1,826 research outputs found

    Pruning and Nonparametric Multiple Change Point Detection

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    Change point analysis is a statistical tool to identify homogeneity within time series data. We propose a pruning approach for approximate nonparametric estimation of multiple change points. This general purpose change point detection procedure `cp3o' applies a pruning routine within a dynamic program to greatly reduce the search space and computational costs. Existing goodness-of-fit change point objectives can immediately be utilized within the framework. We further propose novel change point algorithms by applying cp3o to two popular nonparametric goodness of fit measures: `e-cp3o' uses E-statistics, and `ks-cp3o' uses Kolmogorov-Smirnov statistics. Simulation studies highlight the performance of these algorithms in comparison with parametric and other nonparametric change point methods. Finally, we illustrate these approaches with climatological and financial applications.Comment: 9 pages. arXiv admin note: text overlap with arXiv:1505.0430

    Heavy colored SUSY partners from deflected anomaly mediation

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    We propose a deflected anomaly mediation scenario from SUSY QCD which can lead to both positive and negative deflection parameters (there is a smooth transition between these two deflection parameter regions by adjusting certain couplings). Such a scenario can naturally give a SUSY spectrum in which all the colored sparticles are heavy while the sleptons are light. As a result, the discrepancy between the Brookheaven gμ2g_\mu-2 experiment and LHC data can be reconciled in this scenario. We also find that the parameter space for explaining the gμ2g_\mu-2 anomaly at 1σ1\sigma level can be fully covered by the future LUX-ZEPLIN 7.2 Ton experiment.Comment: 16 pages, 6 figure

    Multisensor Multiobject Tracking With High-Dimensional Object States

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    Passive monitoring of acoustic or radio sources has important applications in modern convenience, public safety, and surveillance. A key task in passive monitoring is multiobject tracking (MOT). This paper presents a Bayesian method for multisensor MOT for challenging tracking problems where the object states are high-dimensional, and the measurements follow a nonlinear model. Our method is developed in the framework of factor graphs and the sum-product algorithm (SPA) and implemented using random samples or "particles". The multimodal probability density functions (pdfs) provided by the SPA are effectively represented by a Gaussian mixture model (GMM). To perform the operations of the SPA in high-dimensional spaces, we make use of Particle flow (PFL). Here, particles are migrated towards regions of high likelihood based on the solution of a partial differential equation. This makes it possible to obtain good object detection and tracking performance even in challenging multisensor MOT scenarios with single sensor measurements that have a lower dimension than the object positions. We perform a numerical evaluation in a passive acoustic monitoring scenario where multiple sources are tracked in 3-D from 1-D time-difference-of-arrival (TDOA) measurements provided by pairs of hydrophones. Our numerical results demonstrate favorable detection and estimation accuracy compared to state-of-the-art reference techniques.Comment: 13 page

    Rotation-invariant features for multi-oriented text detection in natural images.

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    Texts in natural scenes carry rich semantic information, which can be used to assist a wide range of applications, such as object recognition, image/video retrieval, mapping/navigation, and human computer interaction. However, most existing systems are designed to detect and recognize horizontal (or near-horizontal) texts. Due to the increasing popularity of mobile-computing devices and applications, detecting texts of varying orientations from natural images under less controlled conditions has become an important but challenging task. In this paper, we propose a new algorithm to detect texts of varying orientations. Our algorithm is based on a two-level classification scheme and two sets of features specially designed for capturing the intrinsic characteristics of texts. To better evaluate the proposed method and compare it with the competing algorithms, we generate a comprehensive dataset with various types of texts in diverse real-world scenes. We also propose a new evaluation protocol, which is more suitable for benchmarking algorithms for detecting texts in varying orientations. Experiments on benchmark datasets demonstrate that our system compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on variant texts in complex natural scenes

    Blind spheres of paramagnetic dopants in solid state NMR

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    Solid-state NMR on paramagnetically doped crystal structures gives information about the spatial distribution of dopants in the host. Paramagnetic dopants may render NMR active nuclei virtually invisible by relaxation, paramagnetic broadening or shielding. In this contribution blind sphere radii r(0) have been reported, which could be extracted through fitting the NMR signal visibility function f (x) = exp(-ar(0)(3)x) to experimental data obtained on several model compound series: La(1-x)Ln(x)PO(4) (Ln = Nd, Sm, Gd, Dy, Ho, Er, Tm, Yb), Sr1-xEuxGa2S4 and (Zn1-xMnx)(3)(PO4)(2)center dot 4H(2)O. Radii were extracted for H-1, P-31 and Ga-71, and dopants like Nd3+, Gd3+, Dy3+, Ho3+, Er3+, Tm3+, Yb3+ and Mn2+. The observed radii determined differed in all cases and covered a range from 5.5 to 13.5 angstrom. While these radii were obtained from the amount of invisible NMR signal, we also show how to link the visibility function to lineshape parameters. We show under which conditions empirical correlations of linewidth and doping concentration can be used to extract blind sphere radii from second moment or linewidth parameter data. From the second moment analysis of La1-xSmxPO4 P-31 MAS NMR spectra for example, a blind sphere size of Sm3+ can be determined, even though the visibility function remains close to 100% over the entire doping range. Dependence of the blind sphere radius r(0) on the NMR isotope and on the paramagnetic dopant could be suggested and verified: for different nuclei, r(0) shows a 3 root gamma-dependence, gamma being the gyromagnetic ratio. The blind sphere radii r(0) for different paramagnetic dopants in a lanthanide series could be predicted from the pseudo-contact term
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