We define strong lambda-extendibility as a variant of the notion of lambda-extendible properties of graphs (Poljak and Turzik, Discrete Mathematics, 1986). We show that the parameterized APT(Pi) problem - given a conn...
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We define strong lambda-extendibility as a variant of the notion of lambda-extendible properties of graphs (Poljak and Turzik, Discrete Mathematics, 1986). We show that the parameterized APT(Pi) problem - given a connected graph G on n vertices and m edges and an integer parameter k, does there exist a spanning subgraph H of G such that H is an element of Pi and H has at least [GRAPHICS] edges - is fixed-parameter tractable (FPT) for all 0 < lambda < 1, for all strongly lambda-extendible graph properties Pi for which the APT(Pi) problem is FPT on graphs which are 0(k) vertices away from being a graph in which each block is a clique. Our results hold for properties of oriented graphs and graphs with edge labels, generalize the recent result of Crowston et al. (ICALP 2012) on MAX-CUT parameterized above the Edwards-Erdos bound, and yield FPT algorithms for several graph problems parameterized above lower bounds. (C) 2014 Elsevier Inc. All rights reserved.
作者:
Carpenter, J. RussellNASA
Goddard Space Flight Ctr Space Sci Mission Operat Tech Code 444 Greenbelt MD 20771 USA
The epoch-state filter is a recursive sequential estimator that maintains its state estimate and associated covariance at a fixed time known as the epoch, avoiding the need to propagate the covariance between measurem...
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The epoch-state filter is a recursive sequential estimator that maintains its state estimate and associated covariance at a fixed time known as the epoch, avoiding the need to propagate the covariance between measurements. Instead, the filter maps measurement innovations from the measurement time to the epoch time, in a fashion similar to a batch estimator. When process noise is present, the epoch time must follow all but at most the penultimate measurement. Revisiting the topic, this paper contributes several variations, including a factorized form, a factorized information form, and sigma-point versions, and provides a number of clarifying illustrative examples.
Restricted rotation distance between pairs of rooted binary trees measures differences in tree shape and is related to rotation distance. hi restricted rotation distance, the rotations used to transform the trees are ...
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Restricted rotation distance between pairs of rooted binary trees measures differences in tree shape and is related to rotation distance. hi restricted rotation distance, the rotations used to transform the trees are allowed to be only of two types. Restricted rotation distance is larger than rotation distance, since there are only two permissible locations to rotate, but is much easier to compute and estimate. We obtain linear upper and lower bounds for restricted rotation distance in terms of the number of interior nodes in the trees. Further, we describe a linear-time algorithm for estimating the restricted rotation distance between two trees and for finding a sequence of rotations which realizes that estimate. The methods use the metric properties of the abstract group known as Thompson's group F. (C) 2002 Published by Elsevier Science B.V.
To address the issue of intercepting maneuvering targets at a specific time, a polynomial guidance method for impact-time control is proposed in this paper. Based on the relative virtual framework and the classical di...
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To address the issue of intercepting maneuvering targets at a specific time, a polynomial guidance method for impact-time control is proposed in this paper. Based on the relative virtual framework and the classical differential geometry curve theory, such method is divided into two parts: 1) the design of the relative trajectory-length-control (RTLC) guidance law against virtual stationary targets, and 2) the design of the prediction algorithms based on the guidance law or its characteristics. The former realizes RTLC, and the latter establishes the relationship between the desired relative trajectory length-to-go and the desired time-to-go, thus implementing impact-time control. Furthermore, based on the analytical properties of the guidance law in the relative arc-length domain, its performance, characteristics, and allowable impact time are analyzed. Finally, the effectiveness of the proposed guidance method and the validity of the theoretical findings are verified by numerical simulations results.
A skew partition as defined by Chvatal is a partition of the vertex set of a graph into four nonempty parts A(1), A(2), B-1, B-2 such that there are all possible edges between A(1) and A(2), and no edges between B-1 a...
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A skew partition as defined by Chvatal is a partition of the vertex set of a graph into four nonempty parts A(1), A(2), B-1, B-2 such that there are all possible edges between A(1) and A(2), and no edges between B-1 and B-2. We introduce the concept of (n(1), n(2))-extended skew partition which includes all partitioning problems into n(1) + n(2) nonempty parts A(1),..., An(1), B-1,...,Bn-2, such that there are all possible edges between the A(i) parts, no edges between the B-j parts, i is an element of (1, ..., n(1)}, j is an element of {1,..., n(2)}, which generalizes the skew partition. We present a polynomial-time algorithm for testing whether a graph admits an (n(1), n(2))-extended skew partition. As a tool to complete this task we also develop a generalized 2-SAT algorithm, which by itself may have application to other partition problems. (c) 2006 Elsevier B.V. All rights reserved.
Active gust load alleviation is an important technology for reducing loads on future commercial airplanes so that the structure can be designed to be lighter in order to save fuel. For the intense reduction of gust lo...
