Electrical properties of polypyrrole/p‐InP structure

The polypyrrole/p‐InP structure has been fabricated by the electrochemical polymerization of the organic polypyrrole onto the p‐InP substrate. The current–voltage (I–V), capacitance–voltage (C–V), and capacitance–frequency (C–f) characteristics of the PPy/p‐InP structure have been determined at room temperature. The structure showed nonideal I–V behavior with the ideality factor and the barrier height 1.48 and 0.69 eV respectively. C–f measurements of the structure have been carried out using the Schottky capacitance spectroscopy technique and it has been seen that there is a good agreement between the experimental and theoretical values. Also, it has been seen that capacitance almost show a plateau up to a certain value of frequency, after which, the capacitance decreases. The higher values of capacitance at low frequencies were attributed to the excess capacitance resulting from the interface states in equilibrium with the p‐InP that can follow the a.c. signal. The interface state density N_ss and relaxation time τ of the structure were determined from C–f characteristics. © 2006 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 44: 1572–1579, 2006     

水溶性聚合物和两亲聚合物:12.环氧乙烷-环氧丙烷无规共聚醚结构与性能的关系

来用连续加料法,以二元醇-KOH为引发剂合成一组不同组成的环氧乙烷-环氧丙烷无规共聚醚,并用核磁共振、红外光谱、示差扫描量热计和热失重等方法对其本体聚合物,用浊点和表面张力测定的方法对其水溶液,进行系统的表征。     

Optimum gas chromatographic conditions in wall-coated capillary columns. Extended and simplified forms of the Golay-equation

Band broadening in capillary columns is satisfactorily described by the Golay-equation extended to situations of appreciable pressure drop by Giddings. In practice, however, several simplifications are often made. The effect of these simplifications on the calculated values of the minimum plate height and optimum carrier gas velocity are treated systematically.     

Erosion of efficiency in non-uniform linear chromatography

In linear chromatography (i.e. chromatography performed in the absence of sample overloading), when the plate height of a column is roughly uniform along its length, variations in the velocities of solutes are the only possible causes of erosion of efficiency. The sources of these variations (variations in capacity ratio and in the density of the mobile phase, etc.) play no direct role in the erosion of efficiency except through their effect on solute velocities. In other words, what eventually causes the erosion of efficiency is merely variation in the time required for solutes to traverse equally small segments of a column. Significant erosion can only arise from abrupt and deep deceleration of solutes in one or several relatively small segments of a column. If erosion of efficiency caused by pressure gradients in linear SFC is to be large, the depth and the sharpness of the deceleration of a solute must go beyond that hitherto confirmed experimentally. Many relevant examples are analyzed graphically.     

基于引导调制的彩色点云无参考质量评价方法

彩色点云(color point cloud, CPC)作为三维场景和对象的有效描述形式,在虚拟现实、增强现实等许多领域得到重要应用。CPC在其采集、压缩、传输、重建等过程中会引入相应的失真,需要设计有效的评价方法对失真CPC质量进行评测。本文提出一种基于引导调制的CPC无参考质量评价方法。考虑到几何信息与彩色纹理信息的联合失真,利用引导调制的方法联立两者,以综合考虑几何失真、彩色纹理失真、联合失真。结合人眼的多通道性,利用剪切波变换提取特征。最后,将所有特征构成的特征向量输入到支持向量回归模型(support vector regression, SVR)学习预测点云质量。实验结果表明,所提出的方法与人类主观感知具有很好的一致性。     

Secure communication in CloudIoT through design of a lightweight authentication and session key agreement scheme

Internet of Things (IoT) is a newly emerged paradigm where multiple embedded devices, known as things, are connected via the Internet to collect, share, and analyze data from the environment. In order to overcome the limited storage and processing capacity constraint of IoT devices, it is now possible to integrate them with cloud servers as large resource pools. Such integration, though bringing applicability of IoT in many domains, raises concerns regarding the authentication of these devices while establishing secure communications to cloud servers. Recently, Kumari et al proposed an authentication scheme based on elliptic curve cryptography (ECC) for IoT and cloud servers and claimed that it satisfies all security requirements and is secure against various attacks. In this paper, we first prove that the scheme of Kumari et al is susceptible to various attacks, including the replay attack and stolen-verifier attack. We then propose a lightweight authentication protocol for secure communication of IoT embedded devices and cloud servers. The proposed scheme is proved to provide essential security requirements such as mutual authentication, device anonymity, and perfect forward secrecy and is robust against security attacks. We also formally verify the security of the proposed protocol using BAN logic and also the Scyther tool. We also evaluate the computation and communication costs of the proposed scheme and demonstrate that the proposed scheme incurs minimum computation and communication overhead, compared to related schemes, making it suitable for IoT environments with low processing and storage capacity.     

