Search results for "BERT"

showing 10 items of 1789 documents

Acting under the idea of freedom: Kant and the Incorporation Thesis

2010

Este artículo examina un supuesto fundamental de la filosofía moral kantiana, a saber: que sin libertad trascendental, entendida como la propiedad de la voluntad por la que se determina a actuar sin ser afectada por resortes sensibles, no se le pueden imputar al presunto agente actos inmorales. Teóricamente se argumenta contra el sentido lógico del supuesto (se revela la consecuencia aporética de la concepción) y se muestra cuán superfluo es en la práctica. De todos modos, se le reconoce a Kant, contra una línea de argumentación nietzscheana bien conocida, el mérito de haber captado el compromiso humano insuperable con la idea de que somos seres discrecionales o libres trascendentalmente. Y…

CompatibilismoFree willImputaciónCompatibilismFilosofíaArbitrioLlibertatLibertad de la voluntadFreedom of the willImputation
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Quantum like modelling of decision making: quantifying uncertainty with the aid of the Heisenberg-Robertson inequality

2018

This paper contributes to quantum-like modeling of decision making (DM) under uncertainty through application of Heisenberg’s uncertainty principle (in the form of the Robertson inequality). In this paper we apply this instrument to quantify uncertainty in DM performed by quantum-like agents. As an example, we apply the Heisenberg uncertainty principle to the determination of mutual interrelation of uncertainties for “incompatible questions” used to be asked in political opinion pools. We also consider the problem of representation of decision problems, e.g., in the form of questions, by Hermitian operators, commuting and noncommuting, corresponding to compatible and incompatible questions …

Compatible and incompatible questionPsychology (all)Uncertainty principleInequalityComputer sciencemedia_common.quotation_subjectMental stateHeisenberg uncertainty principle050105 experimental psychology03 medical and health sciencessymbols.namesake0302 clinical medicine0501 psychology and cognitive sciencesQuantumGeneral Psychologymedia_commonApplied Mathematics05 social sciencesHilbert spaceObservableDecision problemOrder effect16. Peace & justiceHermitian matrixMental statesymbolsDecision makingMathematical economics030217 neurology & neurosurgery
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An Innovative Ambient Identification Method

2020

Ambient modal identification, also known as Operational Modal Analysis (OMA), aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method based on appl…

Complex representationComputer scienceControl engineeringContext (language use)Operational Modal Analysis Hilbert Transform Analytical.Identification (information)Operational Modal Analysissymbols.namesakeModalsymbolsHilbert transformTime domainSettore ICAR/08 - Scienza Delle CostruzioniRepresentation (mathematics)
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Y ahora ¿qué?

1997

Comportamiento electoralMercado mundialConvergenciaVidal-Beneyto JoséEuropa socialPOLÍTICAConferencia IntergubernamentalTercer pilarUrnasEUROPAEleccionesPublicaciones: Obra periodística: Columnas y artículos de opiniónIzquierda europeaJusticiaDerechaLibertadLuchaDesarrollo tecnológicoCredibilidadSeguridadTercera VíaRuptura electoral
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Upport vector machines for nonlinear kernel ARMA system identification.

2006

Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…

Computer Science::Machine LearningStatistics::TheoryComputer Networks and CommunicationsBiomedical signal processingInformation Storage and RetrievalMachine learningcomputer.software_genrePattern Recognition AutomatedStatistics::Machine LearningArtificial IntelligenceApplied mathematicsStatistics::MethodologyAutoregressive–moving-average modelComputer SimulationMathematicsTelecomunicacionesHardware_MEMORYSTRUCTURESSupport vector machinesModels StatisticalNonlinear system identificationbusiness.industryAutocorrelationSystem identificationSignal Processing Computer-AssistedGeneral MedicineComputer Science ApplicationsSupport vector machineNonlinear systemKernelAutoregressive modelNonlinear DynamicsARMA modelling3325 Tecnología de las TelecomunicacionesArtificial intelligenceNeural Networks ComputerbusinesscomputerSoftwareAlgorithmsReproducing kernel Hilbert spaceIEEE transactions on neural networks
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Hypervisor-assisted dynamic malware analysis

2021

AbstractMalware analysis is a task of utmost importance in cyber-security. Two approaches exist for malware analysis: static and dynamic. Modern malware uses an abundance of techniques to evade both dynamic and static analysis tools. Current dynamic analysis solutions either make modifications to the running malware or use a higher privilege component that does the actual analysis. The former can be easily detected by sophisticated malware while the latter often induces a significant performance overhead. We propose a method that performs malware analysis within the context of the OS itself. Furthermore, the analysis component is camouflaged by a hypervisor, which makes it completely transp…

