Tunis University

About: Tunis University is a education organization based out in Tunis, Tunisia. It is known for research contribution in the topics: Population & Thin film. The organization has 11745 authors who have published 15400 publications receiving 154900 citations. The organization is also known as: University of Tunis & UT.

Physical Activity during a Prolonged Congested Period in a Top-Class European Football Team.

Abstract: PURPOSE: The aim of the present study was to examine the variation in physical activity of elite soccer players within successive prolonged periods of fixture congestion over 5 months of competition during the competitive season 2011-2012. METHODS: Sixteen international players, classified into 6 positions (central defenders: CD; full-backs: FB; central defensive midfielders: CDM; wide midfielders: WM; central attacking midfielders: CAM; forwards: FW), were examined during the French First League, French Cup, and UEFA Champion's League matches. The total distance covered at light (18-21 km.h(-1)), high (>21-23 km.h(-1)), very high (>23-25 km.h(-1)), sub-maximal (>25-27 km.h(-1)), and maximal (>27 km.h(-1)) intensity running (IR) were measured and analysed using a semi-automatic match analysis system (Amisco Pro™). RESULTS: No differences were observed between congested and non-congested periods (two vs. one match a week, respectively) for the total distance covered at all the speed thresholds over 18 km.h(-1), with no variation in physical fitness over the 5 studied months. Specifically to the playing positions, regardless of the congestion periods, FB and WM covered more distance than CDM over 21km.h(-1); FB, WM and FW covered similar distances for all running intensities; and CD and CDM covered shorter distance during non-congested compared to congested periods (PCONCLUSION: The present study reveals that prolonged congested match fixture did not affect the high-intensity physical activity of top-class soccer players during official games during a 5 months fixture period. Language: en

A hybrid approach for Arabic multi-word term extraction

Abstract: Building a domain model from a specialized corpus requires identifying candidate terms. It also includes identifying semantic relations between terms. Once this model is constructed it can be used for many tasks of information retrieval. In this process, multi-word terms have a great importance. In the one hand they constitute domain relevant candidate terms. On the other hand syntactic relations that link their constituents can be used to infer semantic relations between terms. In this paper we propose to extract mutli-word terms from Arabic specialized corpora. The proposed approach uses linguistic rules based on morphological features and POS (Part Of Speech) tags to parse documents and retrieve candidate terms. Statistical measures are used to deal with ambiguities generated by the linguistic tools and to rank candidate terms according to their relevance. We present experiments on a corpus from the environment domain. We report high quality results that are confirm the targets set for the precision metric.