图像边缘检测在DM642上的应用研究

采用TMS320DM642EVM作为数字图像处理硬件平台,利用CCS开发环境来构建程序并对其进行优化;通过对改进后的Log算子和小波多尺度方法提取到的边缘图像进行数据融合,得到一幅新的边缘图像。实验结果表明,该方法提高了边缘检测的运算速度,满足了实时性要求;并能有效地抑制噪声的影响,保留了图像边缘细节。     

基于日志恢复技术的内存数据库快速恢复模型的研究

在研究已有恢复技术的基础上,提出了"快速恢复模型".该模型依据快速日志驱动检查点算法、重栽算法.以及模型架构上的支持,不仅能保证系统的可靠运行,同时能在系统崩溃时提供快速、高效的恢复系统的手段.通过实验证明,该方法相对于其他恢复方法,能控制日志的产生数量,使得在系统崩溃并重新启动时,能以最快的速度恢复到系统崩溃前的最近一致点上.     

面向Java语言生态的软件供应链安全分析技术

随着开源软件技术的不断发展,为提高开发效率并降低人力成本,组件化开发模式逐渐得到行业的认可,开发人员可以利用相关工具便捷地使用第三方组件,也可将自己开发的组件贡献给开发社区,从而形成了软件供应链.然而,这种开发模式必然会导致高危漏洞随组件之间的依赖链条扩散到其他组件或项目,从而造成漏洞影响的扩大化,例如2021年底披露的Log4j2漏洞,通过软件供应链对Java生态安全造成了巨大影响.当前针对Java语言软件供应链安全的分析与研究大多是对组件或项目进行抽样调研,这忽略了组件或项目对整个开源生态的影响,无法精准衡量其对生态所产生的影响.为此,本文针对Java语言生态软件供应链安全分析技术展开研究,首次给出了软件供应链安全领域的组件依赖关系和影响力等重要指标的形式化定义,并依据此提出了基于索引文件的增量式组件配置收集和基于POM语义的多核并行依赖解析,设计实现了Java开源生态组件依赖关系提取与解析框架,收集并提取超过880万个组件版本和6500万条依赖关系.在此基础上,本文以受到漏洞影响的日志库Log4j2为例,全面评估其对生态的影响以及修复比例,结果表明该漏洞影响了生态15.12%的组件(71082个)以及16.87%的组件版本(1488971个)同时仅有29.13%的组件在最新版本中进行了修复.     

Web应用日志分析系统分析与设计

互联网的蓬勃发展为生活、学习、工作提供了诸多便利,但随之而来的网络安全隐患日趋明显.应用日志分析作为一种重要的信息安全保障措施,有效地弥补了传统安全防御技术的缺陷.主要分析了传统日志分析的常用方法,并在此基础上,提出了一种新的日志读取方法和模式匹配算法.通过测试表明,这些改进对提高日志的分析效率起到了积极效果.     

An MRAS method for sensorless control of induction motor over a wide speed range

This paper addresses the problem of wide speed range sensorless control of induction motor.The proposed method is based on model reference adaptive system (MRAS),in which the current model serves as the adjustable model,and a novel hybrid model integrating the modified voltage model (MVM) and high-frequency signal injection method (HFSIM) are established to serve as the reference model.The HFSIM works together with MVM to improve the performance of the rotor speed and rotor flux position estimation at low speed,whereas at high speed,the MVM acts alone.In addition,a rotor resistance online estimation scheme is proposed to update the rotor resistance contained in the adjustable model and to ensure the estimation accuracy further.Experimental results show that the proposed MRAS method is very effective from low to high speed range,including zero speed.     

