Best from Around the Globe features the Best Paper awardees of MODSIM World and IT2EC. Each of the winners was selected by a committee and criteria specific to the particular global conference focus and theme. Come hear the award winners offer their outstanding presentations from these prestigious international conferences. MODSIM World 2023 Best Paper Using Machine Learning for Defect Characterization Victoria Gerardi, Operations Research Analyst, DEVCOM-Armaments Center Antonio Aguirre, DEVCOM- Armaments Center This paper presents a methodology that is under development to analyze large X-ray image datasets for anomaly and/or defect detection using machine learning techniques. The characterization of anomalies and/or defects can be identified through the performance accuracy of either image classification (supervised learning - convolutional neural networks) or anomaly detection (unsupervised learning - autoencoders) models. Each learning technique has unique hyperparameters and design architectures to aid in creating a robust model to predict against X-ray images of varying orientations, brightness and contrast. This method would be a strong complement to the traditional suite of energetic material/component characterization tests, particularly for melt-pour explosives, performance-related design intent, safety, and/or performance-related defect detection. For safety or performance-related defect detection, the methodology enables baselining defects as a feedback loop in the development of new subscale tests and physics-based models to better understand and predict energetic failure modes, a capability under development at DEVCOM Armament Center called Energetic Defect Characterization (EDC). IT2EC 2023 Best Paper VR for Public Safety Response Training Major Koen Ceulemans: Innovation Manager Land Component (TBC) Technology Advisor – 1LT Jeroen Nelis: Innovation Manager Belgian Federal Police (Limburg) – Subject Matter Expert XR Belgian Defence In 2009 a Belgian ship was highjacked by Somalian pirates. In a joint effort to resolve the situation, the special forces of both the Belgian Federal Police and the Belgian Defence trained together to enter the ship. To accomplish the mission, they made a real-life replica of the ship using wood and carton based on the blueprints of the ship. However, building this replica, took a lot of time. Time that could otherwise be spent training. This is why, in 2022 the Belgian military and police officially joined forces to build a proof of concept of a VR-training simulator that would make it possible to more quickly react to these kinds of situations. The aim of the simulator is to bring the interactions of the operators with the virtual environment as close to real life as possible. The collaboration between the police and