Academic literature on the topic 'GATE Monte Carlo simulations'
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Journal articles on the topic "GATE Monte Carlo simulations"
Kathawala, G. A., B. Winstead, and U. Ravaioli. "Monte Carlo simulations of double-gate MOSFETs." IEEE Transactions on Electron Devices 50, no. 12 (December 2003): 2467–73. http://dx.doi.org/10.1109/ted.2003.819699.
Full textAsenov, A., S. Babiker, S. P. Beaumont, and J. R. Barker. "Monte Carlo Calibrated Drift-Diffusion Simulation of Short Channel HFETs." VLSI Design 8, no. 1-4 (January 1, 1998): 319–23. http://dx.doi.org/10.1155/1998/72453.
Full textCamarasu-Pop, Sorina, Tristan Glatard, Jakub T. Mościcki, Hugues Benoit-Cattin, and David Sarrut. "Dynamic Partitioning of GATE Monte-Carlo Simulations on EGEE." Journal of Grid Computing 8, no. 2 (March 23, 2010): 241–59. http://dx.doi.org/10.1007/s10723-010-9153-0.
Full textBuvat, Irène, and Delphine Lazaro. "Monte Carlo simulations in emission tomography and GATE: An overview." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 569, no. 2 (December 2006): 323–29. http://dx.doi.org/10.1016/j.nima.2006.08.039.
Full textBabiker, S., A. Asenov, J. R. Barker, and S. P. Beaumont. "Quadrilateral Finite Element Monte Carlo Simulation of Complex Shape Compound FETs." VLSI Design 6, no. 1-4 (January 1, 1998): 127–30. http://dx.doi.org/10.1155/1998/51378.
Full textRavishankar, R., G. Kathawala, U. Ravaioli, S. Hasan, and M. Lundstrom. "Comparison of Monte Carlo and NEGF Simulations of Double Gate MOSFETs." Journal of Computational Electronics 4, no. 1-2 (April 2005): 39–43. http://dx.doi.org/10.1007/s10825-005-7104-y.
Full textSarrut, David, Mateusz Bała, Manuel Bardiès, Julien Bert, Maxime Chauvin, Konstantinos Chatzipapas, Mathieu Dupont, et al. "Advanced Monte Carlo simulations of emission tomography imaging systems with GATE." Physics in Medicine & Biology 66, no. 10 (May 14, 2021): 10TR03. http://dx.doi.org/10.1088/1361-6560/abf276.
Full textKelsall, R. W., and A. J. Lidsey. "Inclusion of Quantum Confinement Effects in Self-Consistent Monte Carlo Device Simulations." VLSI Design 8, no. 1-4 (January 1, 1998): 21–27. http://dx.doi.org/10.1155/1998/57936.
Full textBabiker, S., A. Asenov, N. Cameron, S. P. Beaumont, and J. R. Barker. "Complete RF Analysis of Compound FETs Based on Transient Monte Carlo Simulation." VLSI Design 8, no. 1-4 (January 1, 1998): 313–17. http://dx.doi.org/10.1155/1998/26067.
Full textPennathur, S., Can K. Sandalci, Çetin K. Koç, and S. M. Goodnick. "3D Parallel Monte Carlo Simulation of GaAs MESFETs." VLSI Design 6, no. 1-4 (January 1, 1998): 273–76. http://dx.doi.org/10.1155/1998/64531.
Full textDissertations / Theses on the topic "GATE Monte Carlo simulations"
Maigne, Lydia. "Personnalized dosimetry using GATE Monte Carlo simulations on a grid architecture." Clermont-Ferrand 2, 2005. http://www.theses.fr/2005CLF21607.
Full textBurg, Samuel. "Segmentation 3D d'images scintigraphiques et simulations très réalistes GATE." Poitiers, 2011. http://nuxeo.edel.univ-poitiers.fr/nuxeo/site/esupversions/b5bc3be2-14be-4526-9e11-61619c11caaf.