IPC-Net: Incomplete point cloud classification network based on data augmentation and similarity measurement

Existing point cloud classification researches are usually conducted on datasets with complete structure and clear semantics. However, in real point cloud scenes, the occlusion and truncation may destroy the completeness of objects affecting the classification performance. To solve this problem, we propose an incomplete point cloud classification network (IPC-Net) with data augmentation and similarity measurement. The proposed network learns the feature representation of incomplete point clouds and the semantic differences compared to the complete ones for classification. Specifically, IPC-Net adopts a random erasing-based data augmentation to deal with incomplete point clouds. IPC-Net also introduces an auxiliary loss function weighted by attention scores to measure the similarity between the incomplete and the complete point clouds. Extensive experiments verify that IPC-Net has the ability to classify incomplete point clouds and significantly improves the robustness of point cloud classification under different completeness.     

基于峰宽修正的玻璃药瓶内氧气残留浓度的检测研究

玻璃药瓶中的氧气残留对瓶中药品的无菌特性造成了严重的威胁。采用波长调制光谱（Wavelength Modulated Spectrum, WMS）技术解调得到的二次谐波信号峰高值作为氧浓度反演的基础。然而,在用二次谐波信号测量气体浓度时,由于调制深度的变化会导致二次谐波峰值的变化,这通常会给系统带来误差,进而降低浓度的反演精度。而调制深度受调制电流波动、温度和压强变化等因素的影响不能直接计算获得进而修正。针对这一问题,本文成功地将调制深度与二次谐波峰高的关系转换为二次谐波峰宽和峰高的关系。然后,利用峰宽校正后的谐波峰高对气体浓度进行反演。初步实验表明,利用峰宽校正后的谐波峰高对瓶内气体浓度进行预测的准确性提高了2.1%,且系统的整体鲁棒性也得以提升。本文提出的校正方法不需要系统参数信息与气体成分信息,可以直接从谐波信号本身出发对调制深度进行校正,十分适合于工业现场的在线氧气浓度预测。     

基于点云配准的多固态激光雷达标定算法

针对多个固态激光雷达协同工作时,需要准确地进行外参标定的实际需求,提出一种基于点云配准的多固态激光雷达自动标定算法。该标定算法由标定物分割、初始配准和精确配准三个阶段构成。在标定物分割阶段,首先通过叠加多帧非重复扫描数据制作标定点云,再使用半径滤波和体素下采样滤波分割出纹理特征明显的目标点云。在初始配准阶段,使用3D-HARRIS算法提取关键点,并使用方向直方图(SHOT)特征描述子进行特征描述,然后匹配对应点并使用采样一致算法完成初始配准;在精配准阶段使用迭代最近邻(ICP)算法进行精确配准,从而获得精确的外参标定效果。在Bunny兔数据集和现场获得的数据上进行实验,结果表明,当保证配准平均误差小于1 mm的前提下,所提出算法的性能优于多种现有算法。     

基于CSAR图像的目标高度提取方法

圆周合成孔径雷达（Circular Synthetic Aperture Radar,CSAR）可以对目标进行360°全方位观测,获得目标全方位散射信息。通过将CSAR成像数据划分成多个子孔径能够直接获取目标高度信息,本文在原有获取目标高度信息的方法基础上,进行了改进和创新,提出了一种新的提取目标高度信息的方法。本文通过对子孔径图像进行高度向投影,在一定程度上提高了计算精度,同时在子孔径选择时,也考虑了子孔径之间的相关性,有效地提高了算法的精确性。最后首次引入自主测量的L波段实测数据对本文所提算法进行验证,证实了该方法的有效性和准确性。