38,312 research outputs found
Capturing Topology in Graph Pattern Matching
Graph pattern matching is often defined in terms of subgraph isomorphism, an
NP-complete problem. To lower its complexity, various extensions of graph
simulation have been considered instead. These extensions allow pattern
matching to be conducted in cubic-time. However, they fall short of capturing
the topology of data graphs, i.e., graphs may have a structure drastically
different from pattern graphs they match, and the matches found are often too
large to understand and analyze. To rectify these problems, this paper proposes
a notion of strong simulation, a revision of graph simulation, for graph
pattern matching. (1) We identify a set of criteria for preserving the topology
of graphs matched. We show that strong simulation preserves the topology of
data graphs and finds a bounded number of matches. (2) We show that strong
simulation retains the same complexity as earlier extensions of simulation, by
providing a cubic-time algorithm for computing strong simulation. (3) We
present the locality property of strong simulation, which allows us to
effectively conduct pattern matching on distributed graphs. (4) We
experimentally verify the effectiveness and efficiency of these algorithms,
using real-life data and synthetic data.Comment: VLDB201
Detecting Lesion Bounding Ellipses With Gaussian Proposal Networks
Lesions characterized by computed tomography (CT) scans, are arguably often
elliptical objects. However, current lesion detection systems are predominantly
adopted from the popular Region Proposal Networks (RPNs) that only propose
bounding boxes without fully leveraging the elliptical geometry of lesions. In
this paper, we present Gaussian Proposal Networks (GPNs), a novel extension to
RPNs, to detect lesion bounding ellipses. Instead of directly regressing the
rotation angle of the ellipse as the common practice, GPN represents bounding
ellipses as 2D Gaussian distributions on the image plain and minimizes the
Kullback-Leibler (KL) divergence between the proposed Gaussian and the ground
truth Gaussian for object localization. We show the KL divergence loss
approximately incarnates the regression loss in the RPN framework when the
rotation angle is 0. Experiments on the DeepLesion dataset show that GPN
significantly outperforms RPN for lesion bounding ellipse detection thanks to
lower localization error. GPN is open sourced at
https://github.com/baidu-research/GP
Mobile IP: state of the art report
Due to roaming, a mobile device may change its network attachment each time it moves to a new link. This might cause a disruption for the Internet data packets that have to reach the mobile node. Mobile IP is a protocol, developed by the Mobile IP Internet Engineering Task Force (IETF) working group, that is able to inform the network about this change in network attachment such that the Internet data packets will be delivered in a seamless way to the new point of attachment. This document presents current developments and research activities in the Mobile IP area
The effects of colloidal nanotopography on initial fibroblast adhesion and morphology
Colloidal lithography offers a simple, inexpensive method of producing irregular nanotopographies, a pattern not easily attainable utilizing conventional serial writing processes. Colloids with 20- or 50-nm diameter were utilized to produce such an irregular topography and were characterized by calculating the percentage area coverage of particles. Interparticle and nearest neighbor spacing were also assessed for the individual colloids in the pattern. Two-way analysis of variance (ANOVA) indicated significant differences between the number of fibroblasts adhering to planar, 20-, and 50-nm-diameter colloidal topographies, the number of fibroblasts adhering to the substrates at the time intervals studied, namely 20 min, 1 h, and 3 h and significant interaction between time and topography on fibroblast adhesion (P<0.01). Tukey tests were utilized for sensitive identification of the differences between the sample means and compounded ANOVA results. Cytoskeletal and general cell morphology were investigated on planar and colloidal substrates, and indicated cells in contact with irregular nanotopographies exhibit many peripheral protrusions while such protrusions are absent in cells on planar control surfaces. These protrusions are rich in microtubules on 20-nm-diameter colloidal surfaces while microfilaments are prevalent on 50-nm-diameter surfaces. Moreover, by 3 h, cells on the colloidal substrates initiate cell-cell adhesions, also absent in controls
Profit-aware Team Grouping in Social Networks: A Generalized Cover Decomposition Approach
In this paper, we investigate the profit-aware team grouping problem in
social networks. We consider a setting in which people possess different skills
and compatibility among these individuals is captured by a social network.
