Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Mert Şekerci

Showing results (1-10 of 6) with videos related to

Pageof 1
Sort By:
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|December 12, 2022
Estimations for (n,α) reaction cross sections at around 14.5MeV using Levenberg-Marquardt algorithm-based artificial neural networkHasan Özdoğan, Yiğit Ali Üncü, Mert Şekerci, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|January 12, 2021
Estimations of level density parameters by using artificial neural network for phenomenological level density modelsHasan Özdoğan, Yiğit Ali Üncü, Mert Şekerci, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|July 6, 2023
Calculation of double differential neutron cross-sections of <sup>56</sup>Fe and <sup>90</sup>Zr isotopesHasan Özdoğan, Yiğit Ali Üncü, Mert Şekerci, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|November 25, 2023
Neural network predictions of (α,n) reaction cross sections at 18.5±3 MeV using the Levenberg-Marquardt algorithmHasan Özdoğan, Yiğit Ali Üncü, Mert Şekerci, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|January 10, 2021
Estimations of giant dipole resonance parameters using artificial neural networkHasan Özdoğan, Yiğit Ali Üncü, Onur Karaman, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|January 28, 2026
Artificial Neural Network-Based prediction of production cross sections of the medical radioisotopes <sup>67</sup>Ga and <sup>89</sup>ZrMurat Okutan, Yiğit Ali Üncü, Gençay Sevim, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|December 12, 2022
Estimations for (n,α) reaction cross sections at around 14.5MeV using Levenberg-Marquardt algorithm-based artificial neural networkHasan Özdoğan, Yiğit Ali Üncü, Mert Şekerci, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|January 12, 2021
Estimations of level density parameters by using artificial neural network for phenomenological level density modelsHasan Özdoğan, Yiğit Ali Üncü, Mert Şekerci, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|July 6, 2023
Calculation of double differential neutron cross-sections of <sup>56</sup>Fe and <sup>90</sup>Zr isotopesHasan Özdoğan, Yiğit Ali Üncü, Mert Şekerci, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|November 25, 2023
Neural network predictions of (α,n) reaction cross sections at 18.5±3 MeV using the Levenberg-Marquardt algorithmHasan Özdoğan, Yiğit Ali Üncü, Mert Şekerci, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|January 10, 2021
Estimations of giant dipole resonance parameters using artificial neural networkHasan Özdoğan, Yiğit Ali Üncü, Onur Karaman, et al.
Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine|January 28, 2026
Artificial Neural Network-Based prediction of production cross sections of the medical radioisotopes <sup>67</sup>Ga and <sup>89</sup>ZrMurat Okutan, Yiğit Ali Üncü, Gençay Sevim, et al.
Pageof 1