The operation of splicing on words was introduced by Tom Head while proposing a theoretical model of DNA recombination. Subsequent investigations on splicing on linear and circular strings of symbols have resulted in ...
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This paper proposes a complex system optimization method to solve economic emission load dispatch. First, a real-world economic emission load dispatch is modeled as a complex system problem, and the optimization objec...
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This paper proposes a complex system optimization method to solve economic emission load dispatch. First, a real-world economic emission load dispatch is modeled as a complex system problem, and the optimization objectives include economic load dispatch, emission load dispatch and transmission network loss. Then a called BBO/complex method is introduced, which extends biogeography-based optimization to a multi-archipelago environment to suit the structure of complex systems. Finally, the proposed method is applied to the economic emission load dispatch, and the results show that it can obtain good performance for economic emission load dispatch studied in this paper, and it is a competitive algorithm for solving complex system optimization problem.
Although the distance between binary codes can be computed fast in Hamming space, linear search is not practical for large scale datasets. Therefore attention has been paid to the efficiency of performing approximate ...
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Although the distance between binary codes can be computed fast in Hamming space, linear search is not practical for large scale datasets. Therefore attention has been paid to the efficiency of performing approximate nearest neighbor search, in which hierarchical clustering trees (HCT) are widely used. However, HCT select cluster centers randomly and build indexes with the entire binary code, this degrades search performance. In this paper, we first propose a new clustering algorithm, which chooses cluster centers on the basis of relative distances and uses a more homogeneous partition of the dataset than HCT has to build the hierarchical clustering trees. Then, we present an algorithm to compress binary codes by extracting distinctive bits according to the standard deviation of each bit. Consequently, a new index is proposed using compressed binary codes based on hierarchical decomposition of binary spaces. Experiments conducted on reference datasets and a dataset of one billion binary codes demonstrate the effectiveness and efficiency of our method.
Recent advances in visual tracking have focused on handling deformations and occlusions using the part-based appearance model. However, it remains a challenge to come up with a reliable target representation using loc...
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In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorith...
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In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.
The two areas of picture languages and membrane computing were linked by array-rewriting P system in which array objects and context-free array-rewriting rules are used in order to generate picture languages. While re...
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This paper introduces identification algorithms for finite impulse response systems under quantized output observations and general quantized inputs. While asymptotically efficient algorithms for quantized identificat...
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A number of approaches have been developed using gene order data to conduct research on both ancestral genomic inference and phylogenetic reconstruction. When investigating species divergence and evolution, gene order...
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ISBN:
(纸本)9781880843994
A number of approaches have been developed using gene order data to conduct research on both ancestral genomic inference and phylogenetic reconstruction. When investigating species divergence and evolution, gene order data has several inherent advantages that enable researchers to determine a more detailed evolutionary scenario. In this study, we propose a framework to integrate free gene and whole genome duplications with gene additions and losses and rearrangements under probabilistic models to infer the gene order of an ancestor and name it PMAG++. We configured a series of experiments to evaluate the performance of PMAG++ on simulated data and we concluded that it can reconstruct ancestral genome content and orientation with high accuracy and efficiency. Copyright ISCA, BICOB 2015.
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