Table 3 Articles related to protection, control, and PPE
Author | Year | Type of study | The purpose of the study | Application intelligence tools | Outcome | Quality assessment | Ref | |
|---|---|---|---|---|---|---|---|---|
Score | Quality | |||||||
Kimura, Yoshitaka | 1990 | Modeling study | Radiation control, development of an expert system for the transfer of radioactive materials with a programming language | UTI-LISP Programming Language | Rationalization of interpretations and judgments for the transportation of radioactive materials | 0.8 | Strong | [64]a |
Al-Mubaid, H | 2012 | Modeling study | A model for extracting material properties for radiation protection | Machine learning | Identifying the most important properties related to the radiation shielding ability of materials is quite effective | 0.8 | strong | [65] |
Duckic, P | 2018 | Modeling study | The sum of the factors creating equivalent environmental dose for Portland concrete | Machine learning | The sum of the factors creating the environment dose equivalent for Portland concrete slabs is calculated using the software | 0.8 | strong | [66] |
Chen, S | 2020 | Modeling study | An approach to ensure the correct use of PPE in decommissioning the Fukushima nuclear power plant | Deep learning | A proposal to identify the correct use of hard hats and full-face masks | 0.7 | moderate | [67] |
Piron, L | 2021 | Modeling study | Progress in preparing instantaneous control schemes for deuterium–tritium operations at JET | Machine learning | This paper deals with isotope ratio controllers to support nuclear fusion processes | 0.8 | strong | [68] |
Tokatli, O | 2021 | Modeling study | Introducing advanced technologies to glove boxes | Robotics and artificial intelligence | Minimize human exposure to hazards | 0.8 | strong | [69] |
Hou, T. Y | 2022 | Modeling study | Customization of orbital angular motion beams | Deep Learning | A useful reference on intelligent control of laser array systems for customizing light beams | 0.7 | moderate | [70] |
Zhu, E. Z | 2022 | Modeling study | Protection against electromagnetic radiation (EM) due to its high spatial filter performance | Deep Learning | Frequency Selective Surface Inverse Design | 0.8 | strong | [71] |
Piron, L | 2023 | Modeling study | A phased approach strategy towards radiation control | Machine learning | Radiation control in deuterium, tritium, and deuterium–tritium JET base plasmas | 0.7 | Moderate | [72] |
Han, H | 2024 | Modeling study | Microscopic tuning of high-performance electromagnetic response mechanism of fiber-based flexible absorbers | Artificial intelligence (AI) | Enhancing the high-frequency electromagnetic damping response of flexible fiber-based wearable absorbers | 0.8 | strong | [73] |