真空热试验通用软件平台工作模式与关键技术

为了改善试验测控软件在通用化、模块化设计、控制算法、试验过程信息化管理等方面的诸多不足,研制航天器热试验通用软件平台。该平台融合了计算机技术、虚拟仪器技术和网络技术,不仅实现从试验准备、试验工况运行、试验数据显示到实验结果分析等工作的自动化,而且应用多项关键技术使该平台成为一个有机整体并具备广泛的通用性、灵活的配置能力、便捷的人机接口。文中重点介绍了该平台的4中工作模式,分别为单机模式、分布式模式、云计算模式、集中控制模式。通过工作模式的介绍说明该平台如何在各种规模真空热试验设备上应用。热试验通用软件平台能够提高热试验的自动化程度、提高热试验的可靠性、有利于热试验技术经验的积累。     

面向分析化学教学的数理统计软件的开发和应用

A statistical software package is developed for the course of chemical analysis. The software calculates cumulative distribution functions and inverse cumulative distribution functions of normal, t, χ², and F distributions; it also provides critical values for tests of statistical significance. The software is designed to substitute for traditional data tables that are insufficient and obscure. Statistical problems can be solved more efficiently with the software than with traditional data tables, which enables students to focus on understanding statistical principles and interpreting results. The software provides information through an intuitive interface, a graph, and natural interactions. Both Matlab and Android versions are presented, and free of charge.     

Modeling and simulation of pollutants transport in rivers

This paper is devoted to mathematical modeling and computer simulation of diffusion and transport of chemicals in rivers. We present one-, two-, and three-dimensional models in terms of time-dependent convection–diffusion–reaction differential equations, further we give the finite difference approximation and appropriate numerical algorithms for these models, and finally we discuss briefly the computer implementation of this methodology in a user friendly software package. To verify the model and the computer code we have used it to study the diffusion and transport of chemicals, in this case NO₃ and PO₄, in two rivers in Western Georgia flowing into the Black Sea. Namely, we considered the river Khobistskali subject to pollution sources Ochkhomuri and Chanistskali river Choga polluted with NO₃.     

红外光谱曲线分峰拟合程序的编写

我们用Ｃ语言开发出了用于解决谱带重叠问题的光谱分峰曲线拟合的Ｃｕｒｖｅｆｉｔ软件，并为程序配合了多种功能和一个友好的人机交互界面以方便使用，经试用表明。该软件无论在运算速度上还是在运算结果的可靠性方面上都是比较令人满意的。     

X射线荧光分析数据处理软件的研究和应用

最小二乘法回归线性方程Ｙ＝ＡＸ＋Ｂ，结合Ｘ射线荧光分析数据的特点，用ＢＡＳＩＣ语言编写应用软件。     

A computer program for ranking analytical methods according to their fitness for purpose

A program for conducting automatic searches for analytical methods, selecting the most suitable ones according to quality requirements, and ranking them based on quality indices calculated from various pre-selected quality parameters is proposed. The program uses an externally updated database (Analytical Abstracts CD-ROMs or other) and customised quality schemes based on accuracy, precision, sensitivity, applicability to real samples, determination range (ratio), throughput and impact factor (from the Citation Index). It can, therefore, be used for a variety of purposes in analytical chemistry.     

Enhancing software reliability modeling and prediction through the introduction of time-variable fault reduction factor

Over the past three decades, many software reliability models with different parameters, reflecting various testing characteristics, have been proposed for estimating the reliability growth of software products. We have noticed that one of the most important parameters controlling software reliability growth is the fault reduction factor (FRF) proposed by Musa. FRF is generally defined as the ratio of net fault reduction to failures experienced. During the software testing process, FRF could be influenced by many environmental factors, such as imperfect debugging, debugging time lag, etc. Thus, in this paper, we first analyze some real data to observe the trends of FRF, and consider FRF to be a time-variable function. We further study how to integrate time-variable FRF into software reliability growth modeling. Some experimental results show that the proposed models can improve the accuracy of software reliability estimation. Finally, sensitivity analyses of various optimal release times based on cost and reliability requirements are discussed. The analytic results indicate that adjusting the value of FRF may affect the release time as well as the development cost.     

Real-time fractal signal processing in the time domain

Fractal analysis has proven useful for the quantitative characterization of complex time series by scale-free statistical measures in various applications. The analysis has commonly been done offline with the signal being resident in memory in full length, and the processing carried out in several distinct passes. However, in many relevant applications, such as monitoring or forecasting, algorithms are needed to capture changes in the fractal measure real-time. Here we introduce real-time variants of the Detrended Fluctuation Analysis (DFA) and the closely related Signal Summation Conversion (SSC) methods, which are suitable to estimate the fractal exponent in one pass. Compared to offline algorithms, the precision is the same, the memory requirement is significantly lower, and the execution time depends on the same factors but with different rates. Our tests show that dynamic changes in the fractal parameter can be efficiently detected. We demonstrate the applicability of our real-time methods on signals of cerebral hemodynamics acquired during open-heart surgery.     

Markovian Imperfect Software Debugging Model and Its Performance Measures

Abstract

This paper considers a Markovian imperfect software debugging model incorporating two types of faults and derives several measures including the first passage time distribution. When a debugging process upon each failure is completed, the fault which causes the failure is either removed from the fault contents with probability p or is remained in the system with probability 1 ? p. By defining the transition probabilities for the debugging process, we derive the distribution of first passage time to a prespecified number of fault removals and evaluate the expected numbers of perfect debuggings and debugging completions up to a specified time. The availability function of a software system, which is the probability that the software is in working state at a given time, is also derived and thus, the availability and working probability of the software system are obtained. Throughout the paper, the length of debugging time is treated to be random and thus its distribution is assumed. Numerical examples are provided for illustrative purposes.     

A Markov modulated Poisson model for software reliability

In this paper, we consider a latent Markov process governing the intensity rate of a Poisson process model for software failures. The latent process enables us to infer performance of the debugging operations over time and allows us to deal with the imperfect debugging scenario. We develop the Bayesian inference for the model and also introduce a method to infer the unknown dimension of the Markov process. We illustrate the implementation of our model and the Bayesian approach by using actual software failure data.