一个不连续不可逆映象中的新型激发

报道了既不连续又不可逆一维映象中出现的一种具有新特征的激发(crisis)模式。这一新型激发产生于不连续性与不可逆性相互作用所导致的“映孔”与混沌吸引子的碰撞。映孔的出现可使迭代过程逃逸原来吸引子所占据的相空间区域,从而发生吸引子的突然扩张。数值计算结果表明,激发的特征时间<τ>与外控参量距其临界值距离的依赖关系为<τ>∝exp(U_0—U_(0c))~(-1/2),τ的不变分布P(τ)随τ增长呈现指数衰减关系。这种产生机制及主要特征与三种常见的激发相比均有新的特点。 关键词：     

200KV重离子加速器及其应用

本文介绍一台采用双潘宁型多电荷重离子源的200kV重离子加速器,简述它在GaP光探测器的研制、聚合物材料和金属材料的离子注入改性等方面的研究与应用。     

一种金属腔体中微波断层成像的最优分层非均一背景

针对基于金属腔体的微波断层成像系统,提出了一种最优分层非均一背景的设计方法.该方法使用一种新的微波断层成像积分算子评价方法和模拟退火法等最优化方法.首先,介绍了一种基于有限元法的微波断层成像积分算子计算方法.然后,提出一种新的微波断层成像积分算子度量,该度量可以综合评价整个积分算子奇异值谱,并通过一组仿真研究证明该度量与反演结果的误差具有相关性;该度量用一个数值综合评价一个积分算子,可以方便地应用于最优化算法中;利用模拟退火法选择圆形金属腔体中分层非均一背景的每一层介质的相对介电常数,从而获得一个最优分层非均一背景.最后,对尺寸小于半波长的圆柱目标和"凹"字形复杂目标进行仿真研究,仿真结果证明该最优分层非均一背景可以提高微波断层成像算法的收敛速度,提高反演结果的准确性.     

沸腾分析

本文对不溶有空气的化学纯液和溶有空气的化学纯液的沸腾问题进行分析,讨论这两种液体沸腾时温度变化的情况,指出它们在液沸腾时都要经过一段过热过程。     

多层纳米Au/DPO薄膜的荧光特性

在低压直流溅射沉积的纳米Au薄膜表面喷涂有机固体晶体2,5-二苯基恶唑（DPO）,制成具有（Au+DPO）单元结构的多层纳米薄膜。利用XRD表征多层纳米薄膜的晶体结构,通过SEM表征各层薄膜的表面形貌,并测试了多层纳米薄膜的紫外荧光特性。与纯DPO薄膜相比,多层纳米薄膜的紫外荧光峰出现了5 nm的蓝移,而且DPO荧光峰形貌发生改变。在多层膜中,DPO薄膜的荧光强度与薄膜层数成反比关系,而纳米Au膜的荧光强度与薄膜层数成正比关系。SEM与XRD测试结果表明,多层薄膜中的DPO薄膜随着薄膜层数的增加逐渐成为无定型结构。DPO薄膜与纳米Au膜相互作用,导致其晶体结构异于单层薄膜,进而改变了其荧光特性。     

Bending dual-core photonic crystal fiber coupler

In this paper, we systematically study a designed structure of a bending dual-core photonic crystal fiber (PCF). We propose the controllable wavelength-selective coupling PCF. This coupler allows highly accurate control of the filtering wavelength. The different wavelengths can be selected by controlling the bending radius of the fiber. Coupling characteristics of novel bending wavelength-selective coupling PCF are evaluated by using a vector finite element method and their application to a multiplexer demultiplexer (MUX–DEMUX) based on the novel coupler is investigated. When the fiber length is 4168 μm, the bending radius of PCF couplers for 1.48/1.55 μm, 1.3/1.55 μm, 0.98/1.55 μm, and 0.85/1.55 μm is calculated, respectively, and the beam propagation analysis is performed. Different from the traditional wavelength-selective coupling PCF, the dual-core PCF is bent and it can realize the separation of multiple wavelengths.     

Relative density-based classification noise detection

Classification noise is a common byproduct of traditional data mining approaches, and no specialized approach for detecting classification noise is currently available. Methods for outlier detection are well-developed, but outliers and classification noise have characteristics different enough to make outlier detection algorithms unsuitable for classification noise detection. In this paper, a new, specialized approach to detect classification noise is proposed, named relative density based classification noise detection (RDBCND). Computational experiments in artificial data sets described herein show that RDBCND has time complexity of O(n log n), indicating greater efficiency than traditional approaches, which exhibit time complexity of at least O(n²). The use of classification noise detection to improve the generalization ability of common classifier algorithms is also described. In particular, a new unified approach based on RDBCND is compared to a cross validation approach applied to a BP neural network. Trials in both artificial and real-life datasets show that the RDBCND-based approach can greatly accelerate the process of identifying the best decision function. The novel method can also eliminate underfitting, as the algorithm simply searches for the highest training accuracy. The experiments also show that the RDBCND-based method has greater accuracy and lower cpu time in reaching global solutions than the cross-validation method. Since the relative density is a local concept, our new approach can be directly used in nonlinear datasets without data transformation. It is a great advantage compared to some linear classifier algorithms. As in current linear classifiers, the kernel functions or other transformations need to be used to make them suitable for non-linear datasets, and that will increase their complexity.     

基于超图结构的科研合作网络演化模型

基于科研论文作者的合作方式, 用超图理论构建了一个科研合作超网络演化模型. 利用平均场理论分析了作者发表论文的演化规律, 发现作者的超度 (即发表论文数) 分布符合幂律分布. 进一步理论分析得到分布的幂指数γ与合作领域作者增长速度相关. γ越大, 新作者增长速度越快, 且存在关系: γ=1+L/M (L/M为作者增长率). 并通过对《物理学报》与《中国科学》2003–2012年期间作者发表论文进行了数据分析, 实证结果与理论分析及模拟结果能很好地符合. 本文对科研合作网络的理论和实证研究有一定的借鉴意义. 关键词： 复杂网络 超图 科研合作网络 演化模型     

玉米叶片的光谱响应及其氮素含量预测研究

以不同施肥水平下两年玉米田间试验为基础,利用高光谱技术探讨大喇叭口期不同层次玉米叶片光谱响应的敏感区域,并依据叶片氮素含量与原始光谱反射率及其一阶导数的相关性,最终构建了叶片氮素含量的预测模型。结果表明：不同施肥水平下叶片光谱反射率差别明显区域集中在550 nm附近波段、761～1 300 nm波段,不同层次间叶片光谱反射率差别明显区域集中在550 nm附近波段,叶片氮素含量与470～760 nm波段光谱反射率及其一阶导数呈极显著相关。经过对比筛选,以光谱指数DSI(564,681)和DSI(681,707)构建的指数预测模型效果最好,预测精度达93.43%和93.39%,能有效估测叶片氮素含量。