5717035
Coarse-Grained Parallel Geometric Search
We present a parallel algorithm for solving thenext element search problemon a set of line segments, using a BSP-like model referred to as thecoarse grained multicomputer(CGM). The algorithm requiresO(1) communication rounds (h-relations withh=O(n/p)),O((n/p)logn) local computation, andO((n/p)logp) memory per processor, assumingn/p?p. Our result implies solutions to the point location, trapezoidal decomposition, and polygon triangulation problems. A simplified version for axis-parallel segments requires onlyO(n/p) memory per processor, and we discuss an implementation of this version. As in a previous paper by Develliers and Fabri (Int. J. Comput. Geom. Appl.6(1996), 487?506), our algorithm is based on a distributed implementation of segment trees which are of sizeO(nlogn). This paper improves onop. cit.in several ways: (1) It studies the more general next element search problem which also solves, e.g., planar point location. (2) The algorithms require onlyO((n/p)logn) local computation instead ofO(logp*(n/p)logn). (3) The algorithms require onlyO((n/p)logp) local memory instead ofO((n/p)logn).
968718
Coarse Grained Parallel Algorithms for Detecting Convex Bipartite Graphs
In this paper, we present parallel algorithms for the coarse grained multicomputer (CGM) and the bulk synchronous parallel computer (BSP) for solving two well known graph problems: (1) determining whether a graph G is bipartite, and (2) determining whether a bipartite graph G is convex. 
 
Our algorithms require O(log p) and O(log2 p) communication rounds, respectively, and linear sequential work per round on a CGM with p processors and N/p local memory per processor, N=|G|. The algorithms assume that N/p ≥ pƐ for some fixed Ɛ > 0, which is true for all commercially available multiprocessors. Our results imply BSP algorithms with O(log p) and O(log2 p) supersteps, respectively, O(g log(p)N/p) communication time, and O(log(p)N/p) local computation time. 
 
Our algorithm for determining whether a bipartite graph is convex includes a novel, coarse grained parallel, version of the PQ tree data structure introduced by Booth and Lueker. Hence, our algorithm also solves, with the same time complexity as indicated above, the problem of testing the consecutive-ones property for (0, 1) matrices as well as the chordal graph recognition problem. These, in turn, have numerous applications in graph theory, DNA sequence assembly, database theory, and other areas.
252376
A Note on Coarse Grained Parallel Integer Sorting
We observe that for n=p p, which is usually the case in practice, there exists a very simple, deterministic, optimal coarse grained parallel integer sorting algorithm with 24 communication rounds (6 n p -relations and 18p-relations), O(n=p) memory per processor and O(n=p) local computation. Experimental data indicates that the algorithm has very good performance in practice.
41263946
Coarse Grained Parallel Graph Planarity Testing
We present a coarse grained parallel algorithm for planarity testing and planar embedding. The algorithm requires O(log p) communication rounds and linear sequential work per round. It assumes that the local memory per processor, N=p, is larger than p for some xed > 0. This assumption is true for all commercially available multiprocessors. Our result implies a BSP algorithm with O(log p) supersteps, O(g log(p) p ) communication, and O(log(p) p ) local computation. Our algorithm is based on the general structure of a previous PRAM method presented by Klein, using a parallel implementation of PQ-trees. The main contribution of this paper lies in the study of many of the individual PRAM steps that are very inefcient on existing commercial parallel machines. We present non-trivial, eÆcient, CGM implementations of the various parts of the overall strategy proposed by Klein. Our main result is a parallel planarity testing algorithm which is much more practical and eÆcient on commercially available multi-
1023852
Coarse grained parallel maximum matching in convex bipartite graphs
We present a coarse grained parallel algorithm for computing a maximum matching in a convex bipartite graph G=(A,B,E). For p processors with N/p memory per processor, N=|A|+|B|,N/p/spl ges/p, the algorithm requires O(log p) communication rounds and O(T/sub sequ/(n/p,m/p)+n/p log p) local computation, where n=|A|,m=|B| and T/sub sequ/(n,m) is the sequential time complexity for the problem. For the BSP model, this implies O(log p) supersteps with O(gN+gn/p log p) communication cost and O(T/sub sequ/(n/p,m/p)+n/p log p) local computation.
