8,430 research outputs found
Wide parameter search for isolated pulsars using the Hough transform
We use the Hough transform to analyze data from the second science run of the
LIGO interferometers, to look for gravitational waves from isolated pulsars. We
search over the whole sky and over a large range of frequencies and spin-down
parameters. Our search method is based on the Hough transform, which is a
semi-coherent, computationally efficient, and robust pattern recognition
technique. We also present a validation of the search pipeline using hardware
signal injections.Comment: Presented at GWDAW-9 in Annecy, France (Dec. 2004). 11 pages, 5
Figures. To appear in Classical and Quantum Gravit
On credit spread slopes and predicting bank risk
The authors examine whether credit-spread curves, engendered by a mandatory subordinated-debt requirement for banks, would help predict bank risk. They extract the credit-spread curves each quarter for each bank in our sample, and analyze the information content of credit-spread slopes. They find that credit-spread slopes are significant predictors of future credit spreads. However, credit-spread slopes do not provide significant additional information on future bank-risk variables, over and above other bank-specific and market-wide information.Bank capital ; Risk
Monitoring and controlling bank risk: does risky debt serve any purpose?
To examine whether mandating banks to issue subordinated debt would enhance market monitoring and control risk-taking, the authors extract the credit-spread curve for each banking firm in their sample. After controlling for changes in market and liquidity variables, they find that changes in credit spreads do not reflect changes in bank risk variables. The result is robust to firm type, examination rating, size, leverage, and profitability, as well as to different model specifications. They also find that issuing subordinated debt does not alter banks' risk-taking behavior. They conclude that a mandatory subordinated debt requirement for banks is unlikely to provide the intended benefits of enhancing risk-monitoring or controlling risk-taking.Bank capital ; Risk
A theory of electric and magnetic birefringence in liquids
This article does not have an abstract
Differential Dynamics at Glycosidic Linkages of an Oligosaccharide as Revealed by 13C NMR Spin Relaxation and Stochastic Modeling
Among biomolecules, carbohydrates are unique in that not only can linkages be formed through different positions but the structures may also be branched. The trisaccharide \uf062-D-Glcp-(1\uf0ae3)[\uf062-D-Glcp-(1\uf0ae2)]-\uf061-D-Manp-OMe represents a model of a branched vicinally disubstituted structure. A 13C site-specific isotopologue with labeling in each of the two terminal glucosyl residues enabled acquisition of high-quality 13C NMR relaxation parameters T1, T2 and heteronuclear NOE, with standard deviations of \uf0a3 0.5%. For interpretation of the experimental NMR data a diffusive chain model was used in which the dynamics of the glycosidic linkages is coupled to the global reorientation motion of the trisaccharide. Brownian dynamics simulations relying on the potential of mean force at the glycosidic linkages were employed to evaluate spectral densities of the spin probes. Calculated NMR relaxation parameters showed very good agreement with experimental data, deviating < 3%. The resulting dynamics is described by correlation times of 196 ps and 174 ps for the \uf062-(1\uf0ae2)- and \uf062-(1\uf0ae3)-linked glucosyl residues, respectively, i.e., different and linkage dependent. Notably, the devised computational protocol was performed without any fitting of parameters
On the diffraction of light by spherical obstacles
The diffraction of light inside the shadow, thrown by a small source of light, of a sphere and a circular disc of the same diameter, was studied, with special reference to the relative intensities of the central bright spots. With the source at about 2 metres from the obstacles, with a quarter-inch polished steel ball, the bright spot could be detected visually up to 3 cm. behind the obstacle, while with a steel disc of the same diameter, with the edges perfectly sharp, smooth and circular, the spot could be traced up to 2 cm. The relative intensities of the two spots were studied at different distances behind the obstacles, qualitatively by photography and quantitatively by visual photometry. At small distances behind the obstacles, the spot inside the shadow of the sphere is much feebler than the disc-spot, however approximating to the latter as we reach farther back from the obstacles, but even at 100 cm. remaining appreciably feebler. A general explanation is suggested
Fused Text Recogniser and Deep Embeddings Improve Word Recognition and Retrieval
Recognition and retrieval of textual content from the large document
collections have been a powerful use case for the document image analysis
community. Often the word is the basic unit for recognition as well as
retrieval. Systems that rely only on the text recogniser (OCR) output are not
robust enough in many situations, especially when the word recognition rates
are poor, as in the case of historic documents or digital libraries. An
alternative has been word spotting based methods that retrieve/match words
based on a holistic representation of the word. In this paper, we fuse the
noisy output of text recogniser with a deep embeddings representation derived
out of the entire word. We use average and max fusion for improving the ranked
results in the case of retrieval. We validate our methods on a collection of
Hindi documents. We improve word recognition rate by 1.4 and retrieval by 11.13
in the mAP.Comment: 15 pages, 8 figures, Accepted in IAPR International Workshop on
Document Analysis Systems (DAS) 2020, "Visit project page, at
http://cvit.iiit.ac.in/research/projects/cvit-projects/fused-text-recogniser-and-deep-embeddings-improve-word-recognition-and-retrieval
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