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Active gust load alleviation is an important technology for reducing loads on future commercial airplanes so that the structure can be designed to be lighter in order to save fuel. For the intense reduction of gust loads, a highly reactive control system of sensors, control algorithms, and actuators is required, which is not yet available. In this paper, a control algorithm based on incremental nonlinear dynamic inversion is extended so that actuators respond faster. The control algorithm is applied to a future medium-range aircraft with distributed trailing-edge flaps. It is assumed that the vertical acceleration of the center of gravity and the displacement, velocity, and acceleration of the first wing bending mode are available as feedback variables. To allow comparability with other actuator and sensor setups, the authors abstract the actuator dynamics and sensor filter as control system time delay. The feedback gains are adjusted automatically to the control system time delay. In simulation, the authors investigate the influence of the control system time delay on the peak gust loads. They show that gust loads can indeed be intensely reduced with sufficiently small control system time delay in simulation.
We provide optimal parallel solutions to several link-distance problems set in trapezoided rectilinear polygons. All our main parallel algorithms are deterministic acid designed to run on the exclusive read exclusive ...
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We provide optimal parallel solutions to several link-distance problems set in trapezoided rectilinear polygons. All our main parallel algorithms are deterministic acid designed to run on the exclusive read exclusive write parallel random access machine (EREW PRAM). Let P be a trapezoided rectilinear simple polygon with n vertices. In O(log n) time using O(n/log n) processors we can optimally compute: 1. Minimum rectilinear link paths, or shortest paths in the L(1) metric from any point in P to all vertices of P. 2. Minimum rectilinear link paths from any segment inside P to all vertices of P. 3. The rectilinear window (histogram) partition of P. 4. Both covering radii and vertex intervals for any diagonal of P. 5. A data structure to support rectilinear link-distance queries between any two points in P (queries can be answered optimally in O(log n) time by uniprocessor). Our solution to 5 is based on a new linear-time sequential algorithm for this problem which is also provided here. This improves on the previously best-known sequential algorithm for this problem which used O(n log n) time and space.(5) We develop techniques for solving link-distance problems in parallel which are expected to find applications in the design of other parallel computational geometry algorithms. We employ these parallel techniques, for example, to compute (on a CREW PRAM) optimally the link diameter, the link center, and the central diagonal of a rectilinear polygon.
We consider an interval coverage problem. Given n intervals of the same length on a line L and a line segment B on L, we want to move the intervals along L such that every point of B is covered by at least one interva...
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We consider an interval coverage problem. Given n intervals of the same length on a line L and a line segment B on L, we want to move the intervals along L such that every point of B is covered by at least one interval and the sum of the moving distances of all intervals is minimized. As a basic geometry problem, it has applications in mobile sensor barrier coverage in wireless sensor networks. The previous work solved the problem in O(n(2)) time. In this paper, by discovering many interesting observations and developing new algorithmic techniques, we present an O(n log n) time algorithm. We also show an Omega (n log n) time lower bound for this problem, which implies the optimality of our algorithm.
We study a data mining problem concerning the elastic peak detection in 2D liquid chromatography-mass spectrometry (LC-MS) data. These data can be modeled as time series, in which the X-axis represents time points and...
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We study a data mining problem concerning the elastic peak detection in 2D liquid chromatography-mass spectrometry (LC-MS) data. These data can be modeled as time series, in which the X-axis represents time points and the Y-axis represents intensity values. A peak occurs in a set of 2D LC-MS data when the sum of the intensity values in a sliding time window exceeds a user-determined threshold. The elastic peak detection problem is to locate all peaks across multiple window sizes of interest in the data set. We propose a new data structure, called a Shifted Aggregation Tree or AggTree for short, and use the data structure to find the different peaks. Our method, called PeakID, solves the elastic peak detection problem in 2D LC-MS data yielding neither false positives nor false negatives. The method works by first constructing an AggTree in a bottom-up manner from the given data set, and then searching the AggTree for the peaks in a top-down manner. We describe a state-space algorithm for finding the topology and structure of an efficient AggTree to be used by PeakID. Our experimental results demonstrate the superiority of the proposed method over other methods on both synthetic and real-world data.
Problems on uncertain data have attracted significant attention due to the imprecise nature of many measurement data. In this paper, we consider the k-center problem on one-dimensional uncertain data. The input is a s...
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Problems on uncertain data have attracted significant attention due to the imprecise nature of many measurement data. In this paper, we consider the k-center problem on one-dimensional uncertain data. The input is a set of (weighted) uncertain points on a real line, and each uncertain point is specified by its probability density function (pdf) which is a piecewise-uniform function (i.e., a histogram). The goal is to find a set Q of k points on the line to minimize the maximum expected distance from the uncertain points of P to their expected closest points in Q. We present efficient algorithms for this uncertain k-center problem and their running times almost match those for the "deterministic" k-center problem. (C) 2015 Elsevier B.V. All rights reserved.
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