17534707
Upfront intra-refresh decision for low-complexity wireless video telephony
An adaptive intra-refresh (IR) technique is proposed for low-complexity video encoding on resource-constrained wireless platforms. The IR decision is made upfront without requiring any pre-encoding, which significantly reduces the complexity and power consumption in real-time communication. To allow upfront mode decision, a novel closed-form solution is provided requiring no algorithmic iteration or exhaustive searches. The IR scheme adapts to multiple factors including the content texture information, the frame-to-frame pixel-value variation, and the estimated channel loss probability. The macroblock-based refresh can be performed using various patterns (i.e., cyclic, random etc.). Experimental results demonstrate superior performance of the adaptive scheme over fixed schemes at all channel loss rates
18455016
Channel-adaptive video streaming using packet path diversity and rate-distortion optimized reference picture selection
In this paper, we present error-resilient Internet video transmission using path diversity and rate-distortion optimized reference picture selection. Under this scheme, the optimal packet dependency is determined adapting to channel characteristics and video content, to achieve a better trade-off between coding efficiency and forming independent streams to increase error resilience. Packets are sent over the selected path that minimizes the distortion, while taking advantage of path diversity. Experiments demonstrate that the proposed scheme provides significant gains over video redundancy coding and the NACK mode of conventional reference picture selection.
1136997
Cooperative Relay Broadcast Channels
The capacity regions are investigated for two relay broadcast channels (RBCs), where relay links are incorporated into two-user broadcast channels to support user cooperation. In the first channel, the partially cooperative RBC, only one user in the system acts as a relay. An achievable rate region is derived based on the relay using the decode-and-forward scheme. An outer bound on the capacity region is derived and is shown to be tighter than the cut-set bound. For the special case where the partially cooperative RBC is degraded, the achievable rate region is shown to be the capacity region. Two Gaussian cases of the partially cooperative RBC are studied. For the system where the additive white Gaussian noise (AWGN) term at one receiver is a degraded version of the other, which we refer to as the D-AWGN partially cooperative RBC, the capacity region is established. For the system where the AWGN term at one receiver is independent of the other, which we refer to as the AWGN partially cooperative RBC, inner and outer bounds on the capacity region are derived and are shown to be close. Furthermore, it is shown that feedback does not increase the capacity region for the degraded partially cooperative RBC, but that it improves the capacity region for the nondegraded version. In particular, feedback improves the capacity region for the AWGN partially cooperative RBC. In the second channel model being studied in the paper, the fully cooperative RBC, both users can act as relay nodes. All the results for the partially cooperative RBC are correspondingly generalized to the fully cooperative RBC. In particular, capacity regions are established for the degraded and D-AWGN fully cooperative RBCs. The capacity region is also established for the fully cooperative RBC with feedback. It is further shown that the AWGN fully cooperative RBC has a larger achievable rate region than its partially cooperative counterpart. The results illustrate that relaying and user cooperation are powerful techniques for improving the capacity of broadcast channels
38500613
On the Feedback Vertex Set Problem in Permutation Graphs
Abstract Brandstadt and Kratsch (1987) presented an O( n 6 ) time algorithm for the minimum weight feedback vertex set problem in a permutation graph of n vertices and m edges. This result was recently improved to O( n.m.m ) by Brandstat (1993), where m is the number of edges in the complement of G . In this paper, we employ a different dynamic programming scheme to reduce the time complexity to O( nm ) for this problem in permutation graphs.
18261713
Differential and trajectory methods for time course gene expression data
MOTIVATION
The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differentiation approaches can reduce the dimensions of data, help to remove redundant genes and noises, and highlight the most relevant genes that are major players in the development of certain diseases or the effect of drug treatment. The purpose of this study is to investigate the efficiency of parametric (including Bayesian and non-Bayesian, linear and non-linear), non-parametric and semi-parametric gene filtering methods through the application of time course microarray data from multiple sclerosis patients being treated with interferon-beta-1a. The analysis of variance with bootstrapping (parametric), class dispersion (semi-parametric) and Pareto (non-parametric) with permutation methods are presented and compared for filtering and finding differentially expressed genes. The Bayesian linear correlated model, the Bayesian non-linear model the and non-Bayesian mixed effects model with bootstrap were also developed to characterize the differential expression patterns. Furthermore, trajectory-clustering approaches were developed in order to investigate the dynamic patterns and inter-dependency of drug treatment effects on gene expression.


RESULTS
Results show that the presented methods performed significant differently but all were adequate in capturing a small number of the potentially relevant genes to the disease. The parametric method, such as the mixed model and two Bayesian approaches proved to be more conservative. This may because these methods are based on overall variation in expression across all time points. The semi-parametric (class dispersion) and non-parametric (Pareto) methods were appropriate in capturing variation in expression from time point to time point, thereby making them more suitable for investigating significant monotonic changes and trajectories of changes in gene expressions in time course microarray data. Also, the non-linear Bayesian model proved to be less conservative than linear Bayesian correlated growth models to filter out the redundant genes, although the linear model showed better fit than non-linear model (smaller DIC). We also report the trajectories of significant genes-since we have been able to isolate trajectories of genes whose regulations appear to be inter-dependent.
10881008
Steiner Set and Connected Domination in Trapezoid Graphs
Abstract Trapezoid graphs are extensions of interval graphs and permutation graphs. This paper presents an O (¦V¦) time algorithm for finding a minimum cardinality Steiner set and an O (¦E¦ + ¦V¦) time algorithm for finding a minimum cardinality connected dominating set in a trapezoid graph G = ( V , E ), given the trapezoid diagram.
23159718
Efficient Algorithms for Finding Depth-First and Breadth-First Search Trees in Permutation Graphs
This paper presents an O(n log log n) time algorithm for finding a depth-first search tree and an O(n) time algorithm for finding a breadth-first search tree in a permutation graph, respectively.