205398210
Chaos controlling of extended nonlinear Liénard system based on the Melnikov theory
Abstract Chaos control may have a dual function, to generate chaos or to suppress it. By the Melnikov theory, two criterions of controlling chaos for a class of nonlinear Lienard system are established. According to the criterions, we implement chaos control using non-feedback method. Two illustrative examples, a Duffing–Rayleigh oscillator imposed with a weak bounded noise control, and a Duffing–van der Pol oscillator subject to a harmonic parametric control are presented here to illustrate the validity of the criterions. To better support the results obtained above, some indicators are used, namely the Lyapunov exponent, phase portrait, Poincare cross-section and time evolution. Both two methods lead to fully consistent results.
11714898
On the number of limit cycles of a cubic polynomials Hamiltonian system under quintic perturbation
Abstract This paper is concerned with the number and distribution of limit cycles of a cubic Hamiltonian system under quintic perturbation. By using the bifurcation theory and the method of detection function, we obtain that this system exists at least 14 limit cycles with the distribution C 9 1 ⊃ [ C 1 1 + 2 ( C 3 2 ⊃ 2 C 1 2 ) ] . These results in the paper are useful for the study of the weakened Hilbert’s 16th problem.
5556814
Travelling wave solutions in the generalized Hirota-Satsuma coupled KdV system
By using the bifurcation theory of dynamical systems to the generalized Hirota-Satsuma coupled KdV system, bifurcation parameter sets are shown. Numbers of solitary waves, kink waves and periodic waves are given. Under various parameter conditions, all explicit formulas of solitary wave solutions and kink wave solutions and periodic wave solutions are listed.
644571
Parametric inference for progressive Type-I hybrid censored data on a simple step-stress accelerated life test model
This paper considers a simple step-stress accelerated life test model under progressive Type-I hybrid censoring scheme. The progressive Type-I hybrid censoring scheme and statistical method in synthetic accelerated stresses are provided so as to decrease the lifetime and reduce the test cost. An exponentially distributed life of test units and a cumulative exposure model are assumed. The maximum likelihood estimates of the model parameters are obtained using a pivotal quantity. Two useful lemmas and a theorem are given to construct the approximate confidence intervals for the model parameters. Finally, simulation results are provided to assess the method of inference developed in this article. The simulation results show that the method does improve for large sample size.
29892228
Bifurcations of traveling wave solutions for a class of the generalized Benjamin-Bona-Mahony equation
Abstract By using the theory of bifurcations of dynamical systems to a class of the generalized Benjamin–Bona–Mahony (GBBM) equation, the existence of solitary wave solutions and uncountably infinite, many smooth and non-smooth periodic wave solutions are obtained. It can be shown that the existence of singular curves in a traveling wave system is the reason why smooth waves converge to cusp waves, finally. When parameters are varied, under different parametric conditions, various sufficient conditions to guarantee the existence of the above solutions are given.
11656353
Bifurcations of traveling wave solutions for a class of the nonlinear equations
Abstract The dynamical behavior of traveling wave solutions in a class of the nonlinear k ( n ,  n ) equations with negative exponents is studied by using the theory of bifurcations of dynamical systems. As a result, the dynamical behavior of different physical structure: solitary patterns, solitons, periodic, kink and anti-kink wave solutions are obtained. When parameters are varied, the conditions under which the above solutions appear are also shown. In addition, some exact explicit solutions are given.
14760977
A nanosensor array-based VLSI gas discriminator
Chemiresistive nanowires can be organized as cross-reactive sensor arrays to mimic the human olfactory system in terms of sensing and discriminating various gases and odors. This paper presents a single chip gas discrimination system that integrates a cross-reactive array of chemiresistive nanosensors with an underlying VLSI pattern classifier to accurately and efficiently identify the gas/odor to which the system is exposed. The main focus of the work is on the design of the underlying VLSI pattern classifier and its interaction with the nanosensors.
1496310
Discriminative learning of visual words for 3D human pose estimation
This paper addresses the problem of recovering 3D human pose from a single monocular image, using a discriminative bag-of-words approach. In previous work, the visual words are learned by unsupervised clustering algorithms. They capture the most common patterns and are good features for coarse-grain recognition tasks like object classification. But for those tasks which deal with subtle differences such as pose estimation, such representation may lack the needed discriminative power. In this paper, we propose to jointly learn the visual words and the pose regressors in a supervised manner. More specifically, we learn an individual distance metric for each visual word to optimize the pose estimation performance. The learned metrics rescale the visual words to suppress unimportant dimensions such as those corresponding to background. Another contribution is that we design an appearance and position context (APC) local descriptor that achieves both selectivity and invariance while requiring no background subtraction. We test our approach on both a quasi-synthetic dataset and a real dataset (HumanEva) to verify its effectiveness. Our approach also achieves fast computational speed thanks to the integral histograms used in APC descriptor extraction and fast inference of pose regressors.
850350
Online System Problem Detection by Mining Patterns of Console Logs
We describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in an online setting. Different from existing solutions, we use a two stage detection system. The first stage uses frequent pattern mining and distribution estimation techniques to capture the dominant patterns (both frequent sequences and time duration). The second stage use principal component analysis based anomaly detection technique to identify actual problems. Using real system data from a 203-node Hadoop [1] cluster, we show that we can not only achieve highly accurate and fast problem detection, but also help operators better understand execution patterns in their system.
15658838
An Improved and Efficient Tool for Analyzing Industrial Security Protocols
Formal methods and automatic tools are always necessary for analyzing security protocols, and model checking has become a hot spot of research for its ability of verifying finite-state concurrent system automatically. In this paper, we propose a model of security protocols based on MSR (multi-set rewriting), coupled with PLTL describing security properties. Based on the model, a series of key automatic analysis algorithms close to the implementation are designed for our own tool. By using the tool, we illustrate the method’s effectiveness with some typical protocols and give the experimental results.
14482286
Document clustering by concept factorization
In this paper, we propose a new data clustering method called concept factorization that models each concept as a linear combination of the data points, and each data point as a linear combination of the concepts. With this model, the data clustering task is accomplished by computing the two sets of linear coefficients, and this linear coefficients computation is carried out by finding the non-negative solution that minimizes the reconstruction error of the data points. The cluster label of each data point can be easily derived from the obtained linear coefficients. This method differs from the method of clustering based on non-negative matrix factorization (NMF) \citeXu03 in that it can be applied to data containing negative values and the method can be implemented in the kernel space. Our experimental results show that the proposed data clustering method and its variations performs best among 11 algorithms and their variations that we have evaluated on both TDT2 and Reuters-21578 corpus. In addition to its good performance, the new method also has the merit in its easy and reliable derivation of the clustering results.