With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, variable knot spline, or variable bandwidth kernel, to the unknown function. Estimation with the aid of an oracle o ers dramatic

Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We

Information retrieval (IR) has changed considerably in the last years with the expansion of the Web (World Wide Web) and the advent of modern and inexpensive graphical user interfaces and mass storage devices. As a result, traditional IR textbooks have become quite out-of-date which has led

This paper describes the introduction, implementation and evaluation of a Problem Based Learning component in the Geodetic Surveying syllabus of the fourth / final year of the honours degree programme in Geomatics at the Department of Spatial Information

Abstract. We describe our software tool Julia for the static analysis of full Java bytecode, for optimisation as well as verification. This tool is generic since abstract domains (analyses) are not part of Julia but rather external classes that specialise its behaviour. Static analysis is performed through a denotational or constraint-based fixpoint calculation, focused on some program points called watchpoints. These points specify where the result of the analysis is useful, and can be automatically placed by the abstract domain or manually provided by the user. Julia can be instructed to include a given set of library Java classes in domains the opportunity to approximate control and data-flow arising from exceptions and subroutines. 1

set of perceptual dimensions (naturalness, openness, roughness, expansion, ruggedness) that represent the dominant spatial structure of a scene. Then, we show that these dimensions may be reliably estimated using spectral and coarsely localized information. The model generates a multidimensional space

Accurate 3D information extraction from large-scale data compressed image and the study of the optimum stereo imaging method

Abstract: With the increasing amount of geographic vector database available over the world, the remote sensing community has a strong potential to quickly produce up-to-date geographic products. In this paper, we propose a geographic object-based image analysis to bridge the gap between the image processing and the geographic vector database. The key component of the method is the automated sample selection refined by a statistical outlier detection algorithm. A preliminary image labelling is performed based on the intersection between a geographic vector database and the result of a multiscale image segmentation. Each class is then cleaned by a non-parametric trimming procedure that iteratively excludes outliers in order to keep only the most relevant training samples. Eventually, each image-object is classified based on a maximum likelyhood and new classes are created by decision rules. This method was succesfully applied to two study areas in a temperate and a Mediterranean region. The objectbased thematic overall accuracy was close to 75%, which was as good as the accuracy of the vector data in the temperate region and a significant improvement in the Mediterranean area. The proposed framework showed very promising results, but further work could still improve the classification step in order to take the most out of the selected training samples. 1

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This article discusses the conduct and evaluation of interpretive research in information systems. While the conventions for evaluating information systems case studies conducted according to the natural science model of social science are now widely accepted, this is not the case for interpretive