输出刚度矩阵

fluent 案例很好用，值得推荐大家学习和参考。(fluent examples. It is worth recommending people to learn and refer to)

bios中断编程 做出一个界面 可拖动 最大化最小化-bios interrupted programming interface can make a drive to maximize the minimum

说明：  用于分析信号的emd函数，可以分离信号和噪声，获取更精确的信号(The EMD function, which is used to analyze the signal, can separate the signal from the noise and obtain more accurate signal)

这个万年历是用java语言编写的，界面很漂亮，简洁大方，使用很简单，还带有节气，时间，阴历，功能强大

均匀化理论的结果读取文件，可以直接读取刚度矩阵(The result of homogenization theory reads the file, and the stiffness matrix can be read directly.)

ns2 wireless仿真 tcl脚本实例 很有参考价值-ns2 wireless simulation

We now compare our method to prior stochastic configurations solutions [19]. This methods

说明：  在探讨D2D 对通信技术未来发展的导向作用基础上，明确了影响D2D 系统设计的多个因素，即D2D 设 备发现、资源分配、缓存技术、D2D-MIMO。从而勾画出基于D2D 技术的光纤前传和软件定义网络实现数据/控制分离的扁平化5G 架构，提出负责接入的下层宏/小基站蜂窝网和负责管理的上层网络云的管理机制。将D2D技术、SDN 技术、边缘计算和物联网技术等关键技术引入未来移动通信网络已经成为研究领域的热点，针对与之相关的、未来大规模网络的移动性、QoS 和大数据特性进行了讨论。(On the basis of discussing the guiding role of D2D in the future development of communication technology, this paper makes clear the factors influencing the design of D2D system, namely D2D hypothesis Standby discovery, resource allocation, caching techniques, d2d-mimo.Thus, the flat 5G architecture for data/control separation is outlined based on D2D technology of optical fiber prepreel and software-defined network, and the management mechanism of the lower macro/small base station cellular network responsible for access and the upper network cloud responsible for management is proposed.The introduction of D2D technology, SDN technology, edge computing and Internet of things into the future mobile communication network has become a hot topic in the research field.)

在频域中组合空间域和局部相位量化（LPQ）的局部二进制模式（LBP）用于面部识别。 首先，从LBP特征和频域中提取人脸图像以提取LPQ特征，然后合并到LBP / LPQ直方图中以比较直方图相似度。 最后，使用最近邻原则来识别。 在YALE和AR标准人脸数据库上的实验表明，该方法获得的结果优于单一方法。(A local binary pattern (LBP) combining spatial domain and local phase quantization (LPQ) in frequency domain for face recognition. Firstly, the face image is extracted from the LBP feature and the frequency domain to extract the LPQ feature, and then merged into the LBP /LPQ histogram to compare the histogram similarity. Finally, the nearest neighbor principle is used to identify. Experiments on the YALE and AR standard face databases show that the results obtained by this method are better than the single method.)

PSCAD，IEEE14节点系统模型，可供参考(PSCAD IEEE 14-bus system model)