一种新的块体接触检测技术及在非连续变形分析方法中的应用

基于隐式网格的空间剖分,采用包围体技术将离散块体通过链表进行表述.所有离散块体的循环可以改造成一个等价的循环模式,在该循环模式内部的操作既不依赖于隐式网格的横向数目,也不依赖于其竖向数目.因此,该新循环模式所需的接触检测CPU总时间不再依赖于隐式网格的数目,即接触检测所需CPU总时间为块体数量的线性函数.算例和数值试验表明:用于接触检测的CPU总时间正比于离散块体的数目;相对于传统方法,该方法可以大大减少接触检测的CPU时间,显著提高计算效率.     

壁面粘贴质量检测系统设计

利用空鼓壁面与正常壁面接受同种敲击体敲击产生音频特性的不同,设计一种以负压吸附爬壁机器人为载体的壁面粘贴质量检测诊断系统,通过计算机软件实现敲击声音信号的提取、分析与处理.音频信号被转化为数字信号后,利用Matlab软件进行数字信号处理:首先应用高通滤波器滤除信号中的风机噪声信号,继而对滤波后的音频信号进行特征参数的分析提取,根据所得特征参数筛选与正常信息不相吻合的故障参数,最终实现对空鼓的判定.实验结果表明,该方法简单易行,准确度较高.     

社交网络环境下社区发现的文献计量研究--基于Web of Science

基于Web of Science中检索得到的文献数据,使用CiteSpace、SATI、UCINET等软件构建科学知识图谱,从国家及机构、关键文献、关键词及突现词等角度对社交网络环境下有关社区发现的研究现状、研究热点和研究前沿进行了文献计量分析。     

一种新型室内空气质量检测仪的设计

为了普通民众能够准确得知室内空气污染状况,设计了一种涉及室内甲醛(HCHO)、氨(NH3)和苯(C6H6)这三种气体浓度的新型室内空气质量快速检测仪.该仪器主要通过气体传感器得到对应气体浓度的微弱电流信号,再通过一种新型的高精度信号处理电路和基于FPGA的模数转换电路得到对应气体的初始浓度值,结合室内环境气压、温湿度情况和修正算法得到更准确的浓度值.该仪器还具有浓度超标报警、测量数据打印输出等功能及检测精度高、速度快、稳定性好、携带方便等优点.     

用天线阵技术无损探测大桥钢筋网的三维分布

常规的探地雷达发射的电磁波和接收的电磁波均为同一频率,因此影响了探测的精度、效率.天线阵探地雷达将不同频率的天线组合到一起工作,实现了一次扫描得到4张雷达图,使深部、浅部探测一次同时完成,提高了探测精度和工作效率,节约了探测成本.另外,由于不同频率的天线对不同深度的被探测体有足够的分辨率,不同位置的天线对同一被探测体进行全区域、多角度的探测,所以天线阵探地雷达能够分辨上下重叠或位置很近的被探测体,使得对一个区域的钢筋网进行三维探测成为可能.     

基于复数FastICA算法的盲多用户检测

针对MIMO-OFDM系统,提出了一种基于复数FastICA的盲多用户检测算法.该算法首先利用复数FastICA算法的快速收敛特性来提高多用户的分离速度,同时利用信号的相关函数对复数FastICA算法引起的幅度不确定性和相位不确定性进行了修正,最后将所提出的改进算法与复数自然梯度学习算法(CNGLA)进行仿真比较.结果表明,相比于传统的自然梯度算法,所提算法不仅收敛速度较快,而且具有更低的误码率,另外随着接收天线的增多,信号的分离效果会更好.     

On design of physical random access channel in high-speed railway LTE systems

For the uplink in the long-term evolution （LTE） systems, the physical random access channel （PRACH） adopts Zadoff-Chu （ZC） sequences as preamble sequences, and each user can choose a unique cyclic shift for user identification. In high-mobility scenario, the Doppler fre- quency shift raises up the false alarm probability by inducing the correlation peak offsetting at the receiver side. Traditional detection method utilizes multiple search win- dows for searching the potential uplink users. When the Doppler frequency shift is larger than the subcarrier spac- ing, the energy of correlation peak leaks outside the search window and increases the false alarm probability. In this paper, we present a novel design for PRACH preamble sequence for high-speed railway scenario. Through numerical observation, we find out that the offset of the correlation peaks only depends on the initial root sequence number and the length of ZC sequences. Therefore, the root number of ZC sequences should be carefully designed to generate a preamble sequence to fight against the Doppler frequency shift. Consequently, those offsets of the corre- lation peaks are concentrated within a single search win- dow, resulting in lower complexity of detection and lower probability of false alarm for random access in LTE uplink.     

A machine learning-based method to detect fluorescent spots and an accelerated,parallel implementation of this method

Under most microscopes, the fluorescent sig- nals emitted from biological structures, such as vesicles, as well as the signals from single molecules will appear as small puncta, which contribute to a Gaussian-like distri- bution. Accurate segmentation of these spots will funda- mentally affect our interpretation of a specific biological progress. Because of the complicated backgrounds in images, many algorithms fail to identify all of the inter- esting signals; the tremendous amount of time required for algorithms to process large datasets can also decrease their utility. Here, we introduce an excellent robust detection method based on the machine learning algorithm Ada- Boost, which outperforms threshold-based segmentation, wavelets, and FDA under most situations. We also provide a GPU/multi-core CPU implementation of this algorithm; this implementation accelerates the algorithm approxi- mately 10- and 7-fold acceleration compared with a single CPU implementation. The great reduction of time should make this method a promising candidate in the processing of large datasets. Furthermore, we demonstrate the use of our algorithm on true fluorescent micrographs, and the results show that machine learning-based detection meth- ods outperform the four other previously reported methods.     

高光谱遥感图像异常检测研究进展

高光谱遥感图像异常检测即是对遥感图像中与背景存在显著光谱差异的像元进行识别,它在灾害预测和环境监测等领域具有很大应用价值.异常检测受到遥感学界的普遍重视,这些年来对异常检测开展的研究取得了不少成果.高光谱图像异常检测研究最初基于传统数据处理和信号分析方法,随着高光谱图像数据处理研究的深入及数据挖掘技术和智能学习方法等相关技术的发展,现在呈现智能和联合处理的新方向.文章对异常检测算法近来的研究进展进行的介绍以期为异常检测的相关研究提供一定参考.     

单幅图像三维目标定位及重建

首先对图像进行拉普拉斯滤波处理,进而利用Canny算子对图像进行边缘检测,通过Hough变换检测目标图像,采用CAD辅助提取边界直线,基于灭点理论标定数码相机,之后采用透视投影模型中基于图像相对深度方法对图像三维信息进行恢复。最后计算出了目标物体的特征点三维坐标,实现目标定位。通过CAD实现模型的重建与显示。