Dual-key-binding cancelable palmprint cryptosystem for palmprint protection and information security

Biometric cryptosystems and cancelable biometrics are both practical and promising schemes to enhance the security and privacy of biometric systems. Though a number of bio-crypto algorithms have been proposed, they have limited practical applicability because they lack of cancelability. Since biometrics are immutable, the users whose biometrics are stolen cannot use bio-crypto systems anymore. Cancelable biometric schemes are of cancelability; however, they are difficult to compromise the conflicts between the security and performance. By embedded a novel cancelable palmprint template, namely “two dimensional (2D) Palmprint Phasor”, the proposed palmprint cryptosystem overcomes the lack of cancelability in existing biometric cryptosystems. Besides, the authentication performance is enhanced when users have different tokens/keys. Furthermore, we develop a novel dual-key-binding cancelable palmprint cryptosystem to enhance the security and privacy of palmprint biometric. 2D Palmprint Phasor template is scrambled by the scrambling transformation based on the chaotic sequence that is generated by both the user's token/key and strong key extracted from palmprint. Dual-key-binding scrambling not only has more robustness to resist against chosen plain text attack, but also enhances the secure requirement of non-invertibility. 2D Palmprint Phasor algorithm and dual-key-binding scrambling both increase the difficulty of adversary's statistical analysis. The experimental results and security analysis confirm the efficiency of the proposed scheme.     

Transient model of induction machine using rotating magnetic field approach

Most simulation models of electric machines use the coupled circuit approach, where the machine is considered as an electric circuit element with time-varying inductances (abc model) or with constant inductances (dq0 model). On the other hand, the rotating magnetic field approach, which considers the electric machine as two groups of windings producing rotating magnetic fields and can give insight into internal phenomena of the machines, has not yet received much attention in electric machines modeling, especially for machine transient analysis. Based on the rotating magnetic field approach, this paper presents a transient model of the induction machine including main flux saturation effect. Based on the direct computation of the magnetizing fluxes of all machine windings, the model represents instantaneous main flux saturation by simply introducing a main flux saturation factor. No iteration process is involved to incorporate the saturation effects. The model combines the advantages of the dq0 and abc models advantages, such as rapid computation time and nonsymmetrical conditions simulation, respectively. The simulation results and the experimental tests show advantages and verification of the model.     

双馈异步发电机滞环矢量控制策略的研究

根据双馈异步发电机的运行特点,推导出了其在静止参考坐标系中的数学模型,采用定子磁链定向的矢量控制技术,并结合滞环电流控制技术,提出了一种新的转子励磁控制策略。利用Matlab仿真软件建立双馈异步发电机的仿真模型,对有功和无功功率的解耦进行了仿真研究。仿真结果表明,该控制策略能够实现双馈发电机有功功率和无功功率的独立解耦控制。     

Fuzzy clustering of time series in the frequency domain

Traditional and fuzzy cluster analyses are applicable to variables whose values are uncorrelated. Hence, in order to cluster time series data which are usually serially correlated, one needs to extract features from the time series, the values of which are uncorrelated. The periodogram which is an estimator of the spectral density function of a time series is a feature that can be used in the cluster analysis of time series because its ordinates are uncorrelated. Additionally, the normalized periodogram and the logarithm of the normalized periodogram are also features that can be used. In this paper, we consider a fuzzy clustering approach for time series based on the estimated cepstrum. The cepstrum is the spectrum of the logarithm of the spectral density function. We show in our simulation studies for the typical generating processes that have been considered, fuzzy clustering based on the cepstral coefficients performs very well compared to when it is based on other features.     

Induction motor fault detection and diagnosis using a current state space pattern recognition

In the last few decades the continuous monitoring of complex dynamic systems has become an increasingly important issue across diverse engineering areas. This paper presents a pattern recognition based system that uses visual-based efficient invariants features for continuous monitoring of induction motors. The procedures presented here are based on the image identification of the 3-D current state space patterns that allow the identification of distinct fault types and, furthermore, their corresponding severity. This automatic fault detection system deals with time-variant electric currents and is based on the identification of three-phase stator currents specified patterns. Several simulation and experimental results are also presented in order to verify the effectiveness of the proposed methodology.