A study of the economic benefits of meteorological satellite data

Satellite data, while most useful in data poor areas, serves to fine tune forecasts in data rich areas. It consequently has a resulting significant economic benefit because, as previously stated, even one improved forecast per client per year can save each client thousands of dollars. Multiply this by several hundred clients and the dollar savings are sizeable. The great educational value which experience with satellite data gives undoubtedly leads to improved forecasts. Any type of future satellite data delivery system should take into account the needs and facilities of the user community to make it most useful

Deep Over-sampling Framework for Classifying Imbalanced Data

Class imbalance is a challenging issue in practical classification problems for deep learning models as well as traditional models. Traditionally successful countermeasures such as synthetic over-sampling have had limited success with complex, structured data handled by deep learning models. In this paper, we propose Deep Over-sampling (DOS), a framework for extending the synthetic over-sampling method to exploit the deep feature space acquired by a convolutional neural network (CNN). Its key feature is an explicit, supervised representation learning, for which the training data presents each raw input sample with a synthetic embedding target in the deep feature space, which is sampled from the linear subspace of in-class neighbors. We implement an iterative process of training the CNN and updating the targets, which induces smaller in-class variance among the embeddings, to increase the discriminative power of the deep representation. We present an empirical study using public benchmarks, which shows that the DOS framework not only counteracts class imbalance better than the existing method, but also improves the performance of the CNN in the standard, balanced settings

Interpolating between the Bose-Einstein and the Fermi-Dirac distributions in odd dimensions

We consider the response of a uniformly accelerated monopole detector that is coupled to a superposition of an odd and an even power of a quantized, massless scalar field in flat spacetime in arbitrary dimensions. We show that, when the field is assumed to be in the Minkowski vacuum, the response of the detector is characterized by a Bose-Einstein factor in even spacetime dimensions, whereas a Bose-Einstein as well as a Fermi-Dirac factor appear in the detector response when the dimension of spacetime is odd. Moreover, we find that, it is possible to interpolate between the Bose-Einstein and the Fermi-Dirac distributions in odd spacetime dimensions by suitably adjusting the relative strengths of the detector's coupling to the odd and the even powers of the scalar field. We point out that the response of the detector is always thermal and we, finally, close by stressing the apparent nature of the appearance of the Fermi-Dirac factor in the detector response.Comment: RevTeX, 7 page

Revisiting loss-specific training of filter-based MRFs for image restoration

It is now well known that Markov random fields (MRFs) are particularly effective for modeling image priors in low-level vision. Recent years have seen the emergence of two main approaches for learning the parameters in MRFs: (1) probabilistic learning using sampling-based algorithms and (2) loss-specific training based on MAP estimate. After investigating existing training approaches, it turns out that the performance of the loss-specific training has been significantly underestimated in existing work. In this paper, we revisit this approach and use techniques from bi-level optimization to solve it. We show that we can get a substantial gain in the final performance by solving the lower-level problem in the bi-level framework with high accuracy using our newly proposed algorithm. As a result, our trained model is on par with highly specialized image denoising algorithms and clearly outperforms probabilistically trained MRF models. Our findings suggest that for the loss-specific training scheme, solving the lower-level problem with higher accuracy is beneficial. Our trained model comes along with the additional advantage, that inference is extremely efficient. Our GPU-based implementation takes less than 1s to produce state-of-the-art performance.Comment: 10 pages, 2 figures, appear at 35th German Conference, GCPR 2013, Saarbr\"ucken, Germany, September 3-6, 2013. Proceeding

Anomalous Noise in the Pseudogap Regime of YBa2_2Cu3_3O7−δ_{7-\delta}

An unusual noise component is found near and below about 250 K in the normal state of underdoped YBCO and Ca-YBCO films. This noise regime, unlike the more typical noise above 250 K, has features expected for a symmetry-breaking collective electronic state. These include large individual fluctuators, a magnetic sensitivity, and aging effects. A possible interpretation in terms of fluctuating charge nematic order is presented.Comment: 4 pages, 4 figure

Negaton and Positon Solutions of the KDV Equation

We give a systematic classification and a detailed discussion of the structure, motion and scattering of the recently discovered negaton and positon solutions of the Korteweg-de Vries equation. There are two distinct types of negaton solutions which we label $[S^{n}]$ and $[C^{n}]$, where $(n+1)$ is the order of the Wronskian used in the derivation. For negatons, the number of singularities and zeros is finite and they show very interesting time dependence. The general motion is in the positive $x$ direction, except for certain negatons which exhibit one oscillation around the origin. In contrast, there is just one type of positon solution, which we label $[\tilde C^n]$. For positons, one gets a finite number of singularities for $n$ odd, but an infinite number for even values of $n$. The general motion of positons is in the negative $x$ direction with periodic oscillations. Negatons and positons retain their identities in a scattering process and their phase shifts are discussed. We obtain a simple explanation of all phase shifts by generalizing the notions of ``mass" and ``center of mass" to singular solutions. Finally, it is shown that negaton and positon solutions of the KdV equation can be used to obtain corresponding new solutions of the modified KdV equation.Comment: 20 pages plus 12 figures(available from authors on request),Latex fil

Housing and Business Investment in Nebraska\u27s Non-metropolitan Communities and Declining Urban Neighborhoods

This study focuses on one subject area of the Urban Affairs Committee\u27s charge: housing and business investment in Nebraska\u27s declining urban neighborhoods and non-metropolitan communities. From its beginning the study has had two primary objectives: First, to ascertain the demand for housing and business investment funds in the declining urban neighborhoods of Nebraska\u27s two major metropolitan cities, Omaha and Lincoln, and in the State\u27s non-metropolitan communities; and the perceptions of homeowners, renters, landlords and businessmen in these communities and neighborhoods regarding the availability to them of such funds. Second, to identify factors which discourage or hamper housing and business investment in the declining urban neighborhoods of Omaha and Lincoln and in the State\u27s non-metropolitan communities, and to recommend legislation and other measures to eliminate such factors and to provide incentives for increased investment in these neighborhoods and communities

Active Galactic Nuclei under the scrutiny of CTA

Active Galactic Nuclei (hereafter AGN) produce powerful outflows which offer excellent conditions for efficient particle acceleration in internal and external shocks, turbulence, and magnetic reconnection events. The jets as well as particle accelerating regions close to the supermassive black holes (hereafter SMBH) at the intersection of plasma inflows and outflows, can produce readily detectable very high energy gamma-ray emission. As of now, more than 45 AGN including 41 blazars and 4 radiogalaxies have been detected by the present ground-based gamma-ray telescopes, which represents more than one third of the cosmic sources detected so far in the VHE gamma-ray regime. The future Cherenkov Telescope Array (CTA) should boost the sample of AGN detected in the VHE range by about one order of magnitude, shedding new light on AGN population studies, and AGN classification and unification schemes. CTA will be a unique tool to scrutinize the extreme high-energy tail of accelerated particles in SMBH environments, to revisit the central engines and their associated relativistic jets, and to study the particle acceleration and emission mechanisms, particularly exploring the missing link between accretion physics, SMBH magnetospheres and jet formation. Monitoring of distant AGN will be an extremely rewarding observing program which will inform us about the inner workings and evolution of AGN. Furthermore these AGN are bright beacons of gamma-rays which will allow us to constrain the extragalactic infrared and optical backgrounds as well as the intergalactic magnetic field, and will enable tests of quantum gravity and other "exotic" phenomena.Comment: 28 pages, 23 figure