SAS-ORA Conference 2022

Author(s): Barros A.  

    |     ISSN: 3005-2092  

We are proud to bring you the first System Analysis and Studies (SAS) issue of the NATO STO Review – the peer reviewed Journal of the NATO Science and Technology Organization. This special edition contains a selection of the papers that were presented at the 16th NATO Operations Research & Analysis (OR&A) conference held at Frederiks Palace in Copenhagen, Denmark on 17-18 October 2022, including the one that was awarded the best paper distinction.

Author(s): Ekström T.;  

    |     ISSN: 3005-2092  

This paper presents the results from a Delphi study in which the researchers modified the design to enhance rigour. The study indicates that research design may influence the results of Delphi studies. Furthermore, the study suggests that there may be limitations to conventional designs, and possibilities with modified designs.

Author(s): Rempel M.; Shiell N.  

    |     ISSN: 3005-2092  

This article examined a MAJMAR scenario in which a large number of individuals, whose health stochastically deteriorates over time, are stranded at a remote location, and must be evacuated. Within this context, a multi-domain evacuation operation was examined, where individuals are evacuated either by air or sea, with the aim of the operation being to maximize the number of survivors.

Author(s): Rösch P. J.; Deuser F.; Habel K.; Oswald N.  

    |     ISSN: 3005-2092  

Cognitive superiority using artificial intelligence aims to extract relevant information from a huge amount of data to create military and non-military situational awareness. Reliable and timely interpretations of visual information are contributing factors to gain such superiority. With the rise of large-scale, multimodal deep learning models like Contrastive Language-Image Pre-training (CLIP), a promising type of neural network is emerging to perform such visual recognition tasks. This kind of network is able to extract knowledge from visual input by applying Optical Character Recognition (OCR), facial recognition, or object classification at once and without being explicitly fine-tuned. This zero-shot capability of CLIP is enabled by the choice of specific text prompts targeting the searched object within an image.