Generolo Jono Žemaičio Lietuvos karo akademija

This article examines the assessment of teaching of selected science and humanities undergraduate courses, some of which were taught remotely and others in person. In a questionnaire survey students compared face-to-face and distance learning of the subjects. The data were statistically processed using descriptive statistics, Mantel-Haenszel test of linear association, Pearson chi-square goodness-of-fit test, and finally cluster analysis. According to the opinion of most students, distance learning was comparable to face-to-face learning. When the respondents were divided into clusters, two comparable groups emerged—one preferring face-to-face learning, the other preferring distance learning. Humanities subjects showed to be less time-consuming and yielding better final grades for the students.

This study evaluates the spatial uniformity of minefields established by different minelaying methods using discrepancy-based metrics. Scatterable, row-based, and quasi-random layouts were compared in a common 200 × 200 m area for mine counts of 60, 120, and 180. Spatial quality was assessed using star discrepancy and 𝐿2-star discrepancy. The results showed that scatterable minefields achieved the highest discrepancy values, while row-based layouts performed substantially better. The most favorable results were obtained for quasi-random layouts generated by the Halton and Hammersley sequences, with the Hammersley sequence producing the lowest discrepancy overall. The findings support the use of discrepancy as an objective tool for evaluating UAV-assisted minelaying.

This article focuses on modeling the spread of disinformation narratives on social media using the SEDPNR epidemiological model, an extension of the basic SEIR model that takes into account the specifics of digital communication. This includes the existence of a "doubt" phase and the division of active users according to their sentiment polarity. The analyzed data describe a specific disinformation narrative, “Biolabs Ukraine,” that spread in connection with the Russian invasion of Ukraine. The results demonstrate that the dissemination of the narrative exhibits characteristics of an infodemic wave: a rapid increase, a brief peak, and a subsequent decline. The analysis confirms the significant role of active users and shows that supportive and critical reactions both contribute to the further dissemination of content.

The military university type of education in the Czech Republic is provided by the University of Defence. As other universities, it has to deal with students prematurely leaving their studies. We have collected available data to assess students’ dropout rate. Using parametric and nonparametric methods, we identified that the highest leaving rate occurs during the first study year reaching a maximum after five and a half months from the studies beginning, then it gradually slows down. We assume that our results can help the academics and commanders to make timely decision and positively encourage the students in their studies.