Effect of the mixing of s-wave and chiral p-wave pairings on electrical shot noise properties of normal metal/superconductor tunnel junctions

We study theoretically the electrical shot noise properties of tunnel junctions between a normal metal and a superconductor with the mixture of singlet s-wave and chiral triplet p-wave pairing due to broken inversion symmetry. We investigate how the shot noise properties vary as the relative amplitude between the two parity components in the pairing potential is changed. It is demonstrated that some characteristics of the electrical shot noise properties of such tunnel junctions may depend sensitively on the relative amplitude between the two parity components in the pairing potential, and some significant changes may occur in the electrical shot noise properties when the relative amplitude between the two parity components is varied from the singlet s-wave pairing dominated regime to the chiral triplet p-wave pairing dominated regime. In the chiral triplet p-wave pairing dominated regime, the ratio of noise power to electric current is close to 2e both in the in-gap and in the out-gap region. In the singlet s-wave pairing dominated regime, the value of this ratio is close to 4e in the inner gap region but may reduce to about 2e in the outer gap region as the relative amplitude of the chiral triplet pairing component is increased. The variations of the differential shot noise with the bias voltage also exhibit some significantly different features in different regimes. Such different features can serve as useful diagnostic tools for the determination of the relative magnitude of the two parity components in the pairing potential.

Range estimation of few-shot underwater sound source in shallow water based on transfer learning and residual CNN

Taking the real part and the imaginary part of complex sound pressure of the sound field as features,a transfer learning model is constructed.Based on the pre-training of a large amount of underwater acoustic data in the preselected sea area using the convolutional neural network(CNN),the few-shot underwater acoustic data in the test sea area are retrained to study the underwater sound source ranging problem.The S5 voyage data of SWellEX-96 experiment is used to verify the proposed method,realize the range estimation for the shallow source in the experiment,and compare the range estimation performance of the underwater target sound source of four methods:matched field processing(MFP),generalized regression neural network(GRNN),traditional CNN,and transfer learning.Experimental data processing results show that the transfer learning model based on residual CNN can effectively realize range estimation in few-shot scenes,and the estimation performance is remarkably better than that of other methods.

Comparison of the effects of submerged laser peening,cavitation peening and shot peening on the improvement of the fatigue strength of magnesium alloy AZ31

To investigate the improvement in the fatigue strength of magnesium alloy by peening methods,magnesium alloy AZ31 was treated by submerged laser peening(SLP),cavitation peening(CP),and shot peening(SP),and the fatigue properties were evaluated by a plane bending fatigue test.In the case of SLP,both the impact induced by laser ablation(LA)and that caused by laser cavitation(LC),which developed after LA,were used.In the present study,the fatigue life at a constant bending stress was examined to determine the suitable coverage.It was found that the fatigue strengths at N=10^(7)for the SLP,CP,and SP specimens treated by each optimum condition were 56%,18%,and 16%higher,respectively,than that of the non-peened(NP)specimen,which was 97 MPa.The key factors in the improvement of fatigue strength by peening methods were work hardening and the introduction of compressive residual stress.

Few-Shot Object Detection Based on the Transformer and High-Resolution Network

Now object detection based on deep learning tries different strategies.It uses fewer data training networks to achieve the effect of large dataset training.However,the existing methods usually do not achieve the balance between network parameters and training data.It makes the information provided by a small amount of picture data insufficient to optimize model parameters,resulting in unsatisfactory detection results.To improve the accuracy of few shot object detection,this paper proposes a network based on the transformer and high-resolution feature extraction(THR).High-resolution feature extractionmaintains the resolution representation of the image.Channels and spatial attention are used to make the network focus on features that are more useful to the object.In addition,the recently popular transformer is used to fuse the features of the existing object.This compensates for the previous network failure by making full use of existing object features.Experiments on the Pascal VOC and MS-COCO datasets prove that the THR network has achieved better results than previous mainstream few shot object detection.

