Direct estimation wave setup as a medium level in swash

The extreme runup is a key parameter for a shore risk analysis in which the accurate and quantitative estimation of the upper limit reached by waves is essential. Runup can be better approximated by splitting the setup and swash semi-amplitude contributions. In an experimental study recording setup becomes difficult due to infragravity motions within the surf zone, hence, it would be desirable to measure the setup with available methodologies and devices. In this research, an analysis is made of evaluated the convenience of direct estimation setup as the medium level in the swash zone for experimental runup analysis through a physical model. A physical mobile bed model was setup in a wave flume at the Laboratory for Maritime Experimentation of CEDEX. The wave flume is 36 metres long, 6.5 metres wide and 1.3 metres high. The physical model was designed to cover a reasonable range of parameters, three different slopes (1/50, 1/30 and 1/20), two sand grain sizes (D50 = 0.12 mm and 0.70 mm) and a range for the Iribarren number in deep water (ξ0) from 0.1 to 0.6. Best formulations were chosen for estimating a theoretical setup in the physical model application. Once theoretical setup had been obtained, a comparison was made with an estimation of the setup directly as a medium level of the oscillation in swash usually considered in extreme runup analyses. A good correlation was noted between both theoretical and time-averaging setup and a relation is proposed. Extreme runup is analysed through the sum of setup and semi-amplitude of swash. An equation is proposed that could be applied in strong foreshore slope-dependent reflective beaches.

Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury

The number and grade of injured neuroanatomic structures and the type of injury determine the degree of impairment after a brain injury event and the recovery options of the patient. However, the body of knowledge and clinical intervention guides are basically focused on functional disorder and they still do not take into account the location of injuries. The prognostic value of location information is not known in detail either. This paper proposes a feature-based detection algorithm, named Neuroanatomic-Based Detection Algorithm (NBDA), based on SURF (Speeded Up Robust Feature) to label anatomical brain structures on cortical and sub-cortical areas. Themain goal is to register injured neuroanatomic structures to generate a database containing patient?s structural impairment profile. This kind of information permits to establish a relation with functional disorders and the prognostic evolution during neurorehabilitation procedures.

Traffic sign detection and tracking using robust 3D analysis

In this paper we present an innovative technique to tackle the problem of automatic road sign detection and tracking using an on-board stereo camera. It involves a continuous 3D analysis of the road sign during the whole tracking process. Firstly, a color and appearance based model is applied to generate road sign candidates in both stereo images. A sparse disparity map between the left and right images is then created for each candidate by using contour-based and SURF-based matching in the far and short range, respectively. Once the map has been computed, the correspondences are back-projected to generate a cloud of 3D points, and the best-fit plane is computed through RANSAC, ensuring robustness to outliers. Temporal consistency is enforced by means of a Kalman filter, which exploits the intrinsic smoothness of the 3D camera motion in traffic environments. Additionally, the estimation of the plane allows to correct deformations due to perspective, thus easing further sign classification.

Efficient hybrid monocular-stereo approach to on-board, video-based traffic sign detection and tracking

In this paper we propose an innovative method for the automatic detection and tracking of road traffic signs using an onboard stereo camera. It involves a combination of monocular and stereo analysis strategies to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. Firstly, an adaptive color and appearance based detection is applied at single camera level to generate a set of traffic sign hypotheses. In turn, stereo information allows for sparse 3D reconstruction of potential traffic signs through a SURF-based matching strategy. Namely, the plane that best fits the cloud of 3D points traced back from feature matches is estimated using a RANSAC based approach to improve robustness to outliers. Temporal consistency of the 3D information is ensured through a Kalman-based tracking stage. This also allows for the generation of a predicted 3D traffic sign model, which is in turn used to enhance the previously mentioned color-based detector through a feedback loop, thus improving detection accuracy. The proposed solution has been tested with real sequences under several illumination conditions and in both urban areas and highways, achieving very high detection rates in challenging environments, including rapid motion and significant perspective distortion

Fast 2D to 3D conversion using a clustering-based hierarchical search in a machine learning framework

