Generalized penetration depth computation

Penetration depth () is a distance measure that is used to describe the extent of overlap between two intersecting objects. Most of the prior work in computation has been restricted to translational, which is defined as the minimal translational motion that one of the overlapping objects must undergo in order to make the two objects disjoint. In this paper, we extend the notion of to take into account both translational and rotational motion to separate the intersecting objects, namely generalized. When an object undergoes a rigid transformation, some point on the object traces the longest trajectory. The generalized between two overlapping objects is defined as the minimum of the longest trajectories of one object, under all possible rigid transformations to separate the overlapping objects.We present three new results to compute generalized between polyhedral models. First, we show that for two overlapping convex polytopes, the generalized is the same as the translational . Second, when the complement of one of the objects is convex, we pose the generalized computation as a variant of the convex containment problem and compute an upper bound using optimization techniques. Finally, when both of the objects are non-convex, we treat them as a combination of the above two cases and present an algorithm that computes a lower and an upper bound on the generalized . We highlight the performance of our algorithms on different models that undergo rigid motion in the 6-dimensional configuration space. Moreover, we utilize our algorithm for complete motion planning of rigid robots undergoing translational and rotational motion in a plane or in 3D space. In particular, we use generalized computation for performing C-obstacle query and checking path non-existence.     

A weakest failure detector-based asynchronous consensus protocol for f<n

has been shown to be the weakest realistic failure detector class needed to solve the consensus problem in an asynchronous distributed system prone to f<n process crashes in which communication is by message-passing. However, the only protocol that is known to meet this bound is based on three layers of protocol construction, and is therefore not efficient. This paper presents a surprisingly simple and very efficient direct message-passing implementation of a -based consensus protocol, and proves its correctness.     

On the security of a visual cryptography scheme for color images

Hou [Visual cryptography for color images, Pattern Recognition 36 (2003) 1619-1629] proposed a four-share visual cryptography scheme for color images. The scheme splits a dithered eight-color secret image into four shares: the black mask and other three shares. It was claimed that without knowing the black mask, no information about the secret image can be obtained even if all the other three shares are known. In this paper, we show that this may be true for a few specific two-color secret images only. In all other cases, however, security cannot be guaranteed. We show that an attacker can compromise a randomly chosen two-color secret image from any two of the other three shares with probability by completely recovering the shape and pattern of the secret image. The advantage will increase to if all the three shares are known. If the secret image has three or four colors, we show that the attacker can compromise it with probability and , respectively. Finally, we show that our technique can be extended to compromising secret images with more than four colors.     

Periodically switched stability induces exponential stability of discrete-time linear switched systems in the sense of Markovian probabilities

The conjecture that periodically switched stability implies absolute asymptotic stability of random infinite products of a finite set of square matrices, has recently been disproved under the guise of the finiteness conjecture. In this paper, we show that this conjecture holds in terms of Markovian probabilities. More specifically, let S_k∈C^n×n,1≤k≤K, be arbitrarily given K matrices and , where n,K≥2. Then we study the exponential stability of the following discrete-time switched dynamics S: where can be an arbitrary switching sequence.For a probability row-vector and an irreducible Markov transition matrix with , we denote by the Markovian probability on corresponding to . By using symbolic dynamics and ergodic-theoretic approaches, we show that, if S possesses the periodically switched stability then, (i) it is exponentially stable -almost surely; (ii) the set of stable switching sequences has the same Hausdorff dimension as . Thus, the periodically switched stability of a discrete-time linear switched dynamics implies that the system is exponentially stable for “almost” all switching sequences.     

