37,614 research outputs found
Extending twin support vector machine classifier for multi-category classification problems
© 2013 – IOS Press and the authors. All rights reservedTwin support vector machine classifier (TWSVM) was proposed by Jayadeva et al., which was used for binary classification
problems. TWSVM not only overcomes the difficulties in handling the problem of exemplar unbalance in binary classification problems, but also it is four times faster in training a classifier than classical support vector machines. This paper proposes one-versus-all twin support vector machine classifiers (OVA-TWSVM) for multi-category classification problems by utilizing the strengths of TWSVM. OVA-TWSVM extends TWSVM to solve k-category classification problems by developing k TWSVM where in the ith TWSVM, we only solve the Quadratic Programming Problems (QPPs) for the ith class, and get the ith nonparallel hyperplane corresponding to the ith class data. OVA-TWSVM uses the well known one-versus-all (OVA) approach to construct a corresponding twin support vector machine classifier. We analyze the efficiency of the OVA-TWSVM theoretically, and perform experiments to test its efficiency on both synthetic data sets and several benchmark data sets from the UCI machine learning repository. Both the theoretical analysis and experimental results demonstrate that OVA-TWSVM can outperform the traditional OVA-SVMs classifier. Further experimental comparisons with other multiclass classifiers demonstrated that comparable performance could be achieved.This work is supported in part by the grant
of the Fundamental Research Funds for the Central Universities of GK201102007 in PR China, and is also supported by Natural Science Basis Research Plan in Shaanxi Province of China (Program No.2010JM3004), and is at the same time supported by Chinese Academy of Sciences under the Innovative
Group Overseas Partnership Grant as well as Natural Science Foundation of China Major International Joint Research Project (NO.71110107026)
Functional analysis of the Bunyamwera orthobunyavirus Gc glycoprotein
The virion glycoproteins Gn and Gc of Bunyamwera orthobunyavirus (family Bunyaviridae) are encoded by the M RNA genome segment and have roles in both viral attachment and membrane fusion. To investigate further the structure and function of the Gc protein in viral replication, we generated 12 mutants that contain truncations from the N terminus. The effects of these deletions were analysed with regard to Golgi targeting, low pH-dependent membrane fusion, infectious virus-like particle (VLP) formation and virus infectivity. Our results show that the N-terminal half (453 residues) of the Gc ectodomain (909 residues in total) is dispensable for Golgi trafficking and cell fusion. However, deletions in this region resulted in a significant reduction in VLP formation. Four mutant viruses that contained N-terminal deletions in their Gc proteins were rescued, and found to be attenuated to different degrees in BHK-21 cells. Taken together, our data indicate that the N-terminal half of the Gc ectodomain is dispensable for replication in cell culture, whereas the C-terminal half is required to mediate cell fusion. A model for the domain structure of the Gc ectodomain is proposed
Oscillation Induced Neutrino Asymmetry Growth in the Early Universe
We study the dynamics of active-sterile neutrino oscillations in the early
universe using full momentum-dependent quantum-kinetic equations. These
equations are too complicated to allow for an analytical treatment, and
numerical solution is greatly complicated due to very pronounced and narrow
structures in the momentum variable introduced by resonances. Here we introduce
a novel dynamical discretization of the momentum variable which overcomes this
problem. As a result we can follow the evolution of neutrino ensemble
accurately well into the stable growing phase. Our results confirm the
existence of a "chaotic region" of mixing parameters, for which the final sign
of the asymmetry, and hence the SBBN prediction of He(4)-abundance cannot be
accurately determined.Comment: 23 pages, 9 eps-figs, Latex, uses JHEP clas
Enhancement of Transition Temperature in FexSe0.5Te0.5 Film via Iron Vacancies
The effects of iron deficiency in FexSe0.5Te0.5 thin films (0.8<x<1) on
superconductivity and electronic properties have been studied. A significant
enhancement of the superconducting transition temperature (TC) up to 21K was
observed in the most Fe deficient film (x=0.8). Based on the observed and
simulated structural variation results, there is a high possibility that Fe
vacancies can be formed in the FexSe0.5Te0.5 films. The enhancement of TC shows
a strong relationship with the lattice strain effect induced by Fe vacancies.
Importantly, the presence of Fe vacancies alters the charge carrier population
by introducing electron charge carriers, with the Fe deficient film showing
more metallic behavior than the defect-free film. Our study provides a means to
enhance the superconductivity and tune the charge carriers via Fe vacancy, with
no reliance on chemical doping.Comment: 15 pages, 4 figure
Optimal time series momentum
We develop a continuous-time asset price model to capture the time series momentum documented recently. The underlying stochastic delay differential system facilitates the analysis of effects of different time horizons used by momentum trading. By studying an optimal asset allocation problem, we find that the performance of time series momentum strategy can be significantly improved by combining with market fundamentals and timing opportunity with respect to market trend and volatility. Furthermore, the results also hold for different time horizons, the out-of-sample tests and with short-sale constraints. The outperformance of the optimal strategy is immune to market states, investor sentiment and market volatility
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