Computer evaluation of topological formulas for network analysis

Single tree-finding program for digital computer evaluation of topological formulas for network analysi

Entity Ranking on Graphs: Studies on Expert Finding

Todays web search engines try to offer services for finding various information in addition to simple web pages, like showing locations or answering simple fact queries. Understanding the association of named entities and documents is one of the key steps towards such semantic search tasks. This paper addresses the ranking of entities and models it in a graph-based relevance propagation framework. In particular we study the problem of expert finding as an example of an entity ranking task. Entity containment graphs are introduced that represent the relationship between text fragments on the one hand and their contained entities on the other hand. The paper shows how these graphs can be used to propagate relevance information from the pre-ranked text fragments to their entities. We use this propagation framework to model existing approaches to expert finding based on the entity's indegree and extend them by recursive relevance propagation based on a probabilistic random walk over the entity containment graphs. Experiments on the TREC expert search task compare the retrieval performance of the different graph and propagation models

Unconventional magnetism in all-carbon nanofoam

We report production of nanostructured carbon foam by a high-repetition-rate, high-power laser ablation of glassy carbon in Ar atmosphere. A combination of characterization techniques revealed that the system contains both sp2 and sp3 bonded carbon atoms. The material is a novel form of carbon in which graphite-like sheets fill space at very low density due to strong hyperbolic curvature, as proposed for ?schwarzite?. The foam exhibits ferromagnetic-like behaviour up to 90 K, with a narrow hysteresis curve and a high saturation magnetization. Such magnetic properties are very unusual for a carbon allotrope. Detailed analysis excludes impurities as the origin of the magnetic signal. We postulate that localized unpaired spins occur because of topological and bonding defects associated with the sheet curvature, and that these spins are stabilized due to the steric protection offered by the convoluted sheets.Comment: 14 pages, including 2 tables and 7 figs. Submitted to Phys Rev B 10 September 200

Le Musée du duc d’Orléans

Rode Paul. Le Musée du duc d’Orléans. In: La Terre et La Vie, Revue d'Histoire naturelle, tome 4, n°2, 1934. pp. 67-75

Study and Analysis of Supervised Vs Unsupervised Classification for Remote Sensing Images

Image classification is a procedure to automatically categorize all pixels in an image [9]. Image classification has emerged as a significant tool for investigating digital images [1].Image classification can be defined as the process of reducing an image to information classes. The categorization of image pixels is based on their digital numbers/grey values in one or more spectral bands. The main objective of image classification is to automatically categorize all pixels in a digital image into information classes or themes. The image classification tool for examination of the digital images. Classification is generally divided into two types as supervised classification and unsupervised classification [8]. This paper gives comparative study of Supervised & Unsupervised image classification

VITALAS at TRECVID-2008

In this paper, we present our experiments in TRECVID 2008 about High-Level feature extraction task. This is the first year for our participation in TRECVID, our system adopts some popular approaches that other workgroups proposed before. We proposed 2 advanced low-level features NEW Gabor texture descriptor and the Compact-SIFT Codeword histogram. Our system applied well-known LIBSVM to train the SVM classifier for the basic classifier. In fusion step, some methods were employed such as the Voting, SVM-base, HCRF and Bootstrap Average AdaBoost(BAAB)