Al-Khwarizmı and the Hermeneutic Circle: Reflections on a Trip to Samarkand

In this paper we discuss al-Khwarzmi\u27s life and aspects of his work and suggest a possible hermeneutic avenue into his contribution to mathematics

Automatic detection of geospatial objects using multiple hierarchical segmentations

Cataloged from PDF version of article.The object-based analysis of remotely sensed imagery provides valuable spatial and structural information that is complementary to pixel-based spectral information in classi- fication. In this paper, we present novel methods for automatic object detection in high-resolution images by combining spectral information with structural information exploited by using image segmentation. The proposed segmentation algorithm uses morphological operations applied to individual spectral bands using structuring elements in increasing sizes. These operations produce a set of connected components forming a hierarchy of segments for each band. A generic algorithm is designed to select meaningful segments that maximize a measure consisting of spectral homogeneity and neighborhood connectivity. Given the observation that different structures appear more clearly at different scales in different spectral bands, we describe a new algorithm for unsupervised grouping of candidate segments belonging to multiple hierarchical segmentations to find coherent sets of segments that correspond to actual objects. The segments are modeled by using their spectral and textural content, and the grouping problem is solved by using the probabilistic latent semantic analysis algorithm that builds object models by learning the object-conditional probability distributions. The automatic labeling of a segment is done by computing the similarity of its feature distribution to the distribution of the learned object models using the Kullback–Leibler divergence. The performances of the unsupervised segmentation and object detection algorithms are evaluated qualitatively and quantitatively using three different data sets with comparative experiments, and the results show that the proposed methods are able to automatically detect, group, and label segments belonging to the same object classes

Automatic mapping of linear woody vegetation features in agricultural landscapes using very high resolution imagery

Cataloged from PDF version of article.Automatic mapping and monitoring of agricultural landscapes using remotely sensed imagery has been an important research problem. This paper describes our work on developing automatic methods for the detection of target landscape features in very high spatial resolution images. The target objects of interest consist of linear strips of woody vegetation that include hedgerows and riparian vegetation that are important elements of the landscape ecology and biodiversity. The proposed framework exploits the spectral, textural, and shape properties of objects using hierarchical feature extraction and decision-making steps. First, a multifeature and multiscale strategy is used to be able to cover different characteristics of these objects in a wide range of landscapes. Discriminant functions trained on combinations of spectral and textural features are used to select the pixels that may belong to candidate objects. Then, a shape analysis step employs morphological top-hat transforms to locate the woody vegetation areas that fall within the width limits of an acceptable object, and a skeletonization and iterative least-squares fitting procedure quantifies the linearity of the objects using the uniformity of the estimated radii along the skeleton points. Extensive experiments using QuickBird imagery from three European Union member states show that the proposed algorithms provide good localization of the target objects in a wide range of landscapes with very different characteristics

Inequality and Procedural Justice in Social Dilemmas

This study investigates the influence of resource inequality and the fairness of the allocation procedure of unequal resources on cooperative behavior in social dilemmas. We propose a simple formal behavioral model that incorporates conflicting selfish and social motivations. This model allows us to predict how inequality influences cooperative behavior. Allocation of resources is manipulated by three treatments that vary in terms of procedural justice: allocating resources randomly, based on merit, and based on ascription. As predicted, procedural justice influences cooperation significantly. Moreover, gender is found to be an important factor interacting with the association between procedural justice and cooperative behavior.

Measures of non-compactness in Orlicz modular spaces

In this paper we show that the ball measure of non-compactness of a norm bounded subset of an Orlicz modular space $L^\psi$ is equal to the limit of its $n$-widths. We also obtain several inequalities between the measures of noncompactness and the limit of the $n$-widths for modular bounded subsets of $L^\psi$ which do not have $\Delta_2$-condition. Minimum conditions on $\psi$ to have such results are specified and an example of such a function $\psi$ is provided