Mining web data for competency management

We present CORDER (COmmunity Relation Discovery by named Entity Recognition) an un-supervised machine learning algorithm that exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and associates. We discuss the problems associated with evaluating unsupervised learners and report our initial evaluation experiments

Electronic, magnetic properties and correlation effects in the layered quaternary iron oxyselenide Na2Fe2Se2O from first principles

By means of the first-principle calculations, we have investigated electronic, magnetic properties and correlation effects for the newly discovered layered oxyselenide Na2Fe2Se2O. Our results reveal that the electron correlations in the Fe 3d bands promote a transition of Na2Fe2Se2O from magnetic metallic or half-metallic states to the antiferromagnetic Mott-insulating state. In addition, the bonding picture in Na2Fe2Se2O is described as an anisotropic mixture of ionic and covalent contributions.Comment: 12 pages, 3 figure

Introducing Small-World Network Effect to Critical Dynamics

We analytically investigate the kinetic Gaussian model and the one-dimensional kinetic Ising model on two typical small-world networks (SWN), the adding-type and the rewiring-type. The general approaches and some basic equations are systematically formulated. The rigorous investigation of the Glauber-type kinetic Gaussian model shows the mean-field-like global influence on the dynamic evolution of the individual spins. Accordingly a simplified method is presented and tested, and believed to be a good choice for the mean-field transition widely (in fact, without exception so far) observed on SWN. It yields the evolving equation of the Kawasaki-type Gaussian model. In the one-dimensional Ising model, the p-dependence of the critical point is analytically obtained and the inexistence of such a threshold p_c, for a finite temperature transition, is confirmed. The static critical exponents, gamma and beta are in accordance with the results of the recent Monte Carlo simulations, and also with the mean-field critical behavior of the system. We also prove that the SWN effect does not change the dynamic critical exponent, z=2, for this model. The observed influence of the long-range randomness on the critical point indicates two obviously different hidden mechanisms.Comment: 30 pages, 1 ps figures, REVTEX, accepted for publication in Phys. Rev.

A Graph Theoretic Approach for Object Shape Representation in Compositional Hierarchies Using a Hybrid Generative-Descriptive Model

A graph theoretic approach is proposed for object shape representation in a hierarchical compositional architecture called Compositional Hierarchy of Parts (CHOP). In the proposed approach, vocabulary learning is performed using a hybrid generative-descriptive model. First, statistical relationships between parts are learned using a Minimum Conditional Entropy Clustering algorithm. Then, selection of descriptive parts is defined as a frequent subgraph discovery problem, and solved using a Minimum Description Length (MDL) principle. Finally, part compositions are constructed by compressing the internal data representation with discovered substructures. Shape representation and computational complexity properties of the proposed approach and algorithms are examined using six benchmark two-dimensional shape image datasets. Experiments show that CHOP can employ part shareability and indexing mechanisms for fast inference of part compositions using learned shape vocabularies. Additionally, CHOP provides better shape retrieval performance than the state-of-the-art shape retrieval methods.Comment: Paper : 17 pages. 13th European Conference on Computer Vision (ECCV 2014), Zurich, Switzerland, September 6-12, 2014, Proceedings, Part III, pp 566-581. Supplementary material can be downloaded from http://link.springer.com/content/esm/chp:10.1007/978-3-319-10578-9_37/file/MediaObjects/978-3-319-10578-9_37_MOESM1_ESM.pd

Surface Roughness and Effective Stick-Slip Motion

The effect of random surface roughness on hydrodynamics of viscous incompressible liquid is discussed. Roughness-driven contributions to hydrodynamic flows, energy dissipation, and friction force are calculated in a wide range of parameters. When the hydrodynamic decay length (the viscous wave penetration depth) is larger than the size of random surface inhomogeneities, it is possible to replace a random rough surface by effective stick-slip boundary conditions on a flat surface with two constants: the stick-slip length and the renormalization of viscosity near the boundary. The stick-slip length and the renormalization coefficient are expressed explicitly via the correlation function of random surface inhomogeneities. The effective stick-slip length is always negative signifying the effective slow-down of the hydrodynamic flows by the rough surface (stick rather than slip motion). A simple hydrodynamic model is presented as an illustration of these general hydrodynamic results. The effective boundary parameters are analyzed numerically for Gaussian, power-law and exponentially decaying correlators with various indices. The maximum on the frequency dependence of the dissipation allows one to extract the correlation radius (characteristic size) of the surface inhomogeneities directly from, for example, experiments with torsional quartz oscillators.Comment: RevTeX4, 14 pages, 3 figure

