Textural classification of land cover using support vector machines: an empirical comparison with parametric, non parametric and hybrid classifiers in the Bolivian Amazon

Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

Aplicació de visió per dispositius mòbils

En aquest projecte es presenta l’aplicació per a dispositius mòbils Doppelganger. La seva funció és, a partir d’una fotografia, detectar la cara i mostrar la persona famosa de la nostra base de dades que més s’assembla a la persona en la fotografia. Per la implementació s’han utilitzat algoritmes de visió per computador i d’aprenentatge automàtic com per exemple el PCA i el K-Nearest Neighbor, tot utilitzant llibreries gratuïtes com són les OpenCV.

Classification of sags according to their origin based on the waveform similarity

A statistical method for classification of sags their origin downstream or upstream from the recording point is proposed in this work. The goal is to obtain a statistical model using the sag waveforms useful to characterise one type of sags and to discriminate them from the other type. This model is built on the basis of multi-way principal component analysis an later used to project the available registers in a new space with lower dimension. Thus, a case base of diagnosed sags is built in the projection space. Finally classification is done by comparing new sags against the existing in the case base. Similarity is defined in the projection space using a combination of distances to recover the nearest neighbours to the new sag. Finally the method assigns the origin of the new sag according to the origin of their neighbours

Exploring the conditions for a mortality crisis: bringing context back into the debate

This study engages with the debate over the mortality crises in the former Soviet Union and Central and Eastern Europe by 1) considering at length and as complementary to each other the two most prominent explanations for the post-communist mortality crisis, stress and alcohol consumption; 2) emphasizing the importance of context by exploiting systematic similarities and differences across the region. Differential mortality trajectories reveal three country groups that cluster both spatially and in terms of economic transition experiences. The first group are the countries furthest west in which mortality rates increased minimally after the transition began. The second group experienced a severe increase in mortality rates in the early 1990s, but recovered previous levels within a few years. These countries are located peripherally to Russia and its nearest neighbours. The final group consists of countries that experienced two mortality increases or in which mortality levels had not recovered to pre-transition levels well into the 21st century. Cross-sectional time-series data analyses of men’s and women’s age and cause-specific death rates reveal that the clustering of these countries and their mortality trajectories can be partially explained by the economic context, which is argued to be linked to stress and alcohol consumption. Above and beyond many basic differences in the country groups that are held constant—including geographically and historically shared cultural, lifestyle and social characteristics—poor economic conditions account for a remarkably consistent share of excess age-specific and cause-specific deaths.

Cardiac motion estimation by joint alignment of tagged MRI sequences

Image registration has been proposed as an automatic method for recovering cardiac displacement fields from Tagged Magnetic Resonance Imaging (tMRI) sequences. Initially performed as a set of pairwise registrations, these techniques have evolved to the use of 3D+t deformation models, requiring metrics of joint image alignment (JA). However, only linear combinations of cost functions defined with respect to the first frame have been used. In this paper, we have applied k-Nearest Neighbors Graphs (kNNG) estimators of the -entropy (H ) to measure the joint similarity between frames, and to combine the information provided by different cardiac views in an unified metric. Experiments performed on six subjects showed a significantly higher accuracy (p < 0.05) with respect to a standard pairwise alignment (PA) approach in terms of mean positional error and variance with respect to manually placed landmarks. The developed method was used to study strains in patients with myocardial infarction, showing a consistency between strain, infarction location, and coronary occlusion. This paper also presentsan interesting clinical application of graph-based metric estimators, showing their value for solving practical problems found in medical imaging.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

An approximation algorithm for #k-SAT

"Vegeu el resum a l'inici del document del fitxer adjunt"

On the system of the functions x (s) / (s-r)k

"Vegeu el resum a l'inici del document del fitxer adjunt."

Síntesi de siRNAs (short interfering RNAs) modificats amb nucleobases 5-metil i 5-propinil pirimidíniques i avaluació de la seva activitat in vitro en cultius cel•lulars i de la seva estabilitat en sèrum humà. Disseny de siRNAs dirigits a la inhibició de l'expressió de mutacions de l'oncogen K-ras.

