Manual classification of errors of English-Slovak translation according to the classification introduced by Vilar et al. [1]. 50 sentences randomly selected from WMT 2011 test set [2] were translated by 3 MT systems described in [3] and MT errors were manually marked and classified. Reference translation is included.
References:
[1] David Vilar, Jia Xu, Luis Fernando D’Haro and Hermann Ney. Error Analysis of Machine Translation Output. In International Conference on Language Resources and Evaluation, pages 697-702. Genoa, Italy, May 2006.
[2] http://www.statmt.org/wmt11/evaluation-task.html
[3] Petra Galuščáková and Ondřej Bojar. Improving SMT by Using Parallel Data of a Closely Related Language. In Human Language Technologies - The Baltic Perspective - Proceedings of the Fifth International Conference Baltic HLT 2012, volume 247 of Frontiers in AI and Applications, pages 58-65, Amsterdam, Netherlands, October 2012. IOS Press. and This work has been supported by the grant Euro-MatrixPlus (FP7-ICT-2007-3-231720 of the EU and
7E09003 of the Czech Republic)
Manually ranked outputs of Czech-Slovak translations. Three annotators manually ranked outputs of five MT systems (Česílko, Česílko2, Google Translate and two Moses setups) on three data sets (100 sentences randomly selected from books, 100 sentences randomly selected from Acquis corpus and 50 first sentences from WMT 2010 test set). Ranking was applied in MT systems comparison in [1].
References:
[1] Ondřej Bojar, Petra Galuščáková, and Miroslav Týnovský. Evaluating Quality of Machine Translation from Czech to Slovak. In Markéta Lopatková, editor, Information Technologies - Applications and Theory, pages 3-9, September 2011 and This work has been supported by the grant Euro-MatrixPlus (FP7-ICT-2007-3-231720 of the EU and
7E09003 of the Czech Republic)
Biocrust sustainability relies on dew and rain availability. A study of dew and rain resources in amplitude and frequency and their evolution is presented from year 2001 to 2020 in southern Africa (Namibia, Botswana, South Africa) where many biocrust sites have been identified. The evaluation of dew is made from a classical energy balance model using meteorological data collected in 18 stations, where are also collected rain data. One observes a strong correlation between the frequency of dew and rain and the corresponding amplitudes. There is a general tendency to see a decrease in dew yield and dew frequency with increasing distance from the oceans, located west, east and south, due to decreasing RH, with a relative minimum in the desert of Kalahari (Namibia). Rain amplitude and frequency decreases when going to west and north. Short-term dew/rain correlation shows that largest dew yields clearly occur during about three days after rainfall, particularly in the sites where humidity is less. The evolution in the period corresponds to a decrease of rain precipitations and frequency, chiefly after 2010, an effect which has been cyclic since now. The effect is more noticeable towards north. An increase of dew yield and frequency is observed, mainly in north and south-east. It results in an increase of the dew contribution with respect to rain, especially after 2010. As no drastic changes in the distribution of biomass of biocrusts have been reported in this period, it is likely that dew should compensate for the decrease in rain precipitation. Since the growth of biocrust is related to dew and rain amplitude and frequency, future evolution should be characterized by either the rain cycle or, due to global change, an acceleration of the present tendency, with more dew and less rainfalls.
Topsoil field-saturated hydraulic conductivity, Kfs, is a parameter that controls the partition of rainfall between
infiltration and runoff and is a key parameter in most distributed hydrological models. There is a mismatch between the
scale of local in situ Kfs measurements and the scale at which the parameter is required in models for regional mapping.
Therefore methods for extrapolating local Kfs values to larger mapping units are required. The paper explores the feasibility
of mapping Kfs in the Cévennes-Vivarais region, in south-east France, using more easily available GIS data
concerning geology and land cover. Our analysis makes uses of a data set from infiltration measurements performed in
the area and its vicinity for more than ten years. The data set is composed of Kfs derived from infiltration measurements
performed using various methods: Guelph permeameters, double ring and single ring infiltrotrometers and tension infiltrometers.
The different methods resulted in a large variation in Kfs up to several orders of magnitude. A method is proposed
to pool the data from the different infiltration methods to create an equivalent set of Kfs. Statistical tests showed
significant differences in Kfs distributions in function of different geological formations and land cover. Thus the mapping
of Kfs at regional scale was based on geological formations and land cover. This map was compared to a map based
on the Rawls and Brakensiek (RB) pedotransfer function (mainly based on texture) and the two maps showed very different
patterns. The RB values did not fit observed equivalent Kfs at the local scale, highlighting that soil texture alone is
not a good predictor of Kfs.