In view of the tracing of the pedestrian history trajectory, a counter-tracking method based on multi-camera is proposed. Firstly, a basic database including many attributes such as video frame rate and perspective relationship is established. Secondly, all of the cameras in the environment are calibrated and the relationships among them are constructed. Various features obtained by ResNet neural network are used to improve the accuracy of recalibration for the processed camera data. Finally, using the mean-shift algorithm realizes target tracking and traceability in reverse-time. Compared with ASMS, ColorKCF and Staple algorithm, experiments in the paper show that the proposed method has some advantages in accuracy and loss rate of target tracking, which is effective in practical application.
ABSTRACTFor solid oxide fuel cells, the percolation model is a mathematical tool to predict the percolating properties (percolating probability, total and effective three-phase boundaries (TPB), etc.) of an electrode. Here, a grid-based 3D percolation model is proposed. Compared with the traditional analytic percolation models, it is more comprehensive because it additionally accounts for the active TPBs near the electrolyte–electrode interface and the percolating probability of pore. Moreover, compared with the pixel-based 3D reconstruction models, this model consumes much less time and memory, which makes large domain size simulation efficient. To characterize the experimental repeatability and reproducibility of the percolating properties among numerous electrodes, distribution profile is introduced to the simulation where quantities of numerical samples are generated and counted. Our model results match well with the reported ones. The optimal porosity is 30%–35% for our studied cases. Our model suggests that the pore percolating probability could not be neglected in the percolation simulations. Finally, domain size effect is investigated. TPB density becomes converged when the domain. size is at least 12 times the particle diameter. This model provides a practical and flexible access to the large domain simulations of the electrode percolating properties.KEYWORDS: Percolation modelSOFC electrodeactive TPBsimulation AcknowledgementsThe work is funded by the National Natural Science Foundation of China (NSFC) under Grant No. 11705003, University Science Research Project of Anhui Province under Grant No. 2022AH030104, and the Key Project of Universities Natural Science Research of Anhui Province under Grant No. KJ2021A0638. We are grateful to the GNU-GCC and python community for their efforts on the free and open-source software.Disclosure statementNo potential conflict of interest was reported by the author(s).
Granular biochar was prepared by fast co-pyrolysis of a mixture of sawdust and kaolin. Both mechanical stability and adsorption performance improved with the addition of FeCl3.
Lithium cobalt oxide (LCO) as a classic layered oxide cathode for lithium-ion batteries is limited by the cutoff voltage, which only delivers about half of the theoretical capacity (∼4.2 V, 140 mA h g-1). Recently, raising the cutoff voltage to 4.6 V has been considered to further improve its specific capacity. However, LCO suffers from serious phase transition of O3 to H1-3, which leads to dramatic volume change and loss of cobalt, finally resulting in rapid capacity decay. In this work, we introduce the NASICON-structured LiZr2(PO4)3 (LZP), an ion conductor for lithium ion, to modify the surface of LCO by a wet-chemical method. Such a surface modification improves lithium-ion diffusion between the interface of LCO and electrolyte and restrains the O3 to H1-3 phase transition. As a result, the optimized LCO with 1 wt % coating (denoted as LCO@LZP-1%) demonstrates enhanced electrochemical performance in both half-cell and full-cell. To be specific, LCO@LZP-1% delivers a high specific capacity of 161.3 mA h g-1 and increases the capacity retention from 37.8 to 75.1% within 100 cycles. Importantly, the full-cell assembled by LCO@LZP-1% and artificial graphite can exhibit an outstanding energy density of 345.5 W h kg-1 (based on the total mass of cathode and anode).
Two key techniques – impulse acoustic microscopy and X-ray microtomography; have been applied in combination for studying bulk microstructure in polymer composites whose properties critically depend on their spatial organization – nanocomposites and fiber reinforced plastics. It has been shown the both techniques are able to represent 3D internal structure with micron resolution. The technique is based on different principles of 3D imaging and employs distinct mechanisms of contrast for microstructure displaying. In many cases they are complementary in 3D microstructure recovering.
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