49,639 research outputs found
Extending twin support vector machine classifier for multi-category classification problems
Ā© 2013 ā 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)
Research on trust model in container-based cloud service
Container virtual technology aims to provide program independence and resource sharing. The container enables flexible cloud service. Compared with traditional virtualization, traditional virtual machines have difficulty in resource and expense requirements. The container technology has the advantages of smaller size, faster migration, lower resource overhead, and higher utilization. Within container-based cloud environment, services can adopt multi-target nodes. This paper reports research results to improve the traditional trust model with consideration of cooperation effects. Cooperation trust means that in a container-based cloud environment, services can be divided into multiple containers for different container nodes. When multiple target nodes work for one service at the same time, these nodes are in a cooperation state. When multi-target nodes cooperate to complete the service, the target nodes evaluate each other. The calculation of cooperation trust evaluation is used to update the degree of comprehensive trust. Experimental simulation results show that the cooperation trust evaluation can help solving the trust problem in the container-based cloud environment and can improve the success rate of following cooperation
Spin-current diode with a ferromagnetic semiconductor
Diode is a key device in electronics: the charge current can flow through the
device under a forward bias, while almost no current flows under a reverse
bias. Here we propose a corresponding device in spintronics: the spin-current
diode, in which the forward spin current is large but the reversed one is
negligible. We show that the lead/ferromagnetic quantum dot/lead system and the
lead/ferromagnetic semiconductor/lead junction can work as spin-current diodes.
The spin-current diode, a low dissipation device, may have important
applications in spintronics, as the conventional charge-current diode does in
electronics.Comment: 5 pages, 3 figure
The spin-polarized state of graphene: a spin superconductor
We study the spin-polarized Landau-level state of graphene. Due to
the electron-hole attractive interaction, electrons and holes can bound into
pairs. These pairs can then condense into a spin-triplet superfluid ground
state: a spin superconductor state. In this state, a gap opens up in the edge
bands as well as in the bulk bands, thus it is a charge insulator, but it can
carry the spin current without dissipation. These results can well explain the
insulating behavior of the spin-polarized state in the recent
experiments.Comment: 6 pages, 4 figure
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