基于One-Shot聚合自编码器的图表示学习

自编码器(AE)是一种高效的图数据表示学习模型,但大多数图自编码器(GAE)为浅层模型,其效率会随着隐藏层的增加而降低。针对上述问题,提出基于One-Shot聚合(OSA)和指数线性(ELU)函数的GAE模型OSA-GAE和图变分自编码器模型OSA-VGAE。首先,利用多层图卷积网络(GCN)构建编码器,并引入OSA和ELU函数;然后,在解码阶段使用内积解码器恢复图的拓扑结构;此外,为了防止模型训练过程中的参数过拟合,在损失函数中引入正则化项。实验结果表明,OSA和ELU函数可以有效提高深层GAE的性能,改善模型的梯度信息传递。在使用6层GCN时,基准引文数据集PubMed的链接预测任务中,深层OSA-VGAE相较于原始的VGAE在ROC曲线下的面积(AUC)和平均精度(AP)上分别提升了8.67和6.85个百分点,深层OSA-GAE相较于原始的GAE在AP和AUC上分别提升了6.82和4.39个百分点。

Effect of Shot Peening on Surface Damage Evolution Behavior of Cu-19Ni Alloy

Shot peening is a surface modification technology with the metal surface nano machine(SNC),which can modify the surface microstructure and extend the fatigue life of Cu-19Ni alloy.The hardness,damage evolution and mechanical properties were investigated and characterized by scanning electron microscope(SEM),laser confocal microscope(LSM)and material surface performance tester(CFT).The results showed that the surface roughness and friction coefficient of Cu-19Ni alloy decreased with the increase of shot peening duration and diameter,while the microhardness and strength increased.Moreover,with the increase in shot peening duration and diameter,SEM observation showed that the fracture dimples became smaller,meanwhile,with the increase of small cleavage planes,shear tearing ridges and the thickness of the surface nano layer,the fracture mode gradually evolved from plastic to brittle fracture.The uniaxial tensile test of shot peened Cu-19Ni alloy was carried out by MTS testing machine combined with digital image correlation technology(DIC).The evolution of Cu-19Ni surface damage was analyzed,and the evolution equations describing the damage of large deformation zone and small deformation zone were established.The effect of shot peening on the damage evolution behavior of Cu-19Ni alloy was revealed.

Effect of wet shot peening on Ti-6Al-4V alloy treated by ceramic beads

Ti-6Al-4V alloy was processed by wet shot peening with ceramic beads. The effects of the shot peened intensity on the microstructure, surface morphology, and residual stress were investigated. A tensile-tensile fatigue test was performed and the fracture mechanism was proposed. The results demonstrate that the surface roughness after wet shot peening is obviously lower than that after dry shot peening. With the increase of the shot peened intensity, the depth of the residual stress layer increases to 250 ktrn, and the maximum stress in this layer increases to -895 MPa. The fatigue strength also increases by 12.4% because of the wet shot peening treatment. The dislocation density of the surface layer is significantly enhanced after the wet shot peening with ceramic beads. The microstructure of the surface layer is obviously refined into ultra-fine grains.

SURFACE CHARACTERISTICS OF 10Ni3MnCuAl STEEL BY SHOT PEENING

The surface of grinding 10Ni3MnCuAl steel is processed by the shot peening with different intensities. After shot peening, the metallographic structure of 10Ni3MnCuAl steel and the micro-structure on the surface layer are analyzed. The micro-hardness in the shot peening affected layer and the residual pressure stress are surveyed. The changes of surface quality, such as micro-hardness, metallographic structure and residual stress caused by shot peening are investigated. The result shows that shot peening can significantly improve surface quality and fatigue life of 10Ni3MnCuAl steel. The over peening effect is produced when the shot peening intensity is high, and it leads to the decrease of the fatigue life. When the optimal arc high value of shot peening is 0. 40 mm in experiments, the best surface quality is obtained and the depth of the residual stress in the precipitation-hardening layer reaches 450μm.

