Utility of ITS1-5.8S-ITS2 sequences for species discrimination and phylogenetic inference of two closely related bucephalid digeneans (Digenea : Bucephalidae): Dollfustrema vaneyi and Dollfustrema hefeiensis

The complete internal transcribed spacer 1 (ITS1), 5.8S ribosomal DNA, and ITS2 region of the ribosomal DNA from 60 specimens belonging to two closely related bucephalid digeneans (Dollfustrema vaneyi and Dollfustrema hefeiensis) from different localities, hosts, and microhabitat sites were cloned to examine the level of sequence variation and the taxonomic levels to show utility in species identification and phylogeny estimation. Our data show that these molecular markers can help to discriminate the two species, which are morphologically very close and difficult to separate by classical methods. We found 21 haplotypes defined by 44 polymorphic positions in 38 individuals of D. vaneyi, and 16 haplotypes defined by 43 polymorphic positions in 22 individuals of D. hefeiensis. There is no shared haplotypes between the two species. Haplotype rather than nucleotide diversity is similar between the two species. Phylogenetic analyses reveal two robustly supported clades, one corresponding to D. vaneyi and the other corresponding to D. hefeiensis. However, the population structures between the two species seem to be incongruent and show no geographic and host-specific structure among them, further indicating that the two species may have had a more complex evolutionary history than expected.

Method for improving classification performance of neural network based on fuzzy input and network inversion

In order to effectively improve the classification performance of neural network, first architecture of fuzzy neural network with fuzzy input was proposed. Next a cost function of fuzzy outputs and non-fuzzy targets was defined. Then a learning algorithm from the cost function for adjusting weights was derived. And then the fuzzy neural network was inversed and fuzzified inversion algorithm was proposed. Finally, computer simulations on real-world pattern classification problems examine the effectives of the proposed approach. The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability.

Coalition and distribution in fuzzy dynamic supply chain systems

In this paper, two models of coalition and income's distribution in FSCS (fuzzy supply chain systems) are proposed based on the fuzzy set theory and fuzzy cooperative game theory. The fuzzy dynamic coalition choice's recursive equations are constructed in terms of sup-t composition of fuzzy relations, where t is a triangular norm. The existence of the fuzzy relations in FSCS is also proved. On the other hand, the approaches to ascertain the fuzzy coalition through the choice's recursive equations and distribute the fuzzy income in FSCS by the fuzzy Shapley values are also given. These models are discussed in two parts: the fuzzy dynamic coalition choice of different units in FSCS; the fuzzy income's distribution model among different participators in the same coalition. Furthermore, numerical examples are given aiming at illustrating these models., and the results show that these models are feasible and validity in FSCS.

feedback fuzzy-dvs scheduling of control tasks

To consider the energy-aware scheduling problem in computer-controlled systems is necessary to improve the control performance, to use the limited computing resource sufficiently, and to reduce the energy consumption to extend the lifetime of the whole system. In this paper, the scheduling problem of multiple control tasks is discussed based on an adjustable voltage processor. A feedback fuzzy-DVS (dynamic voltage scaling) scheduling architecture is presented by applying technologies of the feedback control and the fuzzy DVS. The simulation results show that, by using the actual utilization as the feedback information to adjust the supply voltage of processor dynamically, the high CPU utilization can be implemented under the precondition of guaranteeing the control performance, whilst the low energy consumption can be achieved as well. The proposed method can be applied to the design in computer-controlled systems based on an adjustable voltage processor.

missing data imputation: a fuzzy k-means clustering algorithm over sliding window

Tianjin University of Technology

Bayesian inference of plastosphere viscosities near the Kunlun Fault, northern Tibet

IEECAS SKLLQG