Search results for "ground"

A Non-stationary Fractional Tajimi Kanai Model of Earthquake Ground Motions

2013

Effect of epicentral direction on seismic response of asymmetric buildings

1984

The paper deals with the influence of the epicentral direction on the displacement and stress response of multistorey asymmetric buildings to earthquake horizontal ground motion. A method is given for computing for each plane frame of the complex structure a particular direction of the bidirectional stationary random input for which the horizontal floor displacement of the given frame is maximized. It is shown that this direction can be considered conservative for the corresponding non-stationary process.

European vestibular experiments on the Spacelab-1 mission: 2. Experimental equipment and methods

1986

A series of vestibular experiments were performed in conjunction with the first Spacelab mission, consisting of sets of pre-, in- and postflight tests. A multipurpose experimental apparatus used for the diverse flight and ground tests is presented. Additional apparatus together with the multi-purpose package were used in the baseline data collection facility at the landing site at NASA Dryden Flight Research Facility for the ground tests. The tests involved optokinetic, caloric and mechanical (whole-body or head-alone) stimulation. The latter included linear acceleration in the subject's x, y and z axes, static roll and yaw about an earth-vertical axis. Physiological parameters such as elec…

Domain Adaptation of Landsat-8 and Proba-V Data Using Generative Adversarial Networks for Cloud Detection

2019

Training machine learning algorithms for new satellites requires collecting new data. This is a critical drawback for most remote sensing applications and specially for cloud detection. A sensible strategy to mitigate this problem is to exploit available data from a similar sensor, which involves transforming this data to resemble the new sensor data. However, even taking into account the technical characteristics of both sensors to transform the images, statistical differences between data distributions still remain. This results in a poor performance of the methods trained on one sensor and applied to the new one. In this this work, we propose to use the generative adversarial networks (G…

A 3D Deep Neural Network for Liver Volumetry in 3T Contrast-Enhanced MRI.

2020

 To create a fully automated, reliable, and fast segmentation tool for Gd-EOB-DTPA-enhanced MRI scans using deep learning. Datasets of Gd-EOB-DTPA-enhanced liver MR images of 100 patients were assembled. Ground truth segmentation of the hepatobiliary phase images was performed manually. Automatic image segmentation was achieved with a deep convolutional neural network. Our neural network achieves an intraclass correlation coefficient (ICC) of 0.987, a Sørensen-Dice coefficient of 96.7 ± 1.9 % (mean ± std), an overlap of 92 ± 3.5 %, and a Hausdorff distance of 24.9 ± 14.7 mm compared with two expert readers who corresponded to an ICC of 0.973, a Sørensen-Dice coefficient of 95.2 ± 2.8 %, and…

Blood vessel segmentation and width estimation in ultra-wide field scanning laser ophthalmoscopy.

2014

Features of the retinal vasculature, such as vessel widths, are considered biomarkers for systemic disease. The aim of this work is to present a supervised approach to vessel segmentation in ultra-wide field of view scanning laser ophthalmoscope (UWFoV SLO) images and to evaluate its performance in terms of segmentation and vessel width estimation accuracy. The results of the proposed method are compared with ground truth measurements from human observers and with existing state-of-the-art techniques developed for fundus camera images that we optimized for UWFoV SLO images. Our algorithm is based on multi-scale matched filters, a neural network classifier and hysteresis thresholding. After …

Conjugate Gradient Method for Brain Magnetic Resonance Images Segmentation

2018

Part 8: Pattern Recognition and Image Processing; International audience; Image segmentation is the process of partitioning the image into regions of interest in order to provide a meaningful representation of information. Nowadays, segmentation has become a necessity in many practical medical imaging methods as locating tumors and diseases. Hidden Markov Random Field model is one of several techniques used in image segmentation. It provides an elegant way to model the segmentation process. This modeling leads to the minimization of an objective function. Conjugate Gradient algorithm (CG) is one of the best known optimization techniques. This paper proposes the use of the nonlinear Conjugat…

Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift

2010

Fuel feeding and inhomogeneity of fuel typically cause fluctuations in the circulating fluidized bed (CFB) process. If control systems fail to compensate the fluctuations, the whole plant will suffer from dynamics that is reinforced by the closed-loop controls. This phenomenon causes reducing efficiency and the lifetime of process components. In this paper we address the problem of online mass flow prediction, which is a part of control. Particularly, we consider the problem of learning an accurate predictor with explicit detection of abrupt concept drift and noise handling mechanisms. We emphasize the importance of having domain knowledge concerning the considered case and constructing the…

New Error Measures to Evaluate Features on Three-Dimensional Scenes

2011

In this paper new error measures to evaluate image features in three-dimensional scenes are proposed and reviewed. The proposed error measures are designed to take into account feature shapes, and ground truth data can be easily estimated. As other approaches, they are not error-free and a quantitative evaluation is given according to the number of wrong matches and mismatches in order to assess their validity

Uncertainties in The S-Sebi Model to Estimate Surface Energy Fluxes Over Natural Grasslands in Brazil

2021

Evapotranspiration (ET) is one of the main fluxes in the global water cycle. In this context, we assessed an operational methodology based on the S-SEBI model to accurately estimate energy fluxes over the natural grasslands of Pampa biome. The S-SEBI performance was investigated considering radiation data from both ERA5 reanalysis and tower flux. Comparisons from satellite-based estimates with in situ measurements were performed with and without energy balance closure (EBC). Results indicated that meteorological inputs have low sensitivity on daily ET estimates. In contrast, the instantaneous components are more affected. The impact in the daily ET is lower when in situ data without EBC are…