626 research outputs found
Web Service Retrieval by Structured Models
Much of the information available on theWorldWideWeb cannot effectively be found by the help of search engines because the information is dynamically generated on a userâs request.This applies to online decision support services as well as Deep Web information. We present in this paper a retrieval system that uses a variant of structured modeling to describe such information services, and similarity of models for retrieval. The computational complexity of the similarity problem is discussed, and graph algorithms for retrieval on repositories of service descriptions are introduced. We show how bounds for combinatorial optimization problems can provide filter algorithms in a retrieval context. We report about an evaluation of the retrieval system in a classroom experiment and give computational results on a benchmark library.Economics ;
Simplified Multiuser Detection for SCMA with Sum-Product Algorithm
Sparse code multiple access (SCMA) is a novel non-orthogonal multiple access
technique, which fully exploits the shaping gain of multi-dimensional
codewords. However, the lack of simplified multiuser detection algorithm
prevents further implementation due to the inherently high computation
complexity. In this paper, general SCMA detector algorithms based on
Sum-product algorithm are elaborated. Then two improved algorithms are
proposed, which simplify the detection structure and curtail exponent
operations quantitatively in logarithm domain. Furthermore, to analyze these
detection algorithms fairly, we derive theoretical expression of the average
mutual information (AMI) of SCMA (SCMA-AMI), and employ a statistical method to
calculate SCMA-AMI based specific detection algorithm. Simulation results show
that the performance is almost as well as the based message passing algorithm
in terms of both BER and AMI while the complexity is significantly decreased,
compared to the traditional Max-Log approximation method
Modified bipartite matching for multiobjective optimization: Application to antenna assignments in MIMO systems
Based on the Hungarian algorithm, the Kuhn-Munkres algorithm can provide the maximum weight bipartite matching for assignment problems. However, it can only solve the single objective optimization problem. In this paper, we formulate the multi-objective optimization (MO) problem for bipartite matching, and propose a modified bipartite matching (MBM) algorithm to approach the Pareto set with a low computational complexity and to dynamically select proper solutions with given constraints among the reduced matching set. In addition, our MBM algorithm is extended to the case of asymmetric bipartite graphs. Finally, we illustrate the application of MBM to antenna assignments in wireless multiple-input multiple-output (MIMO) systems for both symmetric and asymmetric scenarios, where we consider the multi-objective optimization problem with the maximization of the system capacity, total traffic priority, and long-term fairness among all mobile users. The simulation results show that MBM can effectively reduce the matching set and dynamically provide the optimized performance with different quality of service (QoS) requirements. © 2006 IEEE.published_or_final_versio
Identification of metabolic pathways using pathfinding approaches: A systematic review
Metabolic pathways have become increasingly available for variousmicroorganisms. Such pathways have spurred the development of a wide array of computational tools, in particular, mathematical pathfinding approaches. This article can facilitate the understanding of computational analysis ofmetabolic pathways in genomics. Moreover, stoichiometric and pathfinding approaches inmetabolic pathway analysis are discussed. Threemajor types of studies are elaborated: stoichiometric identification models, pathway-based graph analysis and pathfinding approaches in cellular metabolism. Furthermore, evaluation of the outcomes of the pathways withmathematical benchmarkingmetrics is provided. This review would lead to better comprehension ofmetabolismbehaviors in living cells, in terms of computed pathfinding approaches. © The Author 2016
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