COUPLING PROCESS FOR Ti AND Si BETWEEN TITANIA SLAGS AND Cu MELTS AT 1500 ℃

ＣＯＵＰＬＩＮＧＰＲＯＣＥＳＳＦＯＲＴｉＡＮＤＳｉＢＥＴＷＥＥＮＴＩＴＡＮＩＡＳＬＡＧＳＡＮＤＣｕＭＥＬＴＳＡＴ１５００℃￥Ｘｕｅ，Ｘｉａｎｇｘｉｎ；Ｃｈｅ，Ｙｉｎｃｈａｎｇ（ＤｅｐａｒｔｍｅｎｔｏｆＦｅｒｒｏｕｓＭｅｔａｌｌｕｒｇｙ，Ｎｏｒｔｈｅａ...     

一种基于潜在引用网络的专利价值评估方法

专利价值指的是在专利购买交易时的交换价值,它可以为专利的拥有者和购买者提供大量关于专利的珍贵信息,为专利的交易提供决策支持。目前的专利价值评估主要是基于训练或引用的方法。前者过于依赖于人工选择的参数,导致专利价值评估结果的可信度较低;后者往往只考虑了直接引用关联,而忽略了间接引用关联和新颖度对专利价值的影响。针对这些问题,提出一种基于潜在引用网络的专利价值评估方法,并设计了相应的算法来评估各个专利的价值。针对基本算法效率较低的问题,提出了专利价值评估改进算法,极大地提高了专利价值评估的效率。最后,由于新专利加入专利集合时各个专利的价值会发生变化,提出了专利价值评估动态更新算法,用于快速地更新各个专利的价值。实验表明,提出的方法是有效的。     

LiDAR点云支持下地物精细分类的实现方法

在遥感数据分类中,获取精细的地物类别无疑能够传递更加丰富的信息量,进一步加深对遥感数据的理解和解译。在机载LiDAR点云高程数据的支持下,提出并实现了遥感影像上地物精细分类的方法。为保证高精度地同种地物再划分,综合考虑配准、辅助数据源、首次回波、点云密度及影像空间分辨率4种因素,并重点解决了点云密度与影像空间分辨率不匹配的问题,利用决策树显著地提高了影像上建筑物、植被的分类数量,使点云与影像联合分类的优势得到体现,达到了分类精度与地物类别数量相统一的目的。     

非接触式IC卡读卡器的二次开发

鉴于IC卡设备资源有限性,提出二次开发IC卡读写器程序的加密盒认证保护的方法及系统。     

Color image segmentation using adaptive unsupervised clustering approach

This paper presents the Region Splitting and Merging-Fuzzy C-means Hybrid Algorithm (RFHA), an adaptive unsupervised clustering approach for color image segmentation, which is important in image analysis and in understanding pattern recognition and computer vision field. Histogram thresholding technique is applied in the formation of all possible cells, used to split the image into multiple homogeneous regions. The merging technique is applied to merge perceptually close homogeneous regions and obtain better initialization for the Fuzzy C-means clustering approach. Experimental results have demonstrated that the proposed scheme could obtain promising segmentation results, with 12% average improvement in clustering quality and 63% reduction in classification error compared with other existing segmentation approaches.     

摩天岭隧道左线涌水特点及综合治理方案

本文着重介绍摩天岭隧道左线进口段反坡施工,多次、多点发生大规模涌水的特点及其成因,并详细介绍了经过专家论证后制定采取的综合治理方案,为长大隧道灰岩地区反坡施工涌水处理提供了宝贵经验。     

c#．net调用matlab进行混合编程

本文结合一个小实例提出了几种混合编程的方法。     

FCMAC网络的软硬件协同设计与实现

提出了FCMAC网络的一种基于NiosII的软硬件协同设计方法,解决了FCMAC软件实现速度慢、硬件实现耗资源的不足。通过Matlab仿真得出FCMAC网络的各参数。分析影响软件实现FCMAC速度的关键算法,对FCMAC算法进行软硬件划分。在NiosII IDE开发环境下,基于C实现软件模块,以用户自定义指令形式实现硬件模块和软硬件的衔接,即完成软硬件的协同设计。试验结果表明,FCMAC的软硬件协同实现在软件实现速度慢、硬件实现耗资源之间实现了折中,可通过不同的软硬件划分,实现速度与资源的互换。     

Network traffic classification based on ensemble learning and co-training

Classification of network traffic is the essential step for many network researches. However,with the rapid evolution of Internet applications the effectiveness of the port-based or payload-based identifi-cation approaches has been greatly diminished in recent years. And many researchers begin to turn their attentions to an alternative machine learning based method. This paper presents a novel machine learning-based classification model,which combines ensemble learning paradigm with co-training tech-niques. Compared to previous approaches,most of which only employed single classifier,multiple clas-sifiers and semi-supervised learning are applied in our method and it mainly helps to overcome three shortcomings:limited flow accuracy rate,weak adaptability and huge demand of labeled training set. In this paper,statistical characteristics of IP flows are extracted from the packet level traces to establish the feature set,then the classification model is created and tested and the empirical results prove its feasibility and effectiveness.