This paper studies a Markovian queue with multiple working vacations and controlled vacation interruption. If there are at least N customers waiting upon completion of a service at a lower rate, the vacation is interr...
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In the traditional dual-frequency radar ranging system,there is a contradiction between ranging precision and ranging *** a tri-frequency ranging method is *** principle of the tri-frequency ranging is that the distan...
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In the traditional dual-frequency radar ranging system,there is a contradiction between ranging precision and ranging *** a tri-frequency ranging method is *** principle of the tri-frequency ranging is that the distance can be achieved by transmitting the three frequencies and then measuring the three phase difference and calculating the number of ***'s more,range ambiguity will not occur within a certain *** experimental results show that,if the waveband is 0.47 ~0.57 m,the measurement of unambiguous distance of 25 ~500m can be *** the wavelength tolerance error is less than ± 10^(-7) and the phase error is less than ± 10^(-3),the precision of the distance ranging can reach 10^(-6).
Linux 2.6 load balancing algorithm on scheduling domain supports CMP, CMT, SMP, NUMA architecture. For SMT, the algorithm try to assign the new process to the idlest CPU of the idlest core, and if the first CPU of a c...
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The instability property of the standing wave uω(t, x) = eiωtφ(x) for the Klein–Gordon– Hartree equation is investigated. For the case N≥3 and w2 〈2/N+4-γ,it is shown that the standing wave eiwtφ(x) is...
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The instability property of the standing wave uω(t, x) = eiωtφ(x) for the Klein–Gordon– Hartree equation
is investigated. For the case N≥3 and w2 〈2/N+4-γ,it is shown that the standing wave eiwtφ(x) is strongly unstable by blow-up in finite time.
Existing data publication methods retain the relationship between the quasi-identifier attributes and sensitive attributes of published data. We call them "positive data publication". However, it will lead t...
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In a negative survey, a category which does not agree with the fact of each participant is collected. Hence, data collectors cannot acquire the realistic data of participants, and this can efficiently protect particip...
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ISBN:
(纸本)9781849199094
In a negative survey, a category which does not agree with the fact of each participant is collected. Hence, data collectors cannot acquire the realistic data of participants, and this can efficiently protect participants' private information and sensitive data. However, existing approaches used to estimate the distribution of positive surveys from negative surveys are not practical and time-consuming. This paper proposed a method in order to acquire practical estimation results with a lower computing cost, namely fastNStoPS. Usually, privacy and utility are used to measure the performances of negative surveys, and they are two conflicting metrics. Users have different demands on privacy (or utility) under different circumstances. The optimal negative surveys are a Pareto font of these two objectives. To demonstrate its practicability, the proposed fastNStoPS method is embedded into a Differential Evolution (DE), which is used to find the optimal negative surveys. The experiment results show that the DE has a much better performance on find the optimal negative surveys, and the computing cost is very low.
Evolutionary Algorithms (EAs) with gradient-based repair, which utilize the gradient information of the constraints set, have been proved to be effective. It is known that it would be time-consuming if all infeasible ...
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ISBN:
(纸本)9781479914869
Evolutionary Algorithms (EAs) with gradient-based repair, which utilize the gradient information of the constraints set, have been proved to be effective. It is known that it would be time-consuming if all infeasible individuals are repaired. Therefore, so far the infeasible individuals to be repaired are randomly selected from the population and the strategy of choosing individuals to be repaired has not been studied yet. In this paper, the Species-based Repair Strategy (SRS) is proposed to select representative infeasible individuals instead of the random selection for gradient-based repair. The proposed SRS strategy has been applied to εDEag which repairs the random selected individuals using the gradient-based repair. The new algorithm is named SRS-εDEag. Experimental results show that SRS-εDEag outperforms εDEag in most benchmarks. Meanwhile, the number of repaired individuals is reduced markedly.
Evolutionary clustering is a hot research topic that clusters the time-stamped data and it is essential to some important applications such as data streams clustering and social network analysis. An evolutionary clust...
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ISBN:
(纸本)9781479914869
Evolutionary clustering is a hot research topic that clusters the time-stamped data and it is essential to some important applications such as data streams clustering and social network analysis. An evolutionary clustering should accurately reflect the current data at any time step while simultaneously not deviate too drastically from the recent past. In this paper, the differential evolution (DE) is applied to deal with the evolutionary clustering problem. Comparing with the typical k-means, evolutionary clustering based on DE (deEC) could perform a global search in the solution space. Experimental results over synthetic and real-world data sets demonstrate that the deEC provides robust and adaptive solutions.
The Shortest Path (SP) problems are conventional combinatorial optimization problems. There are many deterministic algorithms for solving the shortest path problems in static topologies. However, in dynamic topologies...
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The Shortest Path (SP) problems are conventional combinatorial optimization problems. There are many deterministic algorithms for solving the shortest path problems in static topologies. However, in dynamic topologies, these deterministic algorithms are not efficient due to the necessity of restart. In this paper, an improved Genetic Algorithm (GA) with four local search operators for Dynamic Shortest Path (DSP) problems is proposed. The local search operators are inspired by Dijkstra's Algorithm and carried out when the topology changes to generate local shortest path trees, which are used to promote the performance of the individuals in the population. The experimental results show that the proposed algorithm could obtain the solutions which adapt to new environments rapidly and produce high-quality solutions after environmental changes.
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