28240465
Motion Tracking and Intensity Surface Recovery in Microscopic Nuclear Images
Current techniques for microscopic imaging do not provide necessary spatial and temporal resolutions for real time visualization of the nucleus. Images can only be acquired in time lapse mode, leading to significant loss of information between image frames. Such data, if available, can be extremely helpful in the study of nuclear organization and function. In this paper, we present a gamut of geometric-technique-based approaches for solving the problem. Our techniques, working together, can effectively recover complicated motion and deformation as well as the change of intensity surfaces from pairs of images in a microscopic image sequence, and has low time complexity, particularly desirable by many biological applications where large amount of DNA need to be processed. These techniques are also readily applicable to other types of images for reconstructing motion and intensity surfaces of deformable objects.
5727433
An Experimental Study and Comparison of Topological Peeling and Topological Walk
In this paper, we present an experimental study comparing two algorithms, topological peeling and topological walk, for traversing arrangements of planar lines. Given a set H of n lines and a convex region R on a plane, both topological peeling and topological walk sweep the portion AR of the arrangement of H inside R in O(K + n log(n + r)) time and O(n + r) space, where K is the number of cells of AR and r is the number of boundary vertices of R. In our study, we robustly implemented these two algorithms using the LEDA library. Based on the implementation, we carried out experiments to conduct several comparisons, such as the arrangement traversal fashions, memory consumption, and execution time. In general, topological peeling exhibits a better control on the propagation of its sweeping curve (called the wavefront). For memory consumption, two types of measures, logical and physical memory, were examined. Our experiments showed that although both algorithms use nearly the same amount of logical memory, topological peeling could use twice as much physical memory as topological walk. For execution time, experiments revealed an interesting phenomenon that topological peeling has a 10% to 25% faster execution time than topological walk in most cases. Our analysis of this phenomenon indicates that the execution times of topological peeling and topological walk are both sensitive to the ratio of the lower input lines to all input lines. When the ratio of the lower lines to all input lines is around 85%, the two algorithms have roughly the same amount of execution time. Under this ratio, topological peeling considerably outperforms topological walk; above this ratio, topological walk slightly outperforms topological peeling.
21098955
Topological Peeling and Implementation
We present a new approach, called topological peeling, and its implementation for traversing a portion AR of the arrangement formed by n lines within a convex region R on the plane. Topological peeling visits the cells of AR in a fashion of propagating a "wave" of a special shape (called a double-wriggle curve) starting at a single source point. This special traversal fashion enables us to solve several problems (e.g., computing shortest paths) on planar arrangements to which previously best known arrangement traversal techniques such as topological sweep and topological walkm ay not be directly applicable. Our topological peeling algorithm takes O(K + n log(n + r)) time and O(n + r) space, where K is the number of cells in AR and r is the number of boundary vertices of R. Comparing with topological walk, topological peeling uses a simpler and more efficient way to sweep different types of lines, and relies heavily on exploring small local structures, rather than a much larger global structure. Experiments show that, on average, topological peeling outperforms topological walkb y 10 - 15% in execution time.
6260724
Finding an optimal path without growing the tree
For problems on computing an optimal path as well as its length in a certain setting, the "standard" approach for finding an actual optimal path is by building (or "growing") a single-source optimal path tree. In this paper, we study a class of optimal path problems with the following phenomenon: The space complexity of the algorithms for reporting the lengths of single-source optimal paths for these problems is asymptotically smaller than the space complexity of the "standard" tree-growing algorithms for finding actual optimal paths. We present a general and efficient algorithmic paradigm for finding an actual optimal path for such problems without having to grow a single-source optimal path tree. Our paradigm is based on the "marriage-before-conquer" strategy, the prune-and-search technique, and a new data structure called clipped trees. The paradigm enables us to compute an actual path for a number of optimal path problems and dynamic programming problems in computational geometry, graph theory, and combinatorial optimization. Our algorithmic solutions improve the space bounds (in certain cases, the time bounds as well) of the previously best known algorithms, and settle some open problems. Our techniques are likely to be applicable to other problems.
29728094
Graph Bandwidth of Weighted Caterpillars
Graph bandwidth minimization (GBM) is a classical and challenging problem in graph algorithms and combinatorial optimization. Most of existing researches on this problem have focused on unweighted graphs. In this paper, we study the bandwidth minimization problem of weighted caterpillars, and propose several algorithms for solving various types of caterpillars and general graphs. More specifically, we show that the GBM problem on caterpillars with hair-length at most 2 and the GBM problem on star-shape caterpillars are NP-complete, and give a lower bound of the graph bandwidth for general weighted graphs. For caterpillars with hair-length at most 1, we present an O(n log n log(nwmax))-time algorithm to compute an optimal bandwidth layout, where n is the total number of vertices in the graph and wmax is the maximum wedge weight. For caterpillars with hair-length at most k, we give a k-approximation algorithm. For arbitrary caterpillars and general graphs, we give a heuristic algorithm and some experimental results. Experiments show that the solutions obtained by our heuristic algorithm are roughly within a factor of c log(n) of the lower bound for a small number c, which is consistent with the inapproximability results of this problem (i.e., no constant approximation for the GBM problem unless P = NP). © 2006 Published by Elsevier B.V.
