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CAS IR Grid
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长春光学精密机械与物... [4]
自动化研究所 [2]
合肥物质科学研究院 [2]
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数学与系统科学研究院 [1]
过程工程研究所 [1]
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OAI收割 [13]
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期刊论文 [8]
会议论文 [5]
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天文技术与方法 [1]
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DeCASA in AgriVerse: Parallel Agriculture for Smart Villages in Metaverses
期刊论文
OAI收割
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 12, 页码: 2055-2062
作者:
Xiujuan Wang
;
Mengzhen Kang
;
Hequan Sun
;
Philippe de Reffye
;
Fei-Yue Wang
  |  
收藏
  |  
浏览/下载:18/0
  |  
提交时间:2022/12/02
Parallel Agriculture Management and Control
AgriVerse
Agriculture CPSS
ACP
DAO-Based Platform
Precision Agriculture
Dynamic analysis of multi-functional maintenance platform based on Newton-Euler method and improved virtual work principle
期刊论文
OAI收割
NUCLEAR ENGINEERING AND TECHNOLOGY, 2020, 卷号: 52
作者:
  |  
收藏
  |  
浏览/下载:66/0
  |  
提交时间:2020/11/30
China Fusion engineering test reactor
Divertor
Multi-functional maintenance platform
3-RPS parallel Robot
Dynamic analysis
ADAMS simulation
Kinematics analysis and testing of novel 6-P-RR-R-RR parallel platform with offset RR-joints
期刊论文
OAI收割
Proceedings of the Institution of Mechanical Engineers Part C-Journal of Mechanical Engineering Science, 2019, 卷号: 233, 期号: 10, 页码: 3512-3530
作者:
H.Han
;
C.Y.Han
;
Z.B.Xu
;
M.C.Zhu
;
Y.Yu
  |  
收藏
  |  
浏览/下载:35/0
  |  
提交时间:2020/08/24
Parallel platform,Offset RR-joint,Inverse kinematics,6-P-RR-R-RR,kinematic chains,design,mechanism,manipulator
Size optimization of the moving platform for cable-driven parallel manipulators based on stiffness characteristics
期刊论文
OAI收割
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2018, 卷号: 232, 期号: 11, 页码: 2057-2066
作者:
Zhang, Bin
;
Shang, Wei-Wei
;
Cong, Shuang
;
Liu, Yi
  |  
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2019/08/26
Cable-driven parallel manipulators
static stiffness
stable workspace
moving platform
optimization problem
Development of a massively parallel sequencing assay for investigating sequence polymorphisms of 15 short tandem repeats in a Chinese Northern Han population
期刊论文
OAI收割
ELECTROPHORESIS, 2018, 卷号: 39, 期号: 21, 页码: 2725, 2731
作者:
Zhang, QX
;
Yang, M
;
Pan, YJ
;
Zhao, J
;
Qu, BW
  |  
收藏
  |  
浏览/下载:59/0
  |  
提交时间:2018/12/29
Chinese Northern Han
STR LOCI
Forensic science
FORENSIC MARKERS
Massively parallel sequencing
ION PGM(TM)
Sequence variants
PLATFORM
Short tandem repeats
IDENTIFICATION
Parallel Transportation Management and Control System for Subways
期刊论文
OAI收割
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2017, 卷号: 18, 期号: 7, 页码: 1974-1979
作者:
Xiong, Gang
;
Shen, Dayong
;
Dong, Xisong
;
Hu, Bin
;
Fan, Dong
  |  
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2017/09/12
Subways
Acp Approach
Status Perception
Artificial Subway System
Computational Experiments Platform
Parallel Execution System
Modeling and Simulation of a 6-DOF Parallel Platform for Telescope Secondary Mirror
会议论文
OAI收割
Montréal, Quebec, Canada, 2014-6-22
作者:
Yu Ye
;
Bozhong Gu
;
Zhongyu Yue
收藏
  |  
浏览/下载:36/0
  |  
提交时间:2015/03/13
parallel platform
Stewart
telescope secondary mirror
FEM
multi-body dynamics
基于OpenCL的图像重映射算法优化研究
期刊论文
OAI收割
科研信息化技术与应用, 2013, 期号: 1, 页码: 57-66
吴再龙
;
张云泉
;
龙国平
;
徐建良
;
贾海鹏
  |  
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2014/12/16
OpenCL
通用计算
图像重映射算法
跨平台
OpenCL
Parallel computing
Image remap
Cross-platform
Far-field focusing of laser beam based on digital image processing techniques (EI CONFERENCE)
会议论文
OAI收割
Optoelectronic Imaging and Multimedia Technology, October 18, 2010 - October 20, 2010, Beijing, China
作者:
Zhao S.
;
Tian Y.-Z.
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2013/03/25
In order to lead the laser beam transmit in the atmosphere convergently
an experiment of laser focus at the distance of 450m and 300m has been operated in the outdoor place. The actual manipulations are as follows: Firstly
the laser was collimated by a beam expander
then the near-parallel laser beam was transmitted with a Galileo telescope system
and the distance between the concave lens and the convex lens can be tuned through a precise displacement platform
so the focus of the system changed due to the tiny displacement of the concave lens. Secondly
the average power of the laser spot can be measured using power meter
the power is 47.67mW and the standard deviation is 0.67mW while the focal length is 450m. Thirdly
the energy distribution was found through the laser beam analyzer. The spot images were saved using the beam analyzer
then the saved image can be processed with Matlab software afterwards. The function named EDGE and Sobel operator was used in the pre-processing of the saved image
then method of median filter was used in the course of image de-noising and 53H filter was adopted in the signal analysis. The diameter of laser spot was obtained by the method above
the diameter is 5.56mm and the standard deviation is 0.24mm. The spot center excursion is 0.56mm
it is 10.43% of the total diameter of the laser spot. At last
the key factors of the energy dissipation in the focusing system can be summarized as follows: restriction of the diffraction limit
attenuation in the atmosphere
geometrical aberration of optical system
and the diffraction limit and the geometrical aberration are significant in the three factors above
so we can reduce the impact of the both factors during the design of optical system. The reliable referenced data of the system design can be acquired through the primary experiment research. 2010 SPIE.
Image parallel processing based on GPU (EI CONFERENCE)
会议论文
OAI收割
2010 IEEE International Conference on Advanced Computer Control, ICACC 2010, March 27, 2010 - March 29, 2010, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
作者:
Wang J.-L.
;
Wang J.-L.
收藏
  |  
浏览/下载:31/0
  |  
提交时间:2013/03/25
In order to solve the compute-intensive character of image processing
based on advantages of GPU parallel operation
parallel acceleration processing technique is proposed for image. First
efficient architecture of GPU is introduced that improves computational efficiency
comparing with CPU. Then
Sobel edge detector and homomorphic filtering
two representative image processing algorithms
are embedded into GPU to validate the technique. Finally
tested image data of different resolutions are used on CPU and GPU hardware platform to compare computational efficiency of GPU and CPU. Experimental results indicate that if data transfer time
between host memory and device memory
is taken into account
speed of the two algorithms implemented on GPU can be improved approximately 25 times and 49 times as fast as CPU
respectively
and GPU is practical for image processing. 2010 IEEE.