933 resultados para passive filter


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In this paper we present a hybrid technique for correcting distortions that appear when projecting images onto geometrically complex, colored and textured surfaces. It analyzes the optical flow that results from perspective distortions during motions of the observer and tries to use this information for computing the correct image warping. If this fails due to an unreliable optical flow, an accurate -but slower and visiblestructured light projection is automatically triggered. Together with an appropriate radiometric compensation, view-dependent content can be projected onto arbitrary everyday surfaces. An implementation mainly on the GPU ensures fast frame rates.

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Die Grundbegriffe Wölfflins lassen sich mit Hilfe digitaler Algorithmen nachmodellieren. Welches Wissen wird damit gewonnen? Auch Wölfflin hat auf mediale Veränderungen reagiert, indem er die Doppel-Projektion von Dias in den binären Differenzen der Grundbegriffe nachbildete. Sie lesen der Projektion zweier Bilder eine historische Differenz aus, die für die Disziplin der Kunstgeschichte grundlegend ist. Ein digitale Nachbildung dieser Differenz wäre tautologisch: sie würde ein gewusstes Wissen wiederholen. Fruchtbar wird der Einsatz digitaler Algorithmen dann, wenn sie nicht nur etwas bekanntes abbilden, sondern wenn man fragt, zu welcher "methodischen Grenzerweiterung" sie beitragen könnten.

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Skull-stripping (or brain extraction) is an important pre-processing step in neuroimage analysis. This document describes a skull-stripping filter implemented using the Insight Toolkit ITK, which we named itk::StripTsImageFilter. It is a composite filter based on existing ITK classes. The filter has been implemented with usability, robustness, speed and versatility in mind, rather than accuracy. This makes it useful for many pre-processing tasks in neuroimage analysis. This paper is accompanied by the source code, input data and a testing environment.

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This paper addresses the problem of service development based on GSM handset signaling. The aim is to achieve this goal without the participation of the users, which requires the use of a passive GSM receiver on the uplink. Since no tool for GSM uplink capturing was available, we developed a new method that can synchronize to multiple mobile devices by simply overhearing traffic between them and the network. Our work includes the implementation of modules for signal recovery, message reconstruction and parsing. The method has been validated against a benchmark solution on GSM downlink and independently evaluated on uplink channels. Initial evaluations show up to 99% success rate in message decoding, which is a very promising result. Moreover, we conducted measurements that reveal insights on the impact of signal power on the capturing performance and investigate possible reactive measures.

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In this study, we compared direction detection thresholds of passive self-motion in the dark between artistic gymnasts and controls. Twenty-four professional female artistic gymnasts (ranging from 7 to 20 years) and age-matched controls were seated on a motion platform and asked to discriminate the direction of angular (yaw, pitch, roll) and linear (leftward–rightward) motion. Gymnasts showed lower thresholds for the linear leftward–rightward motion. Interestingly, there was no difference for the angular motions. These results show that the outstanding self-motion abilities in artistic gymnasts are not related to an overall higher sensitivity in self-motion perception. With respect to vestibular processing, our results suggest that gymnastic expertise is exclusively linked to superior interpretation of otolith signals when no change in canal signals is present. In addition, thresholds were overall lower for the older (14–20 years) than for the younger (7–13 years) participants, indicating the maturation of vestibular sensitivity from childhood to adolescence.

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It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

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An Ensemble Kalman Filter is applied to assimilate observed tracer fields in various combinations in the Bern3D ocean model. Each tracer combination yields a set of optimal transport parameter values that are used in projections with prescribed CO2 stabilization pathways. The assimilation of temperature and salinity fields yields a too vigorous ventilation of the thermocline and the deep ocean, whereas the inclusion of CFC-11 and radiocarbon improves the representation of physical and biogeochemical tracers and of ventilation time scales. Projected peak uptake rates and cumulative uptake of CO2 by the ocean are around 20% lower for the parameters determined with CFC-11 and radiocarbon as additional target compared to those with salinity and temperature only. Higher surface temperature changes are simulated in the Greenland–Norwegian–Iceland Sea and in the Southern Ocean when CFC-11 is included in the Ensemble Kalman model tuning. These findings highlights the importance of ocean transport calibration for the design of near-term and long-term CO2 emission mitigation strategies and for climate projections.

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Anti-GM1 antibodies are present in some patients with autoimmune neurological disorders. These antibodies are most frequently associated with acute immune neuropathy called Guillain-Barré syndrome (GBS). Some clinical studies associate the presence of these antibodies with poor recovery in GBS. The patients with incomplete recovery have failure of nerve repair, particularly axon regeneration. Our previous work indicates that monoclonal antibodies can inhibit axon regeneration by engaging cell surface gangliosides (Lehmann et al., 2007). We asked whether passive transfer of human anti-GM1 antibodies from patients with GBS modulate axon regeneration in an animal model. Human anti-GM1 antibodies were compared with other GM1 ligands, cholera toxin B subunit and a monoclonal anti-GM1 antibody. Our results show that patient derived anti-GM1 antibodies and cholera toxin beta subunit impair axon regeneration/repair after PNS injury in mice. Comparative studies indicated that the antibody/ligand-mediated inhibition of axon regeneration is dependent on antibody/ligand characteristics such as affinity-avidity and fine specificity. These data indicate that circulating immune effectors such as human autoantibodies, which are exogenous to the nervous system, can modulate axon regeneration/nerve repair in autoimmune neurological disorders such as GBS.

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