Neuroanatomy Learning: Augmented Reality vs. Cross-Sections

Neuroanatomy education is a challenging field which could benefit from modern innovations, such as augmented reality (AR) applications. This study investigates the differences on test scores, cognitive load, and motivation after neuroanatomy learning using AR applications or using cross-sections of the brain. Prior to two practical assignments, a pretest (extended matching questions, double-choice questions and a test on cross-sectional anatomy) and a mental rotation test (MRT) were completed. Sex and MRT scores were used to stratify students over the two groups. The two practical assignments were designed to study (1) general brain anatomy and (2) subcortical structures. Subsequently, participants completed a posttest similar to the pretest and a motivational questionnaire. Finally, a focus group interview was conducted to appraise participants’ perceptions. Medical and biomedical students (n = 31); 19 males (61.3%) and 12 females (38.7%), mean age 19.2 ± 1.7 years participated in this experiment. Students who worked with cross-sections (n = 16) showed significantly more improvement on test scores than students who worked with GreyMapp-AR (P = 0.035) (n = 15). Further analysis showed that this difference was primarily caused by significant improvement on the cross-sectional questions. Students in the cross-section group, moreover, experienced a significantly higher germane (P = 0.009) and extraneous cognitive load (P = 0.016) than students in the GreyMapp-AR group. No significant differences were found in motivational scores. To conclude, this study suggests that AR applications can play a role in future anatomy education as an add-on educational tool, especially in learning three-dimensional relations of anatomical structures.     

Symbolic Management of the Degree of Information Security by Integer Splitting

This paper demonstrates the application of module arithmetic for controlling the level of information security by a new technique referred as integer splitting. The basic definitions and concepts of the method are provided. The mathematical function of arising transformation is described in detail; its properties were studied and the basic theorems were proven that justify the use of splitting in practical applications. An active system was designed and characteristic cases of its operation are considered.     

Automatic path planning for an unmanned drone with constrained flight dynamics

In the article we solve path planning task for an agent being multirotor unmanned aerial vehicle (multicopter). We propose an approach of estimating path geometry constraints based on UAV flight dynamics model and control constraints. Than we introduce a new path finding method which takes into consideration those geometry constraints and study this method both theoretically and empirically.