The short memory principle for solving Abel differential equation of fractional order

In this paper, the short memory principle (SMP) is applied for solving the Abel differential equation with fractional order. We evaluate the approximate solution at the end of required interval, and construct a suitable iteration scheme employing this end point as initial value. Numerical experiments show that our iteration method is simple and efficient, and that a proper length of memory could maintain the validity of the short memory principle.     

A novel approach for analog fault diagnosis based on neural networks and improved kernel PCA

We have developed a neural-network-based fault diagnosis approach of analog circuits using maximal class separability based kernel principal components analysis (MCSKPCA) as preprocessor. The proposed approach can detect and diagnose faulty components efficiently in the analog circuits by analyzing their time responses. First, using wavelet transform to preprocess the time responses obtains the essential and reduced candidate features of the corresponding response signals. Then, the second preprocessing by MCSKPCA further reduces the dimensionality of candidate features so as to obtain the optimal features with maximal class separability as inputs to the neural networks. This simplifies the architectures reasonably and reduces the computational burden of neural networks drastically. The simulation results show that our resulting diagnostic system can classify the faulty components of analog circuits under test effectively and achieves a competitive classification performance.     

SFFS-PC-NN optimized by genetic algorithm for dynamic prediction of financial distress with longitudinal data streams

Recently, research of financial distress prediction has become increasingly urgent. However, existing static models for financial distress prediction are not able to adapt to the situation that the sample data flows constantly with the lapse of time. Financial distress prediction with static models does not meet the demand of the dynamic nature of business operations. This article explores the theoretical and empirical research of dynamic modeling on financial distress prediction with longitudinal data streams from the view of individual enterprise. Based on enterprise’s longitudinal data streams, dynamic financial distress prediction model is constructed by integrating financial indicator selection by using sequential floating forward selection method, dynamic evaluation of enterprise’s financial situation by using principal component analysis at each longitudinal time point, and dynamic prediction of financial distress by using back-propagation neural network optimized by genetic algorithm. This model’s ex-ante prediction efficiently combines its ex-post evaluation. In empirical study, three listed companies’ half-year longitudinal data streams are used as the sample set. Results of dynamic financial distress prediction show that the longitudinal and dynamic model of enterprise’s financial distress prediction is more effective and feasible than static model.     

磁敏测速系统的数据采集平台实现

串口同步采集是工业控制应用的重要环节,为克服由于不准确的数据采集所带来的乘性误差,进而对多串口的同步采集进行了研究。利用VS2005编程环境,设计实现了多串口的上位机数据采集平台,该平台开辟线程对多个串口采取重叠读取方式,实现了对测速系统中大量的串口数据同步读取、保存并实现波形动态显示的功能,满足了智能测速系统的测速算法研究的需要。此平台可以广泛的应用在测速系统之中,也可辅助用于各种工业控制的高级要求。     

基于ZigBee的多机器人通信系统的设计

为解决多机器人协作的问题,设计了可以让机器人之间基于ZigBee网络进行通信的通信方案。机器人硬件系统中引入了ZigBee节点,多个机器人依赖ZigBee形成一个星型网络,每个机器人可以通过中心节点保持通信。实验结果表明,机器人之间可以可靠地进行通信,能够显著提高机器人的工作效率。     

两轴独立的高精度齿形加工数字控制系统

论述了梳理齿条冲齿机的工作原理,控制策略及系统实现,给出了软件编程方法与通信实现.系统采用人机界面和数字通信,实现了冲齿-牵引机构的两轴同步驱动和加工参数的柔性调整.     

Differentially expressed proteins of MCF-7 human breast cancer cells affected by Zilongjin, a complementary Chinese herbal medicine

Purpose : Zilongjin, a complementary Chinese herbal medicine, has been used to alleviate the adverse effects of chemotherapeutic drugs in cancer therapy. However, the mechanisms of anti‐cancer activity of Zilongjin are still largely unkonwn. Experimental design : First, the proteomic approach of combined 2‐DE and ESI‐MS/MS was used to investigate the effect of Zilongjin on the protein expression in MCF‐7 cells. Then, the differential expression of some proteins was confirmed by Western blot, cytoimmunofluoresecnce, and quantitative real‐time RT‐PCR analysis. Results : The identified proteins with differential expression, involved in such events as protein translation, cellular signal transduction, cytoskeleton formation and transportation, include seven downregulating proteins, such as Eukaryotic translation initiation factor 3 subunit I, Eukaryotic translation initiation factor 1A Y‐chromosomal, Ran‐specific GTPase‐activating protein, Ubiquitin‐conjugating enzyme E2 N, Tropomodulin‐3, Macrophage‐capping protein, and Tumor protein D52, as well as two upregulating proteins, HSP β‐1 and keratin18. Moreover, the differential expression of three proteins was confirmed. Conclusions and clinical relevance : (i) These results provide a new insight into the molecular mechanisms of Zilongjin on therapy for breast cancer. (ii) The application of the proteomic approaches will result in the more extended appreciation of Chinese medicine than those known at present.     

STRINGVACUA. A Mathematica package for studying vacuum configurations in string phenomenology

We give a simple tutorial introduction to the Mathematica package STRINGVACUA, which is designed to find vacua of string-derived or inspired four-dimensional N=1 supergravities. The package uses powerful algebro-geometric methods, as implemented in the free computer algebra system Singular, but requires no knowledge of the mathematics upon which it is based. A series of easy-to-use Mathematica modules are provided which can be used both in string theory and in more general applications requiring fast polynomial computations. The use of these modules is illustrated throughout with simple examples.

Program summary

Program title: STRINGVACUACatalogue identifier: AEBZ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBZ_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: GNU GPLNo. of lines in distributed program, including test data, etc.: 31 050No. of bytes in distributed program, including test data, etc.: 163 832Distribution format: tar.gzProgramming language: “Mathematica” syntaxComputer: Home and office spec desktop and laptop machines, networked or stand aloneOperating system: Windows XP (with Cygwin), Linux, Mac OS, running Mathematica V5 or aboveRAM: Varies greatly depending on calculation to be performedClassification: 11.1External routines: Linux: The program “Singular” is called from Mathematica. Windows: “Singular” is called within the Cygwin environment from Mathematica.Nature of problem: A central problem of string-phenomenology is to find stable vacua in the four-dimensional effective theories which result from compactification.Solution method: We present an algorithmic method, which uses techniques of algebraic geometry, to find all of the vacua of any given string-phenomenological system in a huge class.Running time: Varies greatly depending on calculation requested.     

A note on on-line broadcast scheduling with deadlines

In this paper, we study an on-line broadcast scheduling problem with deadlines, in which the requests asking for the same page can be satisfied simultaneously by broadcasting this page, and every request is associated with a release time, deadline and a required page with a unit size. The objective is to maximize the number of requests satisfied by the schedule. In this paper, we focus on an important special case where all the requests have their spans (the difference between release time and deadline) less than 2. We give an optimal online algorithm, i.e., its competitive ratio matches the lower bound of the problem.