Search results for "Bedding"

showing 10 items of 199 documents

Gamma Kernel Intensity Estimation in Temporal Point Processes

2011

In this article, we propose a nonparametric approach for estimating the intensity function of temporal point processes based on kernel estimators. In particular, we use asymmetric kernel estimators characterized by the gamma distribution, in order to describe features of observed point patterns adequately. Some characteristics of these estimators are analyzed and discussed both through simulated results and applications to real data from different seismic catalogs.

Statistics and ProbabilityNonparametric statisticsEstimatorKernel principal component analysisPoint processVariable kernel density estimationKernel embedding of distributionsModeling and SimulationKernel (statistics)Bounded domainStatisticsGamma distributionGamma kernel estimatorIntensity functionTemporal point processes.Settore SECS-S/01 - StatisticaMathematicsCommunications in Statistics - Simulation and Computation
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Geography versus topology in the European Ownership Network

2011

In this paper, we investigate the network of ownership relationships among European firms and its embedding in the geographical space. We carry out a detailed analysis of geographical distances between pairs of nodes, connected by edges or by shortest paths of varying length. In particular, we study the relation between geographical distance and network distance in comparison with a random spatial network model. While the distribution of geographical distance can be fairly well reproduced, important deviations appear in the network distance and in the size of the largest strongly connected component. Our results show that geographical factors allow us to capture several features of the netw…

Strongly connected componentRelation (database)General Physics and Astronomynetwork theory ownership geographyTopology (electrical circuits)Network theoryTopology01 natural sciencesAverage path length010305 fluids & plasmasGeographySpatial networkGeographical distance0103 physical sciencesEmbedding010306 general physics
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A convolutional neural network for virtual screening of molecular fingerprints

2019

In the last few years, Deep Learning (DL) gained more and more impact on drug design because it allows a huge increase of the prediction accuracy in many stages of such a complex process. In this paper a Virtual Screening (VS) procedure based on Convolutional Neural Networks (CNN) is presented, that is aimed at classifying a set of candidate compounds as regards their biological activity on a particular target protein. The model has been trained on a dataset of active/inactive compounds with respect to the Cyclin-Dependent Kinase 1 (CDK1) a very important protein family, which is heavily involved in regulating the cell cycle. One qualifying point of the proposed approach is the use of molec…

Structure (mathematical logic)0303 health sciencesVirtual screening010304 chemical physicsPoint (typography)Computer sciencebusiness.industryDeep learningProcess (computing)Pattern recognition01 natural sciencesConvolutional neural networkDrug designSet (abstract data type)03 medical and health sciencesDeep LearningVirtual Screening0103 physical sciencesMolecular fingerprintsEmbeddingArtificial intelligencebusinessBioactivity prediction030304 developmental biology
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Solving the Problems of Inspection Planning under Parametric Uncertainty of Underlying Models

2013

Certain fatigued structures must be inspected in order to detect fatigue damages that would otherwise not be apparent. A technique for obtaining optimal inspection strategies is proposed for situations where it is difficult to quantify the costs associated with inspections and undetected failure. For fatigued structures for which failures (fatigue damages) are only detected at the time of inspection, it is important to be able to determine the optimal times of inspection. Fewer inspections will lead to lower fatigue reliability of the structure upon demand, and frequent inspection will lead to higher cost. When there is a fatigue reliability requirement, the problem is usually to develop an…

Structure (mathematical logic)EngineeringSequencereliabilitybusiness.industryeducationmaintainabilityoperational researchGeneral MedicinehumanitiesReliability engineeringInvariant embeddingstomatognathic diseasesprobabilistic and statistical models in industrial plant controlDamagessafety and dependability of production systemsbusinessReliability (statistics)Invariant (computer science)Parametric statisticsIFAC Proceedings Volumes
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Decision Making and Optimization for Inspection Planning under Parametric Uncertainty of Underlying Models

2013

Certain fatigued structures must be inspected in order to detect fatigue damages that would otherwise not be apparent. A technique for obtaining optimal inspection strategies is proposed for situations where it is difficult to quantify the costs associated with inspections and undetected failure. For fatigued structures, for which failures (fatigue damages) are only detected at the time of inspection, it is important to be able to determine the optimal times of inspection. Fewer inspections will lead to lower fatigue reliability of the structure upon demand, and frequent inspections will lead to higher cost. When there is a fatigue reliability requirement, the problem is usually to develop …

Structure (mathematical logic)stomatognathic diseasesSequenceComputer scienceeducationDamagesSensitivity analysishumanitiesInvariant (computer science)Reliability (statistics)Invariant embeddingParametric statisticsReliability engineering
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Anisotropic volumetric behaviour of Opalinus clay shale upon suction variation

