一种基于安全状态转移的简并测试集生成方法

在总结前人工作的基础上,结合安全操作系统对测试的特殊需求,提出了简并测试集(degenerate test set,简称DTS)的概念,设计了一种使用模型检测的基于安全状态转移的高效测试集生成方法.该方法以状态转移为化简对象,在利用模型检测技术生成测试用例的同时,归并相同的状态转移并化简需求集中的冗余属性,从而最终达到化简测试集的目的.在此基础上,探讨了单个用例失败时用例集的有效性问题,并对DTS生成算法进行了改进.实验结果表明,该方法可以有效地对测试集中的冗余进行化简.

a backtracking search tool for constructing combinatorial test suites

Combinatorial testing is an important testing method. It requires the test cases to cover various combinations of parameters of the system under test. The test generation problem for combinatorial testing can be modeled as constructing a matrix which has certain properties. This paper first discusses two combinatorial testing criteria: covering array and orthogonal array, and then proposes a backtracking search algorithm to construct matrices satisfying them. Several search heuristics and symmetry breaking techniques are used to reduce the search time. This paper also introduces some techniques to generate large covering array instances from smaller ones. All the techniques have been implemented in a tool called EXACT (EXhaustive seArch of Combinatorial Test suites). A new optimal covering array is found by this tool.

Shallow Water Model On Cubed-Sphere By Multi-Moment Finite Volume Method

A global numerical model for shallow water flows on the cubed-sphere grid is proposed in this paper. The model is constructed by using the constrained interpolation profile/multi-moment finite volume method (CIP/MM FVM). Two kinds of moments, i.e. the point value (PV) and the volume-integrated average (VIA) are defined and independently updated in the present model by different numerical formulations. The Lax-Friedrichs upwind splitting is used to update the PV moment in terms of a derivative Riemann problem, and a finite volume formulation derived by integrating the governing equations over each mesh element is used to predict the VIA moment. The cubed-sphere grid is applied to get around the polar singularity and to obtain uniform grid spacing for a spherical geometry. Highly localized reconstruction in CIP/MM FVM is well suited for the cubed-sphere grid, especially in dealing with the discontinuity in the coordinates between different patches. The mass conservation is completely achieved over the whole globe. The numerical model has been verified by Williamson's standard test set for shallow water equation model on sphere. The results reveal that the present model is competitive to most existing ones. (C) 2008 Elsevier Inc. All rights reserved.

Sensitivity map of laser tweezers Raman spectroscopy for single-cell analysis of colorectal cancer

Raman spectroscopy on single, living epithelial cells captured in a laser trap is shown to have diagnostic power over colorectal cancer. This new single-cell technology comprises three major components: primary culture processing of human tissue samples to produce single-cell suspensions, Raman detection on singly trapped cells, and diagnoses of the cells by artificial neural network classifications. it is compared with DNA flow cytometry for similarities and differences. Its advantages over tissue Raman spectroscopy are also discussed. In the actual construction of a diagnostic model for colorectal cancer, real patient data were taken to generate a training set of 320 Raman spectra and, a test set of 80. By incorporating outlier corrections to a conventional binary neural classifier, our network accomplished significantly better predictions than logistic regressions, with sensitivity improved from 77.5% to 86.3% and specificity improved from 81.3% to 86.3% for the training set and moderate improvements for the test set. Most important, the network approach enables a sensitivity map analysis to quantitate the relevance of each Raman band to the normal-to-cancer transform at the cell level. Our technique has direct clinic applications for diagnosing cancers and basic science potential in the study of cell dynamics of carcinogenesis. (C) 2007 Society of Photo-Optical Instrumentation Engineers.

Sensitivity map of laser tweezers Raman spectroscopy for single-cell analysis of colorectal cancer

Raman spectroscopy on single, living epithelial cells captured in a laser trap is shown to have diagnostic power over colorectal cancer. This new single-cell technology comprises three major components: primary culture processing of human tissue samples to produce single-cell suspensions, Raman detection on singly trapped cells, and diagnoses of the cells by artificial neural network classifications. it is compared with DNA flow cytometry for similarities and differences. Its advantages over tissue Raman spectroscopy are also discussed. In the actual construction of a diagnostic model for colorectal cancer, real patient data were taken to generate a training set of 320 Raman spectra and, a test set of 80. By incorporating outlier corrections to a conventional binary neural classifier, our network accomplished significantly better predictions than logistic regressions, with sensitivity improved from 77.5% to 86.3% and specificity improved from 81.3% to 86.3% for the training set and moderate improvements for the test set. Most important, the network approach enables a sensitivity map analysis to quantitate the relevance of each Raman band to the normal-to-cancer transform at the cell level. Our technique has direct clinic applications for diagnosing cancers and basic science potential in the study of cell dynamics of carcinogenesis. (C) 2007 Society of Photo-Optical Instrumentation Engineers.

