最小二乘法联合光学与雷达遥感数据估算玉米叶面积指数

针对单源数据经验模型估算精度较低等问题,提出采用最小二乘法联合光学和雷达遥感数据构建联合估算模型,以中国科学院河北怀来遥感综合实验站为研究区,以夏季玉米为研究对象,利用Landsat8和Radarsat2影像实现研究区叶面积指数估算:首先分别建立了多光谱数据和雷达数据与实测叶面积指数之间的回归模型,然后利用最小二乘算法联合不同数据间的回归模型构建估算模型,最后利用迭代法估算叶面积指数并通过验证数据对估算结果进行评价分析,同时与单源数据经验模型、多源数据加权平均模型和基于物理模型查找表估算结果进行对比。通过对研究区59个样本点数据分析表明:基于最小二乘算法联合光学与雷达遥感数据能够提高叶面积指数的估算精度(R2=0.5442,RMSE=0.81),优于单源遥感数据拟合经验模型(DVI经验模型:(R2=0.485,RMSE=1.27))、基于权重的光学微波联合模型(R2=0.447,RMSE=1.36)和物理模型查找表法(R2=0.333,RMSE=1.36),并当叶面积指数大于3时,对其由于信息饱和或误差引起的低估或高估现象具有一定的抑制作用。     

基于遗传算法的小波神经网络在多组分气体检测中的应用

由于利用不分光红外吸收法（NDIR）的多组分气体传感器对汽车尾气（主要成分为CO2、CO、HC化合物）进行同时测量时,所测气体浓度是交叉吸收干扰后的结果,造成测量误差大,分析精度低。针对此问题,将遗传算法优化的小波神经网络用于建立基于红外光谱的三组分气体定量分析模型中。采集CO2、CO、HC的浓度信号,作为模型输入,通过模型回归分析,得到对应的混合气体组分浓度,解决气体之间相互干扰的问题。最后通过实验数据对模型性能进行仿真分析,结果表明,该模型的平均误差相比于传统模型明显减低,取得较好的精度。     

基于自适应变异粒子群算法的混合核ε-SVM在混合气体定量分析中的应用

针对利用不分光红外吸收法（NDIR）的多组分气体传感器对汽车尾气进行同时测量时,红外光谱特征吸收谱线重叠较为严重,所测气体浓度是交叉吸收干扰后的结果,造成测量误差大,分析精度低的问题,提出了一种自适应变异粒子群算法的混合核ε-SVM方法,建立三组分混合气体定量分析模型,已消除混合气体之间相互干扰产生的误差问题。实验中,采集CO2、CO、C3H8的浓度信号,作为模型输入,通过模型回归分析,得到对应的混合气体组分浓度,通过实验数据对模型性能进行分析,结果表明,该模型的平均误差相比于传统模型明显减低,取得较好的精度。     

Opaque virtual network mapping algorithms based on available spectrum adjacency for elastic optical networks

Optical network virtualization enables multiple virtual optical networks constructed for different infrastructure users(renters) or applications to coexist over a physical infrastructure. Virtual optical network(VON) mapping algorithm is used to allocate necessary resources in the physical infrastructure to the VON requests(VRs). In this paper, we investigate the opaque VON mapping problems in elastic optical networks(EONs). Based on the concept of available spectrum adjacency(AvS A) on links or paths, we consider both node resource and AvS A on links for node mapping, and present a link mapping method which chooses the routing and spectrum plan whose AvS A on paths is the largest among all the candidates. Finally, the overall VON mapping algorithm(i.e., AvS A-opaque VON mapping, AvS A-OVONM) coordinated node and link mapping is proposed. Extensive simulations are conducted and the results show that AvS A-OVONM has better performance of blocking probability and revenue-to-cost ratio than current algorithms.     

