University of Extremadura

About: University of Extremadura is a education organization based out in Badajoz, Spain. It is known for research contribution in the topics: Population & Hyperspectral imaging. The organization has 7856 authors who have published 18299 publications receiving 396126 citations. The organization is also known as: Universidad de Extremadura.

Semisupervised Hyperspectral Image Segmentation Using Multinomial Logistic Regression With Active Learning

Abstract: This paper presents a new semisupervised segmentation algorithm, suited to high-dimensional data, of which remotely sensed hyperspectral image data sets are an example. The algorithm implements two main steps: 1) semisupervised learning of the posterior class distributions followed by 2) segmentation, which infers an image of class labels from a posterior distribution built on the learned class distributions and on a Markov random field. The posterior class distributions are modeled using multinomial logistic regression, where the regressors are learned using both labeled and, through a graph-based technique, unlabeled samples. Such unlabeled samples are actively selected based on the entropy of the corresponding class label. The prior on the image of labels is a multilevel logistic model, which enforces segmentation results in which neighboring labels belong to the same class. The maximum a posteriori segmentation is computed by the α-expansion min-cut-based integer optimization algorithm. Our experimental results, conducted using synthetic and real hyperspectral image data sets collected by the Airborne Visible/Infrared Imaging Spectrometer system of the National Aeronautics and Space Administration Jet Propulsion Laboratory over the regions of Indian Pines, IN, and Salinas Valley, CA, reveal that the proposed approach can provide classification accuracies that are similar or higher than those achieved by other supervised methods for the considered scenes. Our results also indicate that the use of a spatial prior can greatly improve the final results with respect to a case in which only the learned class densities are considered, confirming the importance of jointly considering spatial and spectral information in hyperspectral image segmentation.

AUX1 Promotes Lateral Root Formation by Facilitating Indole-3-Acetic Acid Distribution between Sink and Source Tissues in the Arabidopsis Seedling

Abstract: Arabidopsis root architecture is regulated by shoot-derived signals such as nitrate and auxin. We report that mutations in the putative auxin influx carrier AUX1 modify root architecture as a result of the disruption in hormone transport between indole-3-acetic acid (IAA) source and sink tissues. Gas chromatography-selected reaction monitoring-mass spectrometry measurements revealed that the aux1 mutant exhibited altered IAA distribution in young leaf and root tissues, the major IAA source and sink organs, respectively, in the developing seedling. Expression studies using the auxin-inducible reporter IAA2::uidA revealed that AUX1 facilitates IAA loading into the leaf vascular transport system. AUX1 also facilitates IAA unloading in the primary root apex and developing lateral root primordium. Exogenous application of the synthetic auxin 1-naphthylacetic acid is able to rescue the aux1 lateral root phenotype, implying that root auxin levels are suboptimal for lateral root primordium initiation in the mutant.

Biodiesel from Used Frying Oil. Variables Affecting the Yields and Characteristics of the Biodiesel

Abstract: A study was performed of the transesterification reaction of used frying oil by means of methanol, using sodium hydroxide, potassium hydroxide, sodium methoxide, and potassium methoxide as catalysts. The objective of the work was to characterize the methyl esters for use as biodiesels in compression ignition motors. The operation variables used were methanol/oil molar ratio (3:1−9:1), catalyst concentration (0.1−1.5 wt %), temperature (25−65 °C), and catalyst type. Also, experiments in two stages of reaction, with separation of the glycerol in the first stage, were carried out. The evolution of the process was followed by gas chromatography, determining the concentration of the methyl esters at different reaction times. The biodiesel was characterized by its density, viscosity, high heating value, cetane index, cloud and pour points, characteristics of distillation, flash and combustion points, saponification value, and iodine value according to ISO norms. The biodiesel with the best properties was obtain...

Advanced Spectral Classifiers for Hyperspectral Images: A review

Abstract: Hyperspectral image classification has been a vibrant area of research in recent years. Given a set of observations, i.e., pixel vectors in a hyperspectral image, classification approaches try to allocate a unique label to each pixel vector. However, the classification of hyperspectral images is a challenging task for a number of reasons, such as the presence of redundant features, the imbalance among the limited number of available training samples, and the high dimensionality of the data.