Cancer subtypes recognition and its gene expression profiles analysis based on geometrical learning

The accurate recognition of cancer subtypes is very significant in clinic. Especially, the DNA microarray gene expression technology is applied to diagnosing and recognizing cancer types. This paper proposed a method of that recognized cancer subtypes based on geometrical learning. Firstly, the cancer genes expression profiles data was pretreated and selected feature genes by conventional method; then the expression data of feature genes in the training samples was construed each convex hull in the high-dimensional space using training algorithm of geometrical learning, while the independent test set was tested by the recognition algorithm of geometrical learning. The method was applied to the human acute leukemia gene expression data. The accuracy rate reached to 100%. The experiments have proved its efficiency and feasibility.

semantic oriented ontology cohesion metrics for ontology-based systems

Ontologies play a core role to provide shared knowledge models to semantic-driven applications targeted by Semantic Web. Ontology metrics become an important area because they can help ontology engineers to assess ontology and better control project management and development of ontology based systems, and therefore reduce the risk of project failures. In this paper, we propose a set of ontology cohesion metrics which focuses on measuring (possibly inconsistent) ontologies in the context of dynamic and changing Web. They are: Number of Ontology Partitions (NOP), Number of Minimally Inconsistent Subsets (NMIS) and Average Value of Axiom Inconsistencies (AVAI). These ontology metrics are used to measure ontological semantics rather than ontological structure. They are theoretically validated for ensuring their theoretical soundness, and further empirically validated by a standard test set of debugging ontologies. The related algorithms to compute these ontology metrics also are discussed. These metrics proposed in this paper can be used as a very useful complementarity of existing ontology cohesion metrics.

