pMapper: Automatic Mapping of Parallel Matlab Programs

Author(s):  
N. Travinin ◽  
H. Hoffmann ◽  
R. Bond ◽  
H. Chan ◽  
J. Kepner ◽  
...  
Author(s):  
Erkan Cakir ◽  
Ayhan Akinturk ◽  
Alejandro Allievi

The aim of the study is to investigate VIV effects, not only on a test cylinder but also on the experimental rig being towed under water at a prescribed depth and operating speeds. For this purpose, a numerical Multi-Physics model was created using one way coupled analysis simultaneously between the Mechanical and Fluent solvers of ANSYS software package. A system coupling was developed in order to communicate force data alternately between the solvers with the help of automatic mapping algorithms within millesimal time periods of a second. Numerical investigation into the dynamic characteristics of pressure and velocity fields for turbulent viscous fluid flow along with structural responses of the system, stressed the significance of time and space scales for convergence and accuracy of our Finite Volume (FV) CFD calculations.


Author(s):  
L. Fang ◽  
L. Hoegner ◽  
U. Stilla

For many research applications like water resources evaluation, determination of glacier specific changes, and for calculation of the past and future contribution of glaciers to sea-level change, parameters about the size and spatial distribution of glaciers is crucial. In this paper, an automatic method for determination of glacier surface area using single track high resolution TerraSAR-X imagery by benefits of low resolution optical and thermal data is presented. Based on the normalized difference snow index (NDSI) and land surface temperature (LST) map generated from optical and thermal data combined with a surface slope data, a low resolution binary mask was derived used for the supervised classification of glacier using SAR imagery. Then, a set of suitable features is derived from the SAR intensity image, such as the texture information generated based on the gray level co-occurrence matrix (GLCM), and the intensity values. With these features, the glacier surface is discriminated from the background by Random Forests (RF) method.


2021 ◽  
Vol 4 ◽  
pp. 1-6
Author(s):  
Bence Dusek ◽  
Mátyás Gede

Abstract. Nowadays, people easily can get into their cars and drive hundreds of kilometers in a few hours, but for that to work efficiently a system of rules must be applied and those rules have to be communicated transparently. This is why traffic signs are an influential part of our lives and every kind of information about each is helping the government, the community, and the drivers. This paper presents a novel and cost-efficient method for acquiring information on traffic signs, such like the category and the 3D position. The former can be gained using camera images and a Convolutional Neural Network model. The latter can be obtained using positioning devices.With the help of a GNSS device the absolute position of the vehicle can be learned and based on that a local coordinate system can be established. From the vehicle’s point of view the coordinates and the orientation of the traffic sign can be acquired by applying a stereo camera and an IMU (Inertial Measurement Unit) sensor. Then, with the help of these attributes a large database can be built, maintained, and updated. This project displays that adequately precise data can easily be accessible using a few cheap devices and sensors.


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