4,223 research outputs found
An Intelligent QoS Identification for Untrustworthy Web Services Via Two-phase Neural Networks
QoS identification for untrustworthy Web services is critical in QoS
management in the service computing since the performance of untrustworthy Web
services may result in QoS downgrade. The key issue is to intelligently learn
the characteristics of trustworthy Web services from different QoS levels, then
to identify the untrustworthy ones according to the characteristics of QoS
metrics. As one of the intelligent identification approaches, deep neural
network has emerged as a powerful technique in recent years. In this paper, we
propose a novel two-phase neural network model to identify the untrustworthy
Web services. In the first phase, Web services are collected from the published
QoS dataset. Then, we design a feedforward neural network model to build the
classifier for Web services with different QoS levels. In the second phase, we
employ a probabilistic neural network (PNN) model to identify the untrustworthy
Web services from each classification. The experimental results show the
proposed approach has 90.5% identification ratio far higher than other
competing approaches.Comment: 8 pages, 5 figure
Self-normalized Cram\'{e}r type moderate deviations for the maximum of sums
Let be independent random variables with zero means and finite
variances, and let and . A
Cram\'{e}r type moderate deviation for the maximum of the self-normalized sums
is obtained. In particular, for identically
distributed it is proved that uniformly for
under the optimal finite third moment of .Comment: Published in at http://dx.doi.org/10.3150/12-BEJ415 the Bernoulli
(http://isi.cbs.nl/bernoulli/) by the International Statistical
Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm
A multi-sensor based online tool condition monitoring system for milling process
Tool condition monitoring has been considered as one of the key enabling technologies for manufacturing optimization. Due to the high cost and limited system openness, the relevant developed systems have not been widely adopted by industries, especially Small and Medium-sized Enterprises. In this research, a cost-effective, wireless communication enabled, multi-sensor based tool condition monitoring system has been developed. Various sensor data, such as vibration, cutting force and power data, as well as actual machining parameters, have been collected to support efficient tool condition monitoring and life estimation. The effectiveness of the developed system has been validated via machining cases. The system can be extended to wide manufacturing applications
First-principles LDA+U and GGA+U study of neptunium dioxide
We have performed a systematic first-principles investigation to calculate
the electronic structures, mechanical properties, and phonon dispersion curves
of NpO. The local density approximation and the generalized gradient
approximation formalisms have been used to account for the strong on-site
Coulomb repulsion among the localized Np electrons. By choosing the
Hubbard \emph{U} parameter around 4 eV, the orbital occupancy characters of Np
5\emph{f} and O 2\emph{p} are in good agreement with recent experiments [J.
Nucl. Mater. \textbf{389}, 470 (2009)]. Comparing with our previous study of
ThO, we note that stronger covalency exists in NpO due to the more
localization behavior of 5\emph{f} electrons of Np in line with the
localization-delocalization trend exhibited by the actinides series.Comment: 7 pages, 6 figure
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