Numerical analysis on compliance and electrical behavior of multi-copper-column flip-chip interconnects for wafer-level packaging

This paper presents modeling and simulation results of a modified copper-column-based flip-chip interconnect with ultrafine pitch for wafer-level packaging, and the process and prototyping procedure are described as well. This interconnect consists of multiple copper columns which are electrically in parallel and supporting a solder bump. A simple analytical model has been developed for correlation between the interconnect geometry and the thermal fatigue life. In comparison to the conventional single-copper-column (SCC) interconnects, numerical analysis reveals that the multi-copper-column (MCC) interconnect features enhanced compliances and, hence, higher thermomechanical reliability, while the associated electrical parasitics (R, L, and C) at dc and moderate frequencies are still kept low. Parametric studies reveal the effects of geometric parameters of MCC interconnects on both compliances and electrical parasitics, which in turn facilitate design optimization for best performance. By using coplanar waveguides (CPWs) as feed lines on both chip and package substrate, a high-frequency (up to 40 GHz) S-parameter analysis is conducted to investigate the transmission characteristics of the MCC interconnects within various scenarios which combines various interconnect pitches and common chip and package substrates. An equivalent lumped circuit model is proposed and the circuit parameters (R, L, C, and G) are obtained throughout a broad frequency range. Good agreement is achieved for the transmission characteristics between the equivalent lumped circuit model and direct simulation results.     

基于多决策树算法的网络入侵检测

将一个大数据集分割成若干个子数据集，在每个子数据集上使用决策树算法进行挖掘，用投票的方式将多棵决策树的结果结合起来，形成全局的判断。将这种方法应用于网络入侵检测，试验表明，该方法不仅提高了数据挖掘算法对海量数据的处理能力，而且降低了误判率。     

Hybrid accident simulation methodology using artificial neural networks for nuclear power plants

A hybrid accident simulation methodology for nuclear power plants is proposed to enhance the capabilities of compact simulator by introducing artificial neural networks. Two neural networks are trained with the target values obtained from the analyses of detailed computer codes and trained results are combined with the compact simulator to perform the following roles: (i) compensation for inaccuracies of a compact simulator occurring from simplified governing equation and reduced number of physical control volumes, and (ii) prediction of the critical parameter usually calculated from the sophisticated computer code: the autoassociative neural network improves the computational results of the compact simulator up to the accuracy level of detailed best estimate computer code, while the backpropagation neural network predicts the minimum departure from nucleate boiling ratio (DNBR). Simulations are carried out to verify the applicability of the proposed methodology for the loss of flow accidents and the results show that the neural networks can be used as a complementary tool to improve the results of a compact simulator.     

Automatic measurement of volume percentage stroma in endometrial images using texture segmentation

The popularity of digital microscopy and tissue microarrays allow the use of high-throughput imaging for pathology research. To coordinate with this new technique, it is essential to automate the process of extracting information from such high amount of images. In this paper, we present a new model called the Subspace Mumford-Shah model for texture segmentation of microscopic endometrial images. The model incorporates subspace clustering techniques into a Mumford-Shah model to solve texture segmentation problems. The method first uses a supervised procedure to determine several optimal subspaces. These subspaces are then embedded into a Mumford-Shah objective function so that each segment of the optimal partition is homogeneous in its own subspace. The method outperforms a widely used method in bioimaging community called k-means segmentation since it can separate textures which are less separated in the full feature space, which confirm the usefulness of subspace clustering in texture segmentation. Experimental results also show that the proposed method is well performed on diagnosing premalignant endometrial disease and is very practical for segmenting image set sharing similar properties.     

Singularity robust algorithm in serial manipulators

Singularity is a fundamental problem with robotic manipulators. Various methods of singularity handling have been published in the past. In this paper, a singularity robust method is presented and its implementation issues discussed. It focuses on the discontinuity problem inherent in the singularity robust techniques with removal of degenerate components. Sources of the discontinuity are discussed and the null motion is proposed as the means of providing a continuous control of the end-effector over the boundary of the singular region. The presentation of this paper covers a complete treatment of singularities, starting from identifications of the singular configurations and the associated singular directions, the handling algorithm and the discontinuity issues. The algorithm was implemented on PUMA 560. The experimental results are presented and discussed.     

基于随机Petri网的服务组合可协调性研究

提出了一种基于随机Petri的服务组合间可协调性研究方法。首先,给出了服务以及服务系统的定义;然后,在服务以及服务组合可协调性定义的基础上给出了可协调行分析算法;最后,以一个电子物流系统为例,在随机Petri网建模的基础下给出了服务组合间的可协调性研究方法。     

船用重油多元模型燃料的构建与验证

为了复现实际船用重油燃料燃烧特性,基于化学解构法原理,提出了重油多元模型燃料。选择了正十四烷、2,6,10-三甲基十二烷、四氢化萘和正癸基苯作为基础燃料,表征实际重油的正构烷烃、异构烷烃、环烷烃和芳烃成分。模型燃料的比例依据带权欧几里得距离算法进行最优化求解。针对发展的多元模型燃料,基于流动反应器试验平台对模型燃料的中低温氧化特性进行点对点比较,多组分模型燃料成功复现了典型反应物、中间产物和生成物浓度随温度变化的趋势。基于"解耦法"的机理简化方法,发展了重油多组分模型燃料骨架机理。该机理成功预测了重油馏分的中低温氧化特性。基于该骨架机理进行敏感性分析,得到烷烃类自由基主导的基元反应与重油碳烟生成密切相关的结论。此外,基于定容燃烧装置数值仿真结果,证明了重油多组分模型燃料对近发动机条件下的喷雾燃烧过程具有较高的预测能力。     

代码生成器形式化验证技术研究

代码生成器已经广泛应用于嵌入式控制软件的开发.对于安全攸关的软件系统,对软件可靠性有很高的要求,代码生成器作为工具软件被要求与所生成代码有相同的可靠性,形式化验证方法可有效保证代码生成器的可靠性.本文介绍了用于构建形式化验证代码生成器的方法,针对Lustre到C的代码生成器给出Lustre和C的抽象语法,并定义Lust...     

InP/InGaAs HBT高频放大器稳定性分析

根据异质结双极晶体管(HBT)的实际结构提出高频小信号电路模型,以此模型用于共射放大电路为出发点,从理论上阐明了高频放大电路产生不稳定的原因,分析了端接电阻的稳定方法,借助matlab快速确定出稳定电阻的取值范围,其理论计算与仿真有很好的一致.     

偏振能量色散X-射线荧光光谱法测定水系沉积物和土壤样品中多种组分

采用粉末样品压片制样,用偏振能量色散X-射线荧光光谱仪对水系沉积物和土壤样品中多种元素进行测定。除Na,Si和Fe外,其余元素利用经验系数和二级靶的康普顿散射线作内标校正基体效应。分别采用了Al2O3,W,BaF2,CsI,Ag,Rb,Mo,Zr,SrF2,KBr,Ge,Fe,Ti和Al等不同偏振靶(或二级靶)对被分析元素进行选择激发和测定。在总测量时间为2 000 s(每个样品)的条件下,除Na,Mg,Al,Si,P,K等轻元素外,其余各元素的检出限达到0.25-14.80μg/g。