Results 11 to 20 of about 1,419,392 (377)

Treatment planning with a 2.5 MV photon beam for radiation therapy

Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022
Abstract Purpose The shallow depth of maximum dose and higher dose fall‐off gradient of a 2.5 MV beam along the central axis that is available for imaging on linear accelerators is investigated for treatment of shallow tumors and sparing the organs at risk (OARs) beyond it.
Navid Khaledi, Chris Hayes, Louise Belshaw, Mark Grattan, Rao Khan, James L. Gräfe   +5 more
wiley   +1 more source

Validation of pencil beam scanning proton therapy with multi‐leaf collimator calculated by a commercial Monte Carlo dose engine

Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022
Abstract This study aimed to evaluate the clinical beam commissioning results and lateral penumbra characteristics of our new pencil beam scanning (PBS) proton therapy using a multi‐leaf collimator (MLC) calculated by use of a commercial Monte Carlo dose engine.
Yuki Tominaga, Yusuke Sakurai, Junya Miyata, Shuichi Harada, Takashi Akagi, Masataka Oita   +5 more
wiley   +1 more source

Evaluation of an EPID in vivo monitoring system using local and external independent audit measurements

Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022
Abstract Purpose The aim of this work was to evaluate the SunCHECK PerFRACTION, the software for in vivo monitoring using EPID images. Materials/Methods First, the PerFRACTION ability to detect errors was investigated simulating two situations: (1) variation of LINAC output and (2) variation of the phantom thickness.
Samuel Ramalho Avelino, Juliana Rosada Dias, Taís Marques Peron, Gabriel Souza Vidal   +3 more
wiley   +1 more source

Accuracy of patient dose estimation in cone beam computed tomography in breast irradiation by size‐specific dose estimates with position correction

Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022
Abstract This study aims to investigate the effects of the position correction of size‐specific dose estimates (SSDE) on patient dose estimation in cone beam computed tomography (CBCT). The relationship between the phantom position and absorbed dose in the right breast was studied using optically stimulated luminescence dosimeters and a simulated human
Hiroyuki Ueno, Kosuke Matsubara, Sayuri Bou, Masato Hizume   +3 more
wiley   +1 more source

Parallel Monte Carlo simulations [PDF]

Physical Review E, 1995
The Monte Carlo (MC) method is an important tool in sampling the state space of a chosen statistical ensemble. It allows the study of thermodynamic averages of configurational properties by generating ``moves'' in a system and accepting or rejecting the thus generated new state depending on the energy of the new system and/or a random choice.
K. Esselink, L.D.J.C. Loyens, B. Smit
openaire   +4 more sources

MENENTUKAN HARGA OPSI DENGAN METODE MONTE CARLO BERSYARAT MENGGUNAKAN BARISAN KUASI ACAK FAURE

E-Jurnal Matematika, 2021
An option contract is a contract that gives the owner the right to sell or even to buy an asset at the predetermined price and period time. The conditional Monte Carlo is one of the several methods that is used to determine the option price which in the ...
PUTU WIDYA ASTUTI, KOMANG DHARMAWAN, KARTIKA SARI   +2 more
doaj   +1 more source

Value at Risk dan Tail Value at Risk dari Peubah Acak Besarnya Kerugian yang Menyebar Alpha Power Pareto

Jambura Journal of Mathematics, 2023
Value at Risk (VaR) and Tail Value at Risk (TVaR) are two measures that are commonly used to quantify the risk associated with a loss severity distribution.
Ruhiyat Ruhiyat, Berlian Setiawaty, Muwafiqo Zamzami Dhuha   +2 more
doaj   +1 more source

The Monte Carlo simulation of the Borexino detector [PDF]

Astroparticle Physics, 2018
We describe the Monte Carlo (MC) simulation package of the Borexino detector and discuss the agreement of its output with data. The Borexino MC 'ab initio' simulates the energy loss of particles in all detector components and generates the resulting scintillation photons and their propagation within the liquid scintillator volume.
F. von Feilitzsch, P. Cavalcante, S. Appel, M. D. Skorokhvatov, M. D. Skorokhvatov, Michael Wurm, A. S. Chepurnov, P. Shakina, D. Bick, D. Bick, M. Misiaszek, I. N. Machulin, I. N. Machulin, A. M. Goretti, A. Razeto, D. Korablev, S. Caprioli, Maurizio Canepa, Gioacchino Ranucci, Lothar Oberauer, J. Thurn, K. Choi, G. Bellini, Lino Miramonti, Cristiano Galbiati, E. V. Unzhakov, G. Testera, G. Zuzel, Manuel Meyer, D. D'Angelo, Caren Hagner, Xuefeng Ding, T. Houdy, F. Gabriele, Paolo Lombardi, Michele Magnozzi, Marco Pallavicini, Z. Bagdasarian, E. Litvinovich, E. Litvinovich, O. Smirnov, Alessandra Re, M. Goeger-Neff, L.F.F. Stokes, Aldo Ianni, N. Rossi, G. Bonfini, M. Gromov, Jay Burton Benziger, A. V. Derbin, E. V. Hungerford, Matthias Laubenstein, D. Jeschke, Marcin Wójcik, K. Altenmüller, L. Borodikhina, L. Di Noto, B. Opitz, D. Kryn, R. Roncin, Fausto Ortica, R. B. Vogelaar, G. Manuzio, D. A. Semenov, L. Papp, Frank Calaprice, F. Lombardi, B. Neumair, S. Davini, S. Weinz, S. Schönert, A. Jany, Matteo Agostini, D. Franco, M. Carlini, S. Marcocci, H. Wang, J. Martyn, Livia Ludhova, D. Basilico, B. Caccianiga, Marco Giammarchi, V. N. Muratova, I. S. Drachnev, Kai Zuber, V. Atroshchenko, Andrey Formozov, F. Froborg, A. Pocar, Sandra Zavatarelli, E. Meroni, G. Lukyanchenko, R. Tartaglia, Aldo Romani, A. Vishneva, C. Ghiano, A. Sotnikov, G. Korga, O. Zaimidoroga, Andrea Ianni, D. Bravo, A. Caminata, Y. Suvorov, Y. Suvorov, K. Fomenko, Z. Yokley, V. V. Kobychev, M. Toropova   +107 more
openaire   +11 more sources

Optimal Control Methods of Experiment Times in System-of-Systems Combat Computer Simulation [PDF]

ITM Web of Conferences, 2019
In the process of scheme optimization, in order to eliminate the influence of random factor, it needs to conduct computer simulation of Monte Carlo. Therefore, it is proposed to introduce confidence interval into systemof-systems combat simulation, and ...
Zhao Zhiqiang, Zhou Feiyue
doaj   +1 more source

PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO

E-Jurnal Matematika, 2012
Value at Risk (VaR) is the maximum potential loss on a portfolio based on the probability at a certain time.  In this research, portfolio VaR values calculated from historical data and Monte Carlo simulation data.
WAYAN ARTHINI, KOMANG DHARMAWAN, LUH PUTU IDA HARINI   +2 more
doaj   +1 more source