Impact of DEM accuracy and resolution on topographic indices

Topography is an important land-surface characteristic that affects most aspects of the water balance in a catchment, including the generation of surface and sub-surface runoff; the flow paths followed by water as it moves down and through hillslopes and the rate of water movement. All of the spatially explicit fully distributed hydraulic and hydrological models use topography (represented by the DEM of the area modelled) to derive bathymetry. DEM is also used to derive some other key information critical in fully distributed hydraulic and hydrological models.With high-resolution DEMs such as LiDAR (Light Detection and Ranging) becoming more readily available and also with the advancements in computing facilities which can handle these large data sets, there is a need to quantify the impact of using different resolution DEMs (e.g. 1 m against 10 m or 25 m) on hydrologically important variables and the loss of accuracy and reliability of the results as we move from high resolution to coarser resolution.The results from statistical analysis carried out to compare field survey elevations with the LiDAR DEM-derived elevations, show that there are small differences between the two data sets but LiDAR DEM is a reasonably good representation of the actual ground surface compared to other commonly used DEMs derived from contour maps.The results from the analysis clearly show that the accuracy and resolution of the input DEM have serious implications on the values of the hydrologically important spatial indices derived from the DEM. The result also indicates that the loss of details by re-sampling the higher resolution DEM to coarser resolution are much less compared to the details captured in the commonly available coarse resolution DEM derived from contour maps. Topographic indices based on contour derived DEMs should be used with caution and where available, the higher resolution DEM should be used instead of the coarse resolution one.     

Parallel Distance: A New Paradigm of Measurement for Parallel Driving

In this paper, a new paradigm named parallel dis-tance is presented to measure the data information in parallel driving system. As an example, the core variables in the parallel driving system are measured and evaluated in the parallel distance framework. First, the parallel driving 3.0 system included control and management platform, intelligent vehicle platform and remote-control platform is introduced. Then, Markov chain (MC) is utilized to model the transition probability matrix of control commands in these systems. Furthermore, to distinguish the control variables in artificial and physical driving conditions, different distance calculation methods are enumerated to specify the differences between the virtual and real signals. By doing this, the real system can be guided and the virtual system can be im-proved. Finally, simulation results exhibit the merits and multiple applications of the proposed parallel distance framework.      

一种适用于无线多媒体传感器网络的节点不相交多路径路由协议

设计了一种适用于无线多媒体传感器网络的高效节点不相交多路径路由协议.以源路由的方式建立多路径,中间节点通过有选择的转发RREQs,降低路由建立开销.将链路质量量化为数据接收率,利用数据接收率、节点能量及路径跳数等,定义了路径效率模型,将路径效率模型引入到路由建立过程中.仿真结果表明,与SMR及TinyONDMR协议相比,新协议建立路由的开销更低,所建路径上节点能量分布更理想,进行数据传输时的能量效率更高,同时不会显著增加路径的传输时延.     

基于TMS320C6678的多核程序加载研究与实现

针对多核D SP系统程序加载复杂的问题,基于T MS320C6678对多核程序加载进行了研究与设计。从一级引导程序出发,设计并优化了多核程序内容存储格式。设计了简洁的二级引导程序,以修正一级引导程序只识别主核程序入口地址,而从核入口地址缺失的现象。为了快速生成特定格式的多核程序内容,设计了多个工具用于添加S PI启动参数表、DDR3启动表、从核程序入口地址以及完成程序内容格式的转换。实现了S PI Flash多核程序加载以及基于I2C主模式的Nand Flash多核程序加载。     

车联网环境下基于重复博弈的恶意车辆节点检测机制

针对车联网内部存在的虚假信息攻击,以及节点动态变化快及密集程度不同造成的恶意车辆节点检测机制效率低下,提出了一种基于重复博弈的恶意车辆节点检测机制。首先,根据车辆在信息交互中的行为建立重复博弈模型,并利用生成的节点收益计算出信任值与动态阈值,经二者比较,筛选出可疑的恶意车辆节点;其次,通过权值投票算法从可疑的恶意车辆节点中判定出恶意车辆节点;最后,从邻居列表中选取信任值最高的下一跳车辆节点进行合作。仿真和分析表明,与现有的相关机制相比,该机制提高了对虚假信息攻击的检测率,降低了误检率。     

面向移动平台人脸检测的FaceYoLo算法

针对移动平台上人脸检测实时性不强的问题,提出了一种基于深度学习的FaceYoLo实时人脸检测算法。首先,在YoLov3检测算法的基础上,加入快速消化卷积层（RDCL）缩小输入空间,然后加入多尺度卷积层（MSCL）丰富不同检测尺度的感受野,最后加入中心损失和致密化策略加强模型的泛化能力和鲁棒性。实验结果表明,在GPU上测试时,该算法较YoLov3算法在速度上提高至原来的8倍,每幅图像的处理速度可达0.002 8 s;精度提高了2.1个百分点;在Android平台上测试时,该算法较最好的MobileNet模型在检测速率上从5 frame/s提升到10 frame/s。通过实验结果可知,该算法能有效提高人脸检测在移动平台上的实时性能。     

基于Logistic混沌系统的图像加密算法研究

给出了一种基于Logistic混沌系统的快速数字图像加密算法.首先通过给定的密钥序列生成混沌系统的初值,由此初值生成混沌矩阵;然后利用此混沌矩阵与原图像进行按位异或运算得到中间过渡图像;最后再对中间过渡图像作混沌置乱运算和混沌块置乱操作.该算法的优点是不论融合还是置乱均是利用混沌序列进行操作.实验数据表明,该算法简单易行,加密与恢复效果良好,具有较好的安全性.     

Multi-objective layout optimization for an orbital propellant depot

Structural and Multidisciplinary Optimization - The overall layout optimization design of an orbital propellant depot involves the optimization of shape, size, and positions of propellant tanks in...     

An elastic net-based hybrid hypothesis method for compressed video sensing

Multimedia Tools and Applications - Compressed Sensing, an emerging framework for signal processing, can be used in image and video application, especially when available resources at the...     

A Novel Robust Pid Controller Design By Fuzzy Neural Network

In this paper, we propose a robust PID controller tuning method for parametric uncertainty systems (or interval plant family) using fuzzy neural networks (FNNs). This robust controller is based on robust gain and phase margin (GM/PM) specifications that satisfy user requirements. Here, the FNN system is used to identify the relation between the PID controller parameters and robust GM/PM. We can use the trained FNN system to determine the parameters of the PID controllers in order to satisfy robust GM/PM specifications that guarantee robustness and performance. Simulation results are shown to illustrate the effectiveness of the robust controller scheme.