A review of: “RETHINKING SYSTEMS ANALYSIS AND DESIGN”, by Gerald M. Weinberg,Dorset House,New York, 1988 (Preface,appendix, annotated bibliography,index + 174 pp).

The aim of this study is to investigate the properties and method of fuzzy scenario analysis. In order to cope with the issues of data shortage and linguistic expression of an expert in a strategic planning, this study incorporates the concept of fuzzy set theory into scenario analysis, so that the uncertainties involved in a strategic planning can be considered.

Based on Brauers and Weber's method in scenario analysis, we propose a method of the fuzzy scenario analysis. It includes: (1) the analysis of factors, (2) the possible analysis of outcomes, (3) the compatible analysis of scenarios, (4) the possible analysis of scenarios, and (5) the determination of the main scenarios. Following this structure, we can describe main pictures of future developments (usually 2 to 4) with their degrees of possibilities. Then we shall compare the proposed method with Brauers &; Weber's method.     

近红外光谱数据分析方法研究

文中将主成分分析和BP神经网络方法相结合,用于对近红外光谱数据进行预处理和回归分析,较好地解决了近红外分析中的非线性关联问题。实验结果表明,该方法在近红外光谱数据的分析中与传统的化学计量学方法相比有较好的应用效果。     

基于KLLDA和ELM的新型模拟电路故障诊断方法

模拟电路是工业设备中最重要的元器件,其故障可能造成重大的人员伤亡,甚至造成巨大的经济损失。针对这一问题,提出一种基于核局部线性判别分析(Kernel Local Linear Discriminant Analysis,KLLDA)的故障诊断方案。利用小波分析和统计分析对原始信号进行预处理,得到原始特征集;利用KLLDA方法进行降维,并与核主成分分析(Kernel Principal Component Analysis,KPCA)和核线性判别分析(Kernel Linear Discriminant Analysis,KLDA)方法进行比较;采用极限学习机(Extreme Learning Machine,ELM)对测试电路的故障进行定位。对两个故障诊断案例的实验结果表明了该方法的有效性,并表明KLLDA在降维方面总体上优于KPCA和KLDA。     

Hierarchical multiple-SIMD architecture for image analysis

Real-time image analysis requires the use of massively parallel machines. Conventional parallel machines consist of an array of identical processors organized in either single instruction multiple data (SIMD) or multiple instruction multiple data (MIMD) configurations. Machines of this type generally only operate effectively on parts of the image analysis problem. SIMD on the low level processing and MIMD on the high level processing. In this paper we describe the Warwick Pyramid Machine, an architecture consisting of both SIMD and MIMD parts in a multiple-SIMD (MSIMD) organization which can operate effectively at all levels of the image analysis problem.     

Analysis of tutorial interactions

In this article the analysis of different interactions between learner and teaching programs is presented and discussed. The analysis is done in terms of a conceptual framework describing primitive learner and system actions at three different levels: (a) a didactic level, (b) a communication level, and (c) a media level. We conclude that this framework may not only be helpful in evaluating the functionality of teaching programs, but also in designing such programs.     

基于因子分析建模的电话语音说话人聚类

现有基于混合高斯模型的说话人聚类方法主要依据最大后验准则,从通用背景模型中自适应得到类别的混合高斯模型,然而自适应数据较少,模型的准确性不够。对此,文中尝试基于本征语音(EV)空间和全变化(TV)空间分析的两种因子分析建模方法,通过对差异空间的建模,减少估计类别混合高斯模型时需要估计的参数个数。结果表明,在美国国家标准技术研究所2008年说话人识别评测的电话语音数据集上,相对于基于最大后验概率准则的基线系统而言,文中所使用的基于EV和TV空间分析的建模方法都可使聚类错误率有较大幅度的下降,并且TV空间分析建模相对于EV空间分析建模能获得更低的聚类错误率。     

小波融合图像效果的因子分析评价方法

因子分析是一种有效的评价融合图像质量的方法。文中采用了小波sym5进行了多尺度图像融合的研究,并且通过主成分分析方法提取了细节信息因子和光谱信息流失因子等参数,作为图像的客观质量评价标准。实验证明,对于小波变换多尺度融合后的图像,该方法能够客观有效地评价其反映细节信息的参数（如信息熵和清晰度）以及反映光谱信息的参数（如扭曲程度和偏差指数）的变化趋势。理论分析结果,因子综合得分和观众评价得分结果具有良好的一致性。     

