155,083 research outputs found
Design of a smart turning tool with application to in-process cutting force measurement in ultraprecision and micro cutting
In modern micromachining, there is a need to measure and monitor certain machining process parameters in process so as to detect tool wear in real time, to optimize the process parameters setup, and to render the machining process some level of smartness and intelligence. This paper presents the innovative design of a smart turning tool using two pieces of piezoelectric films to measure cutting and feed force in real time. The tool was tested on its performance through the calibration and cutting trials against the commercial dynamometer. The results show the smart turning tool has achieved the performance as designed
Privacy-Preserving Outsourcing of Large-Scale Nonlinear Programming to the Cloud
The increasing massive data generated by various sources has given birth to
big data analytics. Solving large-scale nonlinear programming problems (NLPs)
is one important big data analytics task that has applications in many domains
such as transport and logistics. However, NLPs are usually too computationally
expensive for resource-constrained users. Fortunately, cloud computing provides
an alternative and economical service for resource-constrained users to
outsource their computation tasks to the cloud. However, one major concern with
outsourcing NLPs is the leakage of user's private information contained in NLP
formulations and results. Although much work has been done on
privacy-preserving outsourcing of computation tasks, little attention has been
paid to NLPs. In this paper, we for the first time investigate secure
outsourcing of general large-scale NLPs with nonlinear constraints. A secure
and efficient transformation scheme at the user side is proposed to protect
user's private information; at the cloud side, generalized reduced gradient
method is applied to effectively solve the transformed large-scale NLPs. The
proposed protocol is implemented on a cloud computing testbed. Experimental
evaluations demonstrate that significant time can be saved for users and the
proposed mechanism has the potential for practical use.Comment: Ang Li and Wei Du equally contributed to this work. This work was
done when Wei Du was at the University of Arkansas. 2018 EAI International
Conference on Security and Privacy in Communication Networks (SecureComm
Comment on "Superconducting gap anisotropy vs. doping level in high-T_c cuprates" by C. Kendziora et al, PRL 77, 727 (1996)
In a recent paper Kendziora et al concluded that the superconducting gap in
overdoped Bi-2212 is isotropic. From data obtained from electronic Raman
scattering measurements, their conclusion was based on the observation that
pair breaking peaks occured at approximately the same frequency in different
scattering geometries and that the normalized scattering intensity at low
energies was strongly depleted. We discuss a different interpretation of the
raw data and present new data which is consistent with a strongly anisotropic
gap with nodes. The spectra can be successfully described by a model for Raman
scattering in a d_{x^{2}-y^{2}} superconductor with spin fluctuations and
impurity scattering included.Comment: 1 page revtex plus 1 postscript figur
Lattice theory of finite-size effects above the upper critical dimension
We present a perturbative calculation of finite-size effects near of
the lattice model in a -dimensional cubic geometry of size with
periodic boundary conditions for . The structural differences between
the lattice theory and the field theory found previously in
the spherical limit are shown to exist also for a finite number of components
of the order parameter. The two-variable finite-size scaling functions of the
field theory are nonuniversal whereas those of the lattice theory are
independent of the nonuniversal model parameters.One-loop results for
finite-size scaling functions are derived. Their structure disagrees with the
single-variable scaling form of the lowest-mode approximation for any finite
where is the bulk correlation length. At , the large-
behavior becomes lowest-mode like for the lattice model but not for the
field-theoretic model. Characteristic temperatures close to of the
lattice model, such as of the maximum of the susceptibility
, are found to scale asymptotically as ,
in agreement with previous Monte Carlo (MC) data for the five-dimensional Ising
model. We also predict asymptotically. On a
quantitative level, the asymptotic amplitudes of this large - behavior close
to have not been observed in previous MC simulations at because
of nonnegligible finite-size terms caused by the
inhomogeneous modes. These terms identify the possible origin of a significant
discrepancy between the lowest-mode approximation and previous MC data. MC data
of larger systems would be desirable for testing the magnitude of the
and terms predicted by our theory.Comment: Accepted in Int. J. Mod. Phys.
Superior removal of arsenic from water with zirconium metal-organic framework UiO-66
10.1038/srep16613Scientific Reports51661
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