Vacuum assisted high-pressure die casting of AZ91D magnesium alloy at different slow shot speeds

The effects of vacuum assistance on the microstructure and mechanical properties of high-pressure die cast AZ91 D alloy at different slow shot speeds were evaluated. Plate-shaped castings of AZ91 D alloy were carried out on a TOYO BD-350V5 cold chamber die casting machine incorporated with a self-improved TOYO vacuum system. It was found that the vacuum pressure in the die cavity at the beginning of mold filling increases with the increase of slow shot speed, following a cubic polynomial curve, resulting in a decline in the porosity-reduction ability of vacuum assistance with the increase of slow shot speed. The externally solidified crystal（ESC） contents in conventional and vacuum die castings behave similar against the slow shot speed. The tensile properties of vacuum die castings were strongly influenced by the ESC content at relative low slow shot speeds. With the increase of slow shot speed, the influence of the gas porosity level in vacuum die castings would get prominent.

Effect of multi-step slow shot speed on microstructure of vacuum die cast AZ91D magnesium alloy

Two multi-step （two-step and three-step） slow shot speeds were used in the vacuum die casting process of AZ91D magnesium alloy. The vacuum pressure variation in the die cavity before mold filling was monitored by using a pressure sensor. The microstructures of the produced castings were analyzed with optical microscope and image analysis software. The experimental results demonstrate that, the vacuum pressure in the die cavity at the beginning of mold filling is significantly reduced by using three-step slow shot speed, resulting in a low gas porosity level in the produced castings. At an appropriate multi-step slow shot speed, the dwell time of the liquid metal in the shot sleeve before mold filling can be reduced and the flow of the liquid metal in the shot sleeve at the later stage of the slow shot process can be restrained, which cause a low externally solidified crystal content in the produced castings.

基于B-SHOT特征和3D-NDT的点云自动配准

提出一种结合B-SHOT特征的3 D-NDT点云自动配准方法。首先分别提取两个点集的B-SHOT特征点,并且估算这些特征点的B-SHOT特征描述子,然后通过双向汉明距离估计两个点集之间的三维特征匹配点对,并利用随机采样一致性算法估计两个点集的初值转换参数,最后使用3D-NDT算法完成精确配准。实验结果表明,算法能快速精确的进行两个点云集之间的自动配准。

SHOTS模拟系统初体验

伴随着计算机技术的不断进步,与以往实物教学培训有着根本不同的模拟器培训已经在很多行业中得到了运用,致力于模拟器开发的法国Sinapse公司也开发出了适用于印刷的模拟器系统,但该模拟系统在国内的印刷行业还没有得到推广。

SHOTS系统在印刷专业教学中的应用探索

结合印刷技术专业实训操作过程中排除印刷故障耗时长、成本高及操作难度大的现状进行了深入的研究剖析,探索了应用SHOTS系统实现与传统印刷机同步模拟排除印刷故障的方式重构实训环节的总体框架,尝试和创新符合学校实际情况的实训教学模式。以真正实现“做中学、学中做”,将印刷理论与实际操作结合在一起,使学生对印刷机的操作更熟练,从而达到在提高教学效率和教学质量的同时又节约资源的目的。

SHOTS模拟培训的优势及其前景

随着计算机技术的不断进步,模拟器培训已经在各行各业中得到广泛的普及,从飞机操作到各种大型机械的培训,模拟器培训获得普遍好评。

第59届国际技术史学会(SHOT)年会综述

2016年6月22日-26日,国际技术史学会（Society for the History of Technology,SHOT）第59届年会在新加坡国立大学举行。法国哲学家和科学社会学家拉图尔（Bruno Latour）、美国技术史家露丝·史瓦兹·柯望（Ruth Schwartz Cowan）和英国爱丁堡大学社会人类学教授、本届SHOT主席白馥兰（Francesca Bray）女士,分别做了主旨报告。