基于网络流量的赫斯特指数分析

该文通过对生成的布朗运动的Hurst指数分析,发现重置标度极差分析方法即R/S分析和基于小波的分析方法两者得出的H指数差异很大,通过对网络流量数据进行分析则进一步验证了上述结论,并简要分析引起此结果的原因,为今后进一步研究打下基础。     

Algorithms for nonnegative independent component analysis

We consider the task of solving the independent component analysis (ICA) problem x=As given observations x, with a constraint of nonnegativity of the source random vector s. We refer to this as nonnegative independent component analysis and we consider methods for solving this task. For independent sources with nonzero probability density function (pdf) p(s) down to s=0 it is sufficient to find the orthonormal rotation y=Wz of prewhitened sources z=Vx, which minimizes the mean squared error of the reconstruction of z from the rectified version y/sup +/ of y. We suggest some algorithms which perform this, both based on a nonlinear principal component analysis (PCA) approach and on a geodesic search method driven by differential geometry considerations. We demonstrate the operation of these algorithms on an image separation problem, which shows in particular the fast convergence of the rotation and geodesic methods and apply the approach to a musical audio analysis task.     

基于核独立成分分析的盲源信号分离

独立成分分析(ICA)已经广泛用于盲源信号的分离(BSS)。论文介绍了基于核空间的ICA的原理和基本算法,然后介绍了该算法与典型ICA和主成分分析(PCA)在盲源信号分离中的比较。实验表明在盲源信号分离中,基于核空间的ICA与其他典型ICA和PCA算法相比更具有准确性和鲁棒性。     

Cognitive work analysis and the design of user interfaces

When a user interface needs to be designed for a task that depends on information integration, such as navigation, very few theoretical tools are available. Cognitive task analysis (CTA) and hierarchical task analysis (HTA) are the basic analysis techniques. A choice between them depends on the type of task or objective at hand. In this article, it is argued that for interface design a combination of CTA and HTA forms the basis of the interface definition. When this expanded to a full cognitive work analysis (CWA), it will form the human-factors analysis required for the user-interface design.     

Foresight for a responsible future with ICT

The ACM Code of Ethics asserts that computing professionals have an ethical responsibility to minimize the negative consequences of information and communication technologies (ICT). Negative consequences are rarely intended, but they can often be foreseen with careful sociotechnical analysis in advance of system building. Motivated by an interest in extremely complex sociotechnical contexts (e.g., mortgage lending and automated trading) where ICT appears to be having negative consequences in addition to many benefits, this paper identifies and evaluates future-oriented problem analysis and solution design tools in three potentially relevant literatures: 1) ICT ethics, 2) environmental sustainability, and 3) technology hazards. Several promising future-oriented technology analysis techniques (e.g., anticipatory technology ethics, technology roadmapping, morphological analysis, and control structure analysis) were found and are discussed in this paper, but much work remains to be done to customize them, integrate them, and codify them for use in education and high-quality IS research on very complex sociotechnical contexts like the global financial network.     

多变量控制系统频域分析和设计的综述

本文介绍了多变量系统频域分析和设计方法的一些最新发展。在系统分析方面,主要介绍特征轨迹(CL)方法和主增益、主相位的方法。在系统综合方面,主要介绍方向排列(alignment)技术,鲁棒性准则和逆结构正则化(RFN)补偿器,最后作者们对多变量系统分析和设计中的频域法的研究前景进行了展望。     

Criticality analysis of Internet infrastructure

The Internet has evolved into an indispensable component of our daily lives and protecting its critical infrastructure has thus become a crucial task. In this work, we present and compare different methods to assess the criticality of individual facilities of the Internet infrastructure at a national-level: graph-theoretical analysis, route-based analysis, traffic-based analysis, and consequence-based analysis. Our key observations are: (1) The geographical topology, which is derived from a national-level IP backbone network, has a power-law degree distribution and is a small-world network; (2) A few locations appear much more frequently among all paths in the IP backbone topology than others, and they also witness a high percentage of US Internet traffic. (3) Relative ranking of Internet facility locations from traffic-based analysis differs significantly from those derived from graph-theoretical analysis and route-based analysis, suggesting that a comprehensive, high-fidelity Internet model is necessary to assess critical Internet infrastructure facilities. (4) Consequence-based analysis, although computationally intense, cannot be replaced by other rankings, including traffic-based analysis. Conclusions drawn from this work extend our knowledge regarding the Internet and also shed lights on which critical Internet infrastructure facilities should be protected with limited resources.     

