Multifractal detrended cross-correlation analysis for two nonstationary signals

It is ubiquitous in natural and social sciences that two variables, recorded temporally or spatially in a complex system, are cross-correlated and possess multifractal features. We propose a new method called multifractal detrended cross-correlation analysis (MF-DXA) to investigate the multifractal behaviors in the power-law cross-correlations between two records in one or higher dimensions. The method is validated with cross-correlated 1D and 2D binomial measures and multifractal random walks. Application to two financial time series is also illustrated.Comment: 4 RevTex pages including 6 eps figure

A Deep Siamese Network for Scene Detection in Broadcast Videos

We present a model that automatically divides broadcast videos into coherent scenes by learning a distance measure between shots. Experiments are performed to demonstrate the effectiveness of our approach by comparing our algorithm against recent proposals for automatic scene segmentation. We also propose an improved performance measure that aims to reduce the gap between numerical evaluation and expected results, and propose and release a new benchmark dataset.Comment: ACM Multimedia 201

Chosen-Plaintext Cryptanalysis of a Clipped-Neural-Network-Based Chaotic Cipher

In ISNN'04, a novel symmetric cipher was proposed, by combining a chaotic signal and a clipped neural network (CNN) for encryption. The present paper analyzes the security of this chaotic cipher against chosen-plaintext attacks, and points out that this cipher can be broken by a chosen-plaintext attack. Experimental analyses are given to support the feasibility of the proposed attack.Comment: LNCS style, 7 pages, 1 figure (6 sub-figures

Identifying influential spreaders and efficiently estimating infection numbers in epidemic models: a walk counting approach

We introduce a new method to efficiently approximate the number of infections resulting from a given initially-infected node in a network of susceptible individuals. Our approach is based on counting the number of possible infection walks of various lengths to each other node in the network. We analytically study the properties of our method, in particular demonstrating different forms for SIS and SIR disease spreading (e.g. under the SIR model our method counts self-avoiding walks). In comparison to existing methods to infer the spreading efficiency of different nodes in the network (based on degree, k-shell decomposition analysis and different centrality measures), our method directly considers the spreading process and, as such, is unique in providing estimation of actual numbers of infections. Crucially, in simulating infections on various real-world networks with the SIR model, we show that our walks-based method improves the inference of effectiveness of nodes over a wide range of infection rates compared to existing methods. We also analyse the trade-off between estimate accuracy and computational cost, showing that the better accuracy here can still be obtained at a comparable computational cost to other methods.Comment: 6 page

Initiation and Early Kinematic Evolution of Solar Eruptions

We investigate the initiation and early evolution of 12 solar eruptions, including six active region hot channel and six quiescent filament eruptions, which were well observed by the \textsl{Solar Dynamics Observatory}, as well as by the \textsl{Solar TErrestrial RElations Observatory} for the latter. The sample includes one failed eruption and 11 coronal mass ejections, with velocities ranging from 493 to 2140~km~s$^{-1}$. A detailed analysis of the eruption kinematics yields the following main results. (1) The early evolution of all events consists of a slow-rise phase followed by a main-acceleration phase, the height-time profiles of which differ markedly and can be best fit, respectively, by a linear and an exponential function. This indicates that different physical processes dominate in these phases, which is at variance with models that involve a single process. (2) The kinematic evolution of the eruptions tends to be synchronized with the flare light curve in both phases. The synchronization is often but not always close. A delayed onset of the impulsive flare phase is found in the majority of the filament eruptions (5 out of 6). This delay, and its trend to be larger for slower eruptions, favor ideal MHD instability models. (3) The average decay index at the onset heights of the main acceleration is close to the threshold of the torus instability for both groups of events (although based on a tentative coronal field model for the hot channels), suggesting that this instability initiates and possibly drives the main acceleration.Comment: Accepted for publication in ApJ; 24 pages, 12 figures, 3 table