10,307 research outputs found
Memetic Multi-Objective Particle Swarm Optimization-Based Energy-Aware Virtual Network Embedding
In cloud infrastructure, accommodating multiple virtual networks on a single
physical network reduces power consumed by physical resources and minimizes
cost of operating cloud data centers. However, mapping multiple virtual network
resources to physical network components, called virtual network embedding
(VNE), is known to be NP-hard. With considering energy efficiency, the problem
becomes more complicated. In this paper, we model energy-aware virtual network
embedding, devise metrics for evaluating performance of energy aware virtual
network-embedding algorithms, and propose an energy aware virtual
network-embedding algorithm based on multi-objective particle swarm
optimization augmented with local search to speed up convergence of the
proposed algorithm and improve solutions quality. Performance of the proposed
algorithm is evaluated and compared with existing algorithms using extensive
simulations, which show that the proposed algorithm improves virtual network
embedding by increasing revenue and decreasing energy consumption.Comment: arXiv admin note: text overlap with arXiv:1504.0684
Quality management and cost of education at private universities in Bangladesh: An evaluation
An exploratory survey was conducted to analyze the consumers’ evaluation of private higher education sectors in Bangladesh with particular reference to the quality as well as the cost of education. The sample was taken on a random basis from about ten private universities in Dhaka metropolitan area. The respondents (students) were asked to evaluate the quality and the cost of education at private universities in Bangladesh. Respondents ranked the attributes on a number of itemized seven-point scale ratings bounded at each end by one of two bipolar adjectives. The result of this study shows that faculty credentials, academic calendar, campus facility, research facility and cost of education are associated with quality education and that the consumers feel most of the private universities in Bangladesh provide quality education at reasonable costs
Dependent Nonparametric Bayesian Group Dictionary Learning for online reconstruction of Dynamic MR images
In this paper, we introduce a dictionary learning based approach applied to
the problem of real-time reconstruction of MR image sequences that are highly
undersampled in k-space. Unlike traditional dictionary learning, our method
integrates both global and patch-wise (local) sparsity information and
incorporates some priori information into the reconstruction process. Moreover,
we use a Dependent Hierarchical Beta-process as the prior for the group-based
dictionary learning, which adaptively infers the dictionary size and the
sparsity of each patch; and also ensures that similar patches are manifested in
terms of similar dictionary atoms. An efficient numerical algorithm based on
the alternating direction method of multipliers (ADMM) is also presented.
Through extensive experimental results we show that our proposed method
achieves superior reconstruction quality, compared to the other state-of-the-
art DL-based methods
Reconstruction of 3D faces by shape estimation and texture interpolation
This paper aims to address the ill-posed problem of reconstructing 3D faces from single 2D face images. An
extended Tikhonov regularization method is connected with the standard 3D morphable model in order to
reconstruct the 3D face shapes from a small set of 2D facial points. Further, by interpolating the input 2D
texture with the model texture and warping the interpolated texture to the reconstructed face shapes, 3D face
reconstruction is achieved. For the texture warping, the 2D face deformation has been learned from the model
texture using a set of facial landmarks. Our experimental results justify the robustness of the proposed approach
with respect to the reconstruction of realistic 3D face shapes
- …