A Robust Error Concealment Algorithm in Wireless Networks
Compressed video sequences are very vulnerable to channel disturbances when transmitted through the burst-packet-loss wireless channels. Transmission errors not only corrupt the current frame, but may also propagate to succeeding frames. We find that a number of current proposed post-processing error concealment methods exploit the spatial/temporal redundancy in the video stream can not actually conceal the transmission errors effectively, because they ignored the fact that the neighboring blocks can be easily lost by the burst packet losses and the correlation was considered only in the current frame, which all limited the ability to obtain an optimal recovery. In this paper, a novel error concealment algorithm is proposed for video transmissions in a wireless environment. Simulation proves that the proposed algorithm can be chosen as good trade-off between video quality and computational load in wireless networks.

title: Adaptive Video Streaming over P2P Multi-Hop Path

title: An Optimal Node Selection Scheme in Multi-hop Wireless Network
abstract: In this paper, a cooperative wireless multi-hop network is considered, cooperative diversity can be realized by allowing nodes close proximity to cooperate in transmission. In order to group receiver nodes into a cluster, it is necessary to select appropriate nodes. We introduce an optimal node selection algorithm based on MIMO antenna selection, this algorithm, combining with cooperative transmission strategy, gives an optimal node selection algorithm using convex optimization theory. Theoretical analysis and simulation indicate that this scheme can give good performance of maximizing the channel capacity through optimal node selection.

title: Unexpected means of protocol inference
abstract: Network managers are inevitably called upon to associate network traffic with particular applications. Indeed, this operation is critical for a wide range of management functions ranging from debugging and security to analytics and policy support. Traditionally, managers have relied on application adherence to a well established global port mapping: Web traffic on port 80, mail traffic on port 25 and so on. However, a range of factors - including firewall port blocking, tunneling, dynamic port allocation, and a bloom of new distributed applications - has weakened the value of this approach. We analyze three alternative mechanisms using statistical and structural content models for automatically identifying traffic that uses the same application-layer protocol, relying solely on flow content. In this manner, known applications may be identified regardless of port number, while traffic from one unknown application will be identified as distinct from another. We evaluate each mechanism's classification performance using real-world traffic traces from multiple sites.

title: Fast interval-valued statistical modeling of interconnect and effective capacitance
abstract: Correlated interval representations of range uncertainty offer an attractive solution to approximating computations on statistical quantities. The key idea is to use finite intervals to approximate the essential mass of a probability density function (pdf) as it moves through numerical operators; the resulting compact interval-valued solution can be easily interpreted as a statistical distribution and efficiently sampled. This paper first describes improved interval-valued algorithms for asymptotic wave evaluation (AWE)/passive reduced-order interconnect macromodeling algorithm (PRIMA) model order reduction for tree-structured interconnect circuits with correlated resistance, inductance, and capacitance (RLC) parameter variations. By moving to a much faster interval-valued linear solver based on path-tracing ideas, and making more optimal tradeoffs between interval- and scalar-valued computations, the delay statistics roughly 10/spl times/ faster than classical Monte Carlo (MC) simulation, with accuracy to within 5% can be extracted. This improved interval analysis strategy is further applied in order to build statistical effective capacitance (C/sub eff/) models for variational interconnect, and show how to extract statistics of C/sub eff/ over 100/spl times/ faster than classical MC simulation, with errors less than 4%.

title: A Gradient BYY Harmony Learning Algorithm on Mixture of Experts for Curve Detection
abstract: Curve detection is a basic problem in image processing and has been extensively studied in the literature. However, it remains a difficult problem. In this paper, we study this problem from the Bayesian Ying-Yang (BYY) learning theory via the harmony learning principle on a BYY system with the mixture of experts (ME). A gradient BYY harmony learning algorithm is proposed to detect curves (straight lines or circles) from a binary image. It is demonstrated by the simulation and image experiments that this gradient algorithm can not only detect curves against noise, but also automatically determine the number of straight lines or circles during parameter learning.

title: The capacity of time-delay recurrent neural network for storing spatio-temporal sequences
abstract: We investigate the capacity of a type of discrete-time recurrent neural network, called time-delay recurrent neural network, for storing spatio-temporal sequences. By introducing the order of a spatio-temporal sequence, the match law between a time-delay recurrent neural network and a spatio-temporal sequence has been established. It has been proved that the full order time-delay recurrent neural network of l-step feedback is able to learn and memorize (or store) any bipolar (or binary) spatio-temporal sequence of the order k if k≤l, and that the asymptotic memory capacity of the first-order time-delay recurrent neural network of one-step feedback is not less than C1(n)=n+1, where n is the number of processing neurons in the network. Moreover, we substantiate the theoretical results by simulation experiments.

title: A genetic algorithm for optimal 3-connected telecommunication network designs
abstract: In this paper, a genetic algorithm for three connected telecommunication network designs is proposed. The genetic algorithm uses a new approach to solution representation, in which constraints such as diameter and connectivity constraints can be easily encoded and two-point crossover with the operation of swapping duplicated nodes ensures solutions generated through genetic evolution are all feasible so that both checking of the constraints and repair mechanism can be avoided. Both efficiency and effectiveness are increased due to no checking of the constraints and no repair mechanism conducted. In fact, our design algorithm for three-connected network design can he extended to a high-connectivity network design.