Search results for "methods"

showing 10 items of 4526 documents

On the use of EMI for the assessment of dental implant stability

2014

The achievement and the maintenance of dental implant stability are prerequisites for the long-term success of the osseointegration process. Since implant stability occurs at different stages, it is clinically required to monitor an implant over time, i.e. between the surgery and the placement of the artificial tooth. In this framework, non-invasive tests able to assess the degree of osseointegration are necessary. In this paper, the electromechanical impedance (EMI) method is proposed to monitor the stability of dental implants. A 3D finite element model of a piezoceramic transducer (PZT) bonded to a dental implant placed into the bone was created, considering the presence of a bone- impla…

Materials sciencemedicine.medical_treatmentStiffnessOsseointegrationTransducerEMIElectromechanical impedance method dental implants finite element methodsmedicinePulp canalImplantmedicine.symptomDental implantAbutment (dentistry)Biomedical engineering
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Changes in trunk posture and muscle responses in standing during pregnancy and postpartum

2018

Este artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194853 The aim of this study was to analyze the position of the lumbopelvic region and the muscle activation of erector spinae and biceps femoris muscles in a group of pregnant women in the third trimester. The hypothesis was that pregnancy-related biomechanical and morphological changes modify the position of the lumbopelvic region and the activation of extensor muscles. The position of the lumbar spine and pelvis in the sagittal plane, and the EMG activity of the erector spinae and biceps femoris muscles, were recorded during standing…

Maternal HealthPelvis - Muscles.lcsh:MedicineElectromyographyPathology and Laboratory MedicineBicepsBody Mass IndexBackache.0302 clinical medicineDolor pélvico.ElectricityPregnancyColumna vertebral - Propiedades mecánicas.Medicine and Health Scienceslcsh:ScienceMusculoskeletal Systemreproductive and urinary physiologyAbdominal MusclesLumbar VertebraeMultidisciplinarymedicine.diagnostic_testObstetricsMusclesPhysicsPostpartum PeriodObstetrics and GynecologyBioassays and Physiological Analysismedicine.anatomical_structurePelvis - Músculos.Physical SciencesFemaleAnatomyMuscle ElectrophysiologyResearch ArticleAdultmedicine.medical_specialtyPregnancy Trimester ThirdLower Back PainPosturePainLumbar vertebraeResearch and Analysis MethodsColumna vertebral - Músculos.PelvisPelvis - Mechanical properties.03 medical and health sciencesSigns and SymptomsDiagnostic MedicinePelvic pain.medicineHumansPelvis - Propiedades mecánicas.Lumbago.Spine - Muscles.Muscle SkeletalPelvisColumna vertebral - Anomalías y malformaciones.PregnancyDolor de espalda.HipElectromyographybusiness.industrylcsh:RElectrophysiological TechniquesBody WeightBiology and Life SciencesElectromagnetics030229 sport sciencesPregnant women.medicine.diseaseTrunkSpineBody HeightSagittal planeSpine - Abnormalities.Mujeres embarazadas.Women's HealthEmbarazo - Complicaciones y secuelas.lcsh:QbusinessPregnancy - Complications.Spine - Mechanical properties.030217 neurology & neurosurgeryPostpartum period
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Explicit polynomial solutions of fourth order linear elliptic Partial Differential Equations for boundary based smooth surface generation

2011

We present an explicit polynomial solution method for surface generation. In this case the surface in question is characterized by some boundary configuration whereby the resulting surface conforms to a fourth order linear elliptic Partial Differential Equation, the Euler–Lagrange equation of a quadratic functional defined by a norm. In particular, the paper deals with surfaces generated as explicit Bézier polynomial solutions for the chosen Partial Differential Equation. To present the explicit solution methodologies adopted here we divide the Partial Differential Equations into two groups namely the orthogonal and the non-orthogonal cases. In order to demonstrate our methodology we discus…

Mathematical analysisFirst-order partial differential equationExplicit and implicit methodsAerospace EngineeringPartial differential equationExplicit polynomial solutionExponential integratorComputer Graphics and Computer-Aided DesignParabolic partial differential equationSurface generationPDE surfaceLinear differential equationElliptic partial differential equationModeling and SimulationAutomotive EngineeringSymbol of a differential operatorMathematicsComputer Aided Geometric Design
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DEGENERATE MATRIX METHOD FOR SOLVING NONLINEAR SYSTEMS OF DIFFERENTIAL EQUATIONS

1998

Degenerate matrix method for numerical solving nonlinear systems of ordinary differential equations is considered. The method is based on an application of special degenerate matrix and usual iteration procedure. The method, which is connected with an implicit Runge‐Kutta method, can be simply realized on computers. An estimation for the error of the method is given. First Published Online: 14 Oct 2010

Mathematical analysisMathematicsofComputing_NUMERICALANALYSISNumerical methods for ordinary differential equationsExplicit and implicit methods-Backward Euler methodModeling and SimulationCollocation methodQA1-939Crank–Nicolson methodDifferential algebraic equationMathematicsAnalysisMathematicsMatrix methodNumerical partial differential equationsMathematical Modelling and Analysis
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Interactive Multiobjective Robust Optimization with NIMBUS