2016

Opalinus clay shale is under consideration to serve as the host geomaterial for the underground storage of nuclear waste in Switzerland. Water retention behaviour and anisotropic behaviour represent two main features of this geomaterial; however, a comprehensive understanding of the interaction between these two features is still lacking. This paper aims to provide a detailed experimental analysis of the coupling between the water retention capacity and the anisotropic behaviour of two facies (shaly and sandy) of the Opalinus clay shale. The response of the tested geomaterials is characterised by an unequal swelling and shrinkage response in directions parallel and perpendicular to the bed…

SuctionsuctionBedding0211 other engineering and technologiesanisotropy02 engineering and technology010502 geochemistry & geophysicsGeotechnical Engineering and Engineering Geology01 natural sciencesWater retentionstrainFaciesEarth and Planetary Sciences (miscellaneous)medicineGeotechnical engineeringWettingmedicine.symptomAnisotropyOil shaleGeology021101 geological & geomatics engineering0105 earth and related environmental sciencesShrinkageGéotechnique Letters
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The Role of Anisotropy on the Volumetric Behaviour of Opalinus Clay upon Suction Change

2017

An experimental investigation to analyse the anisotropic volumetric response of shaly and sandy facies of Opalinus Clay upon suction variations is presented. Obtained results demonstrate the different behaviour of the tested facies to a wetting-drying cycle. The shaly facies exhibits higher water retention capacity and stronger volumetric response than the sandy facies. Anisotropic response is experienced by both facies with the strain perpendicular to bedding higher than in the parallel direction. The sandy facies exhibits a more pronounced anisotropic behaviour in particular during the drying phase. A detailed analysis of the response in the two directions with respect to the bedding orie…

SuctionsuctionSettore ICAR/07 - GeotecnicaBedding0211 other engineering and technologies02 engineering and technology010502 geochemistry & geophysicsopalinus clay01 natural sciencesSoilPhase (matter)FaciesShalesPerpendicularLaboratory TestingGeotechnical engineeringPetrologyAnisotropyGeology021101 geological & geomatics engineering0105 earth and related environmental sciences
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Pac-Man Josephson junctions: Useful trigonometric puzzles?

2020

Abstract Rather interesting trigonometric equations arise when considering a Josephson junction obtained by embedding a Pac-Man shaped superconducting island in between two superconducting electrodes. In the present work we unfold these equations, written in terms of the superconducting phase difference between the two electrodes, and find the current-phase relation and the maximum superconducting current of the Josephson junction network. The solution of the trigonometric equations defining the superconducting current state of the system can be proposed to advanced high-school students or to undergraduate students in an interdisciplinary lecture.

SuperconductivityPhysicsJosephson effectPhase differenceCurrent (mathematics)PhysicsQC1-999Physics::Physics EducationGeneral Physics and AstronomyQuantum mechanicsEducationTheoretical physicsCondensed Matter::SuperconductivityJosephson junctionEmbeddingTrigonometryJosephson junction; Quantum mechanics; TrigonometryTrigonometry
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Learning non-linear time-scales with kernel -filters

2009

A family of kernel methods, based on the @c-filter structure, is presented for non-linear system identification and time series prediction. The kernel trick allows us to develop the natural non-linear extension of the (linear) support vector machine (SVM) @c-filter [G. Camps-Valls, M. Martinez-Ramon, J.L. Rojo-Alvarez, E. Soria-Olivas, Robust @c-filter using support vector machines, Neurocomput. J. 62(12) (2004) 493-499.], but this approach yields a rigid system model without non-linear cross relation between time-scales. Several functional analysis properties allow us to develop a full, principled family of kernel @c-filters. The improved performance in several application examples suggest…

TelecomunicacionesSupport vector machinesbusiness.industryCognitive NeuroscienceNonlinear System IdentificationPattern recognitionKernel principal component analysisComputer Science ApplicationsKernel methodMercer's KernelArtificial IntelligenceVariable kernel density estimationString kernelKernel embedding of distributionsPolynomial kernelRadial basis function kernelGamma-FiltersArtificial intelligenceTree kernelbusinessMathematicsNeurocomputing
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How much geometry it takes to reconstruct a 2-manifold in R 3

2009

Known algorithms for reconstructing a 2-manifold from a point sample in R 3 are naturally based on decisions/predicates that take the geometry of the point sample into account. Facing the always present problem of round-off errors that easily compromise the exactness of those predicate decisions, an exact and robust implementation of these algorithms is far from being trivial and typically requires employment of advanced datatypes for exact arithmetic, as provided by libraries like CORE, LEDA, or GMP. In this article, we present a new reconstruction algorithm, one whose main novelties is to throw away geometry information early on in the reconstruction process and to mainly operate combina…

Theoretical computer scienceComputer scienceRobustness (computer science)EmbeddingCorrectness proofsReconstruction algorithmGeometryAlgorithmcomputerPredicate (grammar)LedaTheoretical Computer Sciencecomputer.programming_languageACM Journal of Experimental Algorithmics
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