914 resultados para Visual-system Model


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Background: left ventricular wall motion on 2d echo (2de) is usually scored visually. we sought to examine the determinants of visually assessed wall motion scoring on 2de by comparison with myocardial thickening quantified on MRI. Methods: using a 16 segment model, we studied 287 segments in 30 patients aged 61+/ -11 years (6 female), with ischaemic LV dysfunction (defined by at least 2 segments dysfunctional on 2de). 2de was performed in 5 views and wall motion scores (WMS) assigned: 1 (normal) 103 segments, 2 (hypokinetic) 93 segments, 3 (akinetic) 87 segments. MRI was used to measure end systolic wall thickness (ESWT), end diastolic wall thickness (EDWT) and percentage systolic wall thickening (SWT%) in the plane of the 2de and to assess WMS in the same planes visually. No patient had a clinical ischemic event between the tests. Results: visual assessment of wall motion by 2de and MRI showed moderate agreement (kappa = 0.425). Resting 2de wall motion correlated significantly (p

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Recent years have witnessed intense research in multiple input multiple output (MIMO) wireless communications systems, which use multiple element antennas (MEA) for signal transmission and reception. In this paper, we have described a novel electromagnetic model to investigate the effect of mutual coupling, inter-element spacing and array geometry on the capacity of MIMO systems. Simulation results have been presented illustrating the application of the proposed model. The presented model concept stems from a hollow waveguide analogue. Using this model other aspects such as richness of scattering environment (spacing and clustering), the effect of hard versus soft scatterers and pin hole effect can be investigated.

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Probabilistic robotics most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainty to accompany observations of the environment. This paper describes how uncertainty can be characterised for a vision system that locates coloured landmarks in a typical laboratory environment. The paper describes a model of the uncertainty in segmentation, the internal cameral model and the mounting of the camera on the robot. It explains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainty model.

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Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. miniDVMS v1.8 provides a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualisation domain. The advantage of this interface is that the user is directly involved in the data mining process. Principled projection methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), are integrated with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, and user interaction facilities, to provide this integrated visual data mining framework. The software also supports conventional visualisation techniques such as principal component analysis (PCA), Neuroscale, and PhiVis. This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install and use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software.