This paper considers the problem of indoor wireless planning using smart antennas. Smart antennas have gained much attention in wireless networking because of their capability in providing more spatial reuse and incre...
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(纸本)9781424492688
This paper considers the problem of indoor wireless planning using smart antennas. Smart antennas have gained much attention in wireless networking because of their capability in providing more spatial reuse and increased network capacity. Recent research has demonstrated their effectiveness in indoor environments where omni-directional antennas have been traditionally the dominant technology. Much of the work, however, assumes that a network is already deployed and focuses on scheduling antenna patterns. In this work, we investigate finding a wireless plan for an indoor environment where the wireless plan specifies minimum number of antennas required to provide complete coverage of the environment as well as the location, transmission power and beam pattern for each antenna. This problem is more challenging than radio planning using omnidirectional antennas because of the special shape of antenna beams. Both single-beam and multi-beam antenna patterns are considered and integer linear programming formulations are provided for computing the minimum cost wireless plan. Moreover, to solve large-scale instances of the problem an efficient polynomial-time heuristic is proposed.
We present CIDANE, a novel framework for genome-based transcript reconstruction and quantification from RNA-seq reads. CIDANE assembles transcripts efficiently with significantly higher sensitivity and precision than ...
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We present CIDANE, a novel framework for genome-based transcript reconstruction and quantification from RNA-seq reads. CIDANE assembles transcripts efficiently with significantly higher sensitivity and precision than existing tools. Its algorithmic core not only reconstructs transcripts ab initio, but also allows the use of the growing annotation of known splice sites, transcription start and end sites, or full-length transcripts, which are available for most model organisms. CIDANE supports the integrated analysis of RNA-seq and additional gene-boundary data and recovers splice junctions that are invisible to other methods. CIDANE is available at http://***/software/cidane/.
Background: In addition to component-based comparative approaches, network alignments provide the means to study conserved network topology such as common pathways and more complex network motifs. Yet, unlike in class...
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Background: In addition to component-based comparative approaches, network alignments provide the means to study conserved network topology such as common pathways and more complex network motifs. Yet, unlike in classical sequence alignment, the comparison of networks becomes computationally more challenging, as most meaningful assumptions instantly lead to NP-hard problems. Most previous algorithmic work on network alignments is heuristic in nature. Results: We introduce the graph-based maximum structural matching formulation for pairwise global network alignment. We relate the formulation to previous work and prove NP-hardness of the problem. Based on the new formulation we build upon recent results in computational structural biology and present a novel Lagrangian relaxation approach that, in combination with a branch-and-bound method, computes provably optimal network alignments. The Lagrangian algorithm alone is a powerful heuristic method, which produces solutions that are often near-optimal and - unlike those computed by pure heuristics - come with a quality guarantee. Conclusion: Computational experiments on the alignment of protein-protein interaction networks and on the classification of metabolic subnetworks demonstrate that the new method is reasonably fast and has advantages over pure heuristics. Our software tool is freely available as part of the LISA library.
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