7,594 research outputs found
MODEL OF WORKING SHIP CROSSING CHANNEL
An application method for working ship crossing safely is proposed to determine how to make navigation scheme at a certain time. This method makes it possible for decision makers to make reasonable judgments at different times. In this paper, the position relationship between working ship and navigation vessel in waterway is analysed by considering the ship size, hydrological conditions of waterway, ship arrival model and ship navigation trajectory. Using genetic algorithm, the operation scheme of keeping a safe distance between the working ship and the vessel in the channel is solved by taking the speed and direction of the working ship as genetic factors. By analysing the crossing scheme at each starting time in a given time range, the optimal crossing scheme with the farthest distance between the working ship and the vessels in the channel is obtained. According to the measured data, the simulation is carried out with MATLAB to verify the model of working ship crossing channel. The results show that it is safe and reliable to choose the navigation scheme proposed in this paper, which has strong application value
Systematic study of elliptic flow parameter in the relativistic nuclear collisions at RHIC and LHC energies
We employed the new issue of a parton and hadron cascade model PACIAE 2.1 to
systematically investigate the charged particle elliptic flow parameter
in the relativistic nuclear collisions at RHIC and LHC energies. With randomly
sampling the transverse momentum and components of the particles
generated in string fragmentation on the circumference of an ellipse instead of
circle originally, the calculated charged particle and
fairly reproduce the corresponding experimental data in the Au+Au/Pb+Pb
collisions at =0.2/2.76 TeV. In addition, the charged particle
and in the p+p collisions at =7 TeV as well as
in the p+Au/p+Pb collisions at =0.2/5.02 TeV are predicted.Comment: 7 pages, 5 figure
Progressive Domain-Independent Feature Decomposition Network for Zero-Shot Sketch-Based Image Retrieval
Zero-shot sketch-based image retrieval (ZS-SBIR) is a specific cross-modal
retrieval task for searching natural images given free-hand sketches under the
zero-shot scenario. Most existing methods solve this problem by simultaneously
projecting visual features and semantic supervision into a low-dimensional
common space for efficient retrieval. However, such low-dimensional projection
destroys the completeness of semantic knowledge in original semantic space, so
that it is unable to transfer useful knowledge well when learning semantic from
different modalities. Moreover, the domain information and semantic information
are entangled in visual features, which is not conducive for cross-modal
matching since it will hinder the reduction of domain gap between sketch and
image. In this paper, we propose a Progressive Domain-independent Feature
Decomposition (PDFD) network for ZS-SBIR. Specifically, with the supervision of
original semantic knowledge, PDFD decomposes visual features into domain
features and semantic ones, and then the semantic features are projected into
common space as retrieval features for ZS-SBIR. The progressive projection
strategy maintains strong semantic supervision. Besides, to guarantee the
retrieval features to capture clean and complete semantic information, the
cross-reconstruction loss is introduced to encourage that any combinations of
retrieval features and domain features can reconstruct the visual features.
Extensive experiments demonstrate the superiority of our PDFD over
state-of-the-art competitors
2-Chloromethyl-2,3-dihydrothieno[3,4-b][1,4]dioxine
In the molecule of the title compound, C7H7ClO2S, the six-membered ring adopts a twisted conformation. In the crystal structure, weak intermolecular C—H⋯O hydrogen bonds link the molecules. There is also a weak C—H⋯π interaction
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