基于深度学习的秀丽隐杆线虫显微图像分割方法

利用计算机实现自动、准确的秀丽隐杆线虫(C.elegans)的各项形态学参数分析,至关重要的是从显微图像上分割出线虫体态,但由于显微镜下的图像噪声较多,线虫边缘像素与周围环境相似,而且线虫的体态具有鞭毛和其他附着物需要分离,多方面因素导致设计一个鲁棒性的C.elegans分割算法仍然面临着挑战。针对这些问题,提出了一种基于深度学习的线虫分割方法,通过训练掩模区域卷积神经网络(Mask R-CNN)学习线虫形态特征实现自动分割。首先,通过改进多级特征池化将高级语义特征与低级边缘特征融合,结合大幅度软最大损失(LMSL)损失算法改进损失计算;然后,改进非极大值抑制;最后,引入全连接融合分支等方法对分割结果进行进一步优化。实验结果表明,相比原始的Mask R-CNN,该方法平均精确率(AP)提升了4.3个百分点,平均交并比(mIOU)提升了4个百分点。表明所提出的深度学习分割方法能够有效提高分割准确率,在显微图像中更加精确地分割出线虫体。     

不同级配对微表处混和料性能的影响

微表处技术是一种性能优良的路面养护技术。首先检验了微表处用原材料的技术指标,在满足规范的要求下选择了三种不同级配,并对三种不同级配的微表处混和料的使用性能进行了比较。     

On the effects of the packet size distribution on the packet loss process

Real-time multimedia applications have to use forward error correction (FEC) anderror concealment techniques to cope with losses in today’s best-effort Internet. The efficiency of these solutions is known however to depend on the correlation between losses in the media stream. In this paper we investigate how the packet size distribution affects the packet loss process, that is, the distribution of the number of lost packets in a block, the related FEC performance and the average loss run length. We present mathematical models for the loss process of the MMPP+M/D/1/K and the MMPP+M/M/1/K queues; we validate the models via simulations, and compare the results to simulation results with an MPEG-4 coded video trace. We conclude that the deterministic packet size distribution (PSD) not only results in lower stationary loss probability than the exponential one, but also gives a less correlated loss process, both at a particular average link load and at a particular stationary loss probability as seen by the media stream.Our results show that for applications that can only measure the packet loss probability, the effects of the PSD on FEC performance are higher in access networks, where a single multimedia stream might affect the multiplexing behavior. Our results show that the effects of the PSD on FEC performance are higher in access networks, where a single multimedia stream might affect the multiplexing behavior and thus can improve the queuing performance by decreasing the variance of its PSD.     

A review of robust design methods for multiple responses

Problems in engineering design often involve determining design variable settings to optimize individual product performance for multiple criteria, which are often in conflict. We review mathematically rigorous techniques from the statistical literature for finding a vector x of design variable settings, which produces an optimal compromise solution among a group of prioritized response variables. The best compromise solution is typically gained by optimizing an objective function, which incorporates the prioritized demands of multiple responses. Since most multi-response objective functions are constructed by combining the functions used to optimize univariate responses, a review of the prominent univariate approaches is presented first. A multivariate approach from the engineering literature called the compromise Decision Support Problem is also reviewed. Finally a table comparing the relative merits of the different multivariate approaches summarizes the article in a concise and user-friendly fashion.     

抗盐降滤失剂SDX的研究与应用

介绍了抗盐降滤失剂SDX的合成方法与现场应用简况,评价了SDX的抗温、抗盐、防塌及配伍性能。试验结果表明,SDX能耐150℃以上的高温,可抗盐至饱和,具有良好的降滤失和抑制性能,与其它处理剂的配伍性好,适用于各种水基泥浆。     

可生物降解的钻井液降滤失剂SPS的合成与性能研究

以淀粉为主要原料合成了一种可生物降解的钻井液滤失剂ＳＰＳ，考察了ＳＰＳ的生物降解性及其在淡水泥浆，盐水泥浆和海水泥浆中的性能。结果表明，ＳＰＳ具有良好的降滤失与抗温、抗污染性能，在海水中可被生物降解。     

对供电损失率变动规律的分析与预测

通过对历史统计资料的研究,揭示出了供电损失率变动的基本趋势,得出预测的数学模型,同时也获得一种简捷计算供电损失率理论值的方法,便于从宏观角度掌握供电损失率,也可为供电损失管理部门决策提供参考。     

基于改进SSD的变压器套管红外图像油位智能识别方法

为解决现有基于红外图像识别变压器套管油位存在的过于依赖温度信息、人工处理效率低下等问题,文中结合目标检测技术提出了一种基于改进单次检测器(SSD)的套管智能油位识别方法。通过引入SSD目标检测方法,检测红外图像中的套管区域,加入损失函数以改进SSD算法从而提高套管检测准确率,并进一步通过简单线性迭代聚类(SLIC)的应用实现了不依赖红外图像温度信息的油位检测。对比文中提出的基于红外图像的油位识别算法检测结果与人工油位检测结果,表明文中提出的算法不仅在效率上领先于传统的温度检测方式,且其误差较小,仅为0.08%。对比结果验证了所提算法在保证检测精度的情况下可大幅度提高检测效率,有效提升套管故障诊断效率和智能化水平。     

工序能力评价与经济分析

通过对工序能力的分析与评价 ,工序能力并非越高越好 ,提高工序能力有时意味着增加成本 ,故应作经济分析 ,本文介绍了一种经济分析的方法。