Prospects and research issues in multi-dimensional all optical networks多维全光网技术研究与展望

Research into all optical network (AON) technology has been ongoing over the past decade, and new features are constantly being developed. The advantages of AON include large-bandwidth provisioning, lowlatency transmission and low energy consumption. The basic concept underlying AON is transmission of data signals entirely through the optical domain from source to destination nodes, with no optical-electrical-optical (O-E-O) conversion at intermediate nodes. The technologies used to implement AON have undergone a series of evolutions, which encompass time division multiplexing (TDM), frequency division multiplexing (FDM), and space division multiplexing (SDM). Multi-dimensional AON (MD-AON), which leads the trend of AON’s future architecture, provides a vibrant state for emerging applications such as cloud computing and Internet of Things (IoT). In this article, we review the evolution of AON architectures based on the different all optical switching and multiplexing technologies (i.e., TDM, FDM, and SDM), which is one of the main areas of focus in this article. The other main area is detailed discussion of implementations such as data plane and control plane technologies as well as resource optimization technologies for realizing AON. We also introduce several AON testbeds with their compositions and functions, and some potential application scenarios that can be implemented based on these testbeds     

Modulation format independent blind polarization demultiplexing algorithms for elastic optical networks

We demonstrate a novel modulation format independent algorithm for adaptive blind polarization demultiplexing for elastic optical networks (EONs). We compare the proposed algorithm with traditional constant modulus algorithm (CMA) and radius-directed algorithm (RDA), in terms of performance in PM-QPSK, PM-16QAM and PM-64QAM coherent system, by simulating in back-to-back (BTB) and transmission sceneries. The simulation result shows that the modulation format independent algorithm can achieve universal adaptive blind polarization demultiplexing for PM-mQAM signals and gain slightly better performance in condition of lower optical signal noise ratio (OSNR). Furthermore, we also carry out experiments to investigate the performance of the proposed algorithm in BTB and 800 km transmission scenarios for 16 GBaud PM-QPSK and PM-16QAM. The experimental results demonstrate the conclusion of the numerical simulations.     

钯炭催化剂载体对莫西沙星侧链中间体合成的影响

改进了用于莫西沙星侧链中间体合成的钯炭催化剂制备工艺,主要讨论载体材质、粒度及处理方式对催化剂性能的影响。结果表明,选择椰壳炭为载体,粒度(300~400)目,用氢氧化钠处理的载体制备的催化剂与现售催化剂相比,选择性提高2个百分点,重复使用性能提高33%。     

邻硝基苯胺合成邻苯二胺用Pd/C催化剂研究

采用沉淀法,在不同分散剂作用下制备了Pd/C催化剂,并对制备的催化剂进行表征分析。以邻硝基苯胺为原料,研究了Pd/C催化剂在硝基还原催化加氢反应中的性能。结果表明,在分散剂B的作用下所制得的5%Pd/C-B催化剂分散度较高,且在邻硝基苯胺加氢还原反应中表现出优越的催化性能。     

V形尾翼无人机喷流对气动力特性干扰的数值模拟

全球鹰外形的无人机,其V形尾翼位于发动机喷管两侧,发动机的高温、高速喷流对尾翼和飞机的气动干扰影响很大。文章通过数值模拟分析了V形尾翼与发动机喷流的相互干扰作用,给出了全球鹰外形无人机在不同高度、马赫数以及相应的发动机工作状态下的气动力特性,定量对比不带发动机喷流和带有喷流的计算结果,得出了发动机喷流对尾翼及全机的气动影响,可作为无人机V型尾翼和发动机气动布局设计的参考。     

On minimizing coding operations in network coding based multicast: an evolutionary algorithm

In telecommunications networks, to enable a valid data transmission based on network coding, any intermediate node within a given network is allowed, if necessary, to perform coding operations. The more coding operations needed, the more coding resources consumed and thus the more computational overhead and transmission delay incurred. This paper investigates an efficient evolutionary algorithm to minimize the amount of coding operations required in network coding based multicast. Based on genetic algorithms, we adapt two extensions in the proposed evolutionary algorithm, namely a new crossover operator and a neighbourhood search operator, to effectively solve the highly complex problem being concerned. The new crossover is based on logic OR operations to each pair of selected parent individuals, and the resulting offspring are more likely to become feasible. The aim of this operator is to intensify the search in regions with plenty of feasible individuals. The neighbourhood search consists of two moves which are based on greedy link removal and path reconstruction, respectively. Due to the specific problem feature, it is possible that each feasible individual corresponds to a number of, rather than a single, valid network coding based routing subgraphs. The neighbourhood search is applied to each feasible individual to find a better routing subgraph that consumes less coding resource. This operator not only improves solution quality but also accelerates the convergence. Experiments have been carried out on a number of fixed and randomly generated benchmark networks. The results demonstrate that with the two extensions, our evolutionary algorithm is effective and outperforms a number of state-of-the-art algorithms in terms of the ability of finding optimal solutions.