This Coastal and Hydraulic Engineering Technical Note (CHETN) summarizes the state of understanding of the influence of grain size on surf zone sediment transport and is a companion to Smith et al. (2004). This CHETN discusses details of bed-load and suspended load transport, and the classical bed-load regime is shown to encompass two distinct modes of transport. Four LST models with varying le...

In face processing tasks, prior presentation of internal facial features, when compared with external ones, facilitates the recognition of subsequently displayed familiar faces. In a previous ERP study (Olivares & Iglesias, 2010) we found a visibly larger N400-like effect when identity mismatch familiar faces were preceded by internal features, as compared to prior presentation of external ones...

This paper describes the methods we have employed to solve the author profiling task at PAN-2013. Our goal was to use simple features to identify the age group and the gender of the author of a given text. We introduce the features, detail how the classifiers were trained, and how the experiments were run.

      Dust storms are increasingly threatening the forest ecosystem in Western Iran. Due to its coverage of vast area of Zagros forest, the Quercus brantii is at the front line of the attack. Most tree deaths in this forest are from this species. This study aims to investigate the effect of simulated dust on wood development and leaf stomata from seedlings of Persian oak. The oak seedlings were...

biomedical datasets usually include a large number of features relative to the number of samples. however, some data dimensions may be less relevant or even irrelevant to the output class. selection of an optimal subset of features is critical, not only to reduce the processing cost but also to improve the classification results. to this end, this paper presents a hybrid method of filter and wr...

Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...