一种基于规范的可信协同系统分析设计框架

针对可信协同系统分析建模与设计问题,提出了RBN-T模型,分析了模型中的可信保障机制及策略.提出了基于RBN-T模型的可信协同系统分析建模过程,以具体的实例说明了RBN-T模型在可信协同系统分析建模与设计上的可用性.RBN-T模型把基于角色的规范管理提升到适合可信协同系统分析建模与设计的层次,从而有利于在协同系统开发的早期阶段就关注可信问题.     

基于系统动力学的环境污染演化博弈问题研究

用系统动力学建立环境污染管理问题中政府管理部门与生产排污企业之间的一个混合战略演化博弈模型.仿真结果表明:非对称结构的2*2混合策略演化博弈模型不存在演化均衡.从监管部门的角度出发,改变博弈支付矩阵在演化博弈过程始终保持不变的情况,在博弈支付矩阵中考虑动态惩罚策略.结果表明,本策略的演化博弈模型存在演化稳定均衡,即Nash均衡.系统动力学为演化博弈理论的验证和应用提供一个政策仿真实验平台.     

基于位承诺的数字证书敏感信息保护

目前数字证书缺少敏感信息保护机制,容易泄露用户的隐私信息.针对数字证书的敏感信息泄露问题,采用基于单向函数的位承诺协议实现数字证书中敏感信息的隐藏和选择性披露,详细讨论了基于位承诺的证书申请、证书颁发及证书查询验证过程,并分析了位承诺协议的安全性和效率.     

引入趋近律的功率因数校正滑模控制仿真研究

提出一种引入趋近律的滑模变结构控制(SMVSC)方法来实现有源功率因数校正(APFC),减少电流的谐波成分.SMVSC是一种解决非线性时变系统(如APFC系统)问题的良好办法,但是实际应用中SMVSC的"抖振"现象问题必须要解决好.引入趋近律来削弱APFC系统在滑模控制中的"抖振"现象,并且依此推导出了控制APFC系统中的功率开关的PWM占空比.采用Matlab平台进行仿真验证控制策略控制APFC电路几乎得到单位功率因数,同时超调减小、响应时间缩短.     

Research on wind turbine blade damage based on pre-stressed FBG strain sensors

One of the essential parts of a wind power generator that captures wind energy is the wind turbine blade. The safety of the blades rapidly declines as a wind turbine''s operating period grows. For real-time monitoring, a chip-type pre-stressed fiber Bragg grating (FBG) strain sensor was fabricated. The sensor''s structure was improved using simulation analysis along with optimization. It was discovered through calibration trials that the pre-stressing method expanded the sensor''s range of measurement, guaranteed overall linearity, and prevented the potential hysteresis phenomena during compression. The sensor''s final sensitivity was calculated to be 1.970 pm/με, and its linear fitting coefficient was 0.999. Finally, the sensor was used to monitor the wind turbine blades and the strain change curve of the root of a normally functioning blade is found to be a sine curve, which provides a certain reference value for judging whether the blade is damaged in the future.     

Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution

The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR) algorithms applied to CT images to improve the resolution of CT images. However, most of the existing SR algorithms are studied based on natural images, which are not suitable for medical images; and most of these algorithms improve the reconstruction quality by increasing the network depth, which is not suitable for machines with limited resources. To alleviate these issues, we propose a residual feature attentional fusion network for lightweight chest CT image super-resolution (RFAFN). Specifically, we design a contextual feature extraction block (CFEB) that can extract CT image features more efficiently and accurately than ordinary residual blocks. In addition, we propose a feature-weighted cascading strategy (FWCS) based on attentional feature fusion blocks (AFFB) to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature information. Finally, we suggest a global hierarchical feature fusion strategy (GHFFS), which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various levels. Numerous experiments show that our method performs better than most of the state-of-the-art (SOTA) methods on the COVID-19 chest CT dataset. In detail, the peak signal-to-noise ratio (PSNR) is 0.11 dB and 0.47 dB higher on CTtest1 and CTtest2 at SR compared to the suboptimal method, but the number of parameters and multi-adds are reduced by 22K and 0.43G, respectively. Our method can better recover chest CT image quality with fewer computational resources and effectively assist in COVID-19.     

Dynamically modulated intensity interrogation scheme using waveguide coupled surface plasmon resonance sensors

An electro-optically modulated intensity interrogation method based on tunable waveguide coupled surface plasmon resonance sensors has been proposed. It has been theoretically and experimentally demonstrated that the proposed scheme can enable sensitive measurement of measurand variations. By modulating the refractive index in the waveguide layer, this interrogation method yields modulated signal whose amplitude is related to measurand's refractive index. This amplitude modulated signal offers a higher signal to noise ratio and eliminates additive noise in the sensor system. A preliminary investigation using saline buffers with different NaCl concentrations shows a resolution of 2.3 × 10^?6 refractive index unit by our approach. Resolution can be controlled by the amplitude of the applied modulation voltage and can be further enhanced by optimizing the device structure or improving the electro-optical (E-O) coefficient of the E-O material. This approach is simple, stable, and promising for low-cost or multi-channel SPR biosensor applications.     

基于混沌序列的RFID安全加密机制

针对现有RFID系统读写器和标签之间通信安全性低、易受到各种攻击的安全问题,介绍基于Logistic混沌序列的动态实时密钥方法,提出一种基于混沌序列RFID的安全加密机制,采用动态实时密钥对RFID系统中的读写器与电子标签通信消息进行加密。仿真实验结果表明,该方法能够解决RFID系统中非法存取、伪造哄骗、数据泄露、位置跟踪等安全问题。     

一种可视二维条码设计

融合信息隐藏与二维条码编译码技术,提出一种基于图像的可视二维条码设计。对图像进行块误差扩散,得到的半色调图像作为码图,将编码块嵌入置乱后的码图,反置乱使编码块分散在码图中。与以往提出的图像条码相比,该设计注重图像的可视性,可以表达图像信息。实验结果表明,该设计效果较好。