2018

In this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty in the problems. We separate the solution process into two stages: the pre-decision making stage and the decision making stage. We consider the decision maker’s preferences in the nominal case, i.e., with the most typical or undisturbed values of the uncertain parameters. At the same time, the decision maker is informed about the objective function values in the worst case to support her/him to make an informed decision. To help the decision maker to understand the behavio…

Mathematical optimization021103 operations researchComputer sciencepareto-tehokkuuspäätöksenteko0211 other engineering and technologiesPareto principlemultiple criteria decision makingRobust optimization02 engineering and technologyrobustnessinteractive methodsDecision makerMinimaxTwo stagesrobust Pareto optimalitymonitavoiteoptimointiepävarmuusMultiobjective optimization problemRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing
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IRA-EMO : Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization

2019

We propose a new interactive evolutionary multiobjective optimization method, IRA-EMO. At each iteration, the decision maker (DM) expresses her/his preferences as an interesting interval for objective function values. The DM also specifies the number of representative Pareto optimal solutions in these intervals referred to as regions of interest one wants to study. Finally, a real-life engineering three-objective optimization problem is used to demonstrate how IRA-EMO works in practice for finding the most preferred solution. peerReviewed

Mathematical optimization021103 operations researchOptimization problemComputer sciencemieltymykset0211 other engineering and technologiesReservation02 engineering and technologyInterval (mathematics)interactive methodsMulti-objective optimizationmonitavoiteoptimointievolutionary multi-objective optimization0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingregion of interestreference point
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Combined K-Best sphere decoder based on the channel matrix condition number

2008

It is known that sphere decoding (SD) methods can provide maximum-likelihood (ML) detection over Gaussian MIMO channels with lower complexity than the exhaustive search. Channel matrix condition number represents an important influence on the performance of usual detectors. Throughout this paper, two particular cases of a SD method called K-Best carry out a combined detection in order to reduce the computational complexity with predictable performance degradation. Algorithm selection is based on channel matrix condition number thresholding. K-Best is a suboptimal SD algorithm for finding the ML solution of a detection problem. It is based on a fixed complexity tree search, set by a paramete…

Mathematical optimizationComputational complexity theoryGaussianBrute-force searchThresholdingsymbols.namesakeMatrix (mathematics)symbolsCondition numberAlgorithmDecoding methodsComputer Science::Information TheoryMathematicsCommunication channel2008 3rd International Symposium on Communications, Control and Signal Processing
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Explicit Recursive and Adaptive Filtering in Reproducing Kernel Hilbert Spaces

2014

This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the $\gamma$ -filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and elect…

Mathematical optimizationComputer Networks and Communications02 engineering and technologyautoregressive and moving-averagekernel methodssymbols.namesakeArtificial Intelligence0202 electrical engineering electronic engineering information engineeringKernel adaptive filterInfinite impulse responseMathematicsfilterrecursiveHilbert space020206 networking & telecommunicationsFilter (signal processing)AdaptiveComputer Science ApplicationsAdaptive filterKernel methodKernel (statistics)symbols020201 artificial intelligence & image processingAlgorithmSoftwareReproducing kernel Hilbert spaceIEEE Transactions on Neural Networks and Learning Systems
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Iterative momentum relaxation for fast lattice-Boltzmann simulations

2001

Abstract Lattice-Boltzmann simulations are often used for studying steady-state hydrodynamics. In these simulations, however, the complete time evolution starting from some initial condition is redundantly computed due to the transient nature of the scheme. In this article we present a refinement of body-force driven lattice-Boltzmann simulations that may reduce the simulation time significantly. This new technique is based on an iterative adjustment of the local body-force. We validate this technique on three test cases, namely fluid flow around a spherical obstacle, flow in random fiber mats and flow in a static mixer reactor.

Mathematical optimizationComputer Networks and CommunicationsComputer scienceLattice Boltzmann methodsTime evolutionPorous mediaRelaxation (iterative method)Fluid mechanicsMechanicsStatic mixerlaw.inventionMomentumFlow (mathematics)Hardware and ArchitecturelawLattice-Boltzmann methodFluid dynamicsInitial value problemFluid mechanicsPorous mediumSoftware
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Interactive multiobjective optimization with NIMBUS for decision making under uncertainty

2013

We propose an interactive method for decision making under uncertainty, where uncertainty is related to the lack of understanding about consequences of actions. Such situations are typical, for example, in design problems, where a decision maker has to make a decision about a design at a certain moment of time even though the actual consequences of this decision can be possibly seen only many years later. To overcome the difficulty of predicting future events when no probabilities of events are available, our method utilizes groupings of objectives or scenarios to capture different types of future events. Each scenario is modeled as a multiobjective optimization problem to represent differe…

Mathematical optimizationComputer sciencepareto optimalityManagement Science and Operations Researchinteractive methodsDecision makerskenaariotMulti-objective optimizationMoment (mathematics)Conflicting objectivesmultiple objective programmingBusiness Management and Accounting (miscellaneous)uncertainty handlingPortfolio optimizationDecision-makingclassification of objectivesOptimal decisionDecision analysis
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