The large-distance penetration capability of an annular-shaped charge under multipoint synchronous initiation was experimentally investigated. For different annular structures and settings, incident angle, collision type detonation waves, overpressure on the shaped charge’s liner at adjacent points were analyzed using wave propagation theory. Furthermore, a standoff distance 1–15 m from 20 mm t...

Collaborative reflection helps groups to learn from work experiences for future work. Although its potential has been recognized and initial work is available, insights on how tools support people in collaborative reflection at work are scarce. We present an approach to analyze collaborative reflection support based on content analysis and an initial study in which it was applied to four cases ...

Abstract Knowledge distillation is a simple yet effective technique for deep model compression, which aims to transfer the knowledge learned by large teacher small student model. To mimic how teaches student, existing methods mainly adapt an unidirectional transfer, where extracted from different intermedicate layers of used guide However, it turns out that students can learn more effectively t...

The present paper concerns with the effect of initial stress on the propagation of plane waves in a rotating transversely isotropic medium in the context of thermoelasticity theory of GN theory of type-II and III. After solving the governing equations, three waves propagating in the medium are obtained. The fastest among them is a quasi-longitudinal wave. The slowest of them is a thermal wave. ...

Winner-Take-All (WTA) networks. in which inhibitory interconnections are used to determine the most highly-activated of a pool of unilS. are an important part of many neural network models. Unfortunately, convergence of normal WT A networks is extremely sensitive to the magnitudes of their weights, which must be hand-tuned and which generally only provide the right amount of inhibition across a...

The statistical physics of off-learning is applied to Winner-Takes-All and rank-based vector quantization (VQ), including the Neural Gas (NG). The analysis is based on the limit of high training temperatures and the annealed approximation. The typical learning behavior is evaluated for systems of two and three prototypes with data drawn from a mixture of high dimensional Gaussian clusters. The ...