Polarized differential-phase laser scanning microscope

A polarized differential-phase laser scanning microscope, which combines a polarized optical heterodyne Mach-Zehnder interferometer and a differential amplifier to scan the topographic image of a surface, is proposed. In the experiment the differential amplifier, which acts as a PM-AM converter in the experiment, converting phase modulation (PM) into amplitude modulation (AM). Then a novel, to our knowledge, phase demodulator was proposed and implemented for the differential-phase laser scanning microscope. An optical grating (1800 lp/mm) was imaged. The lateral and the depth resolutions of the imaging system were 0.5 mum and 1 nm, respectively. The detection accuracy, which was limited by the reflectivity variation of the test surface, is discussed.     

An Assessment of Testing-Effort Dependent Software Reliability Growth Models

Over the last several decades, many Software Reliability Growth Models (SRGM) have been developed to greatly facilitate engineers and managers in tracking and measuring the growth of reliability as software is being improved. However, some research work indicates that the delayed S-shaped model may not fit the software failure data well when the testing-effort spent on fault detection is not a constant. Thus, in this paper, we first review the logistic testing-effort function that can be used to describe the amount of testing-effort spent on software testing. We describe how to incorporate the logistic testing-effort function into both exponential-type, and S-shaped software reliability models. The proposed models are also discussed under both ideal, and imperfect debugging conditions. Results from applying the proposed models to two real data sets are discussed, and compared with other traditional SRGM to show that the proposed models can give better predictions, and that the logistic testing-effort function is suitable for incorporating directly into both exponential-type, and S-shaped software reliability models     

RWSNet: a semantic segmentation network based on SegNet combined with random walk for remote sensing

ABSTRACT

Semantic segmentation methods based on deep learning considerably improve the segmentation performance of remote sensing images. However, with the extensive application of high-resolution remote sensing images, additional details introduce considerable interference to the learning process for classification, thereby diminishing the accuracy of segmentation and resulting in blurry object boundaries. To address this problem, this study designed Random-Walk-SegNet (RWSNet), a semantic segmentation network based on SegNet combined with random walk. First, SegNet is used as the basic architecture with the sliding window strategy that optimizes the network output to improve the continuity and smoothness of segmentation. Second, seed regions of the random walk are selected in accordance with the classification output of SegNet. Third, the weights of the undirected graph edge are determined by fusing the gradient of the original image and probability map of SegNet. Finally, random walk is implemented on the entire image, thus reducing edge blur and realizing high-performance semantic segmentation of remote sensing images. In comparison with mainstream and other improved methods, the proposed network has lower complexity but better performance, and the algorithm is state-of-the-art and robust.     

用于脉冲涡流检测的新型数据处理方法

脉冲涡流检测是一种广泛应用的无损检测技术,是近年来的研究热点。本文对脉冲涡流检测的一种新型数据处理方法进行研究,为增强脉冲涡流检测技术的智能化水平提供理论依据。首先以感应信号分析为基础,分析了二阶系统拟合方法应用于脉冲涡流检测数据处理的合理性;然后对广义回归神经网络用于模式识别的优势进行分析,并应用该方法对脉冲涡流感应的模型参数进行分类,从而对被测导体进行材质鉴别及量化特征的识别分析;最后,通过实验验证了该"二阶系统拟合-基于GRNN的模式识别"方法的有效性并分析存在的问题,同时也指出了有待进一步深化研究的方向。     

阶段时间对CMICAO工艺低温运行特性的影响

研究了低温下多点交替进水阶式A2/O(CMICAO)工艺阶段运行时间对污染物去除率的影响,探讨了DO、ORP以及pH状态参数与污染物去除率之间的关系。结果表明,水温8~10 ℃,泥龄13 d,水力停留时间16 h,污泥浓度2 680~3 560 mg/L,污泥回流比30%,阶段1至6的运行时间为3、2.5、2、3、2.5、2 h时,工艺出水TN、氨氮、NO3--N和TP浓度的平均值分别为10.1、1.1、7.4和0.8 mg/L。硝化反应结束时,pH由下降转为上升,ORP上升趋于平缓,DO上升趋缓;反硝化结束时,ORP曲线明显跌落,pH由上升趋于平缓并略有下降;释磷结束后ORP曲线由下降趋于平缓。降低前好氧池DO浓度,有助于同步硝化反硝化作用的发生,从而提高脱氮效率,节省能耗。     

