An inverse problem for non-selfadjoint Sturm–Liouville operator with discontinuity conditions inside a finite interval

This paper is concerned with the inverse problem for non-selfadjoint Sturm–Liouville operator with discontinuity conditions inside a finite interval. Firstly, we give the definitions of generalized weight numbers for this operator which may have the multiple spectrum and then investigate the connections between the generalized weight numbers and other spectral characteristics. Secondly, we obtain the generalized spectral data, which consists of the generalized weight numbers and the spectrum. Then the operator is determined uniquely by the method of spectral mappings. Finally, we give an algorithm for reconstructing the potential function and the coefficients of the boundary conditions and the coefficients of the discontinuity conditions.     

New approach to identify the initial condition in degenerate hyperbolic equation

This paper deals with the determination of an initial condition in degenerate hyperbolic equation from final observations. With the aim of reducing the execution time, this inverse problem is solved using an approach based on double regularization: a Tikhonov’s regularization and regularization in equation by viscose-elasticity. So, we obtain a sequence of weak solutions of degenerate linear viscose-elastic problems. Firstly, we prove the existence and uniqueness of each term of this sequence. Secondly, we prove the convergence of this sequence to the weak solution of the initial problem. Also we present some numerical experiments to show the performance of this approach.     

薄壁弱刚性钛合金结构件制造工艺

随着新型材料冶金技术的发展与进步,钛合金作为“崛起的第三代金属”已完全替代了铝镁合金和钢构件,成为航天飞行器上应用范围最广的材料之一。从某新研制航天飞行器外部结构件用钛合金材料的特性及切削特点入手,针对薄壁弱刚性钛合金结构件在实际加工过程中遇到的诸多难点,提出了相应的解决办法,并重新设计了零件工装。结果表明,改进措施不仅保证了零件质量,而且提高了零件加工效率,使单件零件的生产周期缩短了近10h。     

The analysis for morphological evolution and crystallography of degenerate pearlite in 100Mn13 steel

During approximate 773 K aging treatment of 100Mn13 steel, degenerate pearlite will occur and evolve into lamellar pearlite during growth process. The microstructures of degenerate pearlite and its evolutionary lamellar pearlite are observed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The results show that after 748 K, 773 K and 798 K aging, degenerate pearlites occur at grain boundary. At growth front of degenerate pearlite forming at 773 K and 798 K, pearlite presents a morphology of short lamellae of carbide and ferrite, indicating a trend of developing into lamellar pearlite. The higher the temperature is, the more obvious the trend is, and even a conventional lamellar pearlite has developed. However, there is no morphological evolution for degenerate pearlite forming at 748 K aging. Besides, the constituents of degenerate pearlite is identified as M₂₃C₆ and ferrite, and Kurdjumov-Sachs orientation relationship exists between them, (01 )_α//( 1 )_M23C6, [111]_α//[110]_M23C6. This orientation relationship maintains in morphological evolution from degenerate pearlite to lamellar pearlite.     

一种“KooN”结构的马尔可夫简并建模和简化计算的方法

IEC61508等标准提出了几种计算安全仪表系统需求时平均失效概率的方法,但是,对于具有冗余配置的复杂系统,随着组件数量的增加,系统的中间状态数量快速增长,用户难以构建马尔可夫模型,即便借助计算机来建模运算也较为耗时。提出了一种同型“K oo N”简并状态的马尔可夫建模的通用方法,首先是根据降级状态进行判断,将符合条件的状态进行简并,然后对标记为危险失效状态的概率进行计算。通过严格的理论推导,该简并状态方法可以在不损失精度的前提下简化马尔可夫建模。     

深度学习背景下视觉显著性物体检测综述

视觉显著性物体检测是对人类视觉和认知系统的模拟,而深度学习则是对人类大脑计算方式的模拟,将两者有机结合可以有效推动计算机视觉的发展。视觉显著性物体检测的任务是从图像中定位并提取具有明确轮廓的显著性物体实例。随着深度学习的发展,视觉显著性物体检测的精度和效率都得到巨大提升,但仍然面临改进主流算法性能、减少对像素级标注样本的依赖等主要挑战。针对上述挑战,本文从视觉显著性物体检测思想与深度学习方法融合策略的角度对相关论述进行分类总结。1）分析传统显著性物体检测方法带来的启示及其缺点,指出视觉显著性物体检测的核心思路为多层次特征的提取、融合与修整;2）从改进特征编码方式与信息传递结构、提升边缘定位精度、改善注意力机制、提升训练稳定性和控制噪声的角度对循环卷积神经网络、全卷积神经网络和生成对抗网络3种主流算法的性能提升进行分析,从优化弱监督样本处理模块的角度分析了减少对像素级标注样本依赖的方法;3）对协同显著性物体检测、多类别图像显著性物体检测以及未来的研究问题和方向进行介绍,并给出了可能的解决思路。     

基于二次聚类弱监督学习的图像语义分割

针对在给定大量用户标注图像基础上,将图像分割成一系列具有单一语义的完整区域,并同时对各区域实现语义标注的问题,提出了一种基于弱监督学习的二次聚类的图像语义分割算法。将谱聚类和判别式聚类相结合,用谱聚类学到的类标指示函数来指导判别式聚类,学习特征的潜在数据结构,利用弱监督信息对聚类分配标签。该方法能够充分利用区域上下文信息,为每个类别选择判别式特征,并且输出鲁棒的多类分类器,对外来没有标签的图像也可以进行有效的区域标注。通过在公用数据集上的充分实验,证明了本方法的有效性。     

数字化车间多源异构质量数据集成方案研究

针对数字化制造中多源异构质量数据信息量大且缺乏统一、规范和标准化数据管理的问题,提出一种基于面向对象技术和基于映像的数据抽取、转换和加载(Extract-Transform-Load,ETL)技术的异构数据集成方案,该方案简单实用,具有很高的通用性,可提高异构数据的提取精度,有效地解决多源异构质量数据集成问题。