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Grosse Mirco,Boldt Felix,Herm Michel,Roessger Conrado,Stuckert Juri,Weick Sarah,Nahm Daniel 한국원자력학회 2024 Nuclear Engineering and Technology Vol.56 No.3
In order to investigate the occurring processes during long-term dry storage of spent fuel assemblies, a joined project called SPIZWURZ, between the Karlsruhe Institute of Technology and the Gesellschaft für Anlagen-und Reaktorsicherheit (GRS), was started. Aim of the SPIZWURZ project is the determination and quantification of the influence of texture and elastic strain on diffusion and solubility of hydrogen in three different zirconium alloys used in western Europe during a long-term cooling transient (1 K/d) starting at 400 ◦C. The strain in the cladding of an irradiated spent fuel rod shall be measured. Models predicting the formation of radial oriented hydrides will be validated, improved, and implemented in the GRS fuel rod performance code TESPA-ROD. This paper describes the SPIZWURZ project and already obtained first results.
Ortiz, Adrielly Garcia,Soares, Gustavo Hermes,da Rosa, Gabriela Cauduro,Biazevic, Maria Gabriela Haye,Michel-Crosato, Edgard Korean Academy of Oral and Maxillofacial Radiology 2021 Imaging Science in Dentistry Vol.51 No.2
Purpose: This study aimed to assess the usefulness of machine learning and automation techniques to match pairs of panoramic radiographs for personal identification. Materials and Methods: Two hundred panoramic radiographs from 100 patients (50 males and 50 females) were randomly selected from a private radiological service database. Initially, 14 linear and angular measurements of the radiographs were made by an expert. Eight ratio indices derived from the original measurements were applied to a statistical algorithm to match radiographs from the same patients, simulating a semi-automated personal identification process. Subsequently, measurements were automatically generated using a deep neural network for image recognition, simulating a fully automated personal identification process. Results: Approximately 85% of the radiographs were correctly matched by the automated personal identification process. In a limited number of cases, the image recognition algorithm identified 2 potential matches for the same individual. No statistically significant differences were found between measurements performed by the expert on panoramic radiographs from the same patients. Conclusion: Personal identification might be performed with the aid of image recognition algorithms and machine learning techniques. This approach will likely facilitate the complex task of personal identification by performing an initial screening of radiographs and matching ante-mortem and post-mortem images from the same individuals.