A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments perfo…

Cognitive NeuroscienceEntropyFOS: Physical sciencesOverfittingcomputer.software_genreMachine learningGranger causalityArtificial IntelligenceMedicine and Health SciencesEntropy (information theory)Non-uniform embeddingComputer SimulationMathematicsArtificial neural networkbusiness.industryProbability and statisticsModels TheoreticalNeural Networks (Computer)ClassificationNeural networkAlgorithmCausalityPhysics - Data Analysis Statistics and ProbabilitySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityEmbeddingA priori and a posterioriTransfer entropyNeural Networks ComputerArtificial intelligenceData miningbusinesscomputerAlgorithmsNeural networksData Analysis Statistics and Probability (physics.data-an)
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Distributed Pseudo-Gossip Algorithm and Finite-Length Computational Codes for Efficient In-Network Subspace Projection

2013

In this paper, we design a practical power-efficient algorithm for Wireless Sensor Networks (WSN) in order to obtain, in a distributed manner, the projection of an observed sampled spatial field on a subspace of lower dimension. This is an important problem that is motivated in various applications where there are well defined subspaces of interest (e.g., spectral maps in cognitive radios). As opposed to traditional Gossip Algorithms used for subspace projection, where separation of channel coding and computation is assumed, our algorithm combines binary finite-length Computational Coding and a novel gossip-like protocol with certain communication rules, achieving important savings in conve…

Cognitive radioTheoretical computer scienceComputationSignal ProcessingBinary numberEnergy consumptionElectrical and Electronic EngineeringLinear subspaceWireless sensor networkAlgorithmSubspace topologyMathematicsCoding (social sciences)IEEE Journal of Selected Topics in Signal Processing
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Decision Making in Evolving Artificial Systems

2001

The theme of this workshop is artificial perception. In this chapter we will argue that the ecological function of perception is to serve decision-making. If this is so the mechanisms chosen to implement perception, in natural or artificial systems, will be constrained by the requirements of decision-making and theories of decision-making will inevitably influence theories of perception. In what follows we will look at decision-making from what we hope is a new perspective, applying concepts and techniques developed by what we will call “new artificial intelligence”. We will begin, in the second part of the chapter, with a review of traditional, “normative” theories of decision-making and o…

Cognitive scienceArtificial neural networkComputer scienceProspect theoryPerceptionmedia_common.quotation_subjectPerspective (graphical)Evolutionary algorithmEvolutionary roboticsNatural (music)Normativemedia_common
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1993

Genetics and developmental genetics have given us such a wealth of new insight that, at the end of this century, the synthetic theory can no longer be maintained in the strict “orthodox” sense in which it was started.

Cognitive scienceBody planDevelopmental geneticsEvolutionary changeAdaptationBiologySelection (genetic algorithm)
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Adaptive and Generative Learning: Implications from Complexity Theories

2008

One of the most important classical typologies within the organizational learning literature is the distinction between adaptive and generative learning. However, the processes of these types of learning, particularly the latter, have not been widely analyzed and incorporated into the organizational learning process. This paper puts forward a new understanding of adaptive and generative learning within organizations, grounded in some ideas from complexity theories: mainly self-organization and implicate order. Adaptive learning involves any improvement or development of the explicate order through a process of self-organization. Self-organization is a self-referential process characterized …

Cognitive scienceCooperative learningbusiness.industryComputer scienceStrategy and ManagementAlgorithmic learning theoryGeneral Decision SciencesExperiential learningLearning sciencesGenerative modelManagement of Technology and InnovationOrganizational learningAdaptive learningbusinessAction learningInternational Journal of Management Reviews
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The metaphorical species: Evolution, adaptation and speciation of metaphors

2015

Studying cartoons about the economic crisis and focusing on a pair of scissors as a symbol, I prove how they first turn into unambiguous metaphor for the economic crisis and then experience an evolution in order to adapt to new communication contexts. Along these processes, they undergo more complex changes such as coadaptation and speciation. This has allowed for the scissors meme as a symbol of economic cutbacks to permeate society, and for its metaphorical use to occupy many disparate communication scenarios, unlike other symbolic elements that were also used, but turned out to be less cognitively efficient and therefore offered fewer evolutionary possibilities.

Cognitive scienceLinguistics and LanguageCommunicationSocial PsychologyMetaphorbusiness.industryCommunicationmedia_common.quotation_subjectLanguage and LinguisticsSymbolOrder (exchange)AnthropologyGenetic algorithmMemeticsSociologyAdaptation (computer science)businessmedia_commonDiscourse Studies
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Shallow Reductionism and the Problem of Complexity in Psychology

2008

In his recent book The Mind Doesn't Work That Way, Fodor argues that computational modeling of global cognitive processes, such as abductive everyday reasoning, has not been successful. In this article the problem is analyzed in the framework of algorithmic information theory. It is argued that the failed approaches are characterized by shallow reductionism, which is rejected in favor of deep reductionism and nonreductionism.

Cognitive scienceReductionismAlgorithmic information theoryHistory and Philosophy of ScienceConnectionismPhilosophyCognitionGeneral PsychologyEpistemologyTheory & Psychology
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Effect of inter-crystal scatter on estimation methods for random coincidences and subsequent correction.

2008

Random coincidences can contribute substantially to the background in positron emission tomography (PET). Several estimation methods are being used for correcting them. The goal of this study was to investigate the validity of techniques for random coincidence estimation, with various low-energy thresholds (LETs). Simulated singles list-mode data of the MADPET-II small animal PET scanner were used as input. The simulations have been performed using the GATE simulation toolkit. Several sources with different geometries have been employed. We evaluated the number of random events using three methods: delayed window (DW), singles rate (SR) and time histogram fitting (TH). Since the GATE simula…

CoincidenceCrystalRandom AllocationImaging Three-DimensionalHOT RegionHistogramSmall animalStatisticsImage Processing Computer-AssistedAnimalsScattering RadiationRadiology Nuclear Medicine and imagingMathematicsTomography Emission-Computed Single-PhotonModels StatisticalRadiological and Ultrasound TechnologyComputersCompton scatteringReproducibility of ResultsReconstruction algorithmEquipment DesignModels TheoreticalComputational physicsPositron-Emission TomographyEstimation methodsCrystallizationMonte Carlo MethodSoftwarePhysics in medicine and biology
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