Generolo Jono Žemaičio Lietuvos karo akademija

This study evaluates the translation capabilities of selected AI language models in a defence and security context through a multistage multilingual workflow combining translation, language identification, and back-translation. Using 32 English inputs across eight target languages, the study compares offline and online models in terms of translation quality, processing stability, and task performance across varying levels of sentence complexity. The findings indicate that all models perform strongly on basic translation tasks, but notable differences emerge in language identification, back-translation quality, and output stability. The results help clarify the conditions under which AI translation can support security-relevant multilingual workflows.

This study analyses how soldier motivation differs between peacetime and combat security contexts. A structured review of 28 peer‑reviewed studies (2003–2025) from European and North American armed forces shows that peacetime motivation is driven mainly by belonging, prosocial values, and career development, while combat motivation relies on unit cohesion, trust in leadership, and mission meaning. Soldier motivation is thus dynamic, multidimensional, and context‑dependent. The findings support personnel policy, leadership development, and retention in defence organisations.

The present article examines the implementation of small unmanned aerial systems into tactical units of the Czech Armed Forces, with a focus on the systemic capabilities that such integration brings to the areas of doctrine, organization, training, equipment, leadership, personnel, facilities and infrastructure, and interoperability. Systematic reviews and structured qualitative coding are used to derive implementation measures, which are then validated by field and academic experts and prioritized. The findings indicate that priorities extend across all domains and must inform Czech Armed Forces processes and procedures.