Quantum impurity in an antiferromagnet: non-linear sigma model theory

We present a new formulation of the theory of an arbitrary quantum impurity in an antiferromagnet, using the O(3) non-linear sigma model. We obtain the low temperature expansion for the impurity spin susceptibilities of antiferromagnets with magnetic long-range order in the ground state. We also consider the bulk quantum phase transition in d=2 to the gapped paramagnet (d is the spatial dimension): the impurity is described solely by a topological Berry phase term which is an exactly marginal perturbation to the critical theory. The physical properties of the quantum impurity near criticality are obtained by an expansion in (d-1).Comment: 14 pages, 7 figures; (v2) added re

ac Josephson effect in the resonant tunneling through mesoscopic superconducting junctions

We investigate ac Josephson effect in the resonant tunneling through mesoscopic superconducting junctions. In the presence of microwave irradiation, we show that the trajectory of multiple Andreev reflections can be closed by emitting or absorbing photons. Consequently, photon-assisted Andreev states are formed and play the role of carrying supercurrent. On the Shapiro steps, dc component appears when the resonant level is near a series of positions with spacing of half of the microwave frequency. Analytical result is derived in the limit of infinite superconducting gap, based on which new features of ac Josephson effect are revealed.Comment: 11 pages, 3 figure

CD90 is identified as a candidate marker for cancer stem cells in primary high-grade gliomas using tissue microarrays

Although CD90 has been identified as a marker for various kinds of stem cells including liver cancer stem cells (CSCs) that are responsible for tumorigenesis, the potential role of CD90 as a marker for CSCs in gliomas has not been characterized. To address the issue, we investigated the expression of CD90 in tissue microarrays containing 15 glioblastoma multiformes (GBMs), 19 WHO grade III astrocytomas, 13 WHO grade II astrocytomas, 3 WHO grade I astrocytomas and 8 normal brain tissues. Immunohistochemical analysis showed that CD90 was expressed at a medium to high level in all tested high-grade gliomas (grade III and GBM) whereas it was barely detectable in low-grade gliomas (grade I and grade II) and normal brains. Double immunofluorescence staining for CD90 and CD133 in GBM tissues revealed that CD133(+) CSCs are a subpopulation of CD90(+) cells in GBMs in vivo. Flow cytometry analysis of the expression of CD90 and CD133 in GBM-derived stem-like neurospheres further confirmed the conclusion in vitro. The expression levels of both CD90 and CD133 were reduced along with the loss of stem cells after differentiation. Furthermore, the limiting dilution assay demonstrated that the sphere formation ability was comparable between the CD90(+)/CD133(+) and the CD90(+)/CD133(-) populations of GBM neurospheres, which is much higher than that of the CD90(-)/CD133(-) population. We also performed double staining for CD90 and a vascular endothelial cell marker CD31 in tissue microarrays which revealed that the CD90(+) cells were clustered around the tumor vasculatures in high-grade glioma tissues. These findings suggest that CD90 is not only a potential prognostic marker for high-grade gliomas but also a marker for CSCs within gliomas, and it resides within endothelial niche and may also play a critical role in the generation of tumor vasculatures via differentiation into endothelial cells

Grooming of Dynamic Traffic in WDM Star and Tree Networks Using Genetic Algorithm

The advances in WDM technology lead to the great interest in traffic grooming problems. As traffic often changes from time to time, the problem of grooming dynamic traffic is of great practical value. In this paper, we discuss dynamic grooming of traffic in star and tree networks. A genetic algorithm (GA) based approach is proposed to support arbitrary dynamic traffic patterns, which minimizes the number of ADM's and wavelengths. To evaluate the algorithm, tighter bounds are derived. Computer simulation results show that our algorithm is efficient in reducing both the numbers of ADM's and wavelengths in tree and star networks.Comment: 15 page