2962872
Finite element analysis of a class of stress-free martensitic microstructures
This work is concerned with the finite element approximation of a class of stress-free martensitic microstructures modeled by multi-well energy minimization. Finite element energy-minimizing sequences are first constructed to obtain bounds on the minimum energy over all admissible finite element deformations. A series of error estimates are then derived for finite element energy minimizers.
1669054
Nonconforming finite element approximation of crystalline microstructure
We consider a class of nonconforming nite element approxima- tions of a simply laminated microstructure which minimizes the nonconvex variational problem for the deformation of martensitic crystals which can un- dergo either an orthorhombic to monoclinic (double well) or a cubic to tetrag- onal (triple well) transformation. We rst establish a series of error bounds in terms of elastic energies for the L 2 approximation of derivatives of the de- formation in the direction tangential to parallel layers of the laminate, for the L 2 approximation of the deformation, for the weak approximation of the de- formation gradient, for the approximation of volume fractions of deformation gradients, and for the approximation of nonlinear integrals of the deformation gradient. We then use these bounds to give corresponding convergence rates for quasi-optimal nite element approximations.
15445828
Analysis of a class of nonconforming finite elements for crystalline microstructures
An analysis is given for a class of nonconforming Lagrange-type finite elements which have been successfully utilized to approximate the solution of a variational problem modeling the deformation of martensitic crystals with microstructure. These elements were first proposed and analyzed in 1992 by Rannacher and Turek for the Stokes equation. Our analysis highlights the features of these elements which make them effective for the computation of microstructure. New results for superconvergence and numerical quadrature are also given.
15806898
Market-driven bandwidth allocation in selfish overlay networks
Selfish overlay networks consist of autonomous nodes that develop their own strategies by optimizing towards their local objectives and self-interests, rather than following prescribed protocols. It is thus important to regulate the behavior of selfish nodes, so that system-wide properties are optimized. In this paper, we investigate the problem of bandwidth allocation in overlay networks, and propose to use a market-driven approach to regulate the behavior of selfish nodes that either provide or consume services. In such markets, consumers of services select the best service providers, taking into account both the performance and the price of the service. On the other hand, service providers are encouraged to strategically decide their respective prices in a pricing game, in order to maximize their economic revenues and minimize losses in the long run. In order to overcome the limitations of previous models towards similar objectives, we design a decentralized algorithm that uses reinforcement learning to help selfish nodes to incrementally adapt to the local market, and to make optimized strategic decisions based on past experiences. We have simulated our proposed algorithm in randomly generated overlay networks, and have shown that the behavior of selfish nodes converges to their optimal strategies, and resource allocations in the entire overlay are near-optimal, and efficiently adapts to the dynamics of overlay networks.
10610312
Semantic sports video analysis: approaches and new applications
In this paper, we show that event-based semantic analysis of sports video can be achieved through two major classes of methods: approaches using deterministic reasoning and approaches depending on probabilistic inference. Deterministic approaches depend on an explicit description of an event and an explicit representation of the event in terms of low-level aural-visual features that can be automatically detected. Probabilistic approaches are based on some proper state/transition models whose parameters are learnt through labeled training sequences. We first discuss the pros and cons of the two classes of approaches. Next, we present algorithms of these two types for a new application, automatic analysis of coaching video (which is different from sports broadcast programs that have been subject of most prior work).
12626074
Dynamic routing and wavelength assignment in the presence of wavelength conversion for all-optical networks
Blocking probability has been one of the key performance indexes in the design of wavelength-routed all-optical WDM networks. Existing research has demonstrated that an effective Routing and Wavelength Assignment (RWA) algorithm and wavelength conversion are two primary vehicles for improving the blocking performance. However, these two issues have largely been investigated separately; in particular the existing RWA algorithms have seldom considered the presence of wavelength conversion. In this paper, we firstly demonstrate that the existing dynamic RWA algorithms do not work well in the presence of wavelength conversion as they usually only take into account the current traffic, and do not explicitly consider the route lengths. We then propose a weighted least-congestion routing and first-fit wavelength assignment (WLCR-FF) algorithm that considers both the current traffic load and the route lengths jointly. We further introduce an analytical model that can evaluate the blocking performance for WLCR algorithm. We carry out extensive numerical studies over typical topologies including ring, mesh-torus, and the 14-node NSFNET; and compare the performance of WLCR-FF with a wide variety of existing routing algorithms including static routing, fixed-alternate routing and least-loaded routing. The results conclusively demonstrate that the proposed WLCR-FF algorithm can achieve much better blocking performance in the presence of sparse or/and full wavelength conversion.
8043231
QoS-Aware Adaptive Services in Mobile Ad-Hoc Networks
Ad-hoc wireless networks consist of mobile nodes interconnected by multi-hop wireless paths. Unlike conventional wireless networks, ad-hoc networks have no fixed network infrastructure or administrative support. Because of the dynamic nature of the network topology and limited bandwidth of wireless channels, Quality-of-Service (QoS) provisioning is an inherently complex and difficult issue. In this paper, we propose a fully distributed and adaptive algorithm to provide statistical QoS guarantees with respect to accessibility of services in an ad-hoc network. In this algorithm, we focus on the optimization of a new QoS parameter of interest, service efficiency, while keeping protocol overheads to the minimum. To achieve this goal, we first theoretically derive the lower and upper bounds of service efficiency based on a novel model for group mobility, followed by extensive simulation results to verify the effectiveness of our algorithm.
17742402
A Unicode-based Adaptive Segmenter
This paper presents a Unicode based Chinese word segmentor. It can handle Chinese text in Simplified, Traditional, or mixed mode. The system uses the strategy of divide-and-conquer to handle the recognition of personal names, numbers, time and numerical values, etc in the preprocessing stage. The segmentor further uses tagging information to work on disambiguation. Adopting a modular design approach, different functional parts are separately implemented using different modules and each module tackles one problem at a time providing more flexibility and extensibility. Results show that with added pre-processing modules and accessorial modules, the accuracy of the segmentor is increased and the system is easily adaptive to different applications.