This paper describes a two-tiered approach to the self-localization problem for soccer playing robots using g eneric o#-the-shelf color cameras. The solution consists of two layers; the top layer is ag lobal search assuming zero knowledg e, and the bottom layer is a local search, assuming a

Ein interdisziplinäres Grid-Anwenderpraktikum basierend auf Instant-Grid

and evaluate a two-tier ap-proach that combines contemporary scheduling strategies for Grids and for work-flows, and that operates in the harsh environment of production Grids. This com-bined approach uses the “Heterogeneous Earliest-Finish-Time ” algorithm for a full-ahead static schedule of tasks, together

of letters. The recognition problem is decomposed into two problems that are solved simultaneously. To find the best matching word for an input image, a Two-Tier Beam search is performed. In Tier one the search is constrained by a letter to PAW lexicon. In Tier two, the search is constrained by a PAW to word

English: In this paper the ethical problem will be discussed how moral judgments of foreign cultures and bygone epochs can be justified. After ruling out the extremes of moral absolutism (judging without any reservations by the standards of one’s own culture and epoch) and moral relativism (judging only by the respective standards of the time and culture in question) the following solution to the dilemma is sought: A distinction has to be made between judging the norms and institutions in power at a certain place and time and judging people acting within the social institutions of their time and culture. While the former may be judged rigorously, only taking into account the objective possibilities for having other institutions at a certain development stage, the latter should be judged against the background of the common sense morals of the respective time and culture. German: In diesem Aufsatz wird das ethische Problem erörtert, wie moralische Urteile über fremde Kulturen und vergangene Epochen gerechtfertigt werden können. Nach Ausschluss der Extreme des moralischen Absolutismus (uneingeschränkte Beurteilung nach den Maßstäben der eigenen Moral) und des moralischen Relativismus (Beurteilung ausschließlich nach den Maßstäben der beurteilten Kultur oder Epoche) wird die folgende Lösung angestrebt: Es muss eine Un-terscheidung getroffen werden zwischen der Beurteilung der Normen und der Insitutionen, die an einem bestimmten Ort und zu einer bes-

deficiency in kidney transplant recipients

UNIVERSITY OF CEMA Working Paper Series

Antiretroviral treatment and prevention of peripartum and postnatal HIV transmission in West Africa: evaluation of a two-tiered approach.

Image retrieval is an active research area in image processing, pattern recognition, and computer vision. In this project, a multi-tiered tiered CBIR system for microscopic images utilizing a reference database that contains images of more than one disease is described. This system enables both

Content Based Image Retrieval(CBIR) is also known as Query By Image Content(QBIC) is the one of the application of computer vision techniques, which retrieves the images from the image database instead of text. The CBIR is gaining the popularity in medical domain, because CBIR techniques help to search the digital images in the large database. The proper feature extraction and matching process, retrieves stored image from database by supplying the query image. The features such as color, shape texture or combination of them. In this paper, focused on texture and shape feature for extracting the image from database, by introducing the SVM (support vector machine) classifier followed by KNN (K-nearest neighbor). In this paper propose a efficient retrieval of image using a supervised classifier which focused on the texture features. Segmentation based Fractal Texture Analysis or SFTA algorithm is used to extract the texture feature from images. To select best features from extracted features to train the classifier, achieve better feature optimization. The classification is done on the database and it is classified in to three categories such as normal, benign and malignant. The query image is classified using a classifier and retrieve the relevant image from the database from a particular class.