Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Reproducibility of species lists, visual cover estimates and frequency methods for recording high mountain vegetation

Question: When multiple observers record the same spatial units of alpine vegetation, how much variation is there in the records and what are the consequences of this variation for monitoring schemes to detect change? Location: One test summit in Switzerland (Alps) and one test summit in Scotland (Cairngorm Mountains). Method: Eight observers used the GLORIA protocols for species composition and visual cover estimates in percent on large summit sections (>100 m2) and species composition and frequency in nested quadrats (1 m2). Results: The multiple records from the same spatial unit for species composition and species cover showed considerable variation in the two countries. Estimates of pseudoturnover of composition and coefficients of variation of cover estimates for vascular plant species in 1m x 1m quadrats showed less variation than in previously published reports whereas our results in larger sections were broadly in line with previous reports. In Scotland, estimates for bryophytes and lichens were more variable than for vascular plants. Conclusions: Statistical power calculations indicated that, unless large numbers of plots were used, changes in cover or frequency were only likely to be detected for abundant species (exceeding 10% cover) or if relative changes were large (50% or more). Lower variation could be reached with the point methods and with larger numbers of small plots. However, as summits often strongly differ from each other, supplementary summits cannot be considered as a way of increasing statistical power without introducing a supplementary component of variance into the analysis and hence the power calculations.

A inclusão social e digital de pessoas com limitação visual e o uso das tecnologias de informação e de comunicação na produção de páginas para a Internet

Este trabalho relata a atividade do acesso e do uso das tecnologias de informação e de comunicação (TICs), tendo como sujeito uma pessoa com necessidades educacionais especiais (PNEE) na produção de páginas para a Internet. A atividade permitiu a observação das barreiras e dificuldades enfrentadas e superadas, mediante o uso de ambiente de aprendizagem mediado por computador (AAMC). Foram utilizadas várias alternativas, formas de comunicação, tecnologias adequadas para a realização da atividade proposta, resultando em uma postura de compartilhamento no qual cada um tem muito para cooperar, para doar-se na busca de uma construção coletiva e na superação das limitações, sejam estas físicas e/ou tecnológicas. O artigo aponta que, com a educação e o uso das TICs, é possível promover a inclusão social e digital das PNEEs com limitação visual.

Capacitação de bibliotecários com limitação visual pela educação a distância em ambientes virtuais de aprendizagem

Este artigo ressalta a importância da capacitação de bibliotecários, profissionais da informação, por meio da educação aberta e a distância (EAD) mediada por computador, sendo estes videntes ou pessoas com necessidades educacionais especiais (PNEEs) com limitação visual. Apresenta o curso Bibliotec II, realizado pelo DCI/Fabico/UFRGS, ministrado para bibliotecários e com a participação de dois profissionais PNEEs com limitação visual. Aborda temas relacionados à biblioteca escolar, à educação, à acessibilidade e à inclusão social, digital e profissional das PNEEs, e o bibliotecário como educador, sendo um mediador, junto com os professores e os alunos, no uso das TICs, nos processos de interação, colaboração, cooperação em ambientes virtuais de aprendizagem (AVAs).

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Efectos de tipicidad en la percepción visual de escenas naturales

La actuación de las estructuras de conocimiento en el proceso de identificación y codificación de estimulos visuales se ha operativizado frecuentemente mediante conceptos como contexto o tipicidad. Ambos efectos pueden considerarse complementarios y producidos por la actuación de un mecanisrno de tipo atencional. Dicho mecanisrno fue aplicado al procesamiento de escenas por Arnau, Carreras y Salvador (en prensa). A partir de los términos propuestos en dicho modelo se intenta comprobar si la tipicidad es una variable relevante para la identificación de 10s objetos que forman una escena. Los resultados obtenidos en el experimento 1 permiten afirmar que el grado de tipicidad de un objeto respecto a una escena determina el tiempo y exactitud de su identificación. Por otra parte, en el experimento 2 se demuestra que en procesos de memoria a corto plazo el efecto de tipicidad detectado en el experimento 1 se anula. Finalmente se discuten las implicaciones de estos resultados para el estudio de la percepción visual de escenas naturales.

Comparing 'visual' effect size indices for single-case designs

Effect size indices are indispensable for carrying out meta-analyses and can also be seen as an alternative for making decisions about the effectiveness of a treatment in an individual applied study. The desirable features of the procedures for quantifying the magnitude of intervention effect include educational/clinical meaningfulness, calculus easiness, insensitivity to autocorrelation, low false alarm and low miss rates. Three effect size indices related to visual analysis are compared according to the aforementioned criteria. The comparison is made by means of data sets with known parameters: degree of serial dependence, presence or absence of general trend, changes in level and/or in slope. The percent of nonoverlapping data showed the highest discrimination between data sets with and without intervention effect. In cases when autocorrelation or trend is present, the percentage of data points exceeding the median may be a better option to quantify the effectiveness of a psychological treatment.

Factors affecting visual analysis in single-case designs

Visual inspection remains the most frequently applied method for detecting treatment effects in single-case designs. The advantages and limitations of visual inference are here discussed in relation to other procedures for assessing intervention effectiveness. The first part of the paper reviews previous research on visual analysis, paying special attention to the validation of visual analysts" decisions, inter-judge agreement, and false alarm and omission rates. The most relevant factors affecting visual inspection (i.e., effect size, autocorrelation, data variability, and analysts" expertise) are highlighted and incorporated into an empirical simulation study with the aim of providing further evidence about the reliability of visual analysis. Our results concur with previous studies that have reported the relationship between serial dependence and increased Type I rates. Participants with greater experience appeared to be more conservative and used more consistent criteria when assessing graphed data. Nonetheless, the decisions made by both professionals and students did not match sufficiently the simulated data features, and we also found low intra-judge agreement, thus suggesting that visual inspection should be complemented by other methods when assessing treatment effectiveness.

Nutritional status in commercial currant fields

Selostus: Herukkaviljelmien ravinnetila