15424500
Semantically modified diffusion limited aggregation for visualizing large-scale networks
Diffusion-limited aggregation (DLA) is a model of fractal growth. Computer models can simulate the fast aggregation of millions of particles. We propose a modified version of DLA, called semantically modified DLA (SM-DLA), for visualizing large-scale networks. SM-DLA introduces similarity measures between particles so that instead of attaching to the nearest particle in the aggregation, a new particle is stochastically directed to attach to particles that are similar to it. The results of our initial experiment with a co-citation network using SM-DLA are encouraging, suggesting that the algorithm has the potential as an alternative paradigm for visualizing large-scale networks. Further studies in this direction are recommended.
982985
Visualizing and tracking the growth of competing paradigms: Two case studies
In this article we demonstrate the use of an integrative approach to visualizing and tracking the development of scientific paradigms. This approach is designed to reveal the long-term process of competing scientific paradigms. We assume that a cluster of highly cited and cocited scientific publications in a cocitation network represents the core of a predominant scientific paradigm. The growth of a paradigm is depicted and animated through the rise of citation rates and the movement of its core cluster towards the center of the cocitation network. We study two cases of competing scientific paradigms in the real world: (1) the causes of mass extinctions, and (2) the connections between mad cow disease and a new variant of a brain disease in humans — vCJD. Various theoretical and practical issues concerning this approach are discussed.
14518854
Detecting and mapping thematic changes in transient networks
Research fronts are the forefront of a scientific field timely identifying emerging trends and abrupt changes in scientific literature is not only beneficial for users of digital libraries, but also instrumental for users to trace the movement of a research front. A research front can be seen as a dynamic and transient mapping from the state of the art to its immediate prior art - the intellectual base. Citation and co-citation analysis primarily focuses on the structure and dynamics of the intellectual base, information retrieval and related research mainly focuses on intrinsic properties of text documents. In this article, we describe a novel approach that enables us to detect and visualize the transient relationship over time. Temporal associations between content words connected to a surge of interest in scientific papers and high-impact articles in the intellectual base are identified and visualized as a time-variant network. We apply the approach to the detection of thematic changes over time in information visualization and research in terrorism.
16331940
Optimal Parallel Routing in Star Networks
Star networks have recently been proposed as attractive alternatives to the popular hypercube for interconnecting processors on a parallel computer. In this paper, we present an efficient algorithm that constructs an optimal parallel routing in star networks. Our result improves previous results for the problem.
5472476
Image Stitching - Comparisons and New Techniques
This work describes the steps involved in the generation of a panoramic image, i.e., image acquisition, image registration and image merging. Different approaches for each of these steps are discussed and compared. The resultant images from image registration and image merging are quantitatively evaluated to provide an indication to the performance of the different methods. The methods provided in this work can be used to generate panoramic images for the use of interactive panoramic viewing of images, architectural walk-through, and other applications associated with the modelling of 3D environments.
393866
Adaptive discretization for probabilistic model building genetic algorithms
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization problems in the continuous domain. The procedure, effect, and usage of SoD are described in detail. As an example, the integration of SoD and the extended compact genetic algorithm (ECGA), named real-coded ECGA (rECGA), is presented and numerically examined. The experimental results indicate that rECGA works well and SoD is effective. The behavior of SoD is analyzed and discussed, followed by the potential future work for SoD.
12972622
DIKNN: An Itinerary-based KNN Query Processing Algorithm for Mobile Sensor Networks
Current approaches to k nearest neighbor (KNN) search in mobile sensor networks require certain kind of indexing support. This index could be either a centralized spatial index or an in-network data structure that is distributed over the sensor nodes. Creation and maintenance of these index structures, to reflect the network dynamics due to sensor node mobility, may result in long query response time and low battery efficiency, thus limiting their practical use. In this paper, we propose a maintenance-free, itinerary-based approach called density-aware itinerary KNN query processing (DIKNN). The DIKNN divides the search area into multiple cone-shape areas centered at the query point. It then performs a query dissemination and response collection itinerary in each of the cone-shape areas in parallel. The design of the DIKNN scheme also takes into account challenging issues such as the the dynamic adjustment of the search radius (in terms of number of hops) according to spatial irregularity or mobility of sensor nodes. The simulation results show that DIKNN yields substantially better performance and scalability over previous work, both as k increases and as the sensor node mobility increases. It outperforms the second runner with up to 50% saving in energy consumption and up to 40% reduction in query response time, while rendering the same level of query result accuracy.
2976234
Spec-based repeater insertion and wire sizing for on-chip interconnect
Recently Lillis, et al. (see Proc. Custom Integrated Conf., p. 259-262, May 1995) presented an elegant dynamic programming approach to RC interconnect delay optimization through driver sizing, repeater insertion, and, wire sizing which employs the Elmore delay model for RC delay estimation and a crude repeater delay model. This approach, however, ignores an equally important aspect of interconnect optimization: transition time constraints at the sinks. More importantly, Elmore delay techniques because of their inherent inaccuracy are not suited to spec-based design which is directed towards synthesizing nets with user-specified delay/transition time requirements at the sinks. In this paper we present techniques for delay and transition time optimization for RC nets in the context of accurate moment-matching techniques for computing the RC delays and transition times, and an accurate driver/repeater delay model. The asymptotic increase in runtime over the Elmore delay model is O(q/sup 2/) where q is the order of the moment-matching approximation. Experiments on industrial nets indicate that this increase in runtime is acceptable. Our algorithm yields delay and transition time estimates within 5% of circuit simulation results.