17,887 research outputs found
Fashion Conversation Data on Instagram
The fashion industry is establishing its presence on a number of
visual-centric social media like Instagram. This creates an interesting clash
as fashion brands that have traditionally practiced highly creative and
editorialized image marketing now have to engage with people on the platform
that epitomizes impromptu, realtime conversation. What kinds of fashion images
do brands and individuals share and what are the types of visual features that
attract likes and comments? In this research, we take both quantitative and
qualitative approaches to answer these questions. We analyze visual features of
fashion posts first via manual tagging and then via training on convolutional
neural networks. The classified images were examined across four types of
fashion brands: mega couture, small couture, designers, and high street. We
find that while product-only images make up the majority of fashion
conversation in terms of volume, body snaps and face images that portray
fashion items more naturally tend to receive a larger number of likes and
comments by the audience. Our findings bring insights into building an
automated tool for classifying or generating influential fashion information.
We make our novel dataset of {24,752} labeled images on fashion conversations,
containing visual and textual cues, available for the research community.Comment: 10 pages, 6 figures, This paper will be presented at ICWSM'1
Ultrahigh energy neutrino scattering: an update
We update our estimates of charged and neutral current neutrino total cross
sections on isoscalar nucleons at ultrahigh energies using a global (x, Q^2)
fit, motivated by the Froissart bound, to the F_2 (electron-proton) structure
function utilizing the most recent analysis of the complete ZEUS and H1 data
sets from HERA I. Using the large Q^2, small Bjorken-x limits of the "wee"
parton model, we connect the ultrahigh energy neutrino cross sections directly
to the large Q^2, small-x extrapolation of our new fit, which we assume
saturates the Froissart bound. We compare both to our previous work, which
utilized only the smaller ZEUS data set, as well as to recent results of a
calculation using the ZEUS-S based global perturbative QCD parton distributions
using the combined HERA I results as input. Our new results substantiate our
previous conclusions, again predicting significantly smaller cross sections
than those predicted by extrapolating pQCD calculations to neutrino energies
above 10^9 GeV.Comment: 8 pages, 1 figure, 3 table
Polystyrene-Al2O3 composite solid polymer electrolyte for lithium secondary battery
In a common salt-in-polymer electrolyte, a polymer which has polar groups in the molecular chain is necessary because the polar groups dissolve lithium salt and coordinate cations. Based on the above point of view, polystyrene [PS] that has nonpolar groups is not suitable for the polymer matrix. However, in this PS-based composite polymer-in-salt system, the transport of cations is not by segmental motion but by ion-hopping through a lithium percolation path made of high content lithium salt. Moreover, Al2O3 can dissolve salt, instead of polar groups of polymer matrix, by the Lewis acid-base interactions between the surface group of Al2O3 and salt. Notably, the maximum enhancement of ionic conductivity is found in acidic Al2O3 compared with neutral and basic Al2O3 arising from the increase of free ion fraction by dissociation of salt. It was revealed that PS-Al2O3 composite solid polymer electrolyte containing 70 wt.% salt and 10 wt.% acidic Al2O3 showed the highest ionic conductivity of 9.78 × 10-5 Scm-1 at room temperature
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