Projecte de recerca elaborat a partir d’una estada a la Stanford University, EEUU, entre 2007 i 2009. El present projecte es basa 1) en la síntesi de cadenes d'ARN dirigides a la inhibició de l'expressió gènica per un mecanisme d'ARN d'interferència (siRNAs o short interefering RNAs) i 2) en l'avaluació de l'activitat in vitro d'aquests oligonucleòtids en cultius cel•lulars. Concretament, la meva recerca ha estat enfocada principalment a l'estudi de cadenes de siRNA modificades amb nucleobases 5-metil i 5-propinil pirimidíniques. Es tractava d'avaluar l'efecte que exerceixen els factors estèrics en el major groove (solc major) dels siRNAs sobre la seva activitat biològica. En aquest sentit, he dut aterme síntesi de fosforamidits de nucleòsis pirimidínics modificats a la posició C-5 de la nucleobase. A continuació he incorporat aquestes unitats nucleosídiques en cadenes d'ARN emprant un sintetitzador d’ADN/ARN i he estudiat l'estabilitat dels corresponents dúplexs d'ARN mitjançant experiments de desnaturalització tèrmica. Finalment he dut a terme experiments d'inhibició de l'expressió gènica en cèl.lules HeLa per tal d'avaluar l'activitat biològia d'aquests siRNAs modificats. Els resultats d'aquests estudis han posat de manifest que la presència de grups voluminosos com el propinil a l'extrem 5' del dúplex de siRNA (definit per la cadena guia o antisense) influeix de forma molt negativa en la seva activitat biològica. En canvi, grups menys voluminosos com el metil hi influeixen positivament, de manera que algunes de les cadenes sintetitzades han resultat ser més actives que els corresponents siRNAs naturals (wild type siRNAs). A més, aquest tipus de modificació contribueix positivament en l'estabilitat de cadenes de siRNA en sèrum humà. Aquest treball ha estat publicat (Terrazas, M.; Kool, E.T. "Major Groove Modifications Improve siRNA Stability and Biological Activity" Nucleic Acids Res. 2009, in press).

WEB Cas Pràctic boo-k : Gestió d'una Botiga Virtual

L'objectiu d'aquest treball és especificar, dissenyar i implementar una aplicació web que permeti l'operativa real dels serveis de gestió d'una botiga virtual d'Internet, amb el suport d'un sistema de gestió de bases de dades.

K.O. Apel: transcendentalisme i praxi de la veritat.

L'objectiu d'aquest treball és explicar i fer la crítica de la Teoria de la Veritat recentment defensada per Apel. En primer lloc, el consens i pragmàtica de la Teoria de la Veritat d'Apel es presenta en relació amb el projecte de la Teoria Crítica de la Societat de Habermas i el problema dels fonaments en el raonament ètic. En segon lloc, la seva versió idealitzada i transcendental de la Veritat que invoca la noció de convergència en una comunitat ideal d'investigadors lliures és analitzada. Finalment, les entranyes de l'esperit wingensteinià i després de l'últim anàlisi de Putnam, s’ha intentat fer una avaluació crítica. El resultat de tot això serà una més modesta concepció de la Veritat com a tan sols una qualitat de la praxi lingüística humana, però no la seva primera pedra

Constraint algorithm for k-presymplectic Hamiltonian systems. Application to singular field theories

The k-symplectic formulation of field theories is especially simple, since only tangent and cotangent bundles are needed in its description. Its defining elements show a close relationship with those in the symplectic formulation of mechanics. It will be shown that this relationship also stands in the presymplectic case. In a natural way,one can mimick the presymplectic constraint algorithm to obtain a constraint algorithmthat can be applied to k-presymplectic field theory, and more particularly to the Lagrangian and Hamiltonian formulations offield theories defined by a singular Lagrangian, as well as to the unified Lagrangian-Hamiltonian formalism (Skinner--Rusk formalism) for k-presymplectic field theory. Two examples of application of the algorithm are also analyzed.

Videojocs educatius : configuració del perfil del jugador en la plataforma de videojocs educatius K-Pax

Aquest treball presenta una forma de gestionar el perfil dels usuaris de l'aplicació gestora de videojocs educatius en xarxa k-Pax. Paral·lelament al desenvolupament del codi es realitza la documentació de gran part de la plataforma existent, de les accions necessàries per poder tenir-la en mode local i es mostren algunes guies per futurs desenvolupaments.

Programa de gestión de juegos para la plataforma k-PAX

Este proyecto es una mejora sobre la plataforma k-Pax para tratar de realizar búsquedas avanzadas sobre los juegos educativos alojados en la misma.