Using variance analysis of multitemporal MODIS images for rice field mapping in Bali Province,Indonesia

Existing methods for rice field classification have some limitations due to the large variety of land covers attributed to rice fields. This study used temporal variance analysis of daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images to discriminate rice fields from other land uses. The classification result was then compared with the reference data. Regression analysis showed that regency and district comparisons produced coefficients of determination (R ²) of 0.97490 and 0.92298, whereas the root mean square errors (RMSEs) were 1570.70 and 551.36 ha, respectively. The overall accuracy of the method in this study was 87.91%, with commission and omission errors of 35.45% and 17.68%, respectively. Kappa analysis showed strong agreement between the results of the analysis of the MODIS data using the method developed in this study and the reference data, with a kappa coefficient value of 0.8371. The results of this study indicated that the algorithm for variance analysis of multitemporal MODIS images could potentially be applied for rice field mapping.     

Robust genetic programming‐based detection of atrial fibrillation using RR intervals

In this study, two variants of genetic programming, namely linear genetic programming (LGP) and multi‐expression programming (MEP) are utilized to detect atrial fibrillation (AF) episodes. LGP‐ and MEP‐based models are derived to classify samples of AF and Normal episodes based on the analysis of RR interval signals. A weighted least‐squares (WLS) regression analysis is performed using the same features and data sets to benchmark the models. Another important contribution of this paper is identification of the effective time domain features of heart rate variability (HRV) signals upon an improved forward floating selection (IFFS) analysis. The models are developed using MIT‐BIH arrhythmia database. The diagnostic performances of the LGP and MEP classifiers are evaluated through receiver operating characteristics (ROC) analysis. The results indicate that the LGP and MEP models are able to diagnose the AF arrhythmia with an acceptable high accuracy. The proposed models have significantly better diagnosis performances than the regression and several models found in the literature.     

A modified Sobol′ sensitivity analysis method for decision-making in environmental problems

Sensitivity analysis is an important component of environmental modelling and in recent years, variance-based, global sensitivity analysis techniques, such as Sobol′, have been a preferred approach for achieving this. However, these techniques are generally only applicable to simulation models and not to models used to rank alternative options, such as multi-criteria decision analysis (MCDA) methods. In order to overcome this limitation, a modified Sobol′ method for MCDA (Sobol′-MCDA) is introduced in this paper. The method has the following features: (i) it enables the stability or robustness of the relative ranking of two alternatives to be assessed in the light of changes in assessment criteria and stakeholder preferences; and (ii) it enables the sensitivity of the ranking of two alternatives to changes in assessment criteria and stakeholder preferences to be assessed. The approach is demonstrated for a water resources case study from the literature consisting of seven alternatives and ten assessment criteria.     

Evidential Reasoning Approach for Multiattribute Decision Analysis Under Both Fuzzy and Interval Uncertainty

Many multiple attribute decision analysis (MADA) problems are characterized by both quantitative and qualitative attributes with various types of uncertainties. Incompleteness (or ignorance) and vagueness (or fuzziness) are among the most common uncertainties in decision analysis. The evidential reasoning (ER) and the interval grade ER (IER) approaches have been developed in recent years to support the solution of MADA problems with interval uncertainties and local ignorance in decision analysis. In this paper, the ER approach is enhanced to deal with both interval uncertainty and fuzzy beliefs in assessing alternatives on an attribute. In this newly developed fuzzy IER (FIER) approach, local ignorance and grade fuzziness are modeled under the integrated framework of a distributed fuzzy belief structure, leading to a fuzzy belief decision matrix. A numerical example is provided to illustrate the detailed implementation process of the FIER approach and its validity and applicability.      

基于程序分析的自动化漏洞挖掘工具的研究

研究和设计了一个基于程序分析的源代码漏洞分析与检测工具框架,框架中的各个模块如控制流分析(控制流图的构建、函数调用图的实现及过程内分析与过程间分析等)、数据流分析(求定义引用链、污染数据传播的设计、指针别名分析)、结构分析器、安全调度器、规则构建器,本文主要对代码分析的两个阶段进行了较为详细的介绍,同时对主要采取的过程内和过程间分析算法做了说明。