Výsledky vyhledávání - "Tzany Kokalova"

Akademický článek

A feasibility study using an array of LaBr3(Ce) scintillation detectors as a Compton camera for prompt gamma imaging during BNCT

Autor: Kiran Nutter, Tony Price, Tzany Kokalova, Stuart Green, Ben Phoenix

Publikováno v: Frontiers in Physics, Vol 12 (2024)

Boron Neutron Capture Therapy (BNCT) is a binary cancer therapy where a low energy neutron beam is incident upon a patient who has been administered a tumour-seeking 10B loaded compound. The neutron capture reaction on 10B results in the production o

Externí odkaz: https://doaj.org/article/6ee8c3c1ff4040198a1d3e5c757849b4

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Akademický článek

Monte Carlo Model of the Large Modular Array for Positron Emission Particle Tracking

Autor: Matthew Herald, Dawid Hampel, Tzany Kokalova Wheldon, Jonathan Seville, Christopher Windows-Yule

Publikováno v: IEEE Access, Vol 11, Pp 25982-25990 (2023)

Positron emission particle tracking (PEPT) is a non-invasive technique used to study fluid, granular, and multi-phase systems of interest to academia and industry. PEPT employs position-sensitive radiation detectors to record gamma rays in coincidenc

Externí odkaz: https://doaj.org/article/98d459c298044efc92d2107005e74023

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Akademický článek

Autonomous digitizer calibration of a Monte Carlo detector model through evolutionary simulation

Autor: Matthew Herald, Andrei Nicuşan, Tzany Kokalova Wheldon, Jonathan Seville, Christopher Windows-Yule

Publikováno v: Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)

Abstract Simulating the response of a radiation detector is a modelling challenge due to the stochastic nature of radiation, often complex geometries, and multi-stage signal processing. While sophisticated tools for Monte Carlo simulation have been d

Externí odkaz: https://doaj.org/article/186a7a4643064c2ca572468be0c55844

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Akademický článek

Convolutional Neural Networks for Challenges in Automated Nuclide Identification

Autor: Anthony N. Turner, Carl Wheldon, Tzany Kokalova Wheldon, Mark R. Gilbert, Lee W. Packer, Jonathan Burns, Martin Freer

Publikováno v: Sensors, Vol 21, Iss 15, p 5238 (2021)

Improvements in Radio-Isotope IDentification (RIID) algorithms have seen a resurgence in interest with the increased accessibility of machine learning models. Convolutional Neural Network (CNN)-based models have been developed to identify arbitrary m

Externí odkaz: https://doaj.org/article/9d21894fdaf24269b960f5df61615bf3

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