7,221 research outputs found

    Expert Finding by Capturing Organisational Knowledge from Legacy Documents

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    Organisations capitalise on their best knowledge through the improvement of shared expertise which leads to a higher level of productivity and competency. The recognition of the need to foster the sharing of expertise has led to the development of expert finder systems that hold pointers to experts who posses specific knowledge in organisations. This paper discusses an approach to locating an expert through the application of information retrieval and analysis processes to an organization’s existing information resources, with specific reference to the engineering design domain. The approach taken was realised through an expert finder system framework. It enables the relationships of heterogeneous information sources with experts to be factored in modelling individuals’ expertise. These valuable relationships are typically ignored by existing expert finder systems, which only focus on how documents relate to their content. The developed framework also provides an architecture that can be easily adapted to different organisational environments. In addition, it also allows users to access the expertise recognition logic, giving them greater trust in the systems implemented using this framework. The framework were applied to real world application and evaluated within a major engineering company

    Expanding the Family of Grassmannian Kernels: An Embedding Perspective

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    Modeling videos and image-sets as linear subspaces has proven beneficial for many visual recognition tasks. However, it also incurs challenges arising from the fact that linear subspaces do not obey Euclidean geometry, but lie on a special type of Riemannian manifolds known as Grassmannian. To leverage the techniques developed for Euclidean spaces (e.g, support vector machines) with subspaces, several recent studies have proposed to embed the Grassmannian into a Hilbert space by making use of a positive definite kernel. Unfortunately, only two Grassmannian kernels are known, none of which -as we will show- is universal, which limits their ability to approximate a target function arbitrarily well. Here, we introduce several positive definite Grassmannian kernels, including universal ones, and demonstrate their superiority over previously-known kernels in various tasks, such as classification, clustering, sparse coding and hashing

    Moments of spectral functions: Monte Carlo evaluation and verification

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    The subject of the present study is the Monte Carlo path-integral evaluation of the moments of spectral functions. Such moments can be computed by formal differentiation of certain estimating functionals that are infinitely-differentiable against time whenever the potential function is arbitrarily smooth. Here, I demonstrate that the numerical differentiation of the estimating functionals can be more successfully implemented by means of pseudospectral methods (e.g., exact differentiation of a Chebyshev polynomial interpolant), which utilize information from the entire interval (β/2,β/2)(-\beta \hbar / 2, \beta \hbar/2). The algorithmic detail that leads to robust numerical approximations is the fact that the path integral action and not the actual estimating functional are interpolated. Although the resulting approximation to the estimating functional is non-linear, the derivatives can be computed from it in a fast and stable way by contour integration in the complex plane, with the help of the Cauchy integral formula (e.g., by Lyness' method). An interesting aspect of the present development is that Hamburger's conditions for a finite sequence of numbers to be a moment sequence provide the necessary and sufficient criteria for the computed data to be compatible with the existence of an inversion algorithm. Finally, the issue of appearance of the sign problem in the computation of moments, albeit in a milder form than for other quantities, is addressed.Comment: 13 pages, 2 figure

    The Cop Number of the One-Cop-Moves Game on Planar Graphs

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    Cops and robbers is a vertex-pursuit game played on graphs. In the classical cops-and-robbers game, a set of cops and a robber occupy the vertices of the graph and move alternately along the graph's edges with perfect information about each other's positions. If a cop eventually occupies the same vertex as the robber, then the cops win; the robber wins if she can indefinitely evade capture. Aigner and Frommer established that in every connected planar graph, three cops are sufficient to capture a single robber. In this paper, we consider a recently studied variant of the cops-and-robbers game, alternately called the one-active-cop game, one-cop-moves game or the lazy-cops-and-robbers game, where at most one cop can move during any round. We show that Aigner and Frommer's result does not generalise to this game variant by constructing a connected planar graph on which a robber can indefinitely evade three cops in the one-cop-moves game. This answers a question recently raised by Sullivan, Townsend and Werzanski.Comment: 32 page