Logistic视频字幕增强模型

目的：为提高复杂背景下的视频字幕在OCR中的识别率,需要对提取的视频字幕进行有效地字幕增强。该文首次将Logistic模型应用到视频字幕增强中,提出了基于Logistic模型的融合多帧信息的视频字幕增强方法。方法：对字幕进行检测与跟踪,将出现在连续多帧中的同一字幕片段进行对齐;通过分析字幕片段在多帧中信息,提出字幕背景在时域上的变化特征、背景和字幕文本的固有特征,并将三个特征进行量化与融合,构建适用于字幕增强的Logistic模型,实现对视频字幕的增强。结果：对含阴影或描边效果的特殊复杂背景字幕、普通复杂背景字幕、单一背景字幕分别进行实验,增强后的字幕在OCR软件中的识别正确率分别为81.76%、97.13%、98.19%,与对比方法比较均有一定的提高。结论：实验结果表明,该文方法既可以降低字幕背景的复杂度,又可以提高字幕背景与文本的对比度,从而可以对复杂背景和单一背景下的视频字幕进行有效地增强。     

小净距并行隧道力学状态的试验研究

 招宝山隧道作为我国第一座超小净距(< 0. 28B ) 并行隧道的实践工程, 准确掌握隧道在不同施工过程中的力学状态, 是该工程成败的关键。为此, 在设计前对隧道施工状态进行了有限元数值计算模拟, 施工中对地面沉降、洞周收敛、拱顶下沉、岩体位移、围岩压力、支护结构应变、围岩松弛范围及爆破破坏深度等进行了系统测试工作, 有力地保证了这一设计施工新技术的顺利实施, 并为该技术在今后类似条件下的工程应用及完善提供了宝贵的经验。     

An Empirical Study on the Interaction Capability of Arm Stretching

Body-based motion gestures have been gaining popularity in designing interactive systems. However, theories and design guidelines on the use of body movement in design have not been fully evaluated. This article investigates human ability to perform discrete target selection tasks using stretching action through two controlled experiments. The experimental results indicate that: (1) the range of the discrete levels of depth that users can easily discriminate with arm stretching is up to 16 with full visual feedback, but is down to 4 without the feedback; (2) dwelling, a gesture with keeping a hand motionless and the cursor within a target area for a certain amount of time, may be the best gesture for confirmation command; (3) full visual feedback can improve the user performance; and (4) arm stretching action can be modeled using Fitts’ law. We also discuss the design potentials for Stretch Widgets based on these results.     

小流量旋流喷嘴喷雾性能影响因素的试验研究

在超高压燃油喷雾试验台上测试分析了不同环境背压及喷射流量对适用于斯特林发动机的小流量压力旋流喷嘴燃料喷射性能的影响。结果表明:喷嘴的喷雾形态受燃烧室背压的影响最明显,背压升高,喷雾锥角减小;喷射流量的影响受背压的限制,中高背压下,流量增大到一定程度后锥角开始变小,流量继续增大,雾化效果变差。喷嘴设计流量的影响为:增大设计流量,相同工况下的喷雾锥角有增大的趋势,但有效雾化的最小临界流量值变大;设计锥角的影响和设计流量类似:较大喷射流量工况下,大设计锥角喷嘴对高背压的适应性较好。研究认为:小流量工况只能采用小设计流量的喷嘴,且对高背压的适应性较差;在大流量工况下,设计流量和设计锥角均较大的喷嘴对高背压工况具有更好的适应性。     

生物质结渣固体碱催化剂制备生物柴油

采用经气化炉烧结的生物质结渣为固体碱催化剂,催化油脂转化合成生物柴油.对固体碱催化剂进行表征,并考察物质的量之比、反应温度、反应时间和催化剂用量对反应的影响.结果表明:生物质结渣固体碱催化剂主要成分(按质量分数计)为SiO2(40％～60％)、CaO(10％～20％)、K2O(10％～15％)、MgO(≤10％)、Al...