Annotating Relationships between Multiple Mixed-media Digital Objects by Extending Annotea

Annotea provides an annotation protocol to support collaborative Semantic Web-based annotation of digital resources accessible through the Web. It provides a model whereby a user may attach supplementary information to a resource or part of a resource in the form of: either a simple textual comment; a hyperlink to another web page; a local file; or a semantic tag extracted from a formal ontology and controlled vocabulary. Hence, annotations can be used to attach subjective notes, comments, rankings, queries or tags to enable semantic reasoning across web resources. More recently tabbed Browsers and specific annotation tools, allow users to view several resources (e.g., images, video, audio, text, HTML, PDF) simultaneously in order to carry out side-by-side comparisons. In such scenarios, users frequently want to be able to create and annotate a link or relationship between two or more objects or between segments within those objects. For example, a user might want to create a link between a scene in an original film and the corresponding scene in a remake and attach an annotation to that link. Based on past experiences gained from implementing Annotea within different communities in order to enable knowledge capture, this paper describes and compares alternative ways in which the Annotea Schema may be extended for the purpose of annotating links between multiple resources (or segments of resources). It concludes by identifying and recommending an optimum approach which will enhance the power, flexibility and applicability of Annotea in many domains

Elimination of correlation in random codes for arbitrarily varying channels

Ahlswede R. Elimination of correlation in random codes for arbitrarily varying channels. Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete. 1978;44(2):159-175.The author determines for arbitrarily varying channels a) the average error capacity and b) the maximal error capacity in case of randomized encoding. A formula for the average error capacity in case of randomized encoding was announced several years ago by Dobrushin ([3]). Under a mild regularity condition this formula turns out to be valid and follows as consequence from either a) or b)

Worst-Case Optimal Adaptive Prefix Coding

A common complaint about adaptive prefix coding is that it is much slower than static prefix coding. Karpinski and Nekrich recently took an important step towards resolving this: they gave an adaptive Shannon coding algorithm that encodes each character in O(1) amortized time and decodes it in O(log H) amortized time, where H is the empirical entropy of the input string s. For comparison, Gagie’s adaptive Shannon coder and both Knuth’s and Vitter’s adaptive Huffman coders all use Θ(H) amortized time for each character. In this paper we give an adaptive Shannon coder that both encodes and decodes each character in O(1) worst-case time. As with both previous adaptive Shannon coders, we store s in at most (H + 1)|s | + o(|s|) bits. We also show that this encoding length is worst-case optimal up to the lower order term

Problematic pigmented lesions: approach to diagnosis

A number of pigmented lesions are difficult to classify and raise the possibility of a melanoma diagnosis. Care should be exercised to exclude non-melanocytic lesions, and benign melanocytic entities, both of which can mimic melanoma histologically. In addition, the possibility of the lesion being a melanoma variant or epidermotropic metastasis should be considered. There will still be some cases that are difficult to resolve. These usually fall into one of three categories: atypical junctional melanocytic lesion versus early melanoma; naevus versus naevoid melanoma; and atypical Spitz, cellular blue, and deep penetrating naevi versus thick melanoma. These will pose problems even for experts. The atypical Spitz lesions are perhaps the most important category because they tend to be from younger individuals, the differential diagnosis is thick melanoma, and there is no single discriminating histological feature. Key Words: difficult diagnosis • pigmented lesions • melanom