    Magnetic Quantum Dot: A Magnetic Transmission Barrier and Resonator

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    We study the ballistic edge-channel transport in quantum wires with a magnetic quantum dot, which is formed by two different magnetic fields B^* and B_0 inside and outside the dot, respectively. We find that the electron states located near the dot and the scattering of edge channels by the dot strongly depend on whether B^* is parallel or antiparallel to B_0. For parallel fields, two-terminal conductance as a function of channel energy is quantized except for resonances, while, for antiparallel fields, it is not quantized and all channels can be completely reflected in some energy ranges. All these features are attributed to the characteristic magnetic confinements caused by nonuniform fields.Comment: 4 pages, 4 figures, to be published in Physical Review Letter

    The peculiar Type Ia supernova iPTF14atg: Chandrasekhar-mass explosion or violent merger?

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    iPTF14atg, a subluminous peculiar Type Ia supernova (SN Ia) similar to SN 2002es, is the first SN Ia for which a strong UV flash was observed in the early-time light curves. This has been interpreted as evidence for a single-degenerate (SD) progenitor system where such a signal is expected from interactions between the SN ejecta and the non-degenerate companion star. Here, we compare synthetic observables of multi-dimensional state-of-the-art explosion models for different progenitor scenarios to the light curves and spectra of iPTF14atg. From our models, we have difficulties explaining the spectral evolution of iPTF14atg within the SD progenitor channel. In contrast, we find that a violent merger of two carbon-oxygen white dwarfs with 0.9 and 0.76 solar masses, respectively, provides an excellent match to the spectral evolution of iPTF14atg from 10d before to several weeks after maximum light. Our merger model does not naturally explain the initial UV flash of iPTF14atg. We discuss several possibilities like interactions of the SN ejecta with the circum-stellar medium and surface radioactivity from a He ignited merger that may be able to account for the early UV emission in violent merger models.Comment: 12 pages, 7 figures, accepted for publication in MNRA

    Stabilization of single-electron pumps by high magnetic fields

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    We study the effect of perpendicular magnetic fields on a single-electron system with a strongly time-dependent electrostatic potential. Continuous improvements to the current quantization in these electron pumps are revealed by high-resolution measurements. Simulations show that the sensitivity of tunnel rates to the barrier potential is enhanced, stabilizing particular charge states. Nonadiabatic excitations are also suppressed due to a reduced sensitivity of the Fock-Darwin states to electrostatic potential. The combination of these effects leads to significantly more accurate current quantization

    Disease-specific, neurosphere-derived cells as models for brain disorders

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    There is a pressing need for patient-derived cell models of brain diseases that are relevant and robust enough to produce the large quantities of cells required for molecular and functional analyses. We describe here a new cell model based on patient-derived cells from the human olfactory mucosa, the organ of smell, which regenerates throughout life from neural stem cells. Olfactory mucosa biopsies were obtained from healthy controls and patients with either schizophrenia, a neurodevelopmental psychiatric disorder, or Parkinson's disease, a neurodegenerative disease. Biopsies were dissociated and grown as neurospheres in defined medium. Neurosphere-derived cell lines were grown in serum-containing medium as adherent monolayers and stored frozen. By comparing 42 patient and control cell lines we demonstrated significant disease-specific alterations in gene expression, protein expression and cell function, including dysregulated neurodevelopmental pathways in schizophrenia and dysregulated mitochondrial function, oxidative stress and xenobiotic metabolism in Parkinson's disease. The study has identified new candidate genes and cell pathways for future investigation. Fibroblasts from schizophrenia patients did not show these differences. Olfactory neurosphere-derived cells have many advantages over embryonic stem cells and induced pluripotent stem cells as models for brain diseases. They do not require genetic reprogramming and they can be obtained from adults with complex genetic diseases. They will be useful for understanding disease aetiology, for diagnostics and for drug discovery
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