Applying deep learning in football ankle injury for value of high-power magnetic resonance bioimaging evaluation

The Journal of Supercomputing - This study was to evaluate the performance of magnetic resonance imaging (MRI) reconstruction algorithm based on convolutional neural network (CNN) in the diagnosis...     

Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution

The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR) algorithms applied to CT images to improve the resolution of CT images. However, most of the existing SR algorithms are studied based on natural images, which are not suitable for medical images; and most of these algorithms improve the reconstruction quality by increasing the network depth, which is not suitable for machines with limited resources. To alleviate these issues, we propose a residual feature attentional fusion network for lightweight chest CT image super-resolution (RFAFN). Specifically, we design a contextual feature extraction block (CFEB) that can extract CT image features more efficiently and accurately than ordinary residual blocks. In addition, we propose a feature-weighted cascading strategy (FWCS) based on attentional feature fusion blocks (AFFB) to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature information. Finally, we suggest a global hierarchical feature fusion strategy (GHFFS), which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various levels. Numerous experiments show that our method performs better than most of the state-of-the-art (SOTA) methods on the COVID-19 chest CT dataset. In detail, the peak signal-to-noise ratio (PSNR) is 0.11 dB and 0.47 dB higher on CTtest1 and CTtest2 at SR compared to the suboptimal method, but the number of parameters and multi-adds are reduced by 22K and 0.43G, respectively. Our method can better recover chest CT image quality with fewer computational resources and effectively assist in COVID-19.     

商业诽谤犯罪中网络服务提供者行为的技术与法律分析

在本案中,刑法及其司法解释完全从商业诽谤犯罪实行行为的角度进行解释,没有重视网络信息服务提供者的行为特点,实际上导致难以根据刑法以及司法解释分析网络服务提供者在网络商业诽谤违法犯罪中的责任。在商业诽谤刑事案件中,网络服务提供者不仅有义务向侦查机关提供有关资料,而且由于其在信息监管责任缺位,必须对其设置责任追究的机制,从而推动其履行商业诽谤信息审查义务。     

Implementation and evaluation of parallel FFT on Engineering and Scientific Computation Accelerator (ESCA) architecture

The fast Fourier transform (FFT) is a fundamental kernel of many computation-intensive scientific applications.This paper deals with an implementation of the FFT on the accelerator system,a heterogeneous multi-core architecture to accelerate computation-intensive parallel computing in scientific and engineering applications.The Engineering and Scientific Computation Accelerator (ESCA) consists of a control unit and a single instruction multiple data (SIMD) processing element (PE) array,in which PEs communicate with each other via a hierarchical two-level network-on-chip (NoC) with high bandwidth and low latency.We exploit the architecture features of ESCA to implement a parallel FFT algorithm efficiently.Experimental results show that both the proposed parallel FFT algorithm and the ESCA architecture are scalable.The 16-bit fixed-point parallel FFT performance of ESCA is compared with a published work to prove the superiority of the mapping algorithm and the hardware architecture.The floating-point parallel FFT performances of ESCA are evaluated and compared with those of the IBM Cell processor and GPU to demonstrate the computing power of the ESCA system for high performance applications.     

PS对剪贴图层创建图层样式的方法

该文介绍了设计Logo时对剪贴图层创建图层样式的方法。     

一种安全有效的基于身份的门限签密方案

签密是一种将加密和数字签名技术结合在一起的思想,它比采用先签名后加密的方法具有更高的效率.基于双线性对技术,提出了一种新的基于身份的门限签密方案.它利用决策双线性Diffie-Hellman(DBDH)问题的困难性在随机预言模型下给出了方案的语义安全性证明,并利用计算Diffie-Hellman(CDH)问题的困难性证明了方案的不可伪造性,同时指出方案具有较高的效率.     

香港理大设计年展面面观

从对香港理工大学设计年展的整体状况与作品分析,到与国际设计及内地设计教育的比较中,归纳了目前香港设计院校教育及设计的现状特点。立足本地,强调设计的人性化,以及对前沿国际设计的吸纳与开放性的学习都是本次年展中所折射出的主要特征。     

基于MP算法的快速地震信号谱分析

MP(Matching Pursuits)算法以其灵活的自适应性,取得了广泛的应用,但依然存在计算量大的应用瓶颈问题.为了解决传统MP算法运算量大的问题,首先对MP算法的原理进行了介绍,然后针对其计算量大的问题提出了一种基于遗传算法的快速算法,有效地降低了MP算法的运算量,较好地解决了运算量大的问题.最后利用MP算法对地震信号进行了谱分析,消除了Wigner算法中的交叉项,从而有效地揭示了地震信号的时频信息.结果表明,改进后的MP算法可以作为地震信号谱分析的有效算法,为烃类检测和储层描述等提供有地效的手段.     

基于文档空间向量距离的查询扩展

查询扩展是信息检索中优化查询的一种有效方法。在分析几种基于互信息的查询扩展方法的基础上,将检索词在文档空间中的距离引入到互信息计算中,提出基于向量距离的改进互信息的查询扩展方法。实验结果表明,该方法能够有效提高信息检索中的查询效果。     

基于OMNeT++的Ad Hoc网络跨层协议栈仿真

针对OMNeT++的MFW组件中物理层和MAC层模块的错误进行修正和功能改进,实现基于RBAB的IEEE 802.11b协议速率自适应数据传输,建立移动Ad Hoc网络跨层协议栈模型的网络仿真框架,实现将Ad Hoc网络MAC层的速率自适应机制与其路由协议联合优化设计的仿真。结果表明,在移动环境下,采用跨层设计的网络协议栈能大幅提高Ad Hoc网络系统的性能。