ID 原文 译文
39986 研究结果表明：在线翻译搜索指数虽然呈现出显著的波动特征，但大部分时间仍以小波动为主； The results show that:although the search index of online translation shows significant fluctuation characteristics, it is still dominated by small fluctuations in most of the time;
39987 在线翻译网络的最短路径长度分布近似呈偏态分布，网络中从一个符号到另一个符号的转换平均需要3个中间符号； the distribution of the shortest path lengths of the online translation network is approximately skewed distribution, and the conversion from one symbol to another in the network requires three intermediate symbols on average;
39988 波动性较小的符号具有较大的聚类系数； the symbols with less volatility have larger clustering coefficient;
39989 在线翻译整体呈下降趋势，经历了从早期不成熟到逐渐成熟的过程。 online translation shows a downward trend as a whole, and has experienced a process from early immature to gradually mature.
39990 基于肌音信号（Mechanomyogram，MMG）的模式识别是指采集MMG信号，应用机器学习算法进行动作识别的过程。 Mechanomyogram(MMG)-based pattern recognition refers to the process of collecting MMG bands and applying machine learning algorithms to perform motion recognition.
39991 为了实现手语实时分类，本文采用基于STM32芯片的轻量级嵌入式设备，控制双轴加速度传感器采集了前臂3块肌肉的6通道MMG， To realize the real-time classification of sign language motions, six-channel MMG signals of three muscles on forearm are collected by dual-axis acceleration sensors which are controlled by lightweight embedded device with STM32 chip.
39992 应用反向传播神经网络（Back propagation neural network，BPNN）算法建立分类模型，并将模型参数导入嵌入式系统中，实现算法的移植。 The back propagation neural network(BPNN) algorithm is used to establish recognition classification models, where the parameters are extracted and put into the embedded system to transfer BPNN algorithm.
39993 实验结果表明该嵌入式系统可实现30种手语的实时识别，模型自测识别率达99.6%，实时识别中可达97.5%， The embedded device can accomplish real-time recognition of 30 kinds of sign language motions, with the self-test accuracy up to 99.6% and the accuracy of real-time recognition up to 97.5%.
39994 每个动作分类所需时间少于0.52 ms，满足实时性要求，具有较高的实际应用价值。 Moreover, the classification time for each motion is less than 0.52 ms, satisfying the real-time recognition condition.
39995 本文的研究结果可应用于人体康复工程，哑语翻译器，义肢控制等领域。 The results can be applied to the fields of rehabilitation engineering, sign language translator, and prosthetic control, etc.