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.
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.
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.
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
2252341
Capacity of noncoherent time-selective Rayleigh-fading channels
The capacity of noncoherent time-selective Rayleigh-fading channels is studied under various models for the variations in time. The study includes both single-input and single-output (SISO) and multiple-input and multiple-output (MIMO) systems. A block-fading model is first considered where the channel changes correlatively over each block period of length T, and independently across blocks. The predictability of the channel is characterized through the rank Q of the correlation matrix of the vector of channel gains in each block. This model includes, as special cases, the standard block-fading model where the channel remains constant over block periods (Q=1), and models where the fading process has finite differential entropy rate (Q=T). The capacity is initially studied for long block lengths and some straightforward but interesting asymptotes are established. For the case where Q is kept fixed as T/spl rarr//spl infin/, it is shown that the noncoherent capacity converges to the coherent capacity. For the case where both T,Q/spl rarr//spl infin/, with Q/T being held constant, a bound on the capacity loss due to channel unpredictability is established. The more interesting scenario of large signal-to-noise ratio (SNR) is then explored in detail. For SISO systems, useful upper and lower bounds on the large SNR asymptotic capacity are derived, and it is shown that the capacity grows logarithmically with SNR with a slope of T-Q/spl rarr/T, for Q<T. Next, in order to facilitate the analysis of MIMO systems, the rank-Q block-fading model is specialized to the case where each T-symbol block consists of Q subblocks of length L, with the channel remaining constant over each subblock and changing correlatively across subblocks. For this model, it is shown that the log SNR growth behavior of the capacity is the same as that of the standard block-fading model with block length L. Finally, the SISO and MIMO channel models are generalized to allow the fading process to be correlated across blocks in a stationary and ergodic manner. It is shown that the log SNR growth behavior of the capacity is not affected by the correlation across blocks.
41985683
Constraint Satisfaction In "Conscious" Software Agents--A Practical Application
ABSTRACT The U.S. Navy has been trying for many years to automate its personnel assignment process. Periodic assignment of personnel to new jobs is mandatory according to Navy policy. Though various software systems are used regularly, the process is mainly done manually and sequentially by Navy personnel called detailers. This paper is a case study in applying cognitive theories implemented via new AI techniques to produce flexible adaptive human-like software. In it we present a sketch of an intelligent distribution agent that aims to largely automate the detailer's tasks. In particular, we look inside its constraint satisfaction, which is mainly responsible for satisfying the requirements of the Navy's policies, the command's needs, and the sailor's preferences in order to achieve “satisfactory” job assignments, according to ever-evolving Navy standards.
7289490
Low-latency video transmission over lossy packet networks using rate-distortion optimized reference picture selection
Today's Internet video streaming systems employ buffering and multiple retransmissions to guarantee the correct reception of each packet, which leads to high latency in media delivery. In this work, a novel scheme of dynamic management of the dependency across packets is proposed using optimal reference picture selection at the frame level that adapts to the channel. The optimal selection of the reference picture is achieved with a rate-distortion framework, which minimizes the expected end-to-end distortion given a rate constraint. The expected distortion is calculated based on an accurate binary tree modeling with the effects of channel loss and error concealment taken into account. Experiments demonstrate that the proposed :scheme provides significant performance gains over a simple INTRA-insertion scheme. The increased error-resilience eliminates the need of retransmission, which makes it possible to reduce the latency from 10-15 seconds to a few hundred milliseconds, with similar video quality maintained.
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.