电子支付中的密码技术应用（上）

电子支付的本质是网上电子资金流信息,必须严加安全风险防范。没有密码学就没有信息系统的安全。本文着重论述了金融界电子支付中使用的各种密码技术,其中包括了传统对称密码技术、非对称密码技术、密码杂凑函数以及数字证书、OTP等采用的密码技术。电子支付中应用了这些密码技术,确保了电子交易的安全,保障了交易支付数据的完整性、保密性、可靠性、不可否认性和可审计性。     

Adaptive fault-tolerant control of linear systems with actuator saturation and L_2-disturbances

This paper studies the problem of designing adaptive fault-tolerant H-infinity controllers for linear timeinvariant systems with actuator saturation.The disturbance tolerance ability of the closed-loop system is measured by an optimal index.The notion of an adaptive H-infinity performance index is proposed to describe the disturbance attenuation performances of closed-loop systems.New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compe...     

基于ROI多特征和相关反馈的图像检索算法

本文提出了一种基于感兴趣区域(ROI)综合多特征和相关反馈的图像检索算法.在对图像进行四叉树分解的基础上,由用户选择感兴趣区域,综合颜色、纹理和形状三种底层特征进行多层感兴趣区域检索;由相关反馈技术体现用户感知的主观性,通过调整感兴趣区域、特征问、特征内的权重来提高查准率.给出了改进的CBIR通用模型和特征权重模型.实现了一个图像检索原型系统,将不同实验结果进行了比较和分析,实验结果表明,该文提出的方法具有良好的检索效果.     

嵌入式电阻点焊控制器

本文根据ARM芯片和UC/OS-Ⅱ实时操作系统的特点,设计了一个以LPC2292为核心的嵌入式电阻点焊控制系统.该系统根据点焊控制系统的要求,分为不同的任务模块,各模块由嵌入式实时操作系统UC/OS-Ⅱ统一调度.研究表明,该嵌入式系统在提高系统实时性、可靠性及可读性的同时,降低了系统的设计周期,节省了系统开发和维护的费用.     

Blood cell counting based on U-Net++ and YOLOv5

Clinical information about a variety of disorders is available through blood cell counting, which is usually done by manual methods. However, manual methods are complex, time-consuming and susceptible to the subjective experience of inspectors. Although many efforts have been made to develop automated blood cell counting algorithms, the complexity of blood cell distribution and the highly overlapping nature of some red blood cells (RBCs) remain significant challenges that limit the improvement of analytical accuracy. Here, we proposed an end-to-end method for blood cell counting based on deep learning. Firstly, U-Net++ was used to segment the whole blood cell image into several regions of interest (ROI), and each ROI contains only one single cell or multiple overlapping cells. Subsequently, YOLOv5 was used to detect blood cells in each ROI. Specifically, we proposed several strategies, including fine classification of RBCs, adaptive adjustment for non-maximal suppression (NMS) threshold and blood cell morphology constraints to improve the accuracy of detection. Finally, the detection outcomes for each ROI were combined and superimposed. The results show that our method can effectively address the issue of high overlap and precisely segment and detect blood cells, with a 98.18% accuracy rate for blood cell counting.     

基于Conv1d-LSTM模型的能源分配预测

能源分配问题往往与其所在区域环境有关,能源分配的预测可以通过当地环境因素数据来推测之后对该区域的能源分配数值,最大程度上分配好能源. LSTM网络预测短期效果良好,但预测较长时期的数据会导致误差积累,速度慢且准确性差; Informer是近期新提出的能源预测算法模型,速度快但在该任务上预测能力不够.本文提出Conv1d-LSTM模型,预测结果优于上述两个模型,具有更低的平均绝对误差和均方根误差.     

应用引导积分梯度的对抗样本生成

给图片添加特定扰动可以生成对抗样本, 误导深度神经网络输出错误结果, 更加强力的攻击方法可以促进网络模型安全性和鲁棒性的研究. 攻击方法分为白盒攻击和黑盒攻击, 对抗样本的迁移性可以借已知模型生成结果来攻击其他黑盒模型. 基于直线积分梯度的攻击TAIG-S可以生成具有较强迁移性的样本, 但是在直线路径中会受噪声影响, 叠加与预测结果无关的像素梯度, 影响了攻击成功率. 所提出的Guided-TAIG方法引入引导积分梯度, 在每一段积分路径计算上采用自适应调整的方式, 纠正绝对值较低的部分像素值, 并且在一定区间内寻找下一步的起点, 规避了无意义的梯度噪声累积. 基于ImageNet数据集上的实验表明, Guided-TAIG在CNN和Transformer架构模型上的白盒攻击性能均优于FGSM、C&W、TAIG-S等方法, 并且制作的扰动更小, 黑盒模式下迁移攻击性能更强, 表明了所提方法的有效性.     

Label distribution learning for scene text detection

Recently, segmentation-based scene text detection has drawn a wide research interest due to its flexibility in describing scene text instance of arbitrary shapes such as curved texts. However, existing methods usually need complex post-processing stages to process ambiguous labels, i.e., the labels of the pixels near the text boundary, which may belong to the text or background. In this paper, we present a framework for segmentation-based scene text detection by learning from ambiguous labels. We use the label distribution learning method to process the label ambiguity of text annotation, which achieves a good performance without using additional post-processing stage. Experiments on benchmark datasets demonstrate that our method produces better results than state-of-the-art methods for segmentation-based scene text detection.     

三维编织复合材料紧固件剪切强度预报

建立了三维缎纹编织复合材料代表性体积单元(RVE)和紧固件剪切试件模型,引入周期性边界条件,建立了材料的宏观力学性能预报方法,并采用跨尺度计算方法对不同受载角度下的紧固件剪切破坏过程进行了有限元模拟。进行了三维缎纹编织复合材料紧固件的剪切试验,有限元计算结果与试验结果吻合较好,验证了本方法的可行性。分析了不同受载角度对剪切破坏模式及强度的影响,结果表明,该编织复合材料剪切强度随受载角度增大而降低,且具有不同的损伤起始位置和扩展过程。     

DES加密算法在秘密共享中的应用

秘密共享思想提出后,经过几十年的发展已经出现了很多不同方案、模型等。本文根据秘密共享的特性提出了一种基于对称密钥系统的秘密共享方案。该方案解决了一些秘密共享现有的问题的,尤其是可验证性。存储在密钥分发者的信息都是加密后的密文,因此,其抗攻击的强度就是使用的加密算法的强度。通过简单C＋＋程序实现这一方案。对方案的可行性进行分析。