The representativeness threshold for the CETA subcorpus of the Coruña Corpus

The concept of representativeness is the main distinguishing characteristic of specialised corpora in comparison to other sets of texts. The Coruña Corpus of English Scientific Writing currently comprises four published subcorpora (astronomy, life sciences, history, and philosophy) plus three others under compilation (physics, chemistry and linguistics). In this paper we aim to assess the lexical density of the text samples in CETA, the Corpus of English Texts on Astronomy, by means of the ReCor tool, a posteriori. The study is motivated by the following question: does quantitative representativeness analysis using ReCor provide, in the form of a cross-check, further validation of previous research on the representativeness of CETA? Previous work (Crespo and Moskowich, 2010) has indicated that the CETA corpus is well designed and valid for the purposes for which it was intended. We will here suggest metrics to measure these findings. The most important contribution of this study is to offer quantitative data collection results using the ReCor tool, which allows data triangulation and consequently ensures overall data quality. Results show that data analysis with the ReCor tool supports previous findings, and thus we are able to verify that CETA is indeed representative of the language of its time and register.

On the Portrait of the Russian Professional Psychological Community: Sparkles of Reality on the Official Tailcoat

The main distinguishing characteristic of SRI GEP is the atmosphere of comeradery, mutual support, youth's admiration for the older generation and respectful, almost touching care for this youth on the part of the "elders". Now for me it is absolutely obvious that maintaining such an atmosphere would have been impossible if the institute had not possess such an astonishingly and professionally top-level group of "elders".

The Gray World of Practical Data Analysis: An Introduction to Part 2

This chapter provides an overview of the second part of the book. This part is the crux of the matter: how to analyze actual data. While this part builds on Part 1, especially on linear algebra fundamentals covered in Part 1, the two are not redundant. The main distinguishing characteristic of Part 2 is its nuanced grayness. In the ideal world of algebra (and thus in most of part 1), things are black or white: two vectors are either mutually orthogonal or not, real numbers are either zero or not, a vector either solves a linear system or does not. By contrast, realistic data analysis, the province of Part 2, is always gray, always involves subjective decisions.

Dynamic Reconfigurable NoC (DRNoC) Architecture

The aim of this Chapter is to present a highly flexible reconfigurable NoC solution for commercial FPGAs on one side, and on the other side, to provide an innovative approach for fast NoC emulation. The reconfigurable on-chip communication solution that is proposed in this chapter is capable of being reconfigured by means of adapting routers, network interfaces and cores themselves. The main distinguishing characteristic of the presented on-chip communication approach is that it permits to distribute the available on-chip communication resources among different communication topologies and thus, independent and application specific communication strategies can coexist and run in parallel. Furthermore, the proposed solution is not limited to NoCs and it permits to build a vari ety of on-chip communication. The proposed method in this Chapter for fast emulation provides a rapid way of validating different communication alternatives. The emulation method is based on the original idea of hard core re-usability through the exploitation of partial reconfiguration capabilities of some state of the art FPGAs. Both aspects have been tested and validated using a proof of concept approach and are discussed along this Chapter.