Computer engineering. Computer hardwareSoftware_OPERATINGSYSTEMSvirtualisointiComputer Networks and CommunicationsComputer scienceContext (language use)Static program analysiscomputer.software_genreTK7885-7895Artificial IntelligenceComponent (UML)Overhead (computing)tietoturvaMalware analysiskyberturvallisuusbusiness.industryHypervisorQA75.5-76.95haittaohjelmatComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMSTask (computing)Electronic computers. Computer scienceEmbedded systemMalwarebusinesscomputerSoftwareInformation SystemsCybersecurity
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Fast fringe pattern phase demodulation using FIR Hilbert transformers

2016

This paper suggests the use of FIR Hilbert transformers to extract the phase of fringe patterns. This method is computationally faster than any known spatial method that produces wrapped phase maps. Also, the algorithm does not require any parameters to be adjusted which are dependent upon the specific fringe pattern that is being processed, or upon the particular setup of the optical fringe projection system that is being used. It is therefore particularly suitable for full algorithmic automation. The accuracy and validity of the suggested method has been tested using both computer-generated and real fringe patterns. This novel algorithm has been proposed for its advantages in terms of com…

Computer science02 engineering and technology01 natural sciencesGeneralLiterature_MISCELLANEOUSQA76Structured-light 3D scannerlaw.invention010309 opticssymbols.namesakeOpticslaw0103 physical sciences0202 electrical engineering electronic engineering information engineeringDemodulationElectrical and Electronic EngineeringPhysical and Theoretical ChemistryTransformerbusiness.industryAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsTAFringe patternsymbols020201 artificial intelligence & image processingHilbert transformbusinessOptics Communications
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Optimizing Kernel Ridge Regression for Remote Sensing Problems

2018

Kernel methods have been very successful in remote sensing problems because of their ability to deal with high dimensional non-linear data. However, they are computationally expensive to train when a large amount of samples are used. In this context, while the amount of available remote sensing data has constantly increased, the size of training sets in kernel methods is usually restricted to few thousand samples. In this work, we modified the kernel ridge regression (KRR) training procedure to deal with large scale datasets. In addition, the basis functions in the reproducing kernel Hilbert space are defined as parameters to be also optimized during the training process. This extends the n…

Computer science0211 other engineering and technologiesHyperspectral imagingContext (language use)Basis function02 engineering and technology01 natural sciencesData set010104 statistics & probabilityKernel (linear algebra)Kernel methodKernel (statistics)Radial basis function kernel0101 mathematics021101 geological & geomatics engineeringReproducing kernel Hilbert spaceRemote sensingIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Artificial Intelligence in Protecting Smart Building’s Cloud Service Infrastructure from Cyberattacks

2020

Gathering and utilizing stored data is gaining popularity and has become a crucial component of smart building infrastructure. The data collected can be stored, for example, into private, public, or hybrid cloud service infrastructure or distributed service by utilizing data platforms. The stored data can be used when implementing services, such as building automation (BAS). Cloud services, IoT sensors, and data platforms can face several kinds of cybersecurity attack vectors such as adversarial, AI-based, DoS/DDoS, insider attacks. If a perpetrator can penetrate the defenses of a data platform, she can cause significant harm to the system. For example, the perpetrator can disrupt a buildin…

Computer scienceDenial-of-service attackCloud computingComputerApplications_COMPUTERSINOTHERSYSTEMStekoälyComputer securitycomputer.software_genreInsiderpilvipalvelutälytalotComponent (UML)cloud servicetietoturvakyberturvallisuusBuilding automationbusiness.industryattack vectorsartificial intelligencePopularityartificial-intelligence-based applicationsHeating systemälytekniikkabusinessdata platformCloud storagecomputerverkkohyökkäykset
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Intertwining operators between different Hilbert spaces: connection with frames

2009

In this paper we generalize a strategy recently proposed by the author concerning intertwining operators. In particular we discuss the possibility of extending our previous results in such a way to construct (almost) isospectral self-adjoint operators living in different Hilbert spaces. Many examples are discussed in details. Many of them arise from the theory of frames in Hilbert spaces, others from the so-called g-frames.

Computer scienceHilbert spaceFOS: Physical sciencesStatistical and Nonlinear PhysicsMathematical Physics (math-ph)Operator theoryConnection (mathematics)Mathematical OperatorsAlgebrasymbols.namesakeIntertwining operatorsIsospectralOperator (computer programming)Linear algebrasymbolsMathematics::Metric GeometryFrameSettore MAT/07 - Fisica MatematicaEigenvalues and eigenvectorsMathematical Physics
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