A decision tree using ID3 algorithm for English semantic analysis

Natural language processing has been studied for many years, and it has been applied to many researches and commercial applications. A new model is proposed in this paper, and is used in the English document-level emotional classification. In this survey, we proposed a new model by using an ID3 algorithm of a decision tree to classify semantics (positive, negative, and neutral) for the English documents. The semantic classification of our model is based on many rules which are generated by applying the ID3 algorithm to 115,000 English sentences of our English training data set. We test our new model on the English testing data set including 25,000 English documents, and achieve 63.6% accuracy of sentiment classification results.     

BSPNN: boosted subspace probabilistic neural network for email security

In the modern age of Internet connectivity, advanced information systems have accumulated huge volumes of data. Such fast growing, tremendous amount of data, collected and stored in large databases has far exceeded our human ability to comprehend without proper tools. There has been a great deal of research conducted to explore the potential applications of Machine Learning technologies in Security Informatics. This article studies the Network Security Detection problems in which predictive models are constructed to detect network security breaches such as spamming. Due to overwhelming volume of data, complexity and dynamics of computer networks and evolving cyber threats, current security systems suffer limited performance with low detection accuracy and high number of false alarms. To address such performance issues, a novel Machine Learning algorithm, namely Boosted Subspace Probabilistic Neural Network (BSPNN), has been proposed which combines a Radial Basis Function Neural Network with an innovative diversity-based ensemble learning framework. Extensive empirical analyses suggested that BSPNN achieved high detection accuracy with relatively small computational complexity compared with other conventional detection methods.     

Robust control via concave minimization local and global algorithms

This paper is concerned with the robust control problem of linear fractional representation (LFT) uncertain systems depending on a time-varying parameter uncertainty. Our main result exploits a linear matrix inequality (LMI) characterization involving scalings and Lyapunov variables subject to an additional essentially nonconvex algebraic constraint. The nonconvexity enters the problem in the form of a rank deficiency condition or matrix inverse relation on the scalings only. It is shown that such problems, but also more generally rank inequalities and bilinear constraints, can be formulated as the minimization of a concave functional subject to LMI constraints. First of all, a local Frank and Wolfe (1956) feasible direction algorithm is introduced in this context to tackle this hard optimization problem. Exploiting the attractive concavity structure of the problem, several efficient global concave programming methods are then introduced and combined with the local feasible direction method to secure and certify global optimality of the solutions. Computational experiments indicate the viability of our algorithms, and in the worst case, they require the solution of a few LMI programs     

空间曲线的几何Hermite插值问题

在给定的 GC2 插值条件下 ,构造了一条空间四次 Bèzier曲线 (空间曲线的几何 Hermite插值问题 ) ,结果表明了四次 GC2 - Herm ite插值问题的解是局部存在的 ,并且有一个自由度 ;文章还讨论了逼近阶 ,并证明了局部解具有六阶逼近精度 .     

基于Tin改进的LiDAR滤波算法

现有典型的基于Tin的滤波算法只对本格网内的数据进行处理,没有考虑邻近地形的影响,使得滤波处理不能取得很好的效果。本文以待处理格网为中心,将待处理格网最低点与领域格网最低点构成三角网,再对格网内的数据与所在三角形的三个顶点进行比较,判断是否符合阈值来确定是否为地面点。实验的结果表明对改进后的三角网迭代的算法大大改善了滤波效果,提高了滤波处理结果的准确性。     

MCTF与改进SPIHT相结合实现的可分级视频编码方案

编码器首先将视频序列分组进行运动补偿时域提升滤波，然后将滤波形成的高低通帧分别做二维离散小波变换，再对小波系数进行改进的SPIHT编码，最后采用一种巧妙而高效的基于位平面的码流分配策略将SPIHT编码和运动矢量编码一起打包输出完全嵌入式的码流，实现时间和质量的可分级。     

Low temperature synthesis and characterisation of lecontite, (NH4)Na(SO4)·2H20

Lecontite, (NH₄)Na(SO₄).2H₂O, was synthesised at room temperature in high purity compared to earlier work with a minor impurity of mascagnite, (NH₄)₂SO₄. Rietveld refinement of the XRD results confirmed the crystal structure and unit cell dimensions as published earlier. Raman and Infrared spectroscopy, in conjunction with factor group analysis, resulted in a complex pattern of overlapping sulphate, NH and OH modes. The NH modes υ₁ was observed around 2880 cm⁻¹, υ₂ around 1700 cm⁻¹ overlapping with water OH-bending modes, υ₃ around 3300 cm⁻¹ overlapping with water OH-stretching modes around 3023, 3185 and 3422 cm⁻¹, and υ₄ around 1432, 1447 and 1462 cm⁻¹. The sulphate group in the crystal structure displays a decrease in symmetry from T_d as evidenced by the activation of the ν₁ mode at 982 cm⁻¹ and the ν₂ mode around 452 cm⁻¹ in the Infrared spectrum. The υ₃ mode shows clear splitting in the infrared spectra with a strong band at 1064 cm⁻¹ accompanied by two shoulders at 1107 and 1139 cm⁻¹. The Raman spectra show three weak bands at 1068, 1109 and 1135 cm⁻¹ with a shoulder at 1155 cm⁻¹. Similar splitting was observed for the υ₄ mode around 611 and 632 cm⁻¹ in the Infrared and Raman spectra, respectively.     

数字图像中边缘算法的实验研究

边缘检测是图像处理、计算机视觉中的基础内容．也是至今仍未得到圆满解决的一类。目前图像处理大多数都是针对数字图像，本文对数字图像中几种具有代表性的边缘检测算法进行了理论分析，并通过编程实验，对各种算法进行实现，通过比较得出了各自的优缺点和适用范围。     

移动目标的快速识别算法

本文针对现有技术中存在的问题提出一种对复杂背景下的多个移动物体进行目标快速识别与跟踪的复合算法。该算法中采用对连续图像进行差影计算来确定移动目标区域，从而能去除复杂背景干扰，可以明显提高目标识别的速度和准确率。该系统已被实验证明其有效性和实用性．可广泛应用于监测与识别系统，也可应用于无人监控．无人自主操作等各种领域。本文中所提到的算法现为国家某重点项目中的关键技术。     

铁镍稀土自熔性合金粉末研究与应用

研究应用成本较低的铁镍稀土自熔性合金粉末材料代替镍基自熔性合金粉末材料。通过对铁镍稀土自熔性合金粉末材料显微组织分析、摩擦性能和结合强度试验以及实际应用等工作，表明铁镍稀土自熔性合金粉末材料具有熔焊性能好、结合强度高、综合性能优良、成本低等特点。