Search results for "INTERPOLATION"
showing 10 items of 331 documents
Plantar flexor activation capacity and H reflex in older adults: adaptations to strength training.
2002
The purpose of this study was to investigate whether the voluntary neural drive and the excitability of the reflex arc could be modulated by training, even in old age. To this aim, the effects of a 16-wk strengthening program on plantar flexor voluntary activation (VA) and on the maximum Hoffman reflex (Hmax)-to-maximum M wave (Mmax) ratio were investigated in 14 elderly men (65–80 yr). After training, isometric maximum voluntary contraction (MVC) increased by 18% ( P < 0.05) and weight-lifting ability by 24% ( P < 0.001). Twitch contraction time decreased by 8% ( P < 0.01), but no changes in half relaxation time and in peak twitch torque were observed. The VA, assessed by twitch …
Three dimensional reconstruction to visualize atrial fibrillation activation patterns on curved atrial geometry
2021
BackgroundThe rotational activation created by spiral waves may be a mechanism for atrial fibrillation (AF), yet it is unclear how activation patterns obtained from endocardial baskets are influenced by the 3D geometric curvature of the atrium or ‘unfolding’ into 2D maps. We develop algorithms that can visualize spiral waves and their tip locations on curved atrial geometries. We use these algorithms to quantify differences in AF maps and spiral tip locations between 3D basket reconstructions, projection onto 3D anatomical shells and unfolded 2D surfaces.MethodsWe tested our algorithms in N = 20 patients in whom AF was recorded from 64-pole baskets (Abbott, CA). Phase maps were generated by…
Model reduction techniques for the computation of extended Markov parameterizations for generalized Langevin equations
2021
Abstract The generalized Langevin equation is a model for the motion of coarse-grained particles where dissipative forces are represented by a memory term. The numerical realization of such a model requires the implementation of a stochastic delay-differential equation and the estimation of a corresponding memory kernel. Here we develop a new approach for computing a data-driven Markov model for the motion of the particles, given equidistant samples of their velocity autocorrelation function. Our method bypasses the determination of the underlying memory kernel by representing it via up to about twenty auxiliary variables. The algorithm is based on a sophisticated variant of the Prony metho…
Constructing a Pareto front approximation for decision making
2011
An approach to constructing a Pareto front approximation to computationally expensive multiobjective optimization problems is developed. The approximation is constructed as a sub-complex of a Delaunay triangulation of a finite set of Pareto optimal outcomes to the problem. The approach is based on the concept of inherent nondominance. Rules for checking the inherent nondominance of complexes are developed and applying the rules is demonstrated with examples. The quality of the approximation is quantified with error estimates. Due to its properties, the Pareto front approximation works as a surrogate to the original problem for decision making with interactive methods. Qc 20120127
Physics-Aware Gaussian Processes for Earth Observation
2017
Earth observation from satellite sensory data pose challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression and other kernel methods have excelled in biophysical parameter estimation tasks from space. GP regression is based on solid Bayesian statistics, and generally yield efficient and accurate parameter estimates. However, GPs are typically used for inverse modeling based on concurrent observations and in situ measurements only. Very often a forward model encoding the well-understood physical relations is available though. In this work, we review three GP models that respect and learn the physics of the underlying processes …
Investigation of the crack tip stress field in a stainless steel SENT specimen by means of Thermoelastic Stress Analysis
2019
Abstract In this work a Thermoelastic Stress Analysis (TSA) setup is implemented to investigates the Thermoelastic and Second Harmonic signals on a fatigue loaded Single Edge Notched Tension (SENT) specimen made of stainless steel AISI 304L. Three load ratios are in particular applied, R=-1, 0, 0.1. The thermoelastic signal is used to evaluate the Stress Intensity Factor via two approaches, the Stanley-Chan linear interpolation method and the over-deterministic least-square fitting (LSF) method using the Williams’ series expansion. Regarding least-square fitting, an iterative procedure is proposed to identify the optimal crack tip position in the thermoelastic maps. The SIF and T-Stress are…
Analytical Prediction of the Flexural Response of External RC Joints with Smooth Rebars
2018
Nel presente lavoro viene presentato un modello analitico in forma chiusa in grado di riprodurre la risposta flessionale monotonica di nodi esterni trave-colonna in c.a. con armature lisce. La colonna viene sottoposta a carico verti-cale costante e la trave ad una forza laterale crescente monotonicamente applicata all’estremità. Il modello si basa sul comportamen-to flessionale di trave e colonna adottando un modello di cerniera plasticità concentrata che include lo scorrimento delle armature della trave. Si assume un dominio sforzo normale-momento bilineare semplificato da cui viene derivato il momento ultimo associato alla forza assiale di progetto. Per il nodo viene adottato un modello c…
Field estimation in wireless sensor networks using distributed kriging
2012
In this paper, we tackle the problem of spatial interpolation for distributed estimation in Wireless Sensor Networks by using a geostatistical technique called kriging. We present a novel Distributed Iterative Kriging Algorithm (DIKA) which is composed of two main phases. First, the spatial dependence of the field is exploited by calculating semivariograms in an iterative way. Second, the kriging system of equations is solved by an initial set of nodes in a distributed manner, providing some initial interpolation weights to each node. In our algorithm, the estimation accuracy can be improved by iteratively adding new nodes and updating appropriately the weights, which leads to a reduction i…
Moving Least Squares Innovative Strategies For Sheet Forming Design
2011
In the last years a great interest in optimization algorithms aimed to design forming processes was demonstrated by many researches. Proper design methodologies to reduce times and costs have to be developed mostly based on computer aided procedures. Response surface methods (RSM) proved their effectiveness in the recent years also for the application in sheet metal forming aiming to reduce the number of numerical simulations. Actually, the main drawback of such method is the number of direct problem to be solved in order to reach good function approximations. A very interesting aspect in RSM application regards the possibility to build response surfaces basing on moving least squares appro…
G1 rational blend interpolatory schemes: a comparative study
2012
Interpolation of triangular meshes is a subject of great interest in many computer graphics related applications, as, for example, gaming and realtime rendering. One of the main approaches to interpolate the positions and normals of the mesh vertices is the use of parametric triangular Bezier patches. As it is well known, any method aiming at constructing a parametric, tangent plane (G^1) continuous surface has to deal with the vertex consistency problem. In this article, we propose a comparison of three methods appeared in the nineties that use a particular technique called rational blend to avoid this problem. Together with these three methods we present a new scheme, a cubic Gregory patc…