声光效应拉曼-内斯方程矩阵级数解法及声光调制器优化设计

提出一种求解正常声光相互作用拉曼 内斯 (Raman Nath)方程的矩阵级数解法 ,该解法直观方便且具有普遍性。计算结果表明 ,对Q =4 1π ,Bragg衍射的效率只有 97 5 % ;对非对称入射 ,以往的Raman Nath近似解误差较大 ;指出提高Bragg衍射效率的有效途径在于提高声光频率比并给出计算声光器件最优长度的计算公式。     

Evaluation of Monkman-Grant parameters for type 316LN and modified 9Cr-Mo stainless steels

The Monkman-Grant (M-G) and its modified parameters were evaluated for type 316LN and modified 9Cr-Mo stainless steels prepared with minor element variations. Several sets of creep data for the two alloy systems were obtained by constant-load creep tests in 550-650°C temperature range. The M-G parameters,m, m’,C, andC’ were proposed and discussed for the two alloy systems. Them value of the M-G relation was 0.90 in type 316LN steel and 0.84 in modified 9Cr-Mo steel. Them’, value of the modified relation was 0.94 in type 316LN steel and 0.89 in 9Cr-Mo steel. Although creep fracture modes and creep properties between type 316LN and modified 9Cr-Mo steels showed a basic difference, the M-G and its modified relations demonstrated linearity quite well. Them’ of modified relation almost overlapped regardless of the creep testing conditions and chemical variations in the two alloy systems, and the parameterm’ was closer to unity than that of the M-G relation.     

VG7S变频器及其在电梯拖动系统中的应用

指出了由VG7S变频器拖动的电梯系统运转停止时序分析中的几个主要问题,探讨了使用中的抗干扰技术,并对常用控制端子的设定方法和部分调试要点作了较为详尽的说明。     

双时基频率校准电路

提供精确的时间基准是精密仪器和高精度设备计时和工作的关键技术之一。文中采用两套晶振电路，通过分频产生高频和低频两个频率信号，采用编码的方法对两个频率信号在每一个时钟周期内进行动态校核，只有两个晶振的频率在允许的精度范围内，或同时增大（缩小）相同的倍数，校核后频率信号才是正确的，且能给系统提供精确的时间基准。该方法能有效防止系统的时钟周期因意外的原因伸长或缩短。整个电路可以作为精密仪器或高精度设备的一个模块电路。     

用于机器人轨迹定位纠正系统的回声状态神经网络研究

循环神经网络(RecurrentNeuralNetworks)是人工神经网络(ArtificialNeuralNetworks)中重要的分支,与前馈神经网络(ForwardNeuralNetworks)相比具有更好的时间序列学习能力。但长期以来其学习法一直不能脱离前馈神经网络而自成一体,回声状态神经网络(EchoStateNetworks(ESN))是打破这一局面的全新学习方法。其独特的结构,良好的短期记忆能力,方便的学习方法,不俗的非线性特性是以前循环神经网络所不可比的。本文在介绍了回声状态神经网络之后将其用于四轮机器人的位置测量系统中,有良好的表现。     

TSM系统中高层软件测试的方法

任何一个软件，在开发过程中都不可避免地存在错误。软件测试的目的就是跟踪出软件的错误，不同种类的软件开发和测试工具是不相同的。介绍软件测试的基本概念、原理以及方法。主要介绍Telelogical Tau AB公司的TTCN的测试机理，并利用TTCN进行TSM(TD-SCDMA移动通信系统)高层信令测试的方法。     

A versatile data acquisition system for time resolved X-ray scattering using gas proportional detectors with delay line readout

A data acquisition system for time resolved X-ray scattering experiments using linear, quadrant or area gas proportional detectors with delay line readout based on commercially available hardware (National Instruments) is described. The system can easily be configured for recording data from point detectors (e.g. photomultipliers and photodiodes) and/or ancillary data only. Applications involving measurements with two different types of time to digital converters illustrate the features and performances of the system.     

A time series bootstrap procedure for interpolation intervals

A sieve bootstrap procedure for constructing interpolation intervals for a general class of linear processes is proposed. This sieve bootstrap provides consistent estimators of the conditional distribution of the missing values, given the observed data. A Monte Carlo experiment is used to show the finite sample properties of the sieve bootstrap and finally, the performance of the proposed method is illustrated with a real data example.     

Cycle detection using a stack

We present an algorithm for detecting periodicity in sequences produced by repeated application of a given function. Our algorithm uses logarithmic memory with high probability, runs in linear time, and is guaranteed to stop within the second loop through the cycle. We also present a partitioning technique that offers a time/memory tradeoff. Our algorithm is especially well suited for sequences where the cycle length is typically small compared to the length of the acyclic prefix.     

Developing Cost Response Models for Company-Level Cost Flow Forecasting of Project-Based Corporations

The difficulty in applying the standard curve (S-curve) and cost-schedule integration (CSI) techniques for company-level cost flow forecasting in a project-based industry is the prerequisite of forecasting future unknown individual projects and contract classifications. By analyzing cost flows at the company level through a pool of macroeconomic and internal financial data, this paper proposes an innovative approach to firm-specific model estimation. First, a series of data transformations introduce linear relationships between cost, macroeconomic, and internal financial variables. Second, multivariate regression analysis is employed for initial model building. Third, for the purposes of model restructuring, a subsequent application of Yule–Walker estimates and incomplete principal component analysis is used. This paper uses a sample of four project-based construction firms to demonstrate model performance. Using this methodology, mean absolute percentage error (MAPE) values of the forecasting models range from 0.27 to 0.60%. As such, the transformed cost, macroeconomic, internal financial data could strongly predict company-level cost flow forecasting. While converting the predicted cumulative cost data to periodic cost flows, the MAPE values were augmented, ranging from 7.04 to 17.55%, thus, requiring future research.