Automatic Metadata Generation using Associative Networks

In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and co-occurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete-form spreading activation algorithm. This article discusses the general framework for building associative networks, an algorithm for disseminating metadata through such networks, and the results of an experiment and validation of the proposed method using a standard bibliographic dataset

Multi-wavelength VLTI study of the puffed-up inner rim of a circumbinary disc

The presence of stable, compact circumbinary discs of gas and dust around post-asymptotic giant branch (post-AGB) binary systems has been well established. We focus on one such system: IRAS 08544-4431. We present an interferometric multi-wavelength analysis of the circumstellar environment of IRAS 08544-4431. The aim is to constrain different contributions to the total flux in the H, K, L, and N-bands in the radial direction. The data from VLTI/PIONIER, VLTI/GRAVITY, and VLTI/MATISSE range from the near-infrared, where the post-AGB star dominates, to the mid-infrared, where the disc dominates. We fitted two geometric models to the visibility data to reproduce the circumbinary disc: a ring with a Gaussian width and a flat disc model with a temperature gradient. The flux contributions from the disc, the primary star (modelled as a point-source), and an over-resolved component are recovered along with the radial size of the emission, the temperature of the disc as a function of radius, and the spectral dependencies of the different components. The trends of all visibility data were well reproduced with the geometric models. The near-infrared data were best fitted with a Gaussian ring model while the mid-infrared data favoured a temperature gradient model. This implies that a vertical structure is present at the disc inner rim, which we attribute to a rounded puffed-up inner rim. The N-to-K size ratio is 2.8, referring to a continuous flat source, analogues to young stellar objects. By combining optical interferometric instruments operating at different wavelengths we can resolve the complex structure of circumstellar discs and study the wavelength-dependent opacity profile. A detailed radial, vertical, and azimuthal structural analysis awaits a radiative transfer treatment in 3D to capture all non-radial complexity.Comment: 8 pages, 5 figures, accepted for publication in A&A Letter

Model selection in High-Dimensions: A Quadratic-risk based approach

In this article we propose a general class of risk measures which can be used for data based evaluation of parametric models. The loss function is defined as generalized quadratic distance between the true density and the proposed model. These distances are characterized by a simple quadratic form structure that is adaptable through the choice of a nonnegative definite kernel and a bandwidth parameter. Using asymptotic results for the quadratic distances we build a quick-to-compute approximation for the risk function. Its derivation is analogous to the Akaike Information Criterion (AIC), but unlike AIC, the quadratic risk is a global comparison tool. The method does not require resampling, a great advantage when point estimators are expensive to compute. The method is illustrated using the problem of selecting the number of components in a mixture model, where it is shown that, by using an appropriate kernel, the method is computationally straightforward in arbitrarily high data dimensions. In this same context it is shown that the method has some clear advantages over AIC and BIC.Comment: Updated with reviewer suggestion

Direct Measurement of Kirkwood-Rihaczek distribution for spatial properties of coherent light beam

We present direct measurement of Kirkwood-Rihaczek (KR) distribution for spatial properties of coherent light beam in terms of position and momentum (angle) coordinates. We employ a two-local oscillator (LO) balanced heterodyne detection (BHD) to simultaneously extract distribution of transverse position and momentum of a light beam. The two-LO BHD could measure KR distribution for any complex wave field (including quantum mechanical wave function) without applying tomography methods (inverse Radon transformation). Transformation of KR distribution to Wigner, Glauber Sudarshan P- and Husimi or Q- distributions in spatial coordinates are illustrated through experimental data. The direct measurement of KR distribution could provide local information of wave field, which is suitable for studying particle properties of a quantum system. While Wigner function is suitable for studying wave properties such as interference, and hence provides nonlocal information of the wave field. The method developed here can be used for exploring spatial quantum state for quantum mapping and computing, optical phase space imaging for biomedical applications.Comment: 27 pages, 14 figure

Ranking Spaces for Predicting Human Movement in an Urban Environment

A city can be topologically represented as a connectivity graph, consisting of nodes representing individual spaces and links if the corresponding spaces are intersected. It turns out in the space syntax literature that some defined topological metrics can capture human movement rates in individual spaces. In other words, the topological metrics are significantly correlated to human movement rates, and individual spaces can be ranked by the metrics for predicting human movement. However, this correlation has never been well justified. In this paper, we study the same issue by applying the weighted PageRank algorithm to the connectivity graph or space-space topology for ranking the individual spaces, and find surprisingly that (1) the PageRank scores are better correlated to human movement rates than the space syntax metrics, and (2) the underlying space-space topology demonstrates small world and scale free properties. The findings provide a novel justification as to why space syntax, or topological analysis in general, can be used to predict human movement. We further conjecture that this kind of analysis is no more than predicting a drunkard's walking on a small world and scale free network. Keywords: Space syntax, topological analysis of networks, small world, scale free, human movement, and PageRankComment: 11 pages, 5 figures, and 2 tables, English corrections from version 1 to version 2, major changes in the section of introduction from version 2 to

A cylindrical Penning trap for capture, mass selective cooling, and bunching of radioactive ion beams

A Penning trap ion accumulator, cooler, and buncher for low energy ion beams has been developed for the ISOLTRAP mass spectrometer at ISOLDE/CERN. A cylindrical electrode configuration is used for the creation of a nested trapping potential. This is required for efficient accumulation of externally produced ions and for high mass selectivity by buffer gas cooling. The design goal of a mass resolving power of about $1\cdot 10^{5}$ has been achieved. Isobar separation has been demonstrated for radioactive rare earth ion beams delivered by the ISOLDE on-line mass separator

Quantitative Analysis of Bloggers Collective Behavior Powered by Emotions

Large-scale data resulting from users online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms involving emotions expressed in the posted text play a role. Here we combine approaches of statistical physics with machine-learning methods of text analysis to study emergence of the emotional behavior among Web users. Mapping the high-resolution data from digg.com onto bipartite network of users and their comments onto posted stories, we identify user communities centered around certain popular posts and determine emotional contents of the related comments by the emotion-classifier developed for this type of texts. Applied over different time periods, this framework reveals strong correlations between the excess of negative emotions and the evolution of communities. We observe avalanches of emotional comments exhibiting significant self-organized critical behavior and temporal correlations. To explore robustness of these critical states, we design a network automaton model on realistic network connections and several control parameters, which can be inferred from the dataset. Dissemination of emotions by a small fraction of very active users appears to critically tune the collective states

The reporting of distribution power quality surveys

Power quality surveys can contain a large amount of data for many sites and several utilities. A reporting format needs to be adopted which gives useful insights without sacrificing detail. It is recommended that a three level structure be adopted with site, network and utility component styles. The first of these is the presentation of the raw data in slightly abbreviated form while the second allows all sites in one network to be ranked according to severity of their power quality disturbances. Utility reporting allows comparison between the overall power quality performance of different utilities in benchmarking studies. Some new data analysis algorithms are proposed to show how the reporting styles should be implemented

Production and trapping of carbon clusters for absolute mass measurements at ISOLTRAP

Singly-charged carbon clusters C/sub n//sup +/ (n >or= 1) have been produced by laser-induced desorption and fragmentation of C/sub 60/ fullerenes and have been injected into and stored in the Penning trap system of the ISOLTRAP mass spectrometer at ISOLDE/CERN. The present study is the first step to extend the until now direct mass measurements at ISOLTRAP to absolute mass measurements by using clusters of /sup 12/C. (10 refs)