TiAl合金冷却相变研究进展及细晶组织调控

TiAl合金是目前航空航天轻质高温结构的热点材料,其最终显微组织很大程度上决定于其冷却过程。由于TiAl合金相图和相变的复杂性,通过冷却过程控制,获得细晶组织结构成为关注的重要问题。综述了TiAl合金冷却相变的研究成果,并给出了关于Ti-48Al-4Nb-2Cr合金相关的进展:首先介绍了TiAl合金的凝固路径与相变行为,然后分别分析了连续冷却转变(CCT)和等温冷却转变(TTT)行为。进一步建立了Ti-48Al-4Nb-2Cr合金CCT图,并指导获得了一种细晶近片层组织。     

广西化学选锰研究的进展

文章介绍广西化学选锰研究在处理难过矿石、综合回收和废酸利用等方面的进展．     

SWS-DAN: Subtler WS-DAN for fine-grained image classification

Currently, weakly supervised data augmentation network (WS-DAN) has been proved to be one of the state-of-the-art methods for fine-grained image classification due to its effectiveness on attention-guided data augmentation and bilinear attention pooling. Taking WS-DAN as the backbone, in this paper, we further propose a subtler WS-DAN recognition network, namely, SWS-DAN. Specifically, we first construct a novel “salience-guided data augmentation” scheme composed of cutblock, part-aware cropping, and SCutMix operations, which can more effectively expand the number of training dataset and improve the weakness addressed in the data augmentation procedure of WS-DAN. Meanwhile, the novel data-augmentation manner reduces background noise and mines more discriminative regions simultaneously, thereby avoiding the overfitting. In caring about the key issue in fine-grained image classification task is how to distinguish the extremely similar subclasses (e.g., Artic Tern, Elegant Tern, and Forsters Tern), we then design a “Top-k” loss function that mainly focuses on the similar classes so as to find their extraordinary subtle differences. Extensive experiments carried out on common fine-grained image datasets demonstrate that SWS-DAN can surpass WS-DAN with a significant margin in the classification performance.     

Conditional generative adversarial network for EEG-based emotion fine-grained estimation and visualization

In the field of affective computing (AC), coarse-grained AC has been developed and widely applied in many fields. Electroencephalogram (EEG) signals contain abundant emotional information. However, it is difficult to develop fine-grained AC due to the lack of fine-grained labeling data and suitable visualization methods for EEG data with fine labels. To achieve a fine mapping of EEG data directly to facial images, we propose a conditional generative adversarial network (cGAN) to establish the relationship between EEG data associated with emotions, a coarse label, and a facial expression image in this study. In addition, a corresponding training strategy is also proposed to realize the fine-grained estimation and visualization of EEG-based emotion. The experiments prove the reasonableness of the proposed method for the generation of fine-grained facial expressions. The image entropy of the generated image indicates that the proposed method can provide a satisfactory visualization of fine-grained facial expressions.     

Effect of Compression with Oscillatory Torsion Processing on Structure and Properties of Cu

The results presented in this study were concerned with microstructures and mechanical properties of polycrystalline Cu subjected to plastic deformation by a compression with oscillatory torsion process. Different deformation parameters of the compression with oscillatory torsion process were adopted to study their effects on the microstructure and mechanical properties. The deformed microstructure was characterized quantita- tively by electron backscattered diffraction (EBSD) and scanning transmission electron microscopy (STEM). Mechanical properties were determined on an MTS QTest/10 machine equipped with digital image correlation. From the experimental results, processes performed at high compression speed and high torsion frequency are recommended for refining the grain size. The size of structure elements, such as average grain size (D) and subgrain size (d), reached 0.42 μm and 0.30 μm, respectively, and the fraction of high angle boundaries was 35% when the sample was deformed at a torsion frequency f = 1.6 Hz and compression rate v = 0.04 mm/s. These deformation parameters led to an improvement in the strength properties. The material exhibited an ultimate tensile strength (UTS) of 434 MPa and a yield strength (YS) of 418 MPa. These values were about two times greater than those of the initial state.     

Light-Weight Selective Image Encryption for Privacy Preservation

To protect personal privacy and confidential preservation, access control is used to authorize legal users for safe browsing the authorized contents on photos. The access control generates an authorization rule according to each permission assignment. However, the general access control is inappropriate to apply in some social services (e.g., photos posted on Flickr and Instagram, personal image management in mobile phone) because of the increasing popularity of digital images being stored and managed. With low maintenance loads, this paper integrates the data hiding technique to propose an access control mechanism for privacy preservation. The proposed scheme changes the partial regions of a given image as random pads (called selective image encryption) and only allows the authorized people to remedy the random pads back to meaningful ones which are with similar visual qualities of original ones.     

云计算中基于属性的可搜索加密电子病历系统

电子病历是医学报告在云计算技术迅速发展下的一个重要产物,它的出现方便了医院和患者对病历的管理。然而, 患者的相关隐私数据存储在云上,就必然面临着隐私泄露、非法访问等隐患。为保护存储在云端的电子病历数据的私密性,提出了一个基于属性的可搜索加密方案,并给出了它在电子病历系统中的重要应用。与传统的可搜索加密方案相比,本方案降低了多用户环境下密钥管理的难度,且方案中的陷门可以在非安全信道上传输。此外,该方案可隐藏访问结构,具有细粒度访问控制,可根据数据拥有者的请求增加或撤销用户的访问权限。安全性分析表明,该方案保护了关键词的隐私性,可抵抗关键词猜测攻击,能有效防止隐私数据的泄露。关键词陷门匹配算法仅需一次双线性对运算,大大提高了搜索效率。     

基于属性加密的气象云数据访问控制策略研究

随着气象业务水平的不断提高,气象数据的云存储和即时共享问题也日益突出。针对云计算环境下气象数据存储与共享面临的身份认证和访问控制问题,提出了一种基于多方授权的属性加密的访问控制模型。该模型采用一种适合云环境下大数据的属性加密方案,解决了气象部门用户多类性情况下的资料细粒度访问控制问题,同时引入全局ID概念和多方授权机制,解决了不同机构用户在气象部门各资料存储机构间的访问权限问题。系统具有较高的安全性和良好的实用价值。     

Cloud based data sharing with fine-grained proxy re-encryption

Conditional proxy re-encryption (CPRE) enables fine-grained delegation of decryption rights, and has many real-world applications. In this paper, we present a ciphertext-policy attribute based CPRE scheme, together with a formalization of the primitive and its security analysis. We demonstrate the utility of the scheme in a cloud deployment, which achieves fine-grained data sharing. This application implements cloud server-enabled user revocation, offering an alternative yet more efficient solution to the user revocation problem in the context of fine-grained encryption of cloud data. High user-side efficiency is another prominent feature of the application, which makes it possible for users to use resource constrained devices, e.g., mobile phones, to access cloud data. Our evaluations show promising results on the performance of the proposed scheme.     

融合双重权重机制和图卷积神经网络的微博细粒度情感分类

利用深度学习模型和注意力机制对微博文本进行细粒度情感分类,已成为研究的热点,但是现有注意力机制只考虑单词对单词的影响,对单词本身的多种维度特性(如词义、词性、语义等特征信息)缺乏有效的融合.为了解决这个问题,文中提出了一种双重权重机制WDWM(Word and Dimension Weight Mechanism),并...