5663
Mixtures of dynamic textures
A dynamic texture is a linear dynamical system used to model a single video as a sample from a spatio-temporal stochastic process. In this work, we introduce the mixture of dynamic textures, which models a collection of videos consisting of different visual processes as samples from a set of dynamic textures. We derive the EM algorithm for learning a mixture of dynamic textures, and relate the learning algorithm and the dynamic texture mixture model to previous works. Finally, we demonstrate the applicability of the proposed model to problems that have traditionally been challenging for computer vision.
2771556
Probabilistic kernels for the classification of auto-regressive visual processes
We present a framework for the classification of visual processes that are best modeled with spatio-temporal autoregressive models. The new framework combines the modeling power of a family of models known as dynamic textures and the generalization guarantees, for classification, of the support vector machine classifier. This combination is achieved by the derivation of a new probabilistic kernel based on the Kullback-Leibier divergence (KL) between Gauss-Markov processes. In particular, we derive the KL-kernel for dynamic textures in both 1) the image space, which describes both the motion and appearance components of the spatio-temporal process, and 2) the hidden state space, which describes the temporal component alone. Together, the two kernels cover a large variety of video classification problems, including the cases where classes can differ in both appearance and motion and the cases where appearance is similar for all classes and only motion is discriminant. Experimental evaluation on two databases shows that the new classifier achieves superior performance over existing solutions.
2599785
On measuring the change in size of pulmonary nodules
The pulmonary nodule is the most common manifestation of lung cancer, the most deadly of all cancers. Most small pulmonary nodules are benign, however, and currently the growth rate of the nodule provides for one of the most accurate noninvasive methods of determining malignancy. In this paper, we present methods for measuring the change in nodule size from two computed tomography image scans recorded at different times; from this size change the growth rate may be established. The impact of partial voxels for small nodules is evaluated and isotropic resampling is shown to improve measurement accuracy. Methods for nodule location and sizing, pleural segmentation, adaptive thresholding, image registration, and knowledge-based shape matching are presented. The latter three techniques provide for a significant improvement in volume change measurement accuracy by considering both image scans simultaneously. Improvements in segmentation are evaluated by measuring volume changes in benign or slow growing nodules. In the analysis of 50 nodules, the variance in percent volume change was reduced from 11.54% to 9.35% (p=0.03) through the use of registration, adaptive thresholding, and knowledge-based shape matching.
5980281
Scaling an object-oriented system execution visualizer through sampling
Increasingly, applications are being built by combining existing software components. For the most part, a software developer can treat the components as black-boxes. However, for some tasks, such as when performance tuning, a developer must consider how the components are implemented and how they interact. In these cases, a developer may be able to perform the task more effectively by using dynamic information about how the system executes. In previous work, we demonstrated the utility of a tool, called AVID (Architectural VIsualization of Dynamics), that animates dynamic information in terms of developer-chosen architectural views. One limitation of this earlier work was that AVID relied on trace information collected about the system's execution; traces for even small parts of a system's execution can be enormous, limiting the duration of execution that can be considered. To enable AVID to scale to larger longer-running systems, we have been investigating the visualization and animation of sampled dynamic information. In this paper, we discuss the addition of sampling support to AVID, and we present two case studies in which we experimented with animating sampled dynamic information to help with performance tuning tasks.
17099314
A graph-theoretical analysis of multicast authentication
Message authentication is considered as a serious bottleneck to multicast security, particular for stream-type of traffic. The technique of hash chaining/signature amortization has been proposed in many schemes for stream authentication, with or without multicast settings. However, none of them is optimal. They either have a large packet overhead or are not robust to packet loss. Some even have a large receiver delay or require a large receiver buffer size. These schemes are constructed by trial-and-error methods. There lack tools to evaluate and compare their performances. There is no systematic way to construct these schemes either In this paper, we introduce the notion of dependence-graphs which links these hash-chained authentication schemes to the well-known graph theory, and provides an effective analytical tool. Many important metrics of a hash-chained authentication scheme can be readily and easily determined from its dependence-graph. As well, a dependence-graph demonstrates design tradeoff and provides insights into optimizing hash-chained schemes.