25 research outputs found
(Color online) <i>AUC</i><sub><i>s</i></sub> and <i>Ï</i> of the EigenRank algorithm, IBeta method and Vote Aggregation method for the synthetic networks: (a, b) in the random rating attack case when |<i>E</i>| = 7.2 Ă 10<sup>5</sup>; (c, d) in the malicious rating attack case when |<i>E</i>| = 7.2 Ă 10<sup>5</sup>; (e, f) in the random rating attack case when |<i>E</i>| = 1.08 Ă 10<sup>6</sup>; (g, h) in the malicious rating attack case when |<i>E</i>| = 1.08 Ă 10<sup>6</sup>.
The parameter Ï denotes the ratio of random/malicious ratings. It can be seen that both the AUCs and Ï of the EigenRank algorithm exceed their counterparts in the IBeta method and Vote Aggregation method with different Ï and |E|. The results are averaged over 50 independent realizations. The error bars are the corresponding standard deviations.</p
Descriptor table of letters used in this paper.
Descriptor table of letters used in this paper.</p
(Color online) The effectiveness of the EigenRank algorithm under random rating attack for the MovieLens data set: (a) the AUC values <i>AUC</i><sub><i>e</i></sub>; (b-c) Î<i>AUC</i><sub><i>e</i></sub>, the comparison of <i>AUC</i><sub><i>e</i></sub> between EigenRank algorithm and IBeta method (b), Vote Aggregation method (c); (d) the recall <i>R</i><sub><i>c</i></sub>(<i>L</i>); (e-f) Î<i>R</i><sub><i>c</i></sub>(<i>L</i>), the comparison of recall between EigenRank algorithm and IBeta method (e), Vote Aggregation method (f).
The parameters q and p denote the ratio and the activity of spammers, respectively. q ranges from 0.025 to 0.5 in increments of 0.025 and p ranges from 0.01 to 0.2 in increments of 0.01. One observes both the AUCe and Rc(L) of the EigenRank algorithm exceed the ones obtained by the IBeta method and Vote Aggregation method for different (p, q).</p
(Color online) The effectiveness of the EigenRank algorithm under random rating attack for the Netflix data set: (a) the AUC values <i>AUC</i><sub><i>e</i></sub>; (b-c) Î<i>AUC</i><sub><i>e</i></sub>, the comparison of <i>AUC</i><sub><i>e</i></sub> between EigenRank algorithm and IBeta method (b), Vote Aggregation method (c); (d) the recall <i>R</i><sub><i>c</i></sub>(<i>L</i>); (e-f) Î<i>R</i><sub><i>c</i></sub>(<i>L</i>), the comparison of recall between EigenRank algorithm and IBeta method (e), Vote Aggregation method (f).
The parameters q and p denote the ratio and the activity of spammers, respectively and L = q|U|. q ranges from 0.015 to 0.3 in increments of 0.015 and p ranges from 0.005 to 0.1 in increments of 0.005. One observes that both the AUCe and Rc(L) of the EigenRank algorithm exceed those of the IBeta method and Vote Aggregation method for different (p, q).</p
Anisotropic Paramagnetic Properties of Metallofullerene Confined in a MetalâOrganic Framework
Paramagnetic
metallofullerenes have a spherical molecular structure
and stable unpaired spin protected by a fullerene cage and have potential
applications in quantum information processing, etc. For endohedral
azafullerene Y<sub>2</sub>@C<sub>79</sub>N, the N atom on the cage
endows the molecule with unpaired spin and is proposed to induce the
molecule orientation within the MOF pore via hostâguest interaction.
Angular-dependent EPR spectroscopy was employed on the Y<sub>2</sub>@C<sub>79</sub>NâMOF-177 complex to detect the anisotropic
paramagnetic properties. These results experimentally confirmed the
trend of molecule orientation of Y<sub>2</sub>@C<sub>79</sub>N within
MOF-177 under certain conditions, which also induces the presence
of several conformers of Y<sub>2</sub>@C<sub>79</sub>N. The additional
EPR splittings in Y<sub>2</sub>@C<sub>79</sub>NâMOF-177 are
proposed to originate from partially disordered molecules as well
as the N-coupling of Y<sub>2</sub>@C<sub>79</sub>N upon implanting
it into the MOF-177 pore. The N-defect on the fullerene cage of Y<sub>2</sub>@C<sub>79</sub>N is expected to be utilized as an anchor to
build a three-dimensional spin array within MOF matrix
Natural light intensity at the bottom of the tanks during the diel cycle (Nâ=â3, mean ± SE).
<p>Natural light intensity at the bottom of the tanks during the diel cycle (Nâ=â3, mean ± SE).</p
Effect of covering behavior on relative expression of <i>PAX 6</i> in <i>Strongylocentrotus intermedius</i> under photic and aphotic conditions.
<p>Y: covering material present. N: covering material not present. (Nâ=â4, mean ± SE).</p
BCN Nanotubes as Highly Sensitive Torsional Electromechanical Transducers
Owing
to their mechanically tunable electronic properties, carbon
nanotubes (CNTs) have been widely studied as potential components
for nanoelectromechanical systems (NEMS); however, the mechanical
properties of multiwall CNTs are often limited by the weak shear interactions
between the graphitic layers. Boron nitride nanotubes (BNNTs) exhibit
a strong interlayer mechanical coupling, but their high electrical
resistance limits their use as electromechanical transducers. Can
the outstanding mechanical properties of BNNTs be combined with the
electromechanical properties of CNTs in one hybrid structure? Here,
we report the first experimental study of boron carbonitride nanotube
(BCNNT) mechanics and electromechanics. We found that the hybrid BCNNTs
are up to five times torsionally stiffer and stronger than CNTs, thereby
retaining to a large extent the ultrahigh torsional stiffness of BNNTs.
At the same time, we show that the electrical response of BCNNTs to
torsion is 1 to 2 orders of magnitude higher than that of CNTs. These
results demonstrate that BCNNTs could be especially attractive building
blocks for NEMS