Here, we assume a collection of tasks, where each task requires a specific set
of skills, and yields a different profit upon completion. Active and qualified
individuals may collaborate with each other in the form of \emph{teams} to
accomplish a set of tasks. Our goal is to find a grouping method that maximizes
the total profit of the tasks that these teams can complete. Any feasible
grouping must satisfy the following three conditions: (i) each team possesses
all skills required by the task, (ii) individuals within the same team are
social compatible, and (iii) each individual is not overloaded. We refer to
this as the \textsc{TeamGrouping} problem. Our work presents a detailed
analysis of the computational complexity of the problem, and propose a LP-based
approximation algorithm to tackle it and its variants. Although we focus on
team grouping in this paper, our results apply to a broad range of optimization
problems that can be formulated as a cover decomposition problem
Cooperativity in sandpiles: statistics of bridge geometries
Bridges form dynamically in granular media as a result of spatiotemporal
inhomogeneities. We classify bridges as linear and complex, and analyse their
geometrical characteristics. In particular, we find that the length
distribution of linear bridges is exponential. We then turn to the analysis of
the orientational distribution of linear bridges and find that, in three
dimensions, they are {\it vertically diffusive but horizontally
superdiffusive}; thus, when they exist, long linear bridges form `domes'. Our
results are in good accord with Monte Carlo simulations of bridge structure; we
make predictions for quantities that are experimentally accessible, and suggest
that bridges are very closely related to force chains.Comment: 15 pages, 10 figures. Minor changes and update
Low Cost Quality of Service Multicast Routing in High Speed Networks
Many of the services envisaged for high speed networks, such as B-ISDN/ATM, will support real-time applications with large numbers of users. Examples of these types of application range from those used by closed groups, such as private video meetings or conferences, where all participants must be known to the sender, to applications used by open groups, such as video lectures, where partcipants need not be known by the sender. These types of application will require high volumes of network resources in addition to the real-time delay constraints on data delivery. For these reasons, several multicast routing heuristics have been proposed to support both interactive and distribution multimedia services, in high speed networks. The objective of such heuristics is to minimise the multicast tree cost while maintaining a real-time bound on delay. Previous evaluation work has compared the relative average performance of some of these heuristics and concludes that they are generally efficient, although some perform better for small multicast groups and others perform better for larger groups. Firstly, we present a detailed analysis and evaluation of some of these heuristics which illustrates that in some situations their average performance is reversed; a heuristic that in general produces efficient solutions for small multicasts may sometimes produce a more efficient solution for a particular large multicast, in a specific network. Also, in a limited number of cases using Dijkstra's algorithm produces the best result. We conclude that the efficiency of a heuristic solution depends on the topology of both the network and the multicast, and that it is difficult to predict. Because of this unpredictability we propose the integration of two heuristics with Dijkstra's shortest path tree algorithm to produce a hybrid that consistently generates efficient multicast solutions for all possible multicast groups in any network. These heuristics are based on Dijkstra's algorithm which maintains acceptable time complexity for the hybrid, and they rarely produce inefficient solutions for the same network/multicast. The resulting performance attained is generally good and in the rare worst cases is that of the shortest path tree. The performance of our hybrid is supported by our evaluation results. Secondly, we examine the stability of multicast trees where multicast group membership is dynamic. We conclude that, in general, the more efficient the solution of a heuristic is, the less stable the multicast tree will be as multicast group membership changes. For this reason, while the hybrid solution we propose might be suitable for use with closed user group multicasts, which are likely to be stable, we need a different approach for open user group multicasting, where group membership may be highly volatile. We propose an extension to an existing heuristic that ensures multicast tree stability where multicast group membership is dynamic. Although this extension decreases the efficiency of the heuristics solutions, its performance is significantly better than that of the worst case, a shortest path tree. Finally, we consider how we might apply the hybrid and the extended heuristic in current and future multicast routing protocols for the Internet and for ATM Networks.
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