Full textThe objective of this thesis was to propose a new 3D segmentation method for scintigraphic imaging. The first part of the work was to simulate 3D volumes with known ground truth in order to validate a segmentation method over other. MonteCarlo simulations were performed using the GATE software (Geant4 Application for Emission Tomography). For this, we characterized and modeled the gamma camera "Imager" Biospace™ by comparing each measurement from a simulated acquisition to his real equivalent. The "low level" segmentation tool that we have developed is based on a modeling of the levels of the image by probabilistic mixtures. Parameters estimation is done by an SEM algorithm (Stochastic Expectation Maximization). The 3D volume segmentation is achieved by an ICM algorithm (Iterative Conditional Mode). We compared the segmentation based on Gaussian and Poisson mixtures to segmentation by thresholding on the simulated volumes. This showed the relevance of the segmentations obtained using probabilistic mixtures, especially those obtained with Poisson mixtures. Those one has been used to segment real 18FDG PET images of the brain and to compute descriptive statistics of the different tissues. In order to obtain a "high level" segmentation method and find anatomical structures (necrotic part or active part of a tumor, for example), we proposed a process based on the point processes formalism. A feasibility study has yielded very encouraging results
Perrot, Yann. "Evaluation de la dose déposée par des faisceaux d'électrons en radiothérapie dans des fantômes voxelisés en utilisant la plateforme de simulation Monte Carlo GATE fondée sur GEANT4 dans un environnement de grille." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2011. http://tel.archives-ouvertes.fr/tel-00721940.
Full textZahra, Nabil. "Mesure de la dose physique par lms radiochromiques et simulation Monte Carlo pour l'hadronthérapie." Thesis, Lyon 1, 2010. http://www.theses.fr/2010LYO10088/document.
Full textBecause of the increase in dose at the end of the range of ions, dose delivery during patient treatment with hadrontherapy should be controlled with high precision. Monte Carlo codes are now considered mandatory for validation of clinical treatment planing and as a new tool for dosimetry of ion beams. In this work, we aimed to calculate the absorbed dose using Monte Carlo simulation Geant4/Gate. The ejffect on the dose calculation accuracy of dierent Geant4 parameters has been studied for mono-energetic carbon ion beams of 300 MeV/u in water. The parameters are : the production threshold of secandary particules and the maximum step limiter of the particle track. Tolerated criterion were choosen to meet the precision required in radiotherapy (2%, 2mm) and to obtain the best compromise on dose distribution and computational time.We propose here the values of parameters in order to satisfy the precision required. In the second part of this work, we will study the response of radiochromic lms MD-v2-55 for quality control in proton and carbon ion beams. We have particularly observed and studie the quenching effect of dosimetric lms for high LET (20 KeV/m) irradiations in homogeneous and heterogeneous medium. This eject is due to the high ionization density around the track of the particule. We have developped a method to predict the response of radiochromic lms taking into account the saturation effect. This model is called the RADIS model forRAdiochromic films. Dosimetry for Ions using Simulations". It is based on the response of lms under photon irradiations and the saturation of lms due to high linear energy deposit calculated by Monte Carlo. Four beams were used in this study and aimed to validate the model for hadrontherapy applications : carbon ions, protons and photons at different energies. Experiments were performed at Grand Accélérateur National d'Ions Lourds (GANIL), Proton therpay center of Orsay (CPO), A. Lacassagne proton center (CAL) and Leon Berard cancer center (CLB). The model showed very good agreement between the measured and calculated optical density with an error less than 2%
Thiam, C. O. "Dosimétrie en radiothérapie et curiethérapie par simulation Monte-Carlo GATE sur grille informatique." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2007. http://tel.archives-ouvertes.fr/tel-00196405.
Full textThiam, Cheik Oumar. "Dosimétrie en radiothérapie et curiethérapie par simulation Monte-Carlo GATE sur grille informatique." Clermont-Ferrand 2, 2007. http://www.theses.fr/2007CLF21771.
Full textFreudenberg, Robert, Rudi Apolle, Martin Walther, Holger Hartmann, and Jörg Kotzerke. "Molecular imaging using the theranostic agent 197(m)Hg: phantom measurements and Monte Carlo simulations." Springer Open, 2018. https://tud.qucosa.de/id/qucosa%3A33332.
Full textZahra, Mohamad Nabil. "Mesure de la dose physique par lms radiochromiques et simulation Monte Carlo pour l'hadronthérapie." Phd thesis, Université Claude Bernard - Lyon I, 2010. http://tel.archives-ouvertes.fr/tel-00520876.
Full textMaigne, Lydia. "Dosimétrie personnalisée par simulation Monte Carlo GATE sur grille de calcul. Application à la curiethérapie oculaire." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2005. http://tel.archives-ouvertes.fr/tel-00011404.
