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	The Impact of Media Multitasking Behavior on Information Processing Among College Freshmen 期刊论文 OAI收割 Lecture Notes in Electrical Engineering, Volume 1256 LNEE, Pages 3-11, 2024, 2024, 卷号: 1256, 页码: 3-11 作者: Yongmei Zhang; Ting Tao; Wenbin Gao; Ligang Wang; Chunlei Fan \| 收藏 \| 浏览/下载：9/0 \| 提交时间：2024/10/28 media multitasking behaviour information processing depth information processing performance
	A high-speed acquisition and processing system of the laser speckle signal on the magnetic fluid (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2009: Laser Sensing and Imaging, June 17, 2009 - June 19, 2009, Beijing, China 作者: Sun Y.; Sun Y.; Wan Q.-H. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 In order to achieve the dynamical detection and real-time analysis of the movement status of the magnetic fluid according to the difficulties of the detection of the magnetic fluid established a high-speed acquisition and processing system of laser speckle signal on the magnetic fluid. First of all the FPGA (EP2C8T144C8N) drived the linear array CCD(TCD1501D) to scan in the corresponding time sequence given by the computer collected the laser speckle interferometric image in rapid change on the surface of the magnetic fluid which followed the movement of the magnetic fluid and the signal collected by CCD was converted into the digital data through the high-speed A/D convertor and stored into the internal buffer FIFO of the FPGA whose width and depth were designed by the user as required. Then the FPGA sent the digital signal of the laser speckle interferometric images into the computer through the USB2.0 highspeed differential bus whose transmission rate can reach 480Mb/s in theory. Finally the distribution of the laser speckle on the magnetic fluid was messy and random which carried certain information about the surface of the magnetic fluid based on the theories of the statistic correlation and the subdivision of images analysing and processing the laser speckle interferometric images indirectly got the movement status of the magnetic fluid under the electromagnetic field. The experimental results show that: the High Speed Acquisition and Processing System has the advantage of full-court non-contact non-invasive high-precision and high reliability and so on. The detection resolution of high speed acquisition and processing system is superior to 1m and the sample rate is 3Msps which basically meets the requirements of the magnetic fluid movement state detection. 2009 SPIE.
	Displacement estimation by the phase-shiftings of fourier transform in present white noise (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wu Y.-H. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 Displacement estimation is a fundamental problem in Real-time video image processing. It can be typically approached by theories based on features in spatial domain. This paper presents an algorithm which improves the theory for estimating the moving object's displacement in spatial domain by its Fourier transform frequency spectrum. Because of the characters of Fourier transform the result is based on all the features in the image. Utilizing shift theorem of Fourier transform and auto-registration the algorithm employs the phase spectrum difference in polar coordinate of two frame images sequence with the moving target1 2. The method needn't transform frequency spectrum to spatial domain after calculation comparing with the traditional algorithm which has to search Direc peak and it reduces processing time. Since the technique proposed uses all the image information including all the white noise in the image especially and it's hard to overcome the aliasing from noises but the technique can be an effective way to analyze the result in little white noise by the different characters between high and low frequency bands. It can give the displacement of moving target within 1 pixel of accuracy. Experimental evidence of this performance is presented and the mathematical reasons behind these characteristics are explained in depth. It is proved that the algorithm is fast and simple and can be used in image tracking and video image processing.