531 research outputs found
Realistic Simulation of Seasonal Variant Maples
International audienceThis paper presents a biologically-motivated system of seasonal variant scenes generation for maples, which has a obvious leaf color transformation during the time. Given climate data and knowledge on environmental influence to maples, our system is able to simulate this seasonal leaf color transformation process. Our system consists of three steps: environment configuration, climate influence simulation and leaf texture acquisition. The first step decides the general color change timing of the maple tree based on its local environment. Then we make further adjustments to the timing determined in the last step taking into account the influence of climate in the specific case. In the last step, the texture maps of leaves are generated based on the pigment information. Our system is also able to simulate the seasonal color variance of other trees by adjusting related parameters
Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content
With the increasing popularity of smart devices, rumors with multimedia
content become more and more common on social networks. The multimedia
information usually makes rumors look more convincing. Therefore, finding an
automatic approach to verify rumors with multimedia content is a pressing task.
Previous rumor verification research only utilizes multimedia as input
features. We propose not to use the multimedia content but to find external
information in other news platforms pivoting on it. We introduce a new features
set, cross-lingual cross-platform features that leverage the semantic
similarity between the rumors and the external information. When implemented,
machine learning methods utilizing such features achieved the state-of-the-art
rumor verification results
LHC Search of New Higgs Boson via Resonant Di-Higgs Production with Decays into 4W
Searching for new Higgs particle beyond the observed light Higgs boson
h(125GeV) will unambiguously point to new physics beyond the standard model. We
study the resonant production of a CP-even heavy Higgs state in the
di-Higgs channel via, , at the LHC Run-2 and
the high luminosity LHC (HL-LHC). We analyze two types of the decay modes,
one with the same-sign di-leptons () and the
other with tri-leptons (). We
perform a full simulation for the signals and backgrounds, and estimate the
discovery potential of the heavy Higgs state at the LHC Run-2 and the HL-LHC,
in the context of generical two-Higgs-doublet models (2HDM). We determine the
viable parameter space of the 2HDM as allowed by the theoretical constraints
and the current experimental limits. We systematically analyze the allowed
parameter space of the 2HDM which can be effectively probed by the heavy Higgs
searches of the LHC, and further compare this with the viable parameter region
under the current theoretical and experimental bounds.Comment: v3: JHEP published version, 34pp, 10 Figs(36 plots) and 9 Tables.
Only minor typos fixed, references added. v2: JHEP version. All results and
conclusions un-changed, discussions and references added. (This update is
much delayed due to author's traveling and flu.
Robust tile-based texture synthesis using artificial immune system
The original publication is avalaible at www.springerlink.comInternational audienceOne significant problem in tile-based texture synthesis is the presence of conspicuous seams in the tiles. The reason is that sample patches employed as primary patterns of the tile set may not be well stitched if carelessly picked. In this paper, we introduce a robust approach that can stably generate an ω-tile set of high quality and pattern diversity. First, an extendable rule is introduced to increase the number of sample patches to vary the patterns in an ω-tile set. Second, in contrast to other concurrent techniques that randomly choose sample patches for tile construction, ours uses artificial immune system (AIS) to select the feasible patches from the input example. This operation ensures the quality of the whole tile set. Experimental results verify the high quality and efficiency of the proposed algorithm
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