Steve Liu
Texas A&M University
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Publication
Featured researches published by Steve Liu.
Nucleic Acids Research | 2005
Zhanyou Xu; Marco A. van den Berg; Chantel F. Scheuring; Lina Covaleda; Hong Lu; Felipe A. Santos; Taesik Uhm; Mi-Kyung Lee; Chengcang Wu; Steve Liu; Hong-Bin Zhang
Physical mapping with large-insert clones is becoming an active area of genomics research, and capillary electrophoresis (CE) promises to revolutionize the physical mapping technology. Here, we demonstrate the utility of the CE technology for genome physical mapping with large-insert clones by constructing a robust, binary bacterial artificial chromosome (BIBAC)-based physical map of Penicillium chrysogenum. We fingerprinted 23.1x coverage BIBAC clones with five restriction enzymes and the SNaPshot kit containing four fluorescent-ddNTPs using the CE technology, and explored various strategies to construct quality physical maps. It was shown that the fingerprints labeled with one or two colors, resulting in 40-70 bands per clone, were assembled into much better quality maps than those labeled with three or four colors. The selection of fingerprinting enzymes was crucial to quality map construction. From the dataset labeled with ddTTP-dROX, we assembled a physical map for P.chrysogenum, with 2-3 contigs per chromosome and anchored the map to its chromosomes. This map represents the first physical map constructed using the CE technology, thus providing not only a platform for genomic studies of the penicillin-producing species, but also strategies for efficient use of the CE technology for genome physical mapping of plants, animals and microbes.
IEEE Transactions on Geoscience and Remote Sensing | 1999
Lei Zheng; Andrew K. Chan; Steve Liu; Walter H. F. Smith; Ronald J. Holyer
Aerial images are one of the primary data sources for underwater oceanographic studies. These images are often corrupted by clutter induced by surface water waves. Removal of the wave clutter from these images is an important preprocessing step for accurate assessment of information. In this paper, we introduce a novel technique combining the X-ray wavelet transform (XWT) with Markov random field (MRF) for directional noise removal. Surface water waves are classified according to their features into two types: ripple wave (long-wave) and spark wave (short-wave). We show in our numerical experiments that by performing XWT along the direction of wave propagation, the wave clutter can he successfully detected. To remove long-waves, resampling and subband filtering techniques are used. To remove short-waves, on the other hand, a spectral-spatial maximum exclusive mean (SMEM) filter is used in this study. Finally, because of the directional characteristic of the clutter, nonisotropic MRF is introduced into the post-processing step to refine the output. Experimental results show that one can remove both kinds of wave clutter with only small background distortion using the proposed hybrid algorithm.
great lakes symposium on vlsi | 2013
Aditya Belsare; Steve Liu; Sunil P. Khatri
Fast key generation algorithms which can generate random sequences of varying atomic lengths and throughput are important for secure data communication. In this paper, we present a non-linear congruential method for generating high quality random numbers at flexible throughput rates of upto 66 Gbps, on a GPU platform. Each random number can have up to 4096 key bits. The method can be easily extended for implementation on hardware platforms like FPGAs and ASICs as well. Our key generator is comprised of N Linear Congruential Generators (LCGs) running in parallel; we have chosen N=4096 for the GPU implementation. The outputs of the LCGs are combined using N encoded majority functions. The encoded majority function used for any bit is changed in every generation iteration. In our GPU implementation of the Non-Linear Congruential Generator (GPU-NLCG), it is possible to alter the LCG functions on the fly by changing the primes periodically without interrupting the generation. Our GPU-NLCG can be used for high speed cryptographic key generation for rates up to 66 Gbps and can be easily integrated into multi-threaded applications in cryptography and Monte Carlo methods. The GPU-NLCG passes the NIST, Diehard and Dieharder battery of tests of randomness, which ensure the quality of our ciphers.
wireless algorithms, systems, and applications | 2007
Hong Lu; Steve Liu; Anxiao Jiang
Wireless mesh networks have gained significant academic and industry attentions in the recent years. Supporting quality of service in wireless mesh networks is an important and challenging task which involves both medium access control and network layer design. In this paper, we investigate the problem of end-to-end on-demand bandwidth allocation in infrastructure wireless mesh networks. We formulate it as a combinatorial optimization problem, and prove that it is NP- hard. We present a polynomial time 2-approximation algorithm, MCRS (minimum consumption routing and scheduling), based on the concepts of consumption level for routing and bottom set for scheduling. Comprehensive simulation results show that MCRS achieves better performance than traditional methods based on minimum hop routing.
international conference on distributed computing systems | 2008
Hong Lu; Andrew Jiang; Steve Liu
In sensor network applications, sensors often need to retrieve data from each other. Information brokerage is a scheme that stores data (or index files of data) at rendezvous nodes, so that every sensor can efficiently finds the data it needs. A very useful property for information brokerage is locality sensitivity, which means that a sensor close the original source of the data should also be able to retrieve the data with a small communication cost. Given the locality sensitivity requirement, the key is to design an information brokerage scheme that minimizes the storage cost. In this paper, we present a locality sensitive information brokerage scheme. It is designed for general locality-sensitive requirements, which include the linear data-retrieval cost (a frequently studied scenario) as a special case. We also prove that for a large class of networks, in the scenario of linear data-retrieval cost, our scheme achieves the asymptotically optimal storage cost. The result also proves the optimality of a few other schemes in the literature.
wireless algorithms systems and applications | 2006
Hong Lu; Steve Liu
End-to-end throughput θ sd is the maximum amount of data that can be successfully delivered from source s to sink d across a given network in unit time. Determining θ sd is essential to understanding the network limit and is of important value to network design and evaluation. In the past few years, the problem of computing θ sd in multihop wireless networks has been extensively studied in the literature. It has been shown that this problem is NP-hard in general and various approaches have been proposed to compute approximate solutions. In this paper, we study one side of the problem, computing the upperbound of θ sd . We present a general solution framework based on linear program LP(F), where F is an arbitrary set of link sets. We show each choice of F corresponds to an upperbound of θ sd and identify several good choice of F based on the notions of clique and congestion. The tightness of these clique and congestion based upperbounds are evaluated by simulation.
2001 Annual Conference | 2001
Steve Liu; Willis Marti; Wei Zhao
Wavelet applications. Conference | 1997
Tsaifa Yu; Nai-wen Lin; Steve Liu; Andrew K. Chan
Archive | 1998
Andrew K. Chan; Steve Liu
Computer Networks | 2010
Yueping Zhang; Yong Xiong; Steve Liu; Dmitri Loguinov