Full textDes points kernels de dose d'électrons mono-énergétiques et poly-énergétiques ont été simulés en utilisant la plate-forme GATE et comparés à d'autres codes Monte Carlo. Trois versions des packages de librairies ont été utilisées pour les comparaisons (5.2, 6.2 et 7.0). Les résultats montrent que l'implémentation de la diffusion multiple est responsable des différences observées entre les codes. Les simulations de traitements de curiethérapie oculaire comparées avec d'autres Monte Carlo et des mesures montrent un bon accord. La transcription des unités Hounsfield, à partir des données scanner sur l'anatomie du patient, en paramètres tissulaires est l'autre étude présentée pour une utilisation prochaine de GATE sur des images voxélisées pour la dosimétrie personnalisée. Les infrastructures des projets DataGrid puis d'EGEE ont été utilisées pour déployer les simulations GATE afin de réduire leur temps de calcul dans le but de les utiliser en routine clinique.
La méthode utilisée pour paralléliser les simulations GATE est la division du générateur de nombres aléatoires (RNG) en séquences indépendantes. Des tests de temps de calcul réalisés sur des bancs tests de grille montrent qu'un gain significatif est obtenu. Les fonctionnalités pour diviser, lancer et contrôler les simulations GATE sur une infrastructure de grille ont été implémentées sur le portail web GENIUS. Un premier prototype de ce portail est accessible à partir d'un centre hospitalier pour l'utilisation de la précision des algorithmes Monte Carlo de manière transparente et sécurisée pour des traitements de cancer de l'œil.
Pham, Quang Trung. "Couplage et validation de l'extension GeantA-DNA dans la plateforme de simulation Monte Carlo GATE pour l'irradiation de molécules d'ADN dans un environnement de grille de calcul." Thesis, Clermont-Ferrand 2, 2014. http://www.theses.fr/2014CLF22456/document.
Full textThe Monte Carlo simulation methods are successfully being used in various areas of medical physics but also at different scales, for example, from the radiation therapy treatment planning systems to the prediction of the effects of radiation in cancer cells. The Monte Carlo simulation platform GATE based on the Geant4 toolkit offers features dedicated to simulations in medical physics (nuclear medicine and radiotherapy). For radiobiology applications, the Geant4-DNA physical models are implemented to track particles till very low energy (eV) and are adapted for estimation of micro-dosimetric quantities. In order to implement a multi-scale Monte Carlo platform, we first validated the physical models of Geant4-DNA, and integrated them into GATE. Finally, we validated this implementation in the context of radiation therapy and proton therapy. In order to validate the Geant4-DNA physical models, dose point kernels for monoenergetic electrons (10 keV to 100 keV) were simulated using the physical models of Geant4-DNA and were compared to those simulated with Geant4 Standard physical models and another Monte Carlo code EGSnrc. The range and the stopping powers of electrons (7.4 eV to 1 MeV) and protons (1 keV to 100 MeV) calculated with GATE/Geant4-DNA were then compared with literature. We proposed to simulate with the GATE platform the impact of clinical and preclinical beams on cellular DNA. We modeled a clinical proton beam of 193.1 MeV, 6 MeV clinical electron beam and a X-ray irradiator beam. The beams models were validated by comparing absorbed dose computed and measured in liquid water. Then, the beams were used to calculate the frequency of energy deposits in DNA represented by different geometries. First, the DNA molecule was represented by small cylinders : 2 nm x 2 nm ( 10 bp), 5 nm x 10 nm ( nucleosome) and 25 nm x 25 nm ( chromatin fiber). All these cylinders were placed randomly in a sphere of liquid water (500 nm radius). Then we reconstructed the DNA molecule in Geant4 by reading PDB (Protein Data Bank) files representing twelve base pairs of the DNA molecule and a dinucleosome (347 base pairs). Finally, we developed a tool to correlate the positions of direct energy deposit in liquid water with the coordinates of the base pairs of DNA to calculate the number of single and double strand breaks in DNA. All calculations in this work were perfomed on the European Grid Infrastructure; performance tests are available to estimate the utility of this type of architecture for Monte Carlo calculations
Books on the topic "GATE Monte Carlo simulations"
Disordered alloys: Diffuse scattering and Monte Carlo simulations. Berlin: Springer Verlag, 1998.
Find full text1944-, Binder K., ed. A guide to Monte Carlo simulations in statistical physics. 3rd ed. Cambridge: Cambridge University Press, 2009.
Find full textDimitrievski, Kristian. Monte Carlo simulations of supported biomembranes and protein folding. Göteborg: Göteborg University, Department of Physics, 2006.
