787,990 research outputs found
Belt-Barrier Construction Algorithm for WVSNs
[[abstract]]Previous research of barrier coverage did not consider breadth of coverage in Wireless Visual Sensor Networks (WVSNs). In this paper, we consider breadth to increase the Quality of Monitor (QoM) of WVSNs. The proposed algorithm is called Distributed β-Breadth Belt-Barrier construction algorithm (D-TriB). D-TriB constructs a belt-barrier with β breadth to offer β level of QoM, we call β-QoM. D-TriB can not only reduce the number of camera sensors required to construct a barrier but also ensure that any barrier with β-QoM in the network can be identified. Finally, the successful rate of the proposed algorithm is evaluated through simulations.[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20120401~20120404[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Shanghai, Chin
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Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization
The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the algorithm incrementally minimizes the leave-one-out test score. A local regularization method is incorporated naturally into the density construction process to further enforce sparsity. An additional advantage of the proposed algorithm is that it is fully automatic and the user is not required to specify any criterion to terminate the density construction procedure. This is in contrast to an existing state-of-art kernel density estimation method using the support vector machine (SVM), where the user is required to specify some critical algorithm parameter. Several examples are included to demonstrate the ability of the proposed algorithm to effectively construct a very sparse kernel density estimate with comparable accuracy to that of the full sample optimized Parzen window density estimate. Our experimental results also demonstrate that the proposed algorithm compares favourably with the SVM method, in terms of both test accuracy and sparsity, for constructing kernel density estimates
Reverse Line Graph Construction: The Matrix Relabeling Algorithm MARINLINGA Versus Roussopoulos's Algorithm
We propose a new algorithm MARINLINGA for reverse line graph computation,
i.e., constructing the original graph from a given line graph. Based on the
completely new and simpler principle of link relabeling and endnode
recognition, MARINLINGA does not rely on Whitney's theorem while all previous
algorithms do. MARINLINGA has a worst case complexity of O(N^2), where N
denotes the number of nodes of the line graph. We demonstrate that MARINLINGA
is more time-efficient compared to Roussopoulos's algorithm, which is
well-known for its efficiency.Comment: 30 pages, 24 figure
Distributed Construction and Maintenance of Bandwidth-Efficient Bluetooth Scatternets
Bluetooth networks can be constructed as piconets or scatternets depending on the number of nodes in the network. Although piconet construction is a well-defined process specified in Bluetooth standards, scatternet construction policies and algorithms are not well specified. Among many solution proposals for this problem, only a few of them focus on efficient usage of bandwidth in the resulting scatternets. In this paper, we propose a distributed algorithm for the scatternet construction problem, that dynamically constructs and maintains a scatternet based on estimated traffic flow rates between nodes. The algorithm is adaptive to changes and maintains a constructed scatternet for bandwidth-efficiency when nodes come and go or when traffic flow rates change. Based on simulations, the paper also presents the improvements in bandwidth-efficiency provided by the proposed algorithm
Linear-time Computation of Minimal Absent Words Using Suffix Array
An absent word of a word y of length n is a word that does not occur in y. It
is a minimal absent word if all its proper factors occur in y. Minimal absent
words have been computed in genomes of organisms from all domains of life;
their computation provides a fast alternative for measuring approximation in
sequence comparison. There exists an O(n)-time and O(n)-space algorithm for
computing all minimal absent words on a fixed-sized alphabet based on the
construction of suffix automata (Crochemore et al., 1998). No implementation of
this algorithm is publicly available. There also exists an O(n^2)-time and
O(n)-space algorithm for the same problem based on the construction of suffix
arrays (Pinho et al., 2009). An implementation of this algorithm was also
provided by the authors and is currently the fastest available. In this
article, we bridge this unpleasant gap by presenting an O(n)-time and
O(n)-space algorithm for computing all minimal absent words based on the
construction of suffix arrays. Experimental results using real and synthetic
data show that the respective implementation outperforms the one by Pinho et
al
Stable transports between stationary random measures
We give an algorithm to construct a translation-invariant transport kernel
between ergodic stationary random measures and on ,
given that they have equal intensities. As a result, this yields a construction
of a shift-coupling of an ergodic stationary random measure and its Palm
version. This algorithm constructs the transport kernel in a deterministic
manner given realizations and of the measures. The
(non-constructive) existence of such a transport kernel was proved in [8]. Our
algorithm is a generalization of the work of [3], in which a construction is
provided for the Lebesgue measure and an ergodic simple point process. In the
general case, we limit ourselves to what we call constrained densities and
transport kernels. We give a definition of stability of constrained densities
and introduce our construction algorithm inspired by the Gale-Shapley stable
marriage algorithm. For stable constrained densities, we study existence,
uniqueness, monotonicity w.r.t. the measures and boundedness.Comment: In the second version, we change the way of presentation of the main
results in Section 4. The main results and their proofs are not changed
significantly. We add Section 3 and Subsection 4.6. 25 pages and 2 figure
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