BACKGROUND: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustment methods for multiple comparisons such as family-wise error rate (FWER) have been found to be too conservative in analyzing large-screening microarray data, and the False Discovery Rate (FDR), the expected proportion of false positives among all positives, has been recently suggested as an alternative for controlling false positives. Several statistical approaches have been used to estimate and control FDR, but these may not provide reliable FDR estimation when applied to microarray data sets with a small number of replicates. RESULTS: We propose a rank-invariant resampling (RIR) based approach to FDR evaluation. Our proposed method generates a biologically relevant null distribution, which maintains similar variability to observed microarray data. We compare the performance of our RIR-based FDR estimation with that of four other popular methods. Our approach outperforms the other methods both in simulated and real microarray data. CONCLUSION: We found that the SAM's random shuffling and SPLOSH approaches were liberal and the other two theoretical methods were too conservative while our RIR approach provided more accurate FDR estimation than the other approaches.

Abstract We present a novel multi‐resolution algorithm for simulation of complex cloth‐like deforming meshes. Our algorithm precomputes a multi‐resolution hierarchy by using a combination of ‘chromatic decomposition’1and polygonal simplification of the underlying mesh. At runtime we selectively refine or coarsen the mesh based on the collision proximity of the mesh primitives with non‐adjacent primitives. Our algorithm handles all kind of contacts, including self collisions among mesh primitives. The multi‐resolution hierarchy is used to compute simplification of contact manifolds and to accelerate collision detection and response computations. We have implemented our algorithm on a high‐end PC and applied it to complex simulations with tens of thousands of polygons. In practice, our algorithm is able to achieve interactive performance, while maintaining good visual fidelity. Copyright © 2005 John Wiley & Sons, Ltd.

We present a novel algorithm for accurately detecting all contacts, including self-collisions, between deformable models. We precompute a chromatic decomposition of a mesh into non-adjacent primitives using graph coloring algorithms. The chromatic decomposition enables us to check for collisions between non-adjacent primitives using a linear-time culling algorithm. As a result, we achieve higher culling efficiency and significantly reduce the number of false positives. We use our algorithm to check for collisions among complex deformable models consisting of tens of thousands of triangles for cloth modeling and medical simulation. Our algorithm accurately computes all contacts at interactive rates. We observed up to an order of magnitude speedup over prior methods.

Surface texture is among the most salient haptic characteristics of objects; it can induce vibratory contact forces that lead to perception of roughness. We present a new algorithm to display haptic texture information resulting from the interaction between two textured objects. We compute contact forces and torques using low-resolution geometric representations along with texture images that encode surface details. We also introduce a novel force model based on directional penetration depth and describe an efficient implementation on programmable graphics hardware that enables interactive haptic texture rendering of complex models. Our force model takes into account important factors identified by psychophysics studies and is able to haptically display interaction due to fine surface textures that previous algorithms do not capture.

Abstract To improve response time of a Web site, one replicates the site on multiple servers. The effectiveness of a replicated server system will depend on how the incoming requests are distributed among replicas. A large number of load‐balancing strategies for Web server systems have been proposed. In this paper we describe a testbed that can be used to evaluate the performance of different load‐balancing strategies. The testbed uses a general architecture which allows different load‐balancing approaches to be supported easily. It emulates a typical World Wide Web scenario and allows variable load generation and performance measurement. We have performed some preliminary experiments to measure the performance of a few policies for load balancing using this testbed. Copyright © 2003 John Wiley & Sons, Ltd.

MOTIVATION: In microarray studies gene discovery based on fold-change values is often misleading because error variability for each gene is heterogeneous under different biological conditions and intensity ranges. Several statistical testing methods for differential gene expression have been suggested, but some of these approaches are underpowered and result in high false positive rates because within-gene variance estimates are based on a small number of replicated arrays. RESULTS: We propose to use local-pooled-error (LPE) estimates and robust statistical tests for evaluating significance of each gene's differential expression. Our LPE estimation is based on pooling errors within genes and between replicate arrays for genes in which expression values are similar. We have applied our LPE method to compare gene expression in naïve and activated CD8+ T-cells. Our results show that the LPE method effectively identifies significant differential-expression patterns with a small number of replicated arrays. AVAILABILITY: The methodology is implemented with S-PLUS and R functions available at http://hesweb1.med.virginia.edu/bioinformatics

We propose a CSMA-based medium access control protocol for multihop wireless networks that uses multiple channels and a dynamic channel selection method. The proposed protocol uses one control channel and N data channels, where N is independent of the number of nodes in the network. The source uses an exchange of control packets on the control channel to decide on the best channel to send the data packet on. Channel selection is based on maximizing the signal-to-interference plus noise ratio at the receiver. We present performance evaluations obtained from simulations that demonstrate the effectiveness of the proposed protocol.

We present a protocol for managing mobile wireless ad hoc networks. The protocol uses hierarchical clustering of nodes to reduce the number of messages exchanged between the manager and the agents (mobiles). Clustering also enables the network to keep track of mobiles as they roam. The ad hoc network management protocol (ANMP) is fully compatible with simple management protocol, version 3 (SNMPv3) and uses the same protocol data units (PDUs) for data collection. The protocol also implements sophisticated security mechanisms that can be fine-tuned to meet specific requirements. Finally, we have implemented the protocol along with a graphical user interface that allows a manager to change the view or specify management parameters on the fly.