An effective discretization based on Class-Attribute Coherence Maximization

Discretization of continuous data is one of the important pre-processing tasks in data mining and knowledge discovery. Generally speaking, discretization can lead to improved predictive accuracy of induction algorithms, and the obtained rules are normally shorter and more understandable. In this paper, we present the Class-Attribute Coherence Maximization (CACM) algorithm and the Efficient-CACM algorithm. We have compared the performance of our algorithms with the most relevant discretization algorithm, Fast Class-Attribute Interdependence Maximization (Fast-CAIM) discertization algorithm (Kurgan and Cios, 2003). Empirical evaluation of our algorithms and Fast-CAIM on 12 well-known datasets shows that ours generate the superior discretization scheme, which can significantly improve the classification performance of C4.5 and RBF-SVM classifier. As to the execution time of discretization, ours also prove faster than Fast-CAIM algorithm, with the Efficient-CACM algorithm having the shortest execution time.     

一种大基线分布雷达近场相参探测技术

大基线分布式孔径雷达探测近场目标时,由于各孔径对目标的观测角差异较大,雷达接收到的目标散射回波间的相参性差,难以对回波进行相参积累。本文首先研究了目标回波相参性与回波角度和雷达距离分辨率之间的关系;随后,在大基线分布式孔径雷达近场下,通过分辨单元精细刻画,将大散射点目标变为由若干个强散射点组成的“多目标”,进而分别对各强散射点回波进行相参积累;最后,进行仿真分析和试验。结果表明,目标散射回波在大观测角下的相参性得到有效改善,提高了检测信噪比得益,从而验证了本方法的正确性。     

Reconstruction of Full-Length circRNA Sequences Using Chimeric Alignment Information

Circular RNAs (circRNAs) are RNA molecules formed by joining a downstream 3 splice donor site and an upstream 5 splice acceptor site. Several recent studies have identified circRNAs as potential biomarker for different diseases. A number of methods are available for the identification of circRNAs. The circRNA identification methods cannot provide full-length sequences. Reconstruction of the full-length sequences is crucial for the downstream analyses of circRNA research including differential expression analysis, circRNA-miRNA interaction analysis and other functional studies of the circRNAs. However, a limited number of methods are available in the literature for the reconstruction of full-length circRNA sequences. We developed a new method, circRNA-full, for full-length circRNA sequence reconstruction utilizing chimeric alignment information from the STAR aligner. To evaluate our method, we used full-length circRNA sequences produced by isocirc and ciri-long using long-reads RNA-seq data. Our method achieved better reconstruction rate, precision, sensitivity and F1 score than the existing full-length circRNA sequence reconstruction tool ciri-full for both human and mouse data.     

基于多传感信号的火灾探测互相关算法

本文针对复合探测器提出了一种新的互相关算法。该算法首先对采集的数据信号特性进行分析,利用给出的模型公式描述出采集信号的变化特征,再根据互相关函数的性质分析和识别火灾信号与非火灾信号。本文论述了该方法的实现和对试验火以及油烟火的分析结果,证明该算法具有较好的灵敏度,能识别厨房油烟信号,具有较低的误报率。     

磁控溅射法在生物材料表面制备羟基磷灰石涂层的研究现状

主要以牙科种植体为例,介绍钛合金和羟基磷灰石的性能及在生物材料应用中的局限,并简述磁控溅射法的优越性.概述了国内外利用磁控溅射制备生物涂层的动向,得出梯度功能复合膜层制备发展的大趋势及磁控溅射法制备涂层的良好前景,以及在牙科种植体的应用.     

黄土处理煤矿酸性废水的可行性研究

黄土在我国广泛分布,而我国煤矿企业,为维持煤矿采掘正常进行,都要排放SO42-离子含量很高的酸性矿坑废水。本文通过分析黄土与煤矿酸性废水的成分以及可能发生的反应,来阐述利用黄土处理煤矿酸性废水的可行性。     

基于Web的网络计算机技术在高校化学科研与教学中的应用

现代计算机网络使我们的生活和工作发生了革命性的变化.互联网日渐渗透到我们工作和生活的每一个角落,互联网、数据库、多媒体、分子模拟等技术的发展,使化学家的工作变得更加方便快捷.作者等就计算机网络技术在陕西师范大学化学与材料科学学院的应用,及笔者的体会对以下两方面的内容做简要介绍和展望:(1)现代网络计算机技术的发展状况;(2)网络计算机技术在高校化学科研和教学中的应用,及其未来的发展方向.     

基于SSE2的Smith-Waterman算法

Smith-Waterman动态规划算法是生物信息学使用最广泛的序列匹配算法,由于存在严重的数据依赖关系,该算法的细粒度数据并行性开发受到了很大限制。文章从简化数据依赖关系出发,采用前驱计算思想,提出了基于X86处理器多媒体指令集SSE2的Smith-Waterman细粒度并行算法SWSSE2,在相似性显著的情况下比普通的SW算法性能提高5倍,且与测试集无关。一般相似性不显著的情形下,同目前最好的动态规划细粒度并行算法SWMMX相比可以获得1.5倍的加速比。     

过冷处理对Cu45Zr42Al8Ag5非晶热稳定性及力学性能的影响

采用过冷液体等温处理的方法制备出直径为3 mm的Cu45Zr42Al8Ag5合金圆棒,研究了过冷液体等温处理对铜基内生复合材料的热稳定性和力学性能的影响,研究表明,过冷处理后的试样均为原位自生晶体/非晶复合材料,且其有较好的热稳定性.由铜基非晶合金压缩后的应力--应变曲线可以看出,随保温时间的延长,最大抗压强度逐渐降低...     

High Temperature Deformation Behavior of High Strength and Toughness Ti-Ni Base Bulk Metallic Glass CompositesEI北大核心CSCD

Room-temperature brittleness and strain-softening during deformation of bulk metallic glasses, and limited processability of shape memory alloys have been stumbling blocks for their advanced functional structural applications. To solve the key scientific problems, a new shape memory bulk metallic glass based composite, through the approach using transformation-induced plasticity (TRIP) effect of shape memory alloys to enhance both ductility and work-hardening capability of metallic glasses, and superplasticity of bulk metallic glass in supercooled liquid region to realize near net forming, was developed in this work. And the Ti-Ni base bulk metallic glass composites (BMGCs) rods were prepared by the levitation suspend melting-water cooled Cu mold process. Microstructure, thermal behavior, mechanical properties and high temperature deformation behavior of the alloy were investigated. The results show that the as-cast alloy microstructure consists of amorphous matrix, undercooled austenite and thermally-induced martensite. Besides, the size of the crystal phase precipitated on the amorphous matrix in-creases from the surface to the inside. The alloy exhibits excellent comprehensive mechanical properties at room temperature. The yield strength, fracture strength and the plastic strain of alloy are up to 1286 MPa, 2256 MPa and 12.2%, respectively. Under compressive loading in the supercooled liquid region, the composite exhibits approximate Newtonian behavior at lower strain rate in higher deformation temperature, and the optimum deformation temperature is T>480 degrees C and the intersection part with supercooled liquid region (SLR). When the temperature is 560 degrees C and the strain rate is 5x10(-4) s(-1), the stress sensitivity index m and the energy dissipation rate Psi are 0.81 and 0.895, respectively. Furthermore, the volume of activation is quantified to characterize the rheological behavior.