Wyniki wyszukiwania - BazTech

1

Robustness study of the road profile estimation technique under uncertainty

Ben Jdidia Anoire, Ben Hassen Dorra, Hentati Taissir, Abbes Slim, Haddar Mohamed

Journal of Theoretical and Applied Mechanics

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2022

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Vol. 60 nr 3

521--533

EN

This paper studies profile estimation a road. The prediction has been achieved using the Independent Component Analysis Method (ICA). The vehicle dynamic responses were cal- culated for different road profiles which were defined using an ISO norm. The robustness of this method was proven by implementing the stochastic Monte Carlo (MC) technique in the presence of inevitable uncertainty parameters simultaneously associated with the vehicle mass, spring stiffness and damping for different vehicle speeds and wind values. Convergence was assessed when comparing real profiles to simulated ones. The obtained results prove the efficiency of the ICA in estimating the profile variabilities under uncertainties.

2

Monte Carlo calculated CT numbers for improved heavy ion treatment planning

Qamhiyeh S., Wysocka-Rabin A., Jäkel O.

Nukleonika

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2014

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Vol. 59, No. 1

15--23

EN

Better knowledge of CT number values and their uncertainties can be applied to improve heavy ion treatment planning. We developed a novel method to calculate CT numbers for a computed tomography (CT) scanner using the Monte Carlo (MC) code, BEAMnrc/EGSnrc. To generate the initial beam shape and spectra we conducted full simulations of an X-ray tube, filters and beam shapers for a Siemens Emotion CT. The simulation output files were analyzed to calculate projections of a phantom with inserts. A simple reconstruction algorithm (FBP using a Ram-Lak filter) was applied to calculate the pixel values, which represent an attenuation coefficient, normalized in such a way to give zero for water (Hounsfield unit (HU)). Measured and Monte Carlo calculated CT numbers were compared. The average deviation between measured and simulated CT numbers was 4 ± 4 HU and the standard deviation σ was 49 ± 4 HU. The simulation also correctly predicted the behaviour of H-materials compared to a Gammex tissue substitutes. We believe the developed approach represents a useful new tool for evaluating the effect of CT scanner and phantom parameters on CT number values.

3

Bazujący na sygnale wideo algorytm o niskim obliczeniowo koszcie do kontroli bezpieczeństwa osobistego w strefie przemysłowej

Lech P.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 4

335-337

PL

Zapewnienie bezpieczeństwa w strefach przemysłowych jest realizowane w oparciu specjalistyczne systemy eksperckie dedykowane dla konkretnej branży, część z nich działa w oparciu o detekcję zmian w obrazach sekwencji wideo. Prezentowany w pracy szybki algorytm do wykrywania zmian w obrazach, działa w oparciu o metodę Monte Carlo. Badania wykazały dużą szybkość obliczeń wynikającą z redukcji ilości analizowanych danych, odporność na niski poziom zakłóceń oraz wysoką skuteczność wykrywania zmian.

EN

Ensuring safety in the industrial zones is realised on the basis of specialised expert systems, some of them operate on the detection of changes in the image from video sequence. In this paper is presented fast algorithm based on the Monte Carlo method for detecting changes in images. The studies have shown: high-speed calculations resulting from the reduction of the analysed data, resistance to low noise and high efficiency of detection of changes.

4

Implementation of a Monte Carlo method to a two-dimensional particle-in-cell solver using algebraic meshes

Sengil N., Tümüklü Ö., Çelenligil M. C.

Nukleonika

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2012

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Vol. 57, No. 2

313-316

EN

Particle-in-cell (PIC) technique is a widely used computational method in the simulation of low density collisionless plasma flows. In this study, a new two-dimensional (2-D) electrostatic particle-in-cell solver is developed that can be applied to non-rectangular configurations.

5

Simulation of computed tomography (CT) images using a Monte Carlo approach

Wysocka-Rabin A. M., Qamhiyeh S., Jäkel O.

Nukleonika

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2011

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Vol. 56, No. 4

299-304

EN

Heavy ion treatment planning uses an empirical scanner-dependent calibration relation between computed tomography (CT) numbers and ion range. Any deviation in the values of CT numbers will cause a drift in the calibration curve of the CT scanner, which can reduce the accuracy of treatment beam delivery. To reduce uncertainty in the empirical estimation of CT numbers, we developed a simulation that takes into consideration the geometry, composition, and physical process that underlie their measurement. This approach uses Monte Carlo (MC) simulations, followed by a simple filtered back-projection reconstruction. The MC code used is BEAMnrc/EGSnrc. With the manufacturer’s permission, we simulated the components (X-ray tube, associated filters and beam shapers) of a Siemens Emotion CT. We then generated an initial beam shape and spectra, and performed further simulations using the phantom with substitutes. We analyzed the resulting phase space file to calculate projections, taking into account the energy response of the CT detectors. Then, we applied a simple reconstruction algorithm to the calculated projections in order to receive the CT image.