韶钢热轧宽板厂工艺设备参数的优化

采用卷轧与中板轧制相结合的轧制工艺具有投资省、见效快等优点,对于资金不是很充裕需要采取滚动发展的中小型企业是一种可取之路.韶钢通过与国内外专家的技术交流、技术谈判及优化,在有限的场地上(长620m、宽120 m)布置一套先进、实用的3 450现代宽中厚板(卷)生产线,取得了较好的投资效益.     

砂浆立方体抗压强度与底模的关系

建筑砂浆试件的制作目前均执行《建筑砂浆基本性能试验方法》(JGJ70-1990)有关规定，所用底模系含水量不大于2％的普通粘土砖。     

提高E^2PROM中NMOS管源漏穿通电压的实验研究

为了提高Ｅ＾２ＰＲＯＭ中Ｎ管源漏穿通电压，用实验的方法对制造工艺进行了研究。结果表明，高能量注入是提高ＶＰＴ的有效手段，但受到ｐｎ结击穿的限制，只适用于低区短沟Ｎ管；ＤＤＤ工艺大幅度高ＶＰＴ，但ｐｎ结击穿电压低于２０Ｖ，不能应用于高压ＭＯＳ管；采用适量的防穿通注入和适当增大沟道长度为最理想的工艺途径。     

SVPWM三相电压型逆变器的仿真研究

以三相电压型逆变器为基础,根据空间矢量脉宽调制（SVPWM）基本原理详细分析研究了电压矢量作用时间和扇区分配问题,以α-β坐标为基础,建立了互差π/3的x-y-z时间坐标系,提出了不同扇区矢量作用时间长短根据期望极值判断的原则。介绍了MATLAB中M文件编程的仿真方法,建立了MATLAB程序嵌入式主要功能模块,逆变器采用数字PID控制,利用Simulink对系统进行了综合仿真分析及试验,给出了仿真及实验波形,为实现SVPWM逆变器的数字控制提供参考。     

A new algorithm for fast mining frequent itemsets using N-lists

Mining frequent itemsets has emerged as a fundamental problem in data mining and plays an essential role in many important data mining tasks.In this paper,we propose a novel vertical data representation called N-list,which originates from an FP-tree-like coding prefix tree called PPC-tree that stores crucial information about frequent itemsets.Based on the N-list data structure,we develop an efficient mining algorithm,PrePost,for mining all frequent itemsets.Efficiency of PrePost is achieved by the following three reasons.First,N-list is compact since transactions with common prefixes share the same nodes of the PPC-tree.Second,the counting of itemsets’ supports is transformed into the intersection of N-lists and the complexity of intersecting two N-lists can be reduced to O(m + n) by an efficient strategy,where m and n are the cardinalities of the two N-lists respectively.Third,PrePost can directly find frequent itemsets without generating candidate itemsets in some cases by making use of the single path property of N-list.We have experimentally evaluated PrePost against four state-of-the-art algorithms for mining frequent itemsets on a variety of real and synthetic datasets.The experimental results show that the PrePost algorithm is the fastest in most cases.Even though the algorithm consumes more memory when the datasets are sparse,it is still the fastest one.     

Multi-channel SAR imaging based on distributed compressive sensing

The rapid development of compressive sensing(CS)shows that it is possible to recover a sparse signal from very limited measurements.Synthetic aperture radar(SAR)imaging based on CS can reconstruct the target scene with a reduced number of collected samples by solving an optimization problem.For multi-channel SAR imaging based on CS,each channel requires sufficient samples for separate imaging and the total number of samples could still be large.We propose an imaging algorithm based on distributed compressive sensing(DCS)that reconstructs scenes jointly under multiple channels.Multi-channel SAR imaging based on DCS not only exploits the sparsity of the target scene,but also exploits the correlation among channels.It requires significantly fewer samples than multi-channel SAR imaging based on CS.If multiple channels offer different sampling rates,DCS joint processing can reconstruct target scenes with a much more flexible allocation of the number of measurements offered by each channel than that used in separate CS processing.     

基于游程编码思想的条码定位与识别方法

在复杂背景中的定位条码是图像式条码识别系统中的一个关键步骤,如何在复杂的背景中快速、白动地检测出条形码是该文的主要研究内容。首先介绍了条型码的编码结构,然后提出了一种基于游程编码思想的条码定位与识别方法,最后通过给出相关实验结果,验证了该算法的可行性和实用性。