Automatic 2D-to-3D conversion is an important application for filling the gap between the increasing number of 3D displays and the still scant 3D content. However, existing approaches have an excessive computational cost that complicates its practical application. In this paper, a fast automatic 2D-to-3D conversion technique is proposed, which uses a machine learning framework to infer the 3D structure of a query color image from a training database with color and depth images. Assuming that photometrically similar images have analogous 3D structures, a depth map is estimated by searching the most similar color images in the database, and fusing the corresponding depth maps. Large databases are desirable to achieve better results, but the computational cost also increases. A clustering-based hierarchical search using compact SURF descriptors to characterize images is proposed to drastically reduce search times. A significant computational time improvement has been obtained regarding other state-of-the-art approaches, maintaining the quality results.

Appropiate locations for geotextile bag revetments: an analysis

Social pressure exerted by urban development, the increase in erosion on many coastal stretches, and the rise in sea level due to climate change over the last few decades have led governments to increase investment in coastal protection. In turn, a reduction in costs and increases in ease of construction and rate of implementation have led to sand-filled geotextile elements, such as bags, tubes, and containers, becoming an alternative or supplement to traditional coastal defence materials, such as rubble mounds, concrete, and so on. Not all coastal zones are appropriate for sand-filled geotextile structures as coastal defences. This article analyses suitable zones for locating geotextile bag revetments to protect coasts from storm erosion and concludes that the least suitable zones are the surf zone (on an open coast and on a slightly protected coast) and deep water (on an open coast), except if a suitable reinforcement is carried out when the demand makes it necessary this build this kind of defence.

Methods and Techniques for Segmentation of Consumers in Social Media

Los medios sociales han revolucionado la manera en la que los consumidores se relacionan entre sí y con las marcas. Las opiniones publicadas en dichos medios tienen un poder de influencia en las decisiones de compra tan importante como las campañas de publicidad. En consecuencia, los profesionales del marketing cada vez dedican mayores esfuerzos e inversión a la obtención de indicadores que permitan medir el estado de salud de las marcas a partir de los contenidos digitales generados por sus consumidores. Dada la naturaleza no estructurada de los contenidos publicados en los medios sociales, la tecnología usada para procesar dichos contenidos ha menudo implementa técnicas de Inteligencia Artificial, tales como algoritmos de procesamiento de lenguaje natural, aprendizaje automático y análisis semántico. Esta tesis, contribuye al estado de la cuestión, con un modelo que permite estructurar e integrar la información publicada en medios sociales, y una serie de técnicas cuyos objetivos son la identificación de consumidores, así como la segmentación psicográfica y sociodemográfica de los mismos. La técnica de identificación de consumidores se basa en la huella digital de los dispositivos que utilizan para navegar por la Web y es tolerante a los cambios que se producen con frecuencia en dicha huella digital. Las técnicas de segmentación psicográfica descritas obtienen la posición en el embudo de compra de los consumidores y permiten clasificar las opiniones en función de una serie de atributos de marketing. Finalmente, las técnicas de segmentación sociodemográfica permiten obtener el lugar de residencia y el género de los consumidores. ABSTRACT Social media has revolutionised the way in which consumers relate to each other and with brands. The opinions published in social media have a power of influencing purchase decisions as important as advertising campaigns. Consequently, marketers are increasing efforts and investments for obtaining indicators to measure brand health from the digital content generated by consumers. Given the unstructured nature of social media contents, the technology used for processing such contents often implements Artificial Intelligence techniques, such as natural language processing, machine learning and semantic analysis algorithms. This thesis contributes to the State of the Art, with a model for structuring and integrating the information posted on social media, and a number of techniques whose objectives are the identification of consumers, as well as their socio-demographic and psychographic segmentation. The consumer identification technique is based on the fingerprint of the devices they use to surf the Web and is tolerant to the changes that occur frequently in such fingerprint. The psychographic profiling techniques described infer the position of consumer in the purchase funnel, and allow to classify the opinions based on a series of marketing attributes. Finally, the socio-demographic profiling techniques allow to obtain the residence and gender of consumers.

