A simplified multi-class support vector machine with reduced dual optimization

Support vector machine (SVM) was initially designed for binary classification. To extend SVM to the multi-class scenario, a number of classification models were proposed such as the one by Crammer and Singer (2001). However, the number of variables in Crammer and Singer’s dual problem is the product of the number of samples (l) by the number of classes (k), which produces a large computational complexity. This paper presents a simplified multi-class SVM (SimMSVM) that reduces the size of the resulting dual problem from l × k to l by introducing a relaxed classification error bound. The experimental results demonstrate that the proposed SimMSVM approach can greatly speed-up the training process, while maintaining a competitive classification accuracy.     

Strategy of fast and light-load cloud-based proactive benign worm countermeasure technology to contain worm propagation

Benign worms have been attracting wide attention in the field of worm research due to the proactive defense against the worm propagation and patch for the susceptible hosts. In this paper, two revised Worm?CAnti-Worm (WAW) models are proposed for cloud-based benign worm countermeasure. These Re-WAW models are based on the law of worm propagation and the two-factor model. One is the cloud-based benign Re-WAW model to achieve effective worm containment. Another is the two-stage Re-WAW propagation model, which uses proactive and passive switching defending strategy based on the ratio of benign worms to malicious worms. This model intends to avoid the network congestion and other potential risks caused by the proactive scan of benign worms. Simulation results show that the cloud-based Re-WAW model significantly improves the worm propagation containment effect. The cloud computing technology enables rapid delivery of massive initial benign worms, and the two stage Re-WAW model gradually clears off the benign worms with the containment of the malicious worms.     

Modeling NOx emissions from coal-fired utility boilers using support vector regression with ant colony optimization

Modeling NO_x emissions from coal fired utility boiler is critical to develop a predictive emissions monitoring system (PEMS) and to implement combustion optimization software package for low NO_x combustion. This paper presents an efficient NO_x emissions model based on support vector regression (SVR), and compares its performance with traditional modeling techniques, i.e., back propagation (BPNN) and generalized regression (GRNN) neural networks. A large number of NO_x emissions data from an actual power plant, was employed to train and validate the SVR model as well as two neural networks models. Moreover, an ant colony optimization (ACO) based technique was proposed to select the generalization parameter C and Gaussian kernel parameter γ. The focus is on the predictive accuracy and time response characteristics of the SVR model. Results show that ACO optimization algorithm can automatically obtain the optimal parameters, C and γ, of the SVR model with very high predictive accuracy. The predicted NO_x emissions from the SVR model, by comparing with the BPNN model, were in good agreement with those measured, and were comparable to those estimated from the GRNN model. Time response of establishing the optimum SVR model was in scale of minutes, which is suitable for on-line and real-time modeling NO_x emissions from coal-fired utility boilers.     

Numerical simulation of thermal flying height control sliders in heat-assisted magnetic recording

Heat assisted magnetic recording (HAMR) is one of the most promising techniques to extend the recording density in hard disk drives beyond 1?Tb/in². Although the diameter of the spot on the disk that is heated by the laser beam is very small, on the order of nanometers, high local temperatures on the disk and the heat dissipated in the slider during the light delivery process can cause thermal deformations of both the disk and the slider, thereby affecting the flying characteristics at the head-disk interface. In this paper, a finite element model is developed which incorporates a HAMR optical system into a thermal flying height control (TFC) slider with dual heater/insulator elements to study the effect of heat dissipation in the wave guide on the thermal deformation and flying characteristics of a HAMR-TFC slider. In addition, the power input of the laser and design parameters of the heaters are investigated.     

基于有限元法的斜齿轮齿条啮合接触分析

通过Solidworks软件建立了斜齿轮齿条模型.采用有限元法和Solidworks Simu-lation有限元软件计算最恶啮合接触区域以及齿轮齿条啮合时齿根上最大的弯曲应力和接触区域上的接触应力.通过理论经验计算应力公式与有限元法计算的应力值相比较,以验证通过最恶啮合接触区域计算接触应力的可行性.     

MSMSE-based optimal beamforming design and simplification on AF MIMO two-way relay channels

An optimal cooperative beamforming for the amplify-and-forward (AF) MIMO two-way relay channels was designed. Supposing the channel state information (CSI) was perfectly known by the receiver and transmitter as well as the relay, optimal beamforming vectors (matrices) of all nodes were jointly designed based on the criterion of minimizing the sum mean square errors (MSMSE). The analysis result shows that the performance effect of transmitting and receiving beamforming pairs is to maximize the receive signal-to-noise ratio (SNR) at two communication nodes, and the rank of the optimal relay beamforming matrix is no larger than two when there is only one data stream at each source node. A simplified algorithm was put forward to accomplish the design based on the analysis conclusions. Simulation results provide that the system performance, which is characterized in terms of bit error rates (BER), is significantly improved by cooperative beamforming, and the performance of the simplified method is not only very close to the optimal one but also with faster iteration speed and much lower computational complexity.     

一种自适应Huffman算法在无线传感器网络数据压缩中的应用

针对无线传感器网络中数据压缩的问题,提出了一个基于时空相关性和Huffman编码的数据压缩算法,并在传输的比特数和压缩比方面与静态Huffman方法进行了比较。实验结果表明,所提出的算法执行效果更好。     

银川市浅层地温场分布特征及其控制因素探讨

为了探讨银川市浅层地温场分布特征及影响浅层地温场的控制因素,采用自动和人工相结合的方法对银川市90~200 m地温监测孔进行监测.数据显示,200 m以内浅层平均地温梯度一般为1.5~4℃/100 m,高地温带呈NNE向展布于银川市区中部,形态分布与该区重要隐伏活动断裂走向基本一致.研究表明,银川张性断裂是银川市浅层地温场分布的控制因素,是造成浅层地温异常的主要因素.     

Keccak算法非线性变换x的分析

x是keccak算法中唯一的非线性部件,本文研究了x变换的主要密码学性质,指出了x的非线性度为8,差分均匀度为8,代数次数为2,满足平衡性,可逆。计算出了x的逆变换的表达式,并分析了其密码学性质。基于x变换的设计思想,我们试图找到新的方法来构造分组密码中的S盒。