An Inter-domain Routing and Signaling Scheme for Optical Mesh Networks

An inter-domain routing and signaling scheme based on the OBGP protocol for WDM networks with a mesh topology is proposed in the paper. For mesh networks with wavelength conversion, inter-domain routing and signaling are realized by introducing a new message based on an optimal path identifier (OPI) and by establishing the corresponding message-exchange procedures. Considering the wavelength continuity constraint, a strategy called improved destination wavelength assignment (IDWA) combined with the OPI-based message is presented to establish a lightpath dynamically. The scheme is verified on the NSFNET and the CERNET by simulation. Results show that the blocking performance of a non-wavelength-conversion network is even a little lower than that of a wavelength-conversion network.     

ASYMPTOTIC BEHAVIOR OF SOLUTIONS OF NONLINEAR DELAY DIFFERENTIAL EQUATIONS

Sufficient conditions are established for the asymptotic behavior of solutionsof nonlinear delay differential equations x′(t)+sum from i=1 to m(pi(t)x(t-т_i))=F(t,x_t),t≥0where 0<т_1<т_2<…<т_m≤r,pi∈C([0,∞)),i=1,2,…,m,F∈C([0,∞)×C_0,R).C_0=C([-r,0],R)equipped with the sup norm ||·|| forsome r>0. A new result is established, some known results are improved.     

Sensitivity of MEMS microwave power sensor with the length of thermopile based on Fourier equivalent model

A Fourier equivalent model is introduced to research the thermal transfer behavior of a terminating-type MEMS microwave power sensor.The fabrication of this MEMS microwave power sensor is compatible with the GaAs MMIC process.Based on the Fourier equivalent model,the relationship between the sensitivity of a MEMS microwave power sensor and the length of thermopile is studied in particular.The power sensor is measured with an input power from 1 to 100 mW at 10 GHz,and the measurement results show that the power sensor has good input match characteristics and high linearity.The sensitivity calculated from a Fourier equivalent model is about 0.12,0.20 and 0.29 mV/mW with the length at 40,70 and 100μm,respectively,while the sensitivity of the measurement results is about 0.10,0.22 and 0.30 mV/mW,respectively,and the differences are below 0.02 mV/mW. The sensitivity expression based on the Fourier equivalent model is verified by the measurement results.     

Simultaneous CO2 and H2O Activation via Integrated Cu Single Atom and N Vacancy Dual-Site for Enhanced CO Photo-Production

Photocatalytic conversion of CO₂ into fuels using pure water as the proton source is of immense potential in simultaneously addressing the climate-change crisis and realizing a carbon-neutral economy. Single-atom photocatalysts with tunable local atomic configurations and unique electronic properties have exhibited outstanding catalytic performance in the past decade. However, given their single-site features they are usually only amenable to activations involving single molecules. For CO₂ photoreduction entailing complex activation and dissociation process, designing multiple active sites on a photocatalyst for both CO₂ reduction and H₂O dissociation simultaneously is still a daunting challenge. Herein, it is precisely construct Cu single-atom centers and two-coordinated N vacancies as dual active sites on CN (Cu₁/N_2CV-CN). Experimental and theoretical results show that Cu single-atom centers promote CO₂ chemisorption and activation via accumulating photogenerated electrons, and the N_2CV sites enhance the dissociation of H₂O, thereby facilitating the conversion from COO* to COOH*. Benefiting from the dual-functional sites, the Cu₁/N_2CV-CN exhibits a high selectivity (98.50%) and decent CO production rate of 11.12 µmol g⁻¹ h⁻¹. An ingenious atomic-level design provides a platform for precisely integrating the modified catalyst with the deterministic identification of the electronic property during CO₂ photoreduction process.     

基于USB2.0与CPLD的光刻机底面对准系统设计

介绍了光刻机底面对准系统的基本原理,并分析了传统底面对准系统存在的缺点,给出了基于USB2.0与CPLD的光刻机底面对准新系统的设计方案。论述了系统硬件和软件的实现,并对其中的关键模块进行了深入分析。与传统底面对准系统相比,该对准系统成本降低约70%,同时,系统的可靠性大幅提高。实验表明,该系统的底面对准精度达到0.25μm,满足系统设计要求。     

GaAs／AlGaAs发光二极管列阵场分布特性的电光测量

应用一种新颖的无损伤测量技术－连续波电光检测法（ＣＷＥＯＰ）对ＧａＡｓ／ＧａＡｌＡｓ单异质结发光管列阵电场分布进行了扫描测量。实验结果反映了器件内电流注入的方向和载流子扩展情况；通过比较各单元电场分布，反映器件发光均匀性。文中详细介绍了测量原理、实验装置和实验结果及讨论，最后用计算机对电场分布作了模拟计算并与实验结果进行了对照。     

输出千瓦级基模CO_2激光的七折光学谐振腔

报道了一种成功地在横向磁场约束的直流辉光放电激励横向流动ＣＯ２激光器上输出千瓦级基模光束的七折腔的结构、参数及实验结果，并对其进行了讨论。     

Power consumption modeling and optimization for NB-IoT eDRX

To extend the battery life of massive machine type devices (MTD),narrow-band Internet of things (NB-IoT) system extended discontinuous reception (eDRX) mechanism of LTE to the maximum as well as introduced a lower power state named as power saving mode (PSM).Three Markov models were established for three typical NB-IoT traffic scenarios,which called mobile autonomous reporting periodic report (MAR-P),mobile autonomous reporting exception report (MAR-E),software update/reconfiguration (SUR).The states of each Markov model were the working status of MTDs,including connected,idle and PSM state,in which the connected state was divided into random access state and data translating/receiving state to further evaluate the additional power consumption caused by collisions from massive MTDs concurrent access.Thereby,the power consumption and delay models with respect to each traffic scenarios were derived.Since the frequency of MAR-P traffic was far greater than the other two,the battery life of this traffic case with its optimal design choice was comprehensively analyzed.Numerical results show that,the battery life is mostly influenced by transmission period,maximum number of random access attempts,maximum number of data transmissions and traffic load,which can be maximized by appropriate parameters setting up.These works provide good references for NB-IoT device behavior modeling and optimization design.     

Metric and classification model for privacy data based on Shannon information entropy and BP neural network

Aiming at the requirements of privacy metric and classification for the difficulty of private data identification in current network environment, a privacy data metric and classification model based on Shannon information entropy and BP neural network was proposed. The model establishes two layers of privacy metrics from three dimensions. Based on the dataset itself, Shannon information entropy was used to weight the secondary privacy elements, and the privacy of each record in the dataset under the first-level privacy metrics was calculated. The trained BP neural network was used to output the classification result of privacy data without pre-determining the metric weight. Experiments show that the model can measure and classify private data with low false rate and small misjudged deviation.     

带有给定凸切线多边形的保形五次样条逼近

本讨论带有给定切线多边形的保形逼近问题．给出了一条与给定切线多边形相切的保形五次参数祥条曲线。