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A Road Vehicle Detection Algorithm Based on Compressive Sensing
Yiqin CAO,Xiaoci ZHOU,Xiaosheng HUANG 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.1
With the aim to solve the problems of large amount of image data transmission and low accuracy of the initial background image extracted in traditional vehicle detecting system, this article proposes a road vehicle detecting algorithm based on compressive sensing. Image signals are sparse in a wavelet basis and the Gaussian random measurement matrix is adopted to compress videos, which reduce the amount of image data transmission. This article uses the proposed improved initial background extracting method and selective background updating method to obtain the initial background image and background updating which improves the accuracy of the initial background image. The vehicle detection and selective reconstruction of foreground image of vehicle are achieved by integrated background subtraction and the orthogonal matching pursuit algorithm. Through many experiments in video monitoring of real scenes, the article proves the correctness and efficiency of the algorithm. It not only improves the accuracy of the initial background image extracted but also reduces the amount of image data transmission and power consumption as well as the price of video transmission.
Yiqin Lu,Youfang Huang,Bin Yang 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.2
The key to improve the container terminal efficiency is the integrated optimization of the quay crane (QC) and the yard truck (YT) scheduling, which is normally settled separately and considered in a certain condition in classical literatures. To improve the operation efficiency and simulate the practical operation, a PSO-based integrated QC-YT scheduling optimization model with uncertain factors is established in this research, considering two uncertain factors of YT travel speed and unit time of QC loading/discharging operation that affect the operating efficiency of the terminal greatly. The goal is the minimal operated time of QCs with the coordination of YTs. To solve this difficult combinatorial problem, the PSO algorithm is developed. PSO is evaluated for combinatorial problems with uncertain factors, which represents a new application of PSO. Numerical experiments show that the model of this research gives systemic simulation for the scheduling process with uncertain factors. And the results are better than model without uncertainties in terms of the accuracy and stability.
Optimized Assembly of Micro-/Meso-/Macroporous Carbon for Li–S Batteries
Qiong Tang,Heqin Li,Min Zuo,Jing Zhang,Yiqin Huang,Peiwen Bai,Jiaqi Xu,Kuan Zhou 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2017 NANO Vol.12 No.2
In order to explore the effect of hierarchical porous carbon on the performances of Li–S batteries, we synthesized three kinds of micro-/meso-/macroporous carbon materials with different pore properties by facile hard-template method. Different from the majority of reports on porous carbon ensuing large specific surface area (SSA) and total pore volume, it was found that in the case of identically high sulfur content, the pore size distribution substantially influences the performances of Li–S batteries rather than the SSA and total pore volume. Furthermore, in the assembly of micro-/meso-/macropores, the micropore volume ratio to the total pore volume is dominant to the capabilities of batteries. Among the samples, the porous carbon carbonized with the precursor of sucrose at 950℃ presents the highest initial discharge specific capacity of 1327 mAh/g and retention of 630 mAh/g over 100 cycles at 0.2C rate along with the best rate capability. This sample possesses the largest micropore volume ratio of 47.54% but a medium SSA of 1217 m2 /g and inferior total pore volume of 0.54 cm3 /g. The abundant micropores effectively improve the conductivity of dispersed sulfur particles, inhibit the loss of sulfur series and enable the cathode to exhibit superior electrochemical performances.