Improving undergraduate engineering students’ figural spatial ability through digital brain-training game

Undergraduate engineering students often struggle in mastering engineering course contents. Although introductory engineering courses were extensively taught, it was deemed not enough, especially in graphic expression since it requires high levels of spatial ability. Moreover, spatial ability is acquired beyond formal learning through leisure training and not explicitly taught. Thus, a digital brain training game i.e. Cubes Spatial Reasoning FREE (CSR) was used in this study in attempt to improve figural spatial ability. The purpose of this study was to evaluate the impact of the use of CSR on figural spatial ability of undergraduate engineering students in terms of mental rotation and spatial orientation. 30 undergraduate engineering students were selected using purposive sampling method. Mental Rotation Test (MRT) was used to measure mental rotation and Spatial Orientation Test (SOT) was used to measure spatial orientation. Findings indicated that CSR significantly improved figural spatial ability in terms of mental rotation and spatial orientation. In conclusion, as indicated in this preliminary study, CSR may be used as a training tool to potentially improve mental rotation and spatial orientation in undergraduate engineering students

Entropy function and higher derivative corrections to entropies in (anti-)de Sitter space

We first briefly discuss the relation between black hole thermodynamics and the entropy function formalism. We find that an equation which governs the relationship between Sen's entropy function and black hole entropy, can quickly give higher order corrections to entropy of pure (anti-) de Sitter space without knowing the corrected metric. We also show that near horizon geometry and the entropy function extremization is no longer required for pure (anti-)de Sitter space. The entropy of (anti-)de Sitter space and Schwarzschild-(anti-) de Sitter black holes together with Gauss-Bonnet terms, $R^2$ terms and $R^4$ terms are calculated as concrete examples.Comment: 24 pages, contents improved, typos corrected, references adde

A Descriptive Model of Robot Team and the Dynamic Evolution of Robot Team Cooperation

At present, the research on robot team cooperation is still in qualitative analysis phase and lacks the description model that can quantitatively describe the dynamical evolution of team cooperative relationships with constantly changeable task demand in Multi-robot field. First this paper whole and static describes organization model HWROM of robot team, then uses Markov course and Bayesian theorem for reference, dynamical describes the team cooperative relationships building. Finally from cooperative entity layer, ability layer and relative layer we research team formation and cooperative mechanism, and discuss how to optimize relative action sets during the evolution. The dynamic evolution model of robot team and cooperative relationships between robot teams proposed and described in this paper can not only generalize the robot team as a whole, but also depict the dynamic evolving process quantitatively. Users can also make the prediction of the cooperative relationship and the action of the robot team encountering new demands based on this model. Journal web page & a lot of robotic related papers www.ars-journal.co