基于边缘敏感的SLIC和二次密度聚类的GGO分割

针对磨玻璃肺结节(Ground Glass Opacity,GGO)边界对比度低、大小各异和灰度不均匀等造成分割准确率低的问题,提出一种基于边缘敏感的SLIC和二次密度聚类相结合的分割算法。将图像边缘检测结果与SLIC超像素算法相结合,并将其中含有边缘的超像素块用区域质心代替其原始聚类中心,改善SLIC边界黏连性较差的问题;针对密度聚类不能完整分割GGO的问题,提出二次密度聚类的方法,对密度聚类定位到的簇及其邻域簇进行二次密度聚类。实验结果表明,该算法分割GGO的平均准确率达90.17%,灵敏度达84%。     

Temperature stability and fracture toughness of Nd-Fe-B magnets

Temperature stability and toughness of magnets are very important properties especially for application in motor. In this paper, it is found that temperature stability and toughness of magnets are improved when Fe is substituted with Co andheavy rare earth is substituted for Nd in part and suitable rich B grain-boundary phase is added. In addition, heavy rare earth substitution decreases the remanence temperature coefficient greatly, but has a little effect on Curie temperature of the magnets, which is beneficial to Nd-Fe-B magnets for the application in motor.     

EFFECT OF SILICON ON THE TRANSITION OF BRITTLENESS IN A NICKEL BASE WROUGHT SUPERALLOY

Ni-15Cr-6W-3Mo-2Al-2Ti变形高温合金的室温抗张强度、塑性和冲击性能,随着合金中Si含量的变化呈现马鞍型的变化,即在0.4—0.6％Si范围内出现一个低塑性、低拉伸强度和低冲击韧性区。造成这种现象的本质原因是由于Si含量变化改变了晶界碳化物沉淀析出顺序、析出类型、析出量和析出形态。该合金晶界碳化物析出可分为四个阶段:第一阶段,<0.1％Si时,只有单一的M_(23)C_6析出;第二阶段,>0.1％Si以后,除M_(23)C_6外,M_6C开始析出,一直到0.4％Si时增加2缓慢;第三阶段,0.4—0.6％Si时,M_6C大量析出逐渐取代M_(23)C_6;第四阶段,>0.6％Si以后,M_6C量占绝对优势,但增加幅度比第三阶段小得多。从晶界形态来看,第一、二、四阶段皆属不连续的链状形式,只有第三阶段晶界呈现连续膜状。因此,造成性能下降的原因不是因为析出M_6C,而是它的形态,当它以颗粒状分布在晶界上时是一个很好的强化相。第三阶段的不正常析出是性能下降的本质因素。本研究结果打破了只要镍基合金中MO+1/2>W>6％(重量百分比)就形成M_6C的经验判据,“Si”才是该合金碳化物沉淀析出过程的控制因素。本文还对比了冶炼工艺差别对碳化物析出过程的影响。     

基于混合遗传算法的去耦电容网络设计

结合基于目标阻抗的设计方法,将混合遗传算法应用于PDN(电源分配网络)的去耦电容网络设计,对所需去耦电容器的种类和数目进行优化计算,同时与标准遗传算法和传统设计方法进行对比,借助Cadence电源完整性仿真工具验证设计结果的有效性和合理性。避免了传统设计需要借助EDA工具进行反复修改和验证的繁琐过程,同时减少了设计冗余,节省了PCB布局布线空间,为高频电路的PDN设计提供参考。     

3G移动通信系统的无线网络优化论述

近些年来,我国的移动通信业务的规模不断的扩大,移动通信的形式也不断的发展,3G技术已经实现了推广和运行,这种情况下优化无线网络运营环境,实现3G移动通信网络的系统技术升级,就是未来通信行业发展所要面临的最主要的问题.     

Detecting Driver Normal and Emergency Lane-Changing Intentions With Queuing Network-Based Driver Models

Driver intention detection is an important component in human-centric driver assistance systems. This article proposes a novel method for detecting driver normal and emergency left- or right-lane-changing intentions by using driver models based on the queuing network cognitive architecture. Driver lane-changing and lane-keeping models are developed and used to simulate driver behavior data associated with 5 kinds of intentions (i.e., normal and emergency left- or right-lane-changing and lane-keeping intentions). The differences between 5 sets of simulated behavior data and the collected actual behavior data are computed, and the intention associated with the smallest difference is determined as the detection outcome. The experimental results from 14 drivers in a driving simulator show that the method can detect normal and emergency lane-changing intentions within 0.325 s and 0.268 s of the steering maneuver onset, respectively, with high accuracy (98.27% for normal lane changes and 90.98% for emergency lane changes) and low false alarm rate (0.294%).     

Performance analysis on Lv distribution and its applications

A new signal analysis method, known as Lv distribution (LVD), has been reported recently to provide improved estimation accuracy of centroid frequency and chirp rate. In this paper, performances of the LVD on signal concentration, detection, representation errors and computational complexity are discussed and compared with polynomial Fourier transform (PFT) and fractional Fourier transform (FrFT). Based on the results of our theoretical analysis and Monte Carlo simulations, it is shown that the LVD achieves desirable performance improvement compared with those achieved by other methods. By using the accurate estimation of chirp rate provided by the LVD, the performance of local polynomial periodogram (LPP) is investigated. Comparisons with other time–frequency representations, such as the inverse LVD (ILVD) and the PFT-based LPP, are made on signal concentration in the time–frequency domain.     

A Stochastic Vehicle Routing Problem with Travel Time Uncertainty: Trade-Off Between Cost and Customer Service

On-time shipment delivery is critical for just-in-time production and quick response logistics. Due to uncertainties in travel and service times, on-time arrival probability of vehicles at customer locations can not be ensured. Therefore, on-time shipment delivery is a challenging job for carriers in congested road networks. In this paper, such on-time shipment delivery problems are formulated as a stochastic vehicle routing problem with soft time windows under travel and service time uncertainties. A new stochastic programming model is proposed to minimize carrier’s total cost, while guaranteeing a minimum on-time arrival probability at each customer location. The aim of this model is to find a good trade-off between carrier’s total cost and customer service level. To solve the proposed model, an iterated tabu search heuristic algorithm was developed, incorporating a route reduction mechanism. A discrete approximation method is proposed for generating arrival time distributions of vehicles in the presence of time windows. Several numerical examples were conducted to demonstrate the applicability of the proposed model and solution algorithm.     

网络攻击的防范策略

近年来计算机网络受到攻击及瘫痪的现象频频发生,给企业和社会造成极大的经济损失,在社会上影响极坏。因此,除了传统的预防方法之外,为改变这种被动受攻击的局面,本文对网络攻击的防范策略进行了探讨。     

基于单片机的地震仪器采集站控制优化

地震仪器是一种重要的油气勘探设备。在地震仪器中,由电源站为采集站提供电能,采集站的控制方案影响电源站的带道数量。为了提高电源站的带道数量,减少勘探成本,本文根据对地震仪器供电模型的分析,针对采集站启动状态对电源站带道数量的影响,提出了一套采集站单片机控制的优化方案,并进行了实验验证。实验结果表明,在55米道距时,电源站带道数量可提高至40道,优化方案切实、有效。