十八胺及其相关物质Langmuir-Blodgett膜的制备和性质研究

Langmuir-Blodgett（LB）膜技术由于在电子学、非线性光学以及化学传感器等领域具有潜在的应用前景而引起了人们的研究兴趣，其中它的热稳定性对LB膜的应用领域和范围具有一定的影响。本论文在此领域的主要研究内容如下： 利用LB膜技术分别制备了十八胺及硬脂酸、氘代硬脂酸的多层LB膜，采用变温傅立叶变换红外光谱研究了三种LB膜的相变行为。实验发现：十八胺LB膜在55-75 oC温度区间内发生相变，其CH2对称和反对称伸缩振动频率向高能量区发生明显移动；硬脂酸LB膜在70-80 oC的温度区间内发生了明显的相转变，CH2对称和反对称伸缩振动的强度比在升温过程中也有显著改变；氘代硬脂酸LB膜的相行为发生在65-70 oC的温度区间内。 利用LB膜技术制备了十八铵硬脂酸盐(C18H37NH3+C17H35COO-, ODASA)与十八铵氘代硬脂酸盐(C18H37NH3+C17D35COO-, ODASA-d35) Langmuir-Blodgett (LB)膜，使用变温傅立叶变换红外透射光谱研究了它们的热行为。发现LB膜中十八铵硬脂酸盐分子的两个碳氢链高度有序，然而在十八铵氘代硬脂酸盐LB分子中的来自于十八胺的碳氢链部分无序，即在常温下有一些扭曲构象存在于碳氢链中。而十八铵硬脂酸盐的热稳定性也与十八铵氘代硬脂酸盐的热稳定性有些不同。在十八铵硬脂酸盐LB膜中，碳氢链在85 oC到90 oC的温度区间内发生非常明显的有序-无序变化。而在十八铵氘代硬脂酸盐LB膜中，碳氢链和来自于硬脂酸的氘代的烃链各自呈现出不同的热行为，即：碳氢链在80-90 oC的温度区间发生有序-无序变化，尤其是在80-85 oC的温度范围内这个变化非常显著；而氘代的烃链则在70 oC到85 oC这个较长的温度区间发生缓慢的相变。 分别制备了十八铵十二酸盐 （C18H37NH3+C11H23COO-，ODALA）和十八铵二十四酸盐（C18H37NH3+C23H45COO-,ODATA）LB膜，并用变温傅立叶变换红外透射光谱法研究了十八铵十二酸盐和十八铵二十四酸盐LB膜的热行为，比较了十八铵十二酸盐、十八铵硬脂酸盐和十八铵二十四酸盐这三种双链化合物LB膜的热行为。温度相关的红外光谱显示，这三种物质LB膜的热稳定性取决于碳链的长度。其中，十八铵十二酸盐LB膜在50-65 oC的温度区间内发生相变。对应的，十八铵二十四酸盐LB膜在80-90 oC的温度范围内发生有序-无序变化。令人感兴趣的是，十八铵二十四酸盐LB膜的相变温度与十八铵硬脂酸盐LB膜的相变温度基本一样，都是80-90 oC，也即在十八铵二十四酸盐和十八铵硬脂酸盐两种LB膜中，即使二十四酸取代了硬脂酸对前者的热稳定性的影响非常小。以上结果说明，在双长链化合物中，有效链长度取决于双链中的较短的那个烃链，从而来决定膜的热稳定性。在十八铵二十四酸盐LB膜中，十八胺的全部碳链对膜的热稳定性有贡献，而二十四酸的碳链则只有部分（有效部分）烃链有贡献。 制备了十八胺单层和多层LB膜和粒径为几个纳米的金纳米粒子。由于十八胺在pH值小于10.3的溶液中氨基带正电荷，使其置于金纳米溶胶中，利用带正电荷的十八胺和附着负电荷的金纳米粒子之间的静电作用，使得金纳米颗粒成功地吸附组装到十八胺的有序分子膜中，形成有规律的纳米颗粒层。通过紫外-可见光谱、红外光谱以及扫描电镜观察到，金纳米颗粒通过这种方法能够很好的组装在有机分子膜上，而且由于十八胺LB膜的高度有序性使得金纳米颗粒的组装层有序。而且，不同层数的十八胺LB膜对金纳米粒子呈现出不同的吸附行为。 测量了含微量甲醇（体积分数为0.04%~0.24%）的系列乙醇水溶液的近红外光谱，利用近红外光谱分析建立了预测甲醇含量的定量分析模型。比较了用外部检验法（Test Set-Validation）和交叉检验法(Cross-Validaton)建立的数学模型以及研究了使用外部检验法时校正集和检验集样品数的改变对模型预测结果的影响。结果发现，当校正集样品数为15检验集样品数为6（总样品数为21）时，使用外部检验法建立的数学模型预测结果较好，外部检验与交叉检验的预测均方根误差（分别为RMSEE和RMSEP）都较小（分别为0.0105和0.0115）而且很接近。结果表明，近红外光谱方法简单，准确而且实用。

Separation of drug enantiomers by capillary electrophoresis in the presence of neutral cyclodextrins

This is a selected review, highlighting our results obtained in an extended screening program ("The German-Chinese Drug Screening Program"), with a focus on a set of original data obtained with heptakis(2,3,6-tri-O-methyl)-beta-cyclodextrin(TM-beta-CD) as the chiral solvating agent (CSA). The enantioseparation of 86 drugs by capillary zone electrophoresis in the presence of this CSA was successful for 47 drugs. The migration separation factors (alpha(m)) and the migration retardation factors (R-m) were compared with those found for native beta-cyclodextrin (beta-CD). The patterns thus obtained were also compared with those observed for hexakis(2,3,6-tri-O-methyl)-alpha-CD (TM-alpha-CD) and octakis(2,3,6-tri-O-methyl)-gamma-CD (TM-gamma-CD), respectively. From the statistical data, it can be concluded that there is a remarkable influence of the analyte structure on the electrophoretic data. A substructure 4H was found in the analyte structure that has a significant influence on the analytes' behaviour. Thus, analytes bearing the substructure 4H do not only have a strong affinity to the CDs but also a high rate of success of chiral separation in all systems reviewed. In light of this, the different ring sizes of native cyclodextrins (alpha-, beta- and gamma-CD) readily explain their behaviour towards a limited test set of chiral drugs. Sterical considerations point to the significance of side-on-binding versus inclusion in the cavity of the host. In addition to the findings from the screening program, numerous references to the Literature are given. (C) 2000 Elsevier Science B.V. All rights reserved.