Find full text1944-, Binder K., ed. A guide to Monte Carlo simulations in statistical physics. Cambridge: Cambridge University Press, 2000.
Find full textLandau, David P. A guide to Monte Carlo simulations in statistical physics. 2nd ed. Cambridge, UK: Cambridge University Press, 2005.
Find full textLandau, David P. A guide to Monte Carlo simulations in statistical physics. 3rd ed. Cambridge: Cambridge University Press, 2009.
Find full textLandau, David P. A guide to Monte Carlo simulations in statistical physics. 3rd ed. Cambridge: Cambridge University Press, 2009.
Find full textservice), SpringerLink (Online, ed. An Introduction to Kinetic Monte Carlo Simulations of Surface Reactions. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Find full textJansen, A. P. J. An Introduction to Kinetic Monte Carlo Simulations of Surface Reactions. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29488-4.
Full textGallis, Michael A. On the modeling of thermochemical non-equilibrium in particle simulations. London: Imperial College of Science, Technology & Medicine, Dept. of Aeronautics, 1995.
Find full textBook chapters on the topic "GATE Monte Carlo simulations"
Babiker, S., A. Asenov, J. R. Barker, and S. P. Beaumont. "Finite Element Monte Carlo Simulation of Recess Gate FETs." In Simulation of Semiconductor Devices and Processes, 226–29. Vienna: Springer Vienna, 1995. http://dx.doi.org/10.1007/978-3-7091-6619-2_54.
Full textLee, Chang-Lae, Su-Jin Park, Seung-Wan Lee, Dae-Hong Kim, Pil-Hyun Jeon, and Hee-Joung Kim. "Mouse Brain Dosimetry in Small Animal CT with GATE Monte Carlo Simulations." In IFMBE Proceedings, 1149–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-29305-4_301.
Full textFernando, Sumudu, and Martin Müller. "Analyzing Simulations in Monte-Carlo Tree Search for the Game of Go." In Computers and Games, 72–83. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09165-5_7.
Full textFrenkel, D. "Monte Carlo Simulations." In Computer Modelling of Fluids Polymers and Solids, 83–123. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-2484-0_4.
Full textRaabe, Gabriele. "Monte Carlo Simulations." In Molecular Simulation Studies on Thermophysical Properties, 31–82. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3545-6_3.
Full textDeutsch, Hans-Peter. "Monte Carlo Simulations." In Derivatives and Internal Models, 167–79. London: Palgrave Macmillan UK, 2002. http://dx.doi.org/10.1057/9780230502109_12.
Full textEugeniy, E. Mikhailov. "Monte Carlo Simulations." In Programming with MATLAB for Scientists, 149–60. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2017]: CRC Press, 2018. http://dx.doi.org/10.1201/9781351228183-12.
Full textDeutsch, Hans-Peter. "Monte Carlo Simulations." In Derivatives and Internal Models, 169–81. London: Palgrave Macmillan UK, 2004. http://dx.doi.org/10.1057/9781403946089_12.
Full textDeutsch, Hans-Peter. "Monte Carlo Simulations." In Derivatives and Internal Models, 184–98. London: Palgrave Macmillan UK, 2009. http://dx.doi.org/10.1057/9780230234758_11.
Full textEarl, David J., and Michael W. Deem. "Monte Carlo Simulations." In Methods in Molecular Biology, 25–36. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-177-2_2.
Full textConference papers on the topic "GATE Monte Carlo simulations"
Branco, S., S. Jan, and P. Almeida. "Monte Carlo simulations studies in small animal PET using GATE." In 2007 IEEE Nuclear Science Symposium Conference Record. IEEE, 2007. http://dx.doi.org/10.1109/nssmic.2007.4436990.
Full textRavishankar, Kathawala, Ravaioli, Hasan, and Lundstrom. "Comparison of Monte Carlo and NEGF simulations of double gate MOSFETs." In Electrical Performance of Electronic Packaging. IEEE, 2004. http://dx.doi.org/10.1109/iwce.2004.1407341.
Full textZhu, Shufang, Kangliang Wei, Gang Du, and Xiaoyan Liu. "3D Monte Carlo simulation of Gate-All-Around Germanium nMOSFET." In 2011 International Conference of Electron Devices and Solid-State Circuits (EDSSC). IEEE, 2011. http://dx.doi.org/10.1109/edssc.2011.6117723.
