Search results for "Moving"

showing 10 items of 182 documents

Theoretical study on travelling web dynamics and instability under non-homogeneous tension

2013

Problems of dynamics and stability of a moving web, travelling between two rollers at a constant velocity, are studied using analytical approaches. Transverse vibrations of the web are described by a partial differential equation that includes the centrifugal force, in-plane tension, elastic reaction and nonstationary inertial terms. The model of a thin elastic plate subjected to bending and non-homogeneous tension is used to describe the bending moment and the distribution of membrane forces. The stability of the plate is investigated with the help of studies of small out-of-plane vibrations. The influence of linearly distributed in-plane tension on the characteristics of the web vibration…

Centrifugal forceInertial frame of referenceaxially movingBendinglommahdusInstabilityelasticGeneral Materials Sciencebucklingta216epästabiiliusCivil and Structural EngineeringelastinenPhysicsPartial differential equationTension (physics)Mechanical EngineeringplatejännitysMechanicstensionCondensed Matter PhysicsinstabilityBucklingMechanics of Materialsaksiaalisesti liikkuvaBending momentlaatta
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Static instability analysis for travelling membranes and plates interacting with axially moving ideal fluid

2010

The out-of-plane instability of a moving plate, travelling between two rollers with constant velocity, is studied, taking into account the mutual interaction between the buckled plate and the surrounding, axially flowing ideal fluid. Transverse displacement of the buckled plate (assumed cylindrical) is described by an integro-differential equation that includes the centrifugal force, the aerodynamic reaction of the external medium, the vertical projection of membrane tension, and the bending force. The aerodynamic reaction is found analytically as a functional of the displacement. To find the critical divergence velocity of the moving plate and its corresponding buckling mode, an eigenvalue…

Centrifugal forceaxially moving materialsaxial flowMechanical Engineeringideal fluidinstability analysisMechanicsBending of platesInstabilityAerodynamic forcePhysics::Fluid DynamicsClassical mechanicsBucklingReactionFSIpaper webbucklingAxial symmetryDisplacement (fluid)Mathematics
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Overlapped moving windows followed by principal component analysis to extract information from chromatograms and application to classification analys…

2015

Variable generation from chromatograms is conveniently accomplished using unsupervised rather than manual techniques. With unsupervised techniques, there is no need for selecting a few peaks for manual integration and valuable information is quickly and efficiently collected. The generation of variables can be performed by using either peak searching or moving window (MW) strategies. With a MW approach, the peaks are ignored and many variables, only part of them carrying information, are generated. Thus, variable generation by MWs should be followed by data compression to generate the variables to be further used for classification or quantitation purposes. In this work, unsupervised proces…

Chromatographybusiness.industryGeneral Chemical EngineeringGeneral EngineeringPattern recognitionMoving windowLinear discriminant analysisAnalytical Chemistrylaw.inventionVariable (computer science)Window WidthlawPrincipal component analysisRange (statistics)Flame ionization detectorArtificial intelligencebusinessData compressionMathematicsAnalytical Methods
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Anaerobic thermophilic (55°C) treatment of TMP whitewater in reactors based on biomass attachment and entrapment

1999

Abstract Thermomechanical pulping (TMP) whitewater was treated in thermophilic (55°C) anaerobic laboratory-scale reactors using three different reactor configurations. In all reactors up to 70 % COD removals were achieved. The anaerobic hybrid reactor, composed of an upflow anaerobic sludge blanket (UASB) and a filter, gave degradation rates up to 10 kg COD/m 3 d at loading rates of 15 kg COD/m 3 d and hydraulic retention time (HRT) of 3.1 hours. The anaerobic multi-stage reactor, consisting of three compartments, each packed with granular sludge and carrier elements, gave degradation rates up to 9 kg COD/m 3 d at loading rates of 15–16 kg COD/m 3 d, and HRT down to 2.6 hours. Clogging and …

CloggingEnvironmental EngineeringWaste managementHydraulic retention timeMoving bed biofilm reactorChemistryBioreactorBiomassHybrid reactorPulp and paper industryAnaerobic exerciseWater Science and TechnologyFilter (aquarium)Water Science and Technology
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Approximation of functions over manifolds : A Moving Least-Squares approach

2021

We present an algorithm for approximating a function defined over a $d$-dimensional manifold utilizing only noisy function values at locations sampled from the manifold with noise. To produce the approximation we do not require any knowledge regarding the manifold other than its dimension $d$. We use the Manifold Moving Least-Squares approach of (Sober and Levin 2016) to reconstruct the atlas of charts and the approximation is built on-top of those charts. The resulting approximant is shown to be a function defined over a neighborhood of a manifold, approximating the originally sampled manifold. In other words, given a new point, located near the manifold, the approximation can be evaluated…