近红外光谱测定溶液中甲醇的含量

测量了含微量甲醇(体积分数为0.04%～0.24%)的系列乙醇水溶液的近红外光谱,利用近红外光谱分析建立了预测甲醇含量的定量分析模型。比较了用外部检验法(Test Set-Validation)和交叉检验法(Cross-Validaton)建立的数学模型,研究了使用外部检验法时,校正集和检验集样品数的改变对模型预测结果的影响。结果发现,当校正集样品数为15检验集样品数为6(总样品数为21)时,使用外部检验法建立的数学模型预测结果较好,其校正集的均方根误差和检验集的预测均方根误差(分别为RMSEE和RMSEP)均较小(分别为0.0115和0.0105),而且很接近。结果表明,近红外光谱方法简单,准确而且实用。

Classification of valence changes of trivalent rare earth ions in alkaline earth borates using artificial neural networks

The investigations of classification on the valence changes from RE3+ to RE2+ (RE = Eu, Sm, Yb, Tm) in host compounds of alkaline earth berate were performed using artificial neural networks (ANNs). For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods. (C) 1999 Elsevier Science B.V. All rights reserved.

SEARCH FOR THE BASIC REGULARITIES OF THE TRANSITION EMISSION OF EUROPIUM(II) ION IN COMPLEX FLUORIDES USING PATTERN-RECOGNITION

The relationship between structures of complex fluorides and spectral structure of Eu(II) ion in complex fluorides (AB(m)F(n)) is investigated by means of pattern recognition methods, such as KNN, ALKNN, BAYES, LLM, SIMCA and PCA. A learning set consisting of 32 f-f transition emission host compounds and 31 d-f transition emission host compounds and a test set consisting of 27 host compounds were characterized by 12 crystal structural parameters. These parameters, i.e. features, were reduced from 12 to 6 by multiple criteria for the classification of these host compounds as f-f transition emission or d-f transition emission. A recognition rate from 79.4 to 96.8% and prediction capabilities from 85.2 to 92.6% were obtained. According to the above results, the spectral structures of Eu(II) ion in seven unknown host lattices were predicted.

An in silico approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure-activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding to the C-terminal nucleotide-binding domain of mouse P-gp was compiled. The predictive ability of the model was assessed using a test set that was independent of the training set, which showed a standard error of prediction of 0.146 +/- 0.006 (data scaled from 0 to 1). Meanwhile, two other mathematical tools, back-propagation neural network (BPNN) and partial least squares (PLS) were also attempted to build QSAR models. The BRNN provided slightly better results for the test set compared to BPNN, but the difference was not significant according to F-statistic at p = 0.05. The PLS failed to build a reliable model in the present study. Our study indicates that the BRNN-based in silico model has good potential in facilitating the prediction of P-gp flavonoid inhibitors and might be applied in further drug design.

Theory and Application of the Transient Injection Well Test

Based on the theory of the pumping well test, the transient injection well test was suggested in this paper. The design method and the scope of application are discussed in detail. The mathematical models are developed for the short-time and long-time transient injection test respectively. A double logarithm type curve matching method was introduced for analyzing the field transient injection test data. A set of methods for the transient injection test design, experiment performance and data analysis were established. Some field tests were analyzed, and the results show that the test model and method are suitable for the transient injection test and can be used to deal with the real engineering problems.

Influence of mode symmetry on quality factors of degenerate states in microlasers with an equilateral triangle resonator

Modes in equilateral triangle resonator (ETR) are analyzed and classified according to the irreducible representations of the point group C-3v., Both the analytical method based on the far field emission and the numerical method by FDTD technique are used to calculate the quality factors (Q-factors) of the doubly degenerate states in ETR. Results obtained from the two methods are in reasonable agreement. Considering the different symmetry properties of the doubly degenerate eigenstates, we also discuss the ETR joined with an output waveguide at one of the vertices by FDTD technique and the Pade approximation. The variation of Q-factors versus width of output waveguide is analyzed. The numerical results show that doubly degenerate eigenstates of TM0.36 and TM0.38 whose wavelengths are around 1.5 mu m in the resonator with side-length of 5 mu m have the Q-factors larger than 1000 when the width of the output waveguide is smaller than 0.4 mu m. When the width of the output waveguide is set to 0.3 mu m, the symmetrical states that are more efficiently coupled to output waveguide have Q-factors about 8000, which are over 3 times larger than those of asymmetric state.