We introduce the use of Poincaré embeddings to improve existing state-of-the-art approaches to domain-specific taxonomy induction from text as a signal for both relocating wrong hyponym terms within a (pre-induced) taxonomy as well as for attaching disconnected terms in a taxonomy. This method substantially improves previous state-of-the-art results on the SemEval-2016 Task 13 on taxonomy extraction. We demonstrate the superiority of Poincaré embeddings over distributional semantic representations, supporting the hypothesis that they can better capture hierarchical lexical-semantic relationships than embeddings in the Euclidean space. 1 https://github.com/uhh-lt/Taxonomy_ Refinement_Embeddings

No abstract

Summary A solar photovoltaic panel accumulates substantial amount of heat, which deteriorates its performance. Thus, to minimize the panel temperature, 3 new designs (semioval serpentine, circular spiral, and circular spiral semiflattened) of absorbers for back surface cooling are introduced in this paper. Experimental investigations on the panel performances with and without the designed cooling systems are performed. A similar experiment with an existing serpentine design of absorbers is also conducted, and the results of all the experiments are compared. The circular spiral semiflattened design absorber has shown preeminent performance among all the absorbers in terms of the highest improvement in efficiency (4.32%), fill factor (19.80%), etc.

No abstract

No abstract