Computational Geometry (cs.CG)FOS: Computer and information sciencesComputer Science - Machine LearningClosed manifolddimension reductionMachine Learning (stat.ML)010103 numerical & computational mathematicsComplex dimensionTopology01 natural sciencesMachine Learning (cs.LG)Volume formComputer Science - GraphicsStatistics - Machine Learningmanifold learningApplied mathematics0101 mathematicsfunktiotMathematicsManifold alignmentAtlas (topology)Applied Mathematicshigh dimensional approximationManifoldGraphics (cs.GR)Statistical manifold010101 applied mathematicsregression over manifoldsComputational Mathematicsout-of-sample extensionComputer Science - Computational Geometrynumeerinen analyysimonistotapproksimointimoving least-squaresCenter manifold
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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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Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

2012

In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing s…

Computer scienceNeuroscience (miscellaneous)Interval (mathematics)ta3112lcsh:RC321-57103 medical and health sciencesCellular and Molecular Neuroscience0302 clinical medicineMoving averageHistogramBiological neural networkMethods Articleburst analysislcsh:Neurosciences. Biological psychiatry. Neuropsychiatry030304 developmental biology0303 health sciencesspike trainsQuantitative Biology::Neurons and Cognitionmicroelectrode arrayMEAaction potential burstsdeveloping neuronal networksMultielectrode arrayhuman embryonic stem cellsPower (physics)nervous systemSkewnesshESCsSpike (software development)Biological systemNeuroscience030217 neurology & neurosurgeryNeuroscienceFrontiers in Computational Neuroscience
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Dynamic analysis for axially moving viscoelastic panels

2012

In this study, stability and dynamic behaviour of axially moving viscoelastic panels are investigated with the help of the classical modal analysis. We use the flat panel theory combined with the Kelvin–Voigt viscoelastic constitutive model, and we include the material derivative in the viscoelastic relations. Complex eigenvalues for the moving viscoelastic panel are studied with respect to the panel velocity, and the corresponding eigenfunctions are found using central finite differences. The governing equation for the transverse displacement of the panel is of fifth order in space, and thus five boundary conditions are set for the problem. The fifth condition is derived and set at the in-…

Constitutive equationDynamicMaterial derivative02 engineering and technology01 natural sciencesViscoelasticityDisplacement (vector)Physics::Fluid DynamicsViscositystabiilius0203 mechanical engineeringMaterials Science(all)viscoelasticModelling and Simulation0103 physical sciencesGeneral Materials ScienceBoundary value problemta216010301 acousticsMathematicsViscoelasticdynamicominaisarvotMechanical EngineeringApplied MathematicsLiikkuvapalkkiFlexural rigidityBeamEigenvaluesMechanicsviscoelastinenstabilityCondensed Matter Physics020303 mechanical engineering & transportsdynaaminenMechanics of MaterialsModeling and SimulationBending stiffnessbeamMovingliikkuminenStabilityInternational Journal of Solids and Structures
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Forecasting Electricity Consumption and Production in Smart Homes through Statistical Methods

2022

Abstract Over the last years, a steady increase in both domestic electricity consumption and in the adoption of personal clean energy production systems has been observed worldwide. By analyzing energy consumption and production on photovoltaic panels mounted in a house, this work focuses on finding patterns in electrical energy consumption and devising a predictive model. Our goal is to find an accurate method to predict electrical energy consumption and production. Being able to anticipate how consumers will use energy in the near future, homeowners, companies and governments may optimize their behavior and the import and export of electricity. We evaluated the ARIMA and TBATS statistical…

Consumption (economics)Renewable Energy Sustainability and the EnvironmentComputer sciencebusiness.industryTBATSGeography Planning and DevelopmentPhotovoltaic systemElectricity predictionTransportationEnergy consumptionARIMAEnvironmental economicsEnergy management systemSmart housePhotovoltaic panelsWork (electrical)ARIMA; Electricity prediction; Energy management system; Photovoltaic panels; Smart house; TBATSProduction (economics)Autoregressive integrated moving averageElectricityEnergy management systembusinessCivil and Structural EngineeringSustainable Cities and Society
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Next-Day Bitcoin Price Forecast

2019

This study analyzes forecasts of Bitcoin price using the autoregressive integrated moving average (ARIMA) and neural network autoregression (NNAR) models. Employing the static forecast approach, we forecast next-day Bitcoin price both with and without re-estimation of the forecast model for each step. For cross-validation of forecast results, we consider two different training and test samples. In the first training-sample, NNAR performs better than ARIMA, while ARIMA outperforms NNAR in the second training-sample. Additionally, ARIMA with model re-estimation at each step outperforms NNAR in the two test-sample forecast periods. The Diebold Mariano test confirms the superiority of forecast …

Cryptocurrency050208 financeVDP::Samfunnsvitenskap: 200::Økonomi: 210::Samfunnsøkonomi: 212Computer sciencelcsh:Risk in industry. Risk management05 social sciencesARIMAPrice predictionlcsh:HD61cryptocurrencyPrice forecastVDP::Samfunnsvitenskap: 200::Økonomi: 210Autoregressive modellcsh:Financelcsh:HG1-99990502 economics and businessddc:330EconometricsAutoregressive integrated moving average050207 economicsstatic forecastartificial neural networkBitcoinJournal of Risk and Financial Management
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