Common Linux distributions often include package management tools such as apt-get in Debian or yum in RedHat. Using information about package dependencies and conflicts, such tools can determine how to install a new package (and its dependencies) on a system of already installed packages. Using off-the-shelf SAT solvers, pseudoboolean solvers, and Integer Linear Programming solvers, we have developed a new package-management tool, called Opium, that improves on current tools in two ways: (1) Opium is complete, in that if there is a solution, Opium is guaranteed to find it, and (2) Opium can optimize a userprovided objective function, which could for example state that smaller packages should be preferred over larger ones. We performed a comparative study of our tool against Debian's apt-get on 600 traces of real-world package installations. We show that Opium runs fast enough to be usable, and that its completeness and optimality guarantees provides concrete benefits to end users.

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This work describes a dedicated software which detects and characterizes disease lesions on leaves to provide data on the number and type of lesions and the percentage of leaf area diseased (severity). The software, written in C'*, can be used with a standard computer in combination with a colour CCD camera and a frame grabber for image acquisition. The usefulness and adaptability of the software was evaluated using two foliar diseases, Altemaria blight of sunflower and oat leaf rust {Pmcinia coronata f.sp. avenae], which differ in symptoms. Using image segmentation and classification techniques, the software discriminated disease symptoms from the healthy leaf area. The number and size of lesions and severity, obtained using the image processing software, were compared with those calculated using a software planimeter or visual assessment. Significant linear relationships between planimeter and the imaging software were obtained for lesion number and severity in oal leaf rust and for severity in sunflower blight. Artefacts, mistakenly classified as blight lesions by the imaging software resulted in an over-estimation of the number of lesions. Future research is aimed at improving accuracy through better illumination during image capture. A dedicated, compact and portable hardware is currently being developed for field use as a self-contained device for disease assessment. Zusammenfassung Quantitative Erfassung von Lasionsmerkmalen und der BefallsstMrke von Krankheiten mit Hilfe der digitalen Bildbearbeitung Diese Arbeit stellt eine Spezialsoftware vor, die krankheitsbedingte Blattiecken erfaflt und charakterisiert. Dabei tlber Zahl und Art der Lasionen geliefert, ebenso uber den Prozentanteil befallener Blattflache (Befallsstarke). Die in C^^ geschriebene Software kann mit einem handeisublichen Computer in Kombination mit einer Farb-CCD-Kamera und einem Frame grabber fur die Bildaufnahme verwendet werden. Nutzen und Vielseitigkeit der Software wurden anhand von zwei Blattkrankheiten untersucht, die unterschiedliche Symptome hervorrufen: /reraana-Blattfleckenkrankheit der Sonnenblume sowie Haferkronenrost (Puccinia coronata f. sp. avenae). Mit Hilfe von Techniken zur Erzetigung von Teilbildem und zur Bildklassifizierung unterschied die Software befallene und gesunde Blattfiache. Die von der Bildbearbeitungssoftware gelieferten Informationen uber die Zahl und die GroBe der Lasionen sowie uber die Befallsstarke wurden mit den Daten verglichen, die mit einem Sofwareplanimeter berechnet oder durch visuelle Erfassung erbalten wurden. Signifikante lineare Beziehungen zwiscben Planimeter und Bildbearbeitungssoftware ergaben sicb bei Haferkronenrost hinsichtlicb der Zahl der Lasionen und der Befallsstarke, bei der Sonnenblumenkrankheit hinsichtlieh der Befallsstarke. Da die Bildbearbeitungssoftware Artefakte falscblich als Lasionen wertete, gab sie eine uberhohte Zahl von Lasionen an. In zuktinftigen Forschungsarbeiten soil versucht werden, die Genauigkeit durch eine bessere Beleuchtung wahrend der Bildaufnahme zu verbes...

Abstract-This study is part of a project which investigates computational principles which underlie perception and representation of architectural streetscape character. Some of the principles can be associated with fundamental concepts in brain theory and Gestalt psychology. For the experimental analysis streetscapes were represented by sequences of digital images of house façades which were prepared by a team of researchers from architecture. Two methods for non-linear dimensionality reduction, isomap and maximum variance unfolding, were applied to a set of Hough arrays (for lines) of the given images. An analysis of the extracted "streetmanifolds" revealed groupings of house façades with similar visual character and proportions. Comparative tests were conducted on a simple cylinder shaped example manifold to evaluate the geometric stability of the two dimensionality reduction methods. All experiments addressed variations of the distance metric and the neighbourhood parameter.

A quality-monitoring program that identified and provided best-practice recommendations corrected problems associated with using a BCMA system and improved bar-code labeling processes.