980 research outputs found

    Comment on "Drip Paintings and Fractal Analysis", arXiv:0710.4917v2, by K. Jones-Smith, H. Mathur and L.M. Krauss

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    In a recent manuscript (arXiv:0710.4917v2), Jones-Smith et al. attempt to use the well-established box-counting technique for fractal analysis to "demonstrate conclusively that fractal criteria are not useful for authentication". Here, in response to what we view to be an extremely simplistic misrepresentation of our earlier work by Jones-Smith et al., we reiterate our position regarding the potential of fractal analysis for artwork authentication. We also point out some of the flaws in the analysis presented in by Jones-Smith et al.Comment: Comment on arXiv:0710.4917v2 [cond-mat.stat-mech

    3-manifolds which are spacelike slices of flat spacetimes

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    We continue work initiated in a 1990 preprint of Mess giving a geometric parameterization of the moduli space of classical solutions to Einstein's equations in 2+1 dimensions with cosmological constant 0 or -1 (the case +1 has been worked out in the interim by the present author). In this paper we make a first step toward the 3+1-dimensional case by determining exactly which closed 3-manifolds M^3 arise as spacelike slices of flat spacetimes, and by finding all possible holonomy homomorphisms pi_1(M^3) to ISO(3,1).Comment: 10 page

    Efficient Behavior of Small-World Networks

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    We introduce the concept of efficiency of a network, measuring how efficiently it exchanges information. By using this simple measure small-world networks are seen as systems that are both globally and locally efficient. This allows to give a clear physical meaning to the concept of small-world, and also to perform a precise quantitative a nalysis of both weighted and unweighted networks. We study neural networks and man-made communication and transportation systems and we show that the underlying general principle of their construction is in fact a small-world principle of high efficiency.Comment: 1 figure, 2 tables. Revised version. Accepted for publication in Phys. Rev. Let

    Probing the Sensitivity of Electron Wave Interference to Disorder-Induced Scattering in Solid-State Devices

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    The study of electron motion in semiconductor billiards has elucidated our understanding of quantum interference and quantum chaos. The central assumption is that ionized donors generate only minor perturbations to the electron trajectories, which are determined by scattering from billiard walls. We use magnetoconductance fluctuations as a probe of the quantum interference and show that these fluctuations change radically when the scattering landscape is modified by thermally-induced charge displacement between donor sites. Our results challenge the accepted understanding of quantum interference effects in nanostructures.Comment: 8 pages, 5 figures, Submitted to Physical Review

    Effect of resonant magnetic perturbations on low collisionality discharges in MAST and a comparison with ASDEX Upgrade

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    Sustained ELM mitigation has been achieved on MAST and AUG using RMPs with a range of toroidal mode numbers over a wide region of low to medium collisionality discharges. The ELM energy loss and peak heat loads at the divertor targets have been reduced. The ELM mitigation phase is typically associated with a drop in plasma density and overall stored energy. In one particular scenario on MAST, by carefully adjusting the fuelling it has been possible to counteract the drop in density and to produce plasmas with mitigated ELMs, reduced peak divertor heat flux and with minimal degradation in pedestal height and confined energy. While the applied resonant magnetic perturbation field can be a good indicator for the onset of ELM mitigation on MAST and AUG there are some cases where this is not the case and which clearly emphasise the need to take into account the plasma response to the applied perturbations. The plasma response calculations show that the increase in ELM frequency is correlated with the size of the edge peeling-tearing like response of the plasma and the distortions of the plasma boundary in the X-point region.Comment: 31 pages, 28 figures. This is an author-created, un-copyedited version of an article submitted for publication in Nuclear Fusion. IoP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from i

    Political Marketing Activity in Simultaneous Regional Elections 2015

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    Regional head election system was change in 2015. It has impact on political marketing strategy to all stake holders, such as political party and candidatures.The purposes of this research is to analyzeashifting ofpolitical marketing issueson regional election 2015. The research approach uses the mix method with the type of sequential explanatory. The subjects of this research are the candidates, election successful teams or supporting team, and young voters. Location of research based on cluster system district and sub district in Bandung, Cianjur, Magelang, Sleman, and Medan. The data are collected through techniques of questionnaires to young voters; interview to candidates, election successful teams and young voters, as well as the documentation of media and data on Regional General Elections Commission (KPUD). There are also triangular data techniqueinterviews with the General Elections Commission (KPU), the community and supporting team, and documentation and questionnaire form. The result shows that the system of political marketing has already started shifting from product, promotion, price, place, and people known as the 5Ps from mostly dominated by Political Partyinto the role of PEOPLE as candidature in influensing the voters. The Result also tells that shifting from using convetional media into almost using digital media was powerfull

    First data and preliminary experimental results from a new Doppler Backscattering system on the MAST-U spherical tokamak

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    A new Doppler backscattering (DBS) system, consisting of Q-band and V-band, has been installed and achieved its first data on the MAST-U spherical tokamak. The Q-band and V-band have separate microwave source systems, but share the same optical front-end components. The Q-band and V-band sources simultaneously generate eight (34, 36, 38, 40, 42, 44, 46 and 48 GHz) and seven (52.5, 55, 57.5, 60, 62.5, 65 and 67.5 GHz) fixed frequency probe beams, respectively. These frequencies provide a large range of radial positions from the low-field-side edge plasma to the core, and possibly to the high-field-side edge, depending on the plasma conditions. The quasi-optical system consists of a remotely-tunable polarizer, a focusing lens and a remotely-steerable mirror. By steering the mirror, the system provides remote control of the probed density fluctuation wavenumber, and allow the launch angle to match the magnetic field. The range of accessible turbulence wavenumbers (k_\theta) is reasonably large with normalized wavenumber k_\theta\rho_s ranging from <0.5 to 9. The first data acquired by this DBS system is validated by comparing with the data from the other DBS system on MAST-U (introduced in Ref. [21]). An example of measuring the velocity profile spanning from the edge to the center in a high-density plasma is presented, indicating the robust capabilities of the integrated Q-band and V-band DBS systems

    Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation

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    Cine cardiac magnetic resonance (CMR) has become the gold standard for the non-invasive evaluation of cardiac function. In particular, it allows the accurate quantification of functional parameters including the chamber volumes and ejection fraction. Deep learning has shown the potential to automate the requisite cardiac structure segmentation. However, the lack of robustness of deep learning models has hindered their widespread clinical adoption. Due to differences in the data characteristics, neural networks trained on data from a specific scanner are not guaranteed to generalise well to data acquired at a different centre or with a different scanner. In this work, we propose a principled solution to the problem of this domain shift. Domain-adversarial learning is used to train a domain-invariant 2D U-Net using labelled and unlabelled data. This approach is evaluated on both seen and unseen domains from the M\&Ms challenge dataset and the domain-adversarial approach shows improved performance as compared to standard training. Additionally, we show that the domain information cannot be recovered from the learned features.Comment: Accepted at the STACOM workshop at MICCAI 202
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