A Flexible Approach to Bayesian Multiple Curve Fitting

We model sparse functional data from multiple subjects with a mixed-effects regression spline. In this model, the expected values for any subject (conditioned on the random effects) can be written as the sum of a population curve and a subject-specific deviate from this population curve. The population curve and the subject-specific deviates are both modeled as free-knot b-splines with k and k^′ knots located at and , respectively. To identify the number and location of the “free” knots, we sample from the posterior using reversible jump MCMC methods. Sampling from this posterior distribution is complicated, however, by the flexibility we allow for the model’s covariance structure. No restrictions (other than positive definiteness) are placed on the covariance parameters ψ and σ² and, as a result, no analytical form for the likelihood exists. In this paper, we consider two approximations to and then sample from the corresponding approximations to . We also sample from which has a likelihood that is available in closed form. While sampling from this larger posterior is less efficient, the resulting marginal distribution of knots is exact and allows us to evaluate the accuracy of each approximation. We then consider a real data set and explore the difference between and the more accurate approximation to .     

The 2-dipath chromatic number of Halin graphs

A 2-dipath k-coloring f of an oriented graph is a mapping from to the color set {1,2,…,k} such that f(x)≠f(y) whenever two vertices x and y are linked by a directed path of length 1 or 2. The 2-dipath chromatic number of is the smallest k such that has a 2-dipath k-coloring. In this paper we prove that if is an oriented Halin graph, then . There exist infinitely many oriented Halin graphs such that .     

On generalized middle-level problem

Let be the subgraph of the hypercube Q_n induced by levels between k and n-k, where n?2k+1 is odd. The well-known middle-level conjecture asserts that is Hamiltonian for all k?1. We study this problem in for fixed k. It is known that and are Hamiltonian for all odd n?3. In this paper we prove that also is Hamiltonian for all odd n?5, and we conjecture that is Hamiltonian for every k?0 and every odd n?2k+1.     

Convex invariant sets for discrete-time Lur’e systems

In this paper, a method to estimate the domain of attraction of a class of discrete-time Lur’e systems is presented. A new notion of invariance, denoted -invariance, is introduced. An algorithm to determinate the largest -invariant set for this class of systems is proposed. Moreover, it is proven that the -invariant sets provided by this algorithm are polyhedral convex sets and constitute an estimation of the domain of attraction of the non-linear system. It is shown that any contractive set for the Lur’e system is contained in the -invariant set obtained applying the results of this paper. Two illustrative examples are given.     

Estimation of Kendall’s tau from censored data

This paper considers the nonparametric estimation of Kendall’s tau for bivariate censored data. Under censoring, there have been some papers discussing the nonparametric estimation of Kendall’s tau, such as Wang and Wells (2000), Oakes (2008) and Lakhal et al. (2009). In this article, we consider an alternative approach to estimate Kendall’s tau. The main idea is to replace a censored event-time by a proper imputation. Thus, it induces three estimators, say , , and . We also apply the bootstrap method to estimate the variance of , and and to construct the corresponding confidence interval. Furthermore, we analyze two data sets by the suggested approach, and compare these practical estimators of Kendall’s tau in simulation studies.     

Learning of event-recording automata

In regular inference, a regular language is inferred from answers to a finite set of membership queries, each of which asks whether the language contains a certain word. One of the most well-known regular inference algorithms is the L^∗ algorithm due to Dana Angluin. However, there are almost no extensions of these algorithms to the setting of timed systems. We extend Angluin’s algorithm for on-line learning of regular languages to the setting of timed systems. Since timed automata can freely use an arbitrary number of clocks, we restrict our attention to systems that can be described by deterministic event-recording automata (DERAs). We present three algorithms, , and , for inference of DERAs. In and , we further restrict event-recording automata to be event-deterministic in the sense that each state has at most one outgoing transition per action; learning such an automaton becomes significantly more tractable. The algorithm builds on , by attempts to construct a smaller (in number of locations) automaton. Finally, is a learning algorithm for a full class of deterministic event-recording automata, which infers a so called simple DERA, which is similar in spirit to the region graph.     

Finding frequent items over sliding windows with constant update time

In this paper, we consider the problem of finding ?-approximate frequent items over a sliding window of size N. A recent work by Lee and Ting (2006) [7] solves the problem by giving an algorithm that supports query and update time, and uses space. Their query time and memory usage are essentially optimal, but the update time is not. We give a new algorithm that supports O(1) update time with high probability while maintaining the query time and memory usage as .