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	Y-Mat: an improved hybrid finite-discrete element code for addressing geotechnical and geological engineering problems 期刊论文 OAI收割 ENGINEERING COMPUTATIONS, 2022, 页码: 22 作者: Liu, Gang; Ma, Fengshan; Zhang, Maosheng; Guo, Jie; Jia, Jun \| 收藏 \| 浏览/下载：38/0 \| 提交时间：2022/07/05 Y-Mat code Combined FDEM Uniaxial compression test Brazilian split test Anti-dip slope Progressive failure process
	Application of Coded Excitation Signals for Measurement of Rock Ultrasonic Wave Velocity 期刊论文 OAI收割 PURE AND APPLIED GEOPHYSICS, 2020, 卷号: 177, 期号: 1, 页码: 487-496 作者: Wu, He-Zhen; Zhu, Wei; He, Tai-Ming; Liu, Zheng-Yi; Lan, Xiao-Wen \| 收藏 \| 浏览/下载：68/0 \| 提交时间：2020/05/18 Rock ultrasound testing barker code golay-coded excitation pulse compression
	A reconfigurable computing architecture for 5G communication 期刊论文 OAI收割 Journal of Central South University, 2019, 期号: 0, 页码: 0 作者: GUO Yang; LIU Zi-Jun; YANG Lei; LI Huan; WANG Dong-Lin \| 收藏 \| 浏览/下载：93/0 \| 提交时间：2019/07/11 5g Instruction Set Register File Code Compression Throughput Power Consumption.
	Numerical Investigation of Mineral Grain Shape Effects on Strength and Fracture Behaviors of Rock Material 期刊论文 OAI收割 APPLIED SCIENCES-BASEL, 2019, 卷号: 9, 期号: 14, 页码: 14 作者: Han, Zhenhua; Zhang, Luqing; Zhou, Jian \| 收藏 \| 浏览/下载：121/0 \| 提交时间：2019/10/14 mineral grain shape particle flow code uniaxial compression simulation rock mechanical property
	SOPC处理器的程序压缩与解压研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院大学, 2015 作者: 涂吉收藏 \| 浏览/下载：65/0 \| 提交时间：2015/09/02 星载处理机代码压缩存储系统多字典可编程片上系统 On-board Computer Code Compression Memory System Multi-Dictionary System-on-a-Programmable-Chip
	Compression of hyper-spectral images based on quadtree partitioning (EI CONFERENCE) 会议论文 OAI收割 2009 2nd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2009, August 8, 2009 - August 11, 2009, Beijing, China 作者: Zhang W.; Zhang W. 收藏 \| 浏览/下载：42/0 \| 提交时间：2013/03/25 The paper analyzes the characteristic features of hyper-spectral image and presents a compression of hyperspectral images based on quadtree partitioning. Quadtree partition is used to get the mean image of the whole image and the significant correlation of image can be decorrelated by subtract the mean image from original image. The difference image is compressed by DCT and encoded with arithmetic code. Experiment show the algorithm is simple and easy to use in real-time image compressing. 2009 IEEE.
	The compression and storage method of the same kind of medical images-DPCM (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China 作者: Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：16/0 \| 提交时间：2013/03/25 Medical imaging has started to take advantage of digital technology opening the way for advanced medical imaging and teleradiology. Medical images however require large amounts of memory. At over 1 million bytes per image a typical hospital needs a staggering amount of memory storage (over one trillion bytes per year) and transmitting an image over a network (even the promised superhighway) could take minutes - too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. Several compression techniques with different compression ratio have been developed. However the lossless techniques which allow for perfect reconstruction of the original images yield modest compression ratio while the techniques that yield higher compression ratio are lossy that is the original image is reconstructed only approximately Medical imaging poses the great challenge of having compression algorithms that are lossless (for diagnostic and legal reasons) and yet have high compression ratio for reduced storage and transmission time. To meet this challenge we are developing and studying some compression schemes which are either strictly lossless or diagnostically lossless taking advantage of the peculiarities of medical images and of the medical practice. In order to increase the Signal to-Noise Ratio (SNR) by exploitation of correlations within the source signal a method of combining differential pulse code modulation (DPCM) is presented.
	Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China 作者: Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：41/0 \| 提交时间：2013/03/25 An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image thus facilitating accurate diagnosis of course at the expense of higher bit rates i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization wavelet coding neural networks and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1 or even more) they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image but the achievable compression ratios are only of the order 2:1 up to 4:1. In our paper we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance so that all the low rate codes are included at the beginning of the bit stream. Typically the encoding process stops when the target bit rate is met. Similarly the decoder can interrupt the decoding process at any point in the bil stream and still reconstruct the image. Therefore a compression scheme generating an embedded code can start sending over the network the coarser version of the image first and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.
	Wavelet packet and neural network basis medical image compression (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China Zhao X.; Wei J.; Zhai L. 收藏 \| 浏览/下载：20/0 \| 提交时间：2013/03/25 It is difficult to get high compression ratio and good reconstructed image by conventional methods we give a new method of compression on medical image. It is to decompose and reconstruct the medical image by wavelet packet. Before the construction the image use neural network in place of other coding method to code the coefficients in the wavelet packet domain. By using the Kohonen's neural network algorithm not only for its vector quantization feature but also for its topological property. This property allows an increase of about 80% for the compression rate. Compared to the JPEG standard this compression scheme shows better performances (in terms of PSNR) for compression rates higher than 30. This method can get big compression ratio and perfect PSNR. Results show that the image can be compressed greatly and the original image can be recovered well. In addition the approach can be realized easily by hardware.