Full textEndoh, Akira, Issei Watanabe, Akifumi Kasamatsu, and Takashi Mimura. "Monte Carlo simulation of InAlAs/InGaAs HEMTs with buried gate." In 2013 25th International Conference on Indium Phosphide and Related Materials (IPRM). IEEE, 2013. http://dx.doi.org/10.1109/iciprm.2013.6562605.
Full textReuillon, R., D. R. C. Hill, C. Gouinaud, Z. El Bitar, V. Breton, and I. Buvat. "Monte Carlo simulation with the GATE software using grid computing." In the 8th international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1416729.1416762.
Full textStrologas, John, and Wei Chang. "Assessing the performance of C-SPECT cardiac tomographer using GATE-based Monte Carlo simulations." In 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference (2012 NSS/MIC). IEEE, 2012. http://dx.doi.org/10.1109/nssmic.2012.6551806.
Full textLan, Li-Cheng, Wei Li, Ting-Han Wei, and I.-Chen Wu. "Multiple Policy Value Monte Carlo Tree Search." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/653.
Full textRowedder, Blake A., Hui Wang, and Yu Kuang. "Gate Cloud: An Integration of Gate Monte Carlo Simulation with a Cloud Computing Environment." In 2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom). IEEE, 2014. http://dx.doi.org/10.1109/cloudcom.2014.124.
Full textMATEOS, JAVIER, TOMÁS GONZÁLEZ, DANIEL PARDO, SYLVAIN BOLLAERT, THIERRY PARENTY, and ALAIN CAPPY. "NOISE OPTIMIZATION OF ULTRA-SHORT GATE HEMTs USING MONTE CARLO SIMULATION." In Proceedings of the 16th International Conference. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812811165_0055.
Full textAldegunde, Manuel, Antonio J. Garcia-Loureiro, Antonio Martinez, and Karol Kalna. "3D Monte Carlo simulation of Tri-Gate MOSFETs using tetrahedral finite elements." In 2008 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD 2008). IEEE, 2008. http://dx.doi.org/10.1109/sispad.2008.4648260.
Full textReports on the topic "GATE Monte Carlo simulations"
Blue, James L., Isabel Beichl, and Francis Sullivan. Faster BKL Monte Carlo simulations. Gaithersburg, MD: National Institute of Standards and Technology, 1994. http://dx.doi.org/10.6028/nist.ir.5489.
Full textToor, A., and A. A. Marchetti. Monte Carlo Simulations for Mine Detection. Office of Scientific and Technical Information (OSTI), March 2000. http://dx.doi.org/10.2172/792767.
Full textPalmer, R. B., J. C. Gallardo, R. C. Fernow, Y. Torun, D. Neuffer, and D. Winn. Monte Carlo simulations of muon production. Office of Scientific and Technical Information (OSTI), March 1995. http://dx.doi.org/10.2172/46704.
Full textRambo, P. W., and J. Denavit. Monte Carlo simulations of solid-state photoswitches. Office of Scientific and Technical Information (OSTI), September 1995. http://dx.doi.org/10.2172/123236.
Full textChason, E., and B. K. Kellerman. Monte Carlo simulations of ion-enhanced island coarsening. Office of Scientific and Technical Information (OSTI), August 1996. http://dx.doi.org/10.2172/378876.
Full textAguayo Navarrete, Estanislao, John L. Orrell, and Richard T. Kouzes. Monte Carlo Simulations of Cosmic Rays Hadronic Interactions. Office of Scientific and Technical Information (OSTI), April 2011. http://dx.doi.org/10.2172/1022429.
Full textKroll, D. M., and G. Gompper. The Conformation of Fluid Membranes: Monte Carlo Simulations. Fort Belvoir, VA: Defense Technical Information Center, February 1992. http://dx.doi.org/10.21236/ada271695.
Full textBurns, Kimberly A. Monte Carlo Simulations for Homeland Security Using Anthropomorphic Phantoms. Office of Scientific and Technical Information (OSTI), January 2008. http://dx.doi.org/10.2172/1025694.
Full textALAM, TODD M. Monte Carlo simulations of phosphate polyhedron connectivity in glasses. Office of Scientific and Technical Information (OSTI), January 2000. http://dx.doi.org/10.2172/750883.
Full textMarchetti, A. A. ,. LLNL. New Monte Carlo simulations of the LLNL pulsed-sphere experiments. Office of Scientific and Technical Information (OSTI), July 1998. http://dx.doi.org/10.2172/304515.
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