基于模糊负反馈算法的可演化安全策略研究

在分析现有访问控制策略研究的基础上,基于模糊负反馈算法,创建一个安全策略可演化的访问控制系统。通过对角色、权限以及安全策略的模糊化处理及分析。给出安全策略的描述方法,定义安全偏序关系。并在此基础上给出安全策略调整的方法,探讨算法调整时机。对用户的访问权限进行判断。在此基础上引入控制论的负反馈原理,对安全策略进行求精、演化,并通过实验初步验证算法的效果。     

一种基于Diameter协议的NAS模型

随着日益复杂的路由器和网络接入服务器大量投入使用,使得当前AAA协议在安全性和稳定性上的缺点日益明显。基于Diameter、EAP和PANA协议,设计了一个础诅接入服务器模型。该模型覆盖了Diameter NASREQ应用和EAP应用、PANA协议中PAA和EP的功能,以及EAP协议中认证者的功能。对原型系统进行了系统测试,测试结果表明,原型系统基本实现了Diameter、EAP和PANA协议对网络接入服务器的要求,具有较好的安全性和稳定性。     

基于.NET的数据访问基类的构建

为提高数据库应用程序的设计效率,基于VS.NET开发平台,利用ADO.NET的强大数据访问功能,设计了抽象的数据访问基类。主要通过代码的方式阐述了整个基类的创建过程,并重点介绍了创建存储过程参数的操作方法,在调用存储过程中,通过方法重载实现不同的数据库操作。利用该类并结合存储过程的优势构造数据服务层,统一整个系统的数据操作入口,提高开发效率,便于系统的升级、维护和移植。     

多元线性回归分析在机组发电耗水率中的应用

多元线性回归分析是一个有广泛适用性的多元统计分析方法。本文利用葛洲坝发电站的部分数据,对葛洲坝发电站一段时间内的库水位、出库流量及其对应的机组耗水率利用多元线性回归进行建模分析。显然,对这个问题的深入研究,可以有效地认识各种因素对机组发电耗水率的影响程度,从而可以更好地对机组发电耗水率进行预测。     

平流层通信平台MAC层的调度方案建模及仿真

平流层升空平台能够满足可提供战时服务、能快速部署,适用于区域性覆盖.为满足平台支持的多用户、多优先权、综合业务的接入策略并解决资源动态分配问题.提出了一种可以满足平台MAC层的服务质量(QoS)和动态带宽分配的调度架构,架构包括移动中心站(MCS)对移动站(MS)的带宽分配和移动站内上行业务的二级带宽调度架构,并根据不同业务需求采用不同的调度算法.仿真结果表明:调度方案能很好的满足所有类型业务的服务质量需求.并提供了较好的公平性,保证了架构的可行性.     

Characterizing the role of Weibo and WeChat in sharing original information in a crisis

Strategically differentiated managerial evidence of different social media platforms is of great importance to enhance crisis communication processes by balancing their strengths and weaknesses. This study aims to uncover the platform-specific situational information-sharing characteristics by differentiating the major types of information published in Weibo and WeChat during different phases of a crisis. The subject of the study is the Changsheng fake vaccine crisis which happened in China in 2018. Multiple supervised machine learning and topic modelling methods are used for the characterization of situational information types of the crisis during three phases in both platforms. Our study found that WeChat shares more situational information such as notifications, caution and advice, and criticizing information, whereas Weibo shares more emotional support and help-seeking information. This study provides social media analytics and empirical evidence of platform-specific situational information-sharing characteristics to aid authorities/researchers for better crisis communication and public emergency management.     

Event-triggered control for stochastic systems with multiple delays

This paper investigates the stabilization problem for continuous-time stochastic systems with multiple delays under continuous event-triggered mechanisms, of which both static case and dynamic case are considered individually. In order to avoid zeno phenomenon in every sample path, a suspension time after each successful execution is forced for our event-triggered mechanisms, resulting in intermittent detection of system states. Under such control strategy, we deduce mean square exponential stability of stochastic systems with multiple delays by means of Hanalay-type inequality and obtain a delay-dependent-based and less-conservative stabilization criterion without involving the upper bound of time delays. Besides, a co-design procedure is proposed for linear controller and event-triggered mechanisms. In the end, an illustrative example is presented to show effectiveness of the proposed co-design procedure and contrasts the system performance under static and dynamic event-triggered mechanisms.     

混响噪声下声源定位与跟踪的多特征自适应IMM粒子滤波算法EI北大核心CSCD

针对混响噪声下声源定位精度低和鲁棒性弱等问题,提出了多特征自适应IMM粒子滤波算法.该算法以麦克风接收信号的多特征作为观测信息,采用空时相关和迭代滤波建立了时延选择机制和波束输出能量优化机制,并在两者的基础上构建了似然函数以获得合理的声源位置信息.考虑到说话人运动的随机性,给出了自适应IMM算法,通过在线粒子集生成并将不同过程方差的模型进行交互来拟合说话人的不同运动模式,改善了说话人跟踪系统的稳健性.仿真和实测结果表明,所提算法利用了多特征定位信息的互补性,降低了观测误差不确定性对声源位置估计的影响,增强了随机运动声源跟踪系统的鲁棒性,提高了系统的定位精度.     

Teachers cooperation: team-knowledge distillation for multiple cross-domain few-shot learning

Although few-shot learning (FSL) has achieved great progress, it is still an enormous challenge especially when the source and target set are from different domains, which is also known as cross-domain few-shot learning (CD-FSL). Utilizing more source domain data is an effective way to improve the performance of CD-FSL. However, knowledge from different source domains may entangle and confuse with each other, which hurts the performance on the target domain. Therefore, we propose team-knowledge distillation networks (TKD-Net) to tackle this problem, which explores a strategy to help the cooperation of multiple teachers. Specifically, we distill knowledge from the cooperation of teacher networks to a single student network in a meta-learning framework. It incorporates task-oriented knowledge distillation and multiple cooperation among teachers to train an efficient student with better generalization ability on unseen tasks. Moreover, our TKD-Net employs both response-based knowledge and relation-based knowledge to transfer more comprehensive and effective knowledge. Extensive experimental results on four fine-grained datasets have demonstrated the effectiveness and superiority of our proposed TKD-Net approach.     

Adaptive Particle Swarm Optimization Data Hiding for High Security Secret Image Sharing

The main aim of this work is to improve the security of data hiding for secret image sharing. The privacy and security of digital information have become a primary concern nowadays due to the enormous usage of digital technology. The security and the privacy of users’ images are ensured through reversible data hiding techniques. The efficiency of the existing data hiding techniques did not provide optimum performance with multiple end nodes. These issues are solved by using Separable Data Hiding and Adaptive Particle Swarm Optimization (SDHAPSO) algorithm to attain optimal performance. Image encryption, data embedding, data extraction/image recovery are the main phases of the proposed approach. DFT is generally used to extract the transform coefficient matrix from the original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtaining the encrypted image by data-hider, additional data embedding is formulated into high-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the image for secret bits concealment. In addition, the secret data embedding capacity enhancement is focused on image visual quality maintenance. Hence, it is observed from the simulation results that the proposed SDHAPSO technique offers high-level security outcomes with respect to higher PSNR, security level, lesser MSE and higher correlation than existing techniques. Hence, enhanced sensitive information protection is attained, which improves the overall system performance.