Los congresos internacionales de la lengua española

Desde 1997, con aparente periodicidad trienal, se celebra el Congreso Internacional de la Lengua Española (CILE) y en este documento se recogen las ideas más destacadas ofrecidas en los diferentes congresos a lo largo de los años. En todas sus ediciones expertos hispanistas y demás intelectuales discuten acerca de la lengua española, su situación actual, sus dilemas y sus desafíos de futuro. En su última edición, los debates han girado en torno al libro, en todos sus formatos, como herramienta de educación, de aprendizaje y de difusión del idioma español

Recognition rates with benchmark dataset.

<p>Recognition rates with benchmark dataset.</p

Tissue image datasets in IICBU 2008.

<p>Tissue image datasets in IICBU 2008.</p

Supramolecular Ferric Porphyrins as Cyanide Receptors in Aqueous Solution

All fundamental data about binding of the cyanide to a supramolecular complex composed of a per-<i>O</i>-methylated β-cyclodextrin dimer having an imidazole linker (Im3CD) and an anionic ferric porphyrin (Fe^(III)TPPS) indicate that the Fe^(III)TPPS/Im3CD complex is much better as an cyanide receptor in vivo than hydroxocobalamin, whose cyanide binding ability is lowered by its strong binding to serum proteins in the blood

Recognition rates in UCI machine leaning repository.

<p>The results for (a) <i>Satimage</i>, (b) <i>Shuttle</i>, (c) <i>Optdigits</i>, (d) <i>Pendigits</i>, and (e) <i>Isolet</i>. The lines show the classification accuracies in the transformed feature spaces for each method. The colors indicate the transformation methods, as shown in the legend.</p

Recognition rates with IICBU 2008 by calculating NN classifier.

<p>Recognition rates with IICBU 2008 by calculating NN classifier.</p

Recognition rates with MITOS-ATYPIA-14 by using GIST features.

<p>Recognition rates with MITOS-ATYPIA-14 by using GIST features.</p

Recognition rates in IICBU 2008 by using NN classifier.

<p>The results for (a) <i>Liver aging</i>, (b) <i>Liver gender (CR)</i>, and (c) <i>Liver gender (AL)</i>. The lines show the classification accuracies in the transformed feature spaces for each method. The colors indicate the feature transformation methods, as shown in the legend.</p

Examples of tissue images.

<p>(a) Tissue image for a 24-month-old female mouse on an ad libitum diet. (b) Tissue image for 6-month-old female mouse on a calorie-restricted diet.</p

Benchmark datasets for classification.

<p>Benchmark datasets for classification.</p