D2D协作边缘缓存系统中基于传输时延的缓存策略

为了满足5G系统低时延高可靠的需求,针对单缓存终端直传(D2D)协作边缘缓存系统,提出了一种基于传输时延的缓存策略.运用随机几何理论,将请求用户和空闲用户的动态分布建模为相互独立的齐次泊松点过程,综合考虑内容流行度、用户位置信息、设备传输功率以及干扰,推导出用户的平均传输时延与缓存概率分布的关系式.以平均传输时延为目标...     

多传感器图像的二次匹配算法

针对光学图像的多光谱、多传感器图像的自动配准,提出了一种基于边缘重心的多传感器图像二次匹配算法.首先,通过边缘检测和相应的后期链接处理,提取出较为完整的图像边缘;然后,根据图像边缘的链码相关以及区域不变矩策略,寻找匹配边缘,并对已匹配边缘的重心进行一致性检验获得控制点对;最后,采用最小二乘法估计图像粗匹配变换参数.在粗匹配的基础上,根据匹配后图像共有区域内边缘的主要方向和重心,再次对图像进行细匹配,修正匹配参数以提高匹配精度.多种遥感图像数据的配准实验和对比试验证实了该自动算法具有较高的可靠性和配准精度.     

基于无人机高光谱特征参数和株高估算马铃薯地上生物量

地上生物量(above-ground biomass,AGB)是评价作物长势及其产量估测的重要指标,对指导农业管理具有重要的作用.因此,快速准确地获取生物量信息,对于监测马铃薯生长状况,提高产量具有重要的意义.于马铃薯现蕾期、块茎形成期、块茎增长期、淀粉积累期、成熟期获取成像高光谱影像、实测株高(heigh,H)、地上...     

一种基于逐点阈值分割的图像边缘检测方法

提出一种对图像中每个点逐一取阈值进行分类的一种新的阈值分割算法.该算法利用图像中像素邻域的灰度值均值统计信息作为该点阈值设置的标准,并引入该点邻域内像素灰度值方差作为附加判断条件,使提取出来的日标点是图像的边缘点.事实上该阈值分割算法起到了边缘提取的效果.实验证明,本文算法起到了良好的边缘检测效果,并且验证了本算法对于以邻域统计信息作为阈值估计标准的合理性.     

区域指导的自适应图像插值算法

提出了一种以图像区域的一致性为指导的自适应选择插值公式(简称ADA)的图像插值算法.首先将图像分割成不同区域,然后结合近邻法和众数法确定待插值点所属区域,将待插值点分类处理:对于区域内的点,采用线性插值;对于区域间的过渡点,设计非线性插值公式,分配较大的权值给与待插值点属于同一区域的邻域像素,分配较小的权值给其它邻域像素.实验表明,ADA图像插值算法得到的插值图像有较好的主观图像质量,其峰值信噪比(PSNR)比传统方法平均提高了3.11～4.39 dB.     

基于视觉图像的石英摆片参数精密测量方法

为了解决检测石英摆片易划伤和提高检测的速度、精度,提出了利用视觉图像进行石英摆片平面几何参数测量的非接触测量方法.该方法通过视觉系统对石英摆片图像进行摄取, 由Sobel算子对图像进行单像素精度的边缘初始位置定位,进而利用改进的Zernike矩亚像素定位算法实现对目标边缘的精确定位,最后通过最小二乘法拟合边缘点得出石英摆片的平面几何参数.实验结果表明:该方法稳定性好,测量精度高,定位精度优于0.1 pixel,可实现石英摆片平面几何参数的精密测量.     

涡轮叶片前缘阵列冲击冷却流动及传热特性数值研究

本文采用SST湍流模型模拟了类前缘通道内蒸汽射流阵列冲击冷却的流动与传热特性,分析了雷诺数(Re=10000～50000)、孔径比(d/H=0.5～0.9)和孔间距比(S/H=2～6)对流动及传热性能的影响规律,得到了相应的传热和摩擦关联式。结果表明:在不同雷诺数下,d/H从0.5到0.9变化时,通道压力损失系数降低了76%～79%,靶面平均努塞尔数降低了45%～49%;S/H从2增至6时,通道压力损失系数增加了1.64～1.92倍,靶面平均努塞尔数增加了54%～64%;增大d/H、减小S/H可有效提高类前缘通道蒸汽冲击冷却的综合热力系数。本文研究结果可为未来先进燃气轮机高温涡轮叶片蒸汽冷却结构的设计提供参考和借鉴。     

守恒律方程组的大时间步长叠波格式

大时间步长叠波格式最初思想为LeVeque提出的大时间步长Godunov格式,通过叠加间断分解发出的强波来构造数值格式.原方法只给出了间断强波的穿越叠加方法,文章对其进行了完善,并推广到多维.针对膨胀波提出了一种网格单元分解法可以自动满足熵条件,避免出现非物理解.给出了格式的具体计算公式,并用单个守恒律方程、一维/多维Euler方程组进行了数值计算.计算结果表明,新格式除了可以采用大时间步长的优点外,在一定范围内随CFL数增加其耗散反而更低,因而对激波接触间断膨胀波的分辨率更高.     

Neighbor Sum Distinguishing Index of Sparse Graphs

A proper k-edge coloring of a graph G is an assignment of one of k colors to each edge of G such that there are no two edges with the same color incident to a common vertex. Let f(v) denote the sum of colors of the edges incident to v. A k-neighbor sum distinguishing edge coloring of G is a proper k-edge coloring of G such that for each edge uv∈E(G), f(u)≠f(v). By χ'_∑(G), we denote the smallest value k in such a coloring of G. Let mad(G) denote the maximum average degree of a graph G. In this paper, we prove that every normal graph with mad(G) ■ and Δ(G) ≥ 8 admits a(Δ(G) + 2)-neighbor sum distinguishing edge coloring. Our approach is based on the Combinatorial Nullstellensatz and discharging method.     

Integration of multi access edge computing with unmanned aerial vehicles: Current techniques,open issues and research directions

During the last decade, research and development in the field of multi access edge computing (MEC) has rapidly risen to prominence. One of the factors propelling MEC’s evolution is the ability to deploy edge servers capable of providing both communication and computational services in close proximity to the mobile user terminal. MEC has been regarded as a potentially transformative technique for fifth-generation (5G) and beyond 5G (B5G) wireless communication systems, as well as a possible complement to traditional cloud computing. Additionally, unmanned aerial vehicles (UAVs) integrated with MEC will play a critical role by introducing an additional mobility based computational layer to provide more secure, efficient and faster services. UAV enabled MEC offers seamless connectivity, fulfilling the promise of 5G’s ubiquitous connectivity. Due to the enormous interest in UAV enabled MEC, there has been a tremendous increase in the number of published research articles in this domain; however, the research area still lacks a systematic study and categorization. We present a systematic literature review (SLR) on UAV enabled MEC, examining and analyzing data on the current state of the art using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. To streamline our assessment, this study analyzes several research papers carefully selected through a multi-stage process satisfying the eligibility criteria defined in the paper. One of the SLR’s primary contributions is to broadly classify the research in the UAV enabled MEC domain into different categories including energy efficiency, resource allocation, security, architecture, and latency. We have identified key findings, technology, and pros and cons for the selected articles under each category. Additionally, we discuss the key open issues related to scalability and fairness, resource allocation and offloading optimization, service delivery with a focus on quality of experience (QoE) and quality of service (QoS), and standardization. Finally, we discuss several future research directions that would address the aforementioned issues and emerging use cases for UAV enabled MEC.