语义Blog系统研究

Blog是现在网络上最流行的沟通工具之一.文章在总结现有Blog系统的特点和存在问题的基础上,提出建设语义Blog系统,利用语义网的思想解决传统Blog存在的问题,增强Blog系统的语义数据描述功能和社区功能,描述Blog系统中不同主体的结构和联系,更方便用户发布和获取信息,实现Blog系统中人与人之间更加有效的沟通.     

Packet loss analysis in optical packet-switched networks with limited deflection routing

We present an approximate analytical method for the evaluation of packet loss probability in synchronous optical packet-switched networks which operate under limited deflection routing with the contention resolution method based on priorities. Packets are lost because they are removed by nodes. They are removed because they experience too many deflections and stay prohibitively long in the network. Such packets have to be removed because they will be ignored by the transmission protocols (like TCP) and because the quality of their optical signal is unacceptable. Presented are results for the network in the topology of the torus of the two-dimensional grid, which operates at a steady state with the uniform load u, . The strength of our analysis is its novel mathematical approach, which is capable of providing very low packet loss probabilities. For the network composed of 100 nodes, we predict the packet loss probability as low as 10⁻⁹ or lower, while simulation provided results only at the order of 10⁻⁶. For a given permissible packet loss probability, our analysis provides the maximal network load and the number of allowed deflections. We verify the analysis with simulation in the cases for which simulation gave results.

兴国北部“8.13”暴雨洪水简析

１９９５年８月１３日兴国县北部及东北部普降大到暴雨，这场暴雨所产一的洪水一级在本地区有实测资料记录以来的首位，为分析该地可能最大暴雨和最大洪水的研究提供了资料和依据，这次暴雨直接经济损失达１７７０万元。     

三峡船闸岩质高边坡稳定性分析

三峡永久船闸系在花岗岩体系中深挖修建，两侧形成一般高度７０－１２０ｍ、最大高度达１７０ｍ的人工开挖岩质高边坡。边坡稳定是保证通航建筑物的安全与正常运行的基本前提。取船闸区的典型断面为分析对象，考虑自重、地下水渗压力、地震力及预力锚索锚固力等荷载作用，对边坡稳定进行了极限平衡分析。结果表明，边坡具有足够的稳定性。     

离散傅里叶变换误差分析与参数设置

离散傅里叶变换( Discrete Fourier Transform,DFT) 是数字信号处理教学的重点和难点,其参数设置的正确与否直接影响信号频谱分析的准确性。本文对连续与离散周期信号、非周期信号分别进行DFT运算,从時域和频域角度分析实际频谱与理想频谱之间的误差。通过MATLAB仿真,加深学生对DFT的理解,引导学生正确设置DFT参数。     

用矩阵的LU分解算线性方程组的解

以求解线性方程组为代表的数值计算在现代科学研究和工程技术中得到广泛应用,数值分析问题的求解方法、数值计算的算法以及数值计算的计算机软件长期以来一直是人们的重要研究课题.     

On Finite Word Length Computing Error of Fixed-Point SAR Imaging Processing

Synthetic aperture radar （SAR） imaging system is generally realized by fixed-point with the purpose of reducing system implementation scale and enhancing real-time performance. Finite word length computing error of fixed-point SAR imaging system is studied. The characteristic of computing error in SAlt imaging system is analyzed. A finite word length computing error model of SAR imaging system is built, by means of which the empirical formula of system＇s output noise-to-signal ratio is derived. Based on the empirical formula, SAR imaging system processing word length is presented according to different processing granularities. The validity of this proposed finite word length computing error model of SAR imaging system is verified by system level fixed-point sivaulation.     

临近空间中核爆源区电磁脉冲与等离子体流场耦合

对临近空间中核爆源区电磁脉冲与飞行器等离子体流场的耦合进行了分析计算。对源区辐射场采用平面波近和源区感应场直接计入等离子体电导率的影响,推导出新的差分迭代公式计算。计算结果可供临近空间飞行器电磁兼容性研究参考。     

Semantic guided knowledge graph for large-scale zero-shot learning

Zero-shot learning has received growing attention, which aims to improve generalization to unseen concepts. The key challenge in zero-shot tasks is to precisely model the relationship between seen and unseen classes. Most existing zero-shot learning methods capture inter-class relationships via a shared embedding space, leading to inadequate use of relationships and poor performance. Recently, knowledge graph-based methods have emerged as a new trend of zero-shot learning. These methods use a knowledge graph to accurately model the inter-class relationships. However, the currently dominant method for zero-shot learning directly extracts the fixed connection from off-the-shelf WordNet, which will inherit the inherent noise in WordNet. In this paper, we propose a novel method that adopts class-level semantic information as a guidance to construct a new semantic guided knowledge graph (SG-KG), which can correct the errors in the existing knowledge graph and accurately model the inter-class relationships. Specifically, our method includes two main steps: noise suppression and semantic enhancement. Noise suppression is used to eliminate noise edges in the knowledge graph, and semantic enhancement is used to connect two classes with strong relations. To promote high efficient information propagation among classes, we develop a novel multi-granularity fusion network (MGFN) that integrates discriminative information from multiple GCN branches. Extensive experiments on the large-scale ImageNet-21K dataset and AWA2 dataset demonstrate that our method consistently surpasses existing methods and achieves a new state-of-the-art result.     

一种改进型DCSK保密通信系统性能分析

差分混沌键控(DCSK)的输出信号具有固有的抗噪声以及宽频特性,由于其采用非相干解调技术,不必在收发两端建立同步,相比传统通信系统有很多优势。但其传输速率较低、保密性差。针对上述问题,提出一种改进型DCSK保密通信系统。该系统将信息分散于两个正交信道中传输,不仅保证了传输速率而且提高了安全性。理论分析和仿真结果证明,改进型DCSK保密通信系统较原系统性能有极大的提高。