14297439
Geometric permutations of high dimensional spheres
We prove the maximum number of geometric permutations, induced by line transversals to a set of <i>n</i> pairwise disjoint congruent spheres in <i>R<sup>d</sup></i> with <i>d</i> ⪈ 3, is no more than 4 when <i>n</i> is sufficiently large, achieving the best known upper bound for this problem. We also prove the maximum number of geometric permutations of a set of <i>n</i> noncongruent spheres of bounded radius ratio in R<sup>d</sup>, <i>d</i> ⪈ 3, is at most 2<sup>[√2<i>M</i>]+1</sup>, where <i>M</i> is the ratio or the largest radius and the smallest radius. Our result settles a conjecture in combinatorial geometry.
1351954
Cost-Sensitive Learning of SVM for Ranking
In this paper, we propose a new method for learning to rank. ‘Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classification on instance pairs and performs the classification by means of Support Vector Machines (SVM). In Ranking SVM, the losses for incorrect classifications of instance pairs between different rank pairs are defined as the same. We note that in many applications such as information retrieval the negative effects of making errors between higher ranks and lower ranks are larger than making errors among lower ranks. Therefore, it is natural to bring in the idea of cost-sensitive learning to learning to rank, or more precisely, to set up different losses for misclassification of instance pairs between different rank pairs. Given a cost-sensitive loss function we can construct a Ranking SVM model on the basis of the loss function. Simulation results show that our method works better than Ranking SVM in practical settings of ranking. Experimental results also indicate that our method can outperform existing methods including Ranking SVM on real information retrieval tasks such as document search and definition search.
7639532
Fault diameter of Cartesian product graphs
The (k-1)-fault diameter D"k(G) of a k-connected graph G is the maximum diameter of G-F for any F@?V(G) with |F|=1 for i=1,2.
1896644
Sketch Guided Sampling - Using On-Line Estimates of Flow Size for Adaptive Data Collection
Monitoring the traffic in high-speed networks is a data intensive problem. Uniform packet sampling is the most popular technique for reducing the amount of data the network monitoring hardware/software has to process. However, uniform sampling captures far less information than can be potentially obtained with the same overall sampling rate. This is because uni- form sampling (unnecessarily) draws the vast majority of samples from large flows, and very few from small and medium flows. This information loss on small and medium flows significantly affects the accuracy of the estimation of various network statistics. In this work, we develop a new packet sampling methodol- ogy called "sketch-guided sampling" (SGS), which offers better statistics than obtainable from uniform sampling, given the same number of raw samples gathered. Its main idea is to make the probability with which an incoming packet is sampled a decreasing sampling function f of the size of the flow the packet belongs to. This way our scheme is able to significantly increase the packet sampling rate of the small and medium flows at slight expense of the large flows, resulting in much more accurate estimations of various network statistics. However, the exact sizes of all flows are available only if we keep per-flow information for every flow, which is prohibitively expensive for high-speed links. Our SGS scheme solves this problem by using a small (lossy) synopsis data structure called counting sketch to encode the approximate sizes of all flows. Our evaluation on real-world Internet traffic traces shows that our sampling theory based the approximate flow size estimates from the counting sketch works almost as well as if we know the exact sizes of the flows.
2775894
Rigorous development of a safety-critical system based on coordinated atomic actions
This paper describes our experience using coordinated atomic (CA) actions as a system structuring tool to design and validate a sophisticated control system for a complex industrial application that has high reliability and safety requirements. Our study is based on the "Fault-Tolerant Production Cell", which represents a manufacturing process involving redundant mechanical devices (provided in order to enable continued production in the presence of machine faults). The challenge posed by the model specification is to design a control system that maintains specified safety and liveness properties even in the presence of a large number and variety of device and sensor failures. We discuss in this paper: i) a design for a control program that uses CA actions to deal with both safety-related and fault tolerance concerns, and ii) the formal verification of this design based on the use of model-checking. We found that CA action structuring facilitated both the design and verification tasks by enabling the various safety problems (e.g. clashes of moving machinery) to be treated independently. The formal verification activity was performed in parallel with the design activity the interaction between them resulted in a combined exercise in "design for validation".
17341019
Automatically detecting criminal identity deception: an adaptive detection algorithm
Identity deception, specifically identity concealment, is a serious problem encountered in the law enforcement and intelligence communities. In this paper, the authors discuss techniques that can automatically detect identity deception. Most of the existing techniques are experimental and cannot be easily applied to real applications because of problems such as missing values and large data size. The authors propose an adaptive detection algorithm that adapts well to incomplete identities with missing values and to large datasets containing millions of records. The authors describe three experiments to show that the algorithm is significantly more efficient than the existing record comparison algorithm with little loss in accuracy. It can identify deception having incomplete identities with high precision. In addition, it demonstrates excellent efficiency and scalability for large databases. A case study conducted in another law enforcement agency shows that the authors' algorithm is useful in detecting both intentional deception and unintentional data errors