Strong natural selection causes microscale allozyme variation in a marine snail.

Natural selection is one of the most fundamental processes in biology. However, there is still a controversy over the importance of selection in microevolution of molecular traits. Despite the general lack of data most authors hold the view that selection on molecular characters may be important, but at lower rates than selection on most phenotypic traits. Here we present evidence that natural selection may contribute substantially to molecular variation on a scale of meters only. In populations of the marine snail Littorina saxatilis living on exposed rocky shores, steep microclines in allele frequencies between splash and surf zone groups are present in the enzyme aspartate aminotransferase (allozyme locus Aat; EC. 2.6.1.1). We followed one population over 7 years, including a period of strong natural perturbation. The surf zone part of the population dominated by the allele Aat100 was suddenly eliminated by a bloom of a toxin-producing microflagellate. Downshore migration of splash zone snails with predominantly Aat120 alleles resulted in a drastic increase in surf zone frequency of Aat120, from 0.4 to 0.8 over 2 years. Over the next four to six generations, however, the frequency of Aat120 returned to the original value. We estimated the coefficient of selection of Aat120 in the surf zone to be about 0.4. Earlier studies show similar or even sharper Aat clines in other countries. Thus, we conclude that microclinal selection is an important evolutionary force in this system.

Comparativa de detectores de características visuales y su aplicación al SLAM

Comunicación presentada en el X Workshop of Physical Agents, Cáceres, 10-11 septiembre 2009.

Large scale SLAM with visual features

Comunicación presentada en el X Workshop of Physical Agents, Cáceres, 10-11 septiembre 2009.

Ground-based electromagnetic (EM) and drill-hole ice and snow thickness measurements during Polarstern cruise ARK-XVII/2 in 2001

Late-summer thickness distributions of large ice floes in the Transpolar Drift between Svalbard and the North Pole in 1991, 1996, 1998, and 2001 are compared. They have been derived from drilling and electromagnetic (EM) sounding. Results show a strong interannual variability, with significantly reduced thickness in 1998 and 2001. The mean thickness decreased by 22.5% from 3.11 m in 1991 to 2.41 m in 2001, and the modal thickness by 22% from 2.50 m in 1991 to 1.95 m in 2001. Since modal thickness represents the thickness of level ice, the observed thinning reflects changes in thermodynamic conditions. Together with additional data from the Laptev Sea obtained in 1993, 1995, and 1996, results are in surprising agreement with recently published thickness anomalies retrieved from satellite radar altimetry for Arctic regions south of 81.5°N. This points to a strong sensitivity of radar altimetry data to level ice thickness.

Tylotus ecuadoriensis; Gracilariaceae

Gracilaria ecuadoriensis (Taylor) Dawson

Transport of dredged sediment placed in the nearshore zone--Currituck sand-bypass study (phase I) /

New dredge-disposal techniques may serve the dual role of aiding sand by-passing across coastal inlets, and beach nourishment, provided the dredged sediments placed seaward of the surf zone move shoreward into that zone. During the summer of 1976, 26,750 cubic meters of relatively coarse sediment was dredged from New River Inlet, North Carolina, moved down coast by a split-hull barge, and placed in a 215-meter coastal reach between the 2- and 4-meter depth contours. Bathymetric changes on the disposal piles and in the adjacent beach and nearshore area were studied for a 13-week period (August to November 1976) to determine the modification of the surrounding beach and nearshore profile, and the net transport direction of the disposal sediment. The sediment piles initially created a local shoal zone with minimum depths of 0.6 meter. Disposal sediment was coarser (Mn = 0.49 millimeter) than the native sand at the disposal site (Mn = 0.14 millimeter) and coarser than the composite mean grain size of the entire profile (Mn = 0.21 millimeter). Shoaling and breaking waves caused rapid erosion of the pile tops and a gradual coalescing of the piles to form a disposal bar located seaward (= 90 meters) of a naturally occurring surf zone bar. As the disposal bar relief was reduced, the disposal bar-associated breaker zone was restricted to low tide times or periods of high wave conditions.