一种基于ISS-SHOT特征的点云配准算法

针对点云配准过程中易产生错误对应点、收敛速度慢、配准时间长等问题,提出了一种基于内部形态描述子(ISS)及方向直方图描述子(SHOT)特征的点云配准算法。运用体素格网法下采样后,采用ISS算法提取特征点,并用SHOT对特征点进行描述,利用余弦相似度匹配对应点对,再采用RANSAC算法剔除错误对应点对,使得两片点云获得良好的初始位姿,最后采用点到平面的ICP算法进行精确配准。试验结果表明,与传统ICP算法及基于ISS的SAC-IA+ICP算法相比,本文算法配准精度及配准效率更高,对数据量大、重叠率较低点云具有很好的稳健性。

Correction of buckling distortion by ultrasonic shot peening treatment for 5A06 aluminum alloy welded structure

Ultrasonic shot peening treatment （USPT） was proposed to correct welding buckling distortion. The residual stress distribution along the depth direction of the peened zone was measured by an X-ray diffractometer. The microstructure of the treated specimens was investigated by scanning electron microscopy （SEM）. The Vickers microhardness was measured in different areas of welded joint before USPT and along the depth direction of the weld after USPT. The experimental results indicated that the welding buckling distortion of 5A06 aluminum alloy butt joint can be essentially corrected by USPT; the average correction rate reached 90.8% in this study. Furthermore, USPT enhanced specimens by work hardening. The microstructure of the peened zone was improved; moreover, the distribution of the precipitates and grains presented an apparent orientation.

基于one-shot学习的小样本植物病害识别

针对植物病害小样本问题提出一种基于one-shot学习的植物病害识别方法。以公开数据集PlantVillage中8类样本数量较少的植物病害图像作为识别对象,使用焦点损失函数(focal loss,FL)训练基于关系网络的植物病害分类器。训练过程中,调整FL超参数使模型聚焦于困难样本,从而提高植物病害识别精确率。结果表明:该方法在5-way、1-shot任务中识别精确率达到89.90%,相比原始关系网络模型精确率提高了4.69个百分点。同时,与匹配网络和迁移学习相比,改进后的方法在实验数据集上识别精确率分别提高了25.02个百分点和41.90个百分点。

技术史学会(SHOT)年会信息统计分析及启示:2000~2019年

以技术史学会(SHOT)2000~2019年年会日程信息为主要数据源,对会议基本信息进行梳理统计,包括对学者、所属机构和国家、担任重要角色次数进行排序,运用共现方法和聚类分析展示参会者及其所在机构和国家组成的网络,对标题进行词频和时段统计,以及通过对比方式量化显示中国大陆学者和学术机构在年会中的参与情况。统计结果显示了技术史学会年会逐渐增加的规模、年会网络中日趋紧密的学者社区及参会机构存在历时性变化、各国参与程度分组后逐渐递减、会议重视现当代议题等特点,为中国技术史学界的未来发展提供借鉴意义。

基于SHOT、PPF特征的遮挡目标识别研究

针对机器人无序工件分拣过程中在遮挡情况下不同外形工件识别率差异较大的问题,对全局特征描述子和局部特征描述子的描述及投票过程进行详细地分析,分别选取其中实时性较好的PPF(Point Pair Feature)和SHOT(Signature of Histograms of OrienTations)描述子在不同程度遮挡情况下使用不同外形工件进行识别实验,有针对性地对机器人无序分拣中不同外形工件适用的算法进行实验对比和总结,使在不同外形工件上的识别率达到最大化,实验结果表明:PPF全局描述子对工件点云模型的外形特征和遮挡较为敏感,特征不明显工件的识别率为0%,对于外形特征明显、无遮挡的点云模型工件识别速度较快(1 s内)且准确率较高,SHOT局部描述子对遮挡的鲁棒性较强,并且对外形特征不明显工件有一定的识别能力,特征明显与特征不明显工件的识别率均保持在90%以上。