基于SHA512哈希函数和Rijndael加密算法QR二维码信息安全设计

随着二维码技术广泛应用于电子票务、银行支票、电子保单等多个领域,二维码的信息泄露和信息篡改等安全问题日益突出。为提高二维码内部信息的安全性能,从对二维码内部信息加密和二维码信息防篡改俩个角度来提高。基于Visual Studio 2008 C#平台,设计了一种采用SHA512哈希函数和Rijndael加密算法混合加密的方法,该方法利用Rijndael加密和SHA512数字签名等技术,对Rijndael第一次加密密钥系统随机分配,并对系统随机分配密钥采用二次Rijndael加密防护方法,并通过SHA512对二维码内部信息防篡改校验,达到对二维码信息及其加密密钥的安全保护。在生成QR二维码之前实现了信息加密,并从系统构架、算法原理和实现及安全性能等多个方面进行了测试和分析。分析表明此方法提高了二维码信息的安全性能,达到对密钥高效管理和对信息的多重保护,而在加密后密文信息容量较明文信息有所增加。     

Iterative learning control for a class of mixed hyperbolic-parabolic distributed parameter systems

This paper deals with the problem of iterative learning control algorithm for a class of mixed distributed parameter systems. Here, the considered distributed parameter systems are composed of mixed hyperbolic-parabolic partial differential equations. The domain of the system is divided into two parts in which the system is hyperbolic and parabolic, respectively, with transmission conditions at the interface. According to the characteristics of the systems, iterative learning control laws are proposed for such mixed hyperbolic-parabolic distributed parameter systems based on P-type learning scheme. Using the contraction mapping method, it is shown that the scheme can guarantee the output tracking errors on L ² space converge along the iteration axis. A simulation example illustrates the effectiveness of the proposed method.     

A novel color image watermarking scheme in nonsampled contourlet-domain

Geometric distortion is known as one of the most difficult attacks to resist, for it can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust color image watermarking scheme against geometric distortions. Based on the support vector regression (SVR) and nonsubsampled contourlet transform (NSCT), we propose a new color image watermarking algorithm with good visual quality and reasonable resistance toward geometric distortions in this paper. Firstly, the geometrically invariant space is constructed by using color image normalization, and a significant region is obtained from the normalized color image by utilizing the invariant centroid theory. Then, the NSCT is performed on the green channel of the significant region. Finally, the digital watermark is embedded into host color image by modifying the low frequency NSCT coefficients, in which the HVS masking is used to control the watermark embedding strength. In watermark detection, according to the high correlation among different channels of the color image, the digital watermark can be recovered by using SVR technique. Experimental results show that the proposed color image watermarking is not only invisible and robust against common image processing operations such as filtering, noise adding, and JPEG compression etc., but also robust against the geometrical distortions.     

Decentralized iterative learning control for large-scale interconnected linear systems with fixed initial shifts

This paper deals with the problem of iterative learning control for large-scale interconnected linear systems in the presence of fixed initial shifts. According to the characteristics of the systems, iterative learning control laws are proposed for such large-scale interconnected linear systems based on the PD-type learning schemes. The proposed controller of each subsystem only relies on local output variables without any information exchanges with other subsystems. Using the contraction mapping method, we show that the schemes can guarantee the output of the system converges uniformly to the corresponding output limiting trajectory over the whole time interval along the iteration axis. Simulation examples illustrate the effectiveness of the proposed method.     

IBPSO-Based MUSIC Algorithm for Broken Rotor Bars Fault Detection of Induction Motors

In spectrum analysis of induction motor current, the characteristic components of broken rotor bars (BRB) fault are often submerged by the fundamental component. Although many detection methods have been proposed for this problem, the frequency resolution and accuracy are not high enough so that the reliability of BRB fault detection is affected. Thus, a new multiple signal classification (MUSIC) algorithm based on particle swarm intelligence search is developed. Since spectrum peak search in MUSIC is a multimodal optimization problem, an improved bare-bones particle swarm optimization algorithm (IBPSO) is proposed first. In the IBPSO, a modified strategy of subpopulation determination is introduced into BPSO for realizing multimodal search. And then, the new MUSIC algorithm, called IBPSO-based MUSIC, is proposed by replacing the fixed-step traversal search with IBPSO. Meanwhile, a simulation signal is used to test the effectiveness of the proposed algorithm. The simulation results show that its frequency precision reaches 10^?5, and the computational cost is only comparable to that of traditional MUSIC with 0.1 search step. Finally, the IBPSO-based MUSIC is applied in BRB fault detection of an induction motor, and the effectiveness and superiority are proved again. The proposed research provides a modified MUSIC algorithm which has sufficient frequency precision to detect BRB fault in induction motors.     

Islet transplantation reverses the effects of maternal diabetes on mouse oocytes

Maternal diabetes adversely affects preimplantation embryo development and oocyte maturation. Thus, it is important to identify ways to eliminate the effects of maternal diabetes on preimplantation embryos and oocytes. The objectives of this study were to investigate whether islet transplantation could reverse the effects of diabetes on oocytes. Our results revealed that maternal diabetes induced decreased ovulation; increased the frequency of meiotic spindle defects, chromosome misalignment, and aneuploidy; increased the relative expression levels of Mad2 and Bub1; and enhanced the sensitivity of oocytes to parthenogenetic activation. Islet transplantation prevented these detrimental effects. Therefore, we concluded that islet transplantation could reverse the effects of diabetes on oocytes, and that this technique may be useful to treat the fundamental reproductive problems of women with diabetes mellitus.     

拟除虫菊酯类农药对斑马鱼幼鱼的神经毒性作用研究

摘要：目的 探究四种拟除虫菊酯类农药（溴氰菊酯、丙烯菊酯、高效氯氰菊酯、顺式氰戊菊酯）对斑马鱼神经毒性的作用,并与大鼠毒性结果进行比较,以期为斑马鱼在食品安全评价中的应用提供参考。方法 对四种农药采用静态暴露方法,分析其在高中低三种剂量下对斑马鱼幼鱼的形态、神经行为的影响;同时以活性氧（Reactive oxygen,ROS）、超氧化物歧化酶（(superoxide dismutase,SOD）、乙酰胆碱酯酶（Acetylcholinesterase,AchE）为指标,研究各农药在高中低剂量下对斑马鱼幼鱼神经化学的影响。结果 四种拟除虫菊酯类农药均对斑马鱼幼鱼造成了体长变短、脊柱弯曲等形态变化;除丙烯菊酯外,其他三种农药均使斑马鱼幼鱼出现显著的运动活性降低趋势;在神经化学方面,与空白组和对照组相比,四种农药随着浓度增加均使斑马鱼幼鱼体内的AchE活性显著下降、SOD活性显著升高;但四种农药对ROS活性变化各有差异：溴氰菊酯与高效氯氰菊酯对斑马鱼幼鱼的ROS影响无显著性差异,而丙烯菊酯和顺式氰戊菊酯在高中剂量下均可导致斑马鱼幼鱼ROS显著增加。结论 拟除虫菊酯农药对斑马鱼幼鱼产生了显著的神经毒性作用,首次发现形态变化和AchE活性的变化与大鼠相关结果体现出较好的一致性,有望替代大鼠用于更加简便快捷的食品安全风险评估;其余指标与大鼠呈现不同程度的差异,可能与两者生物学特性的差别有关。     

A Robust, Digital-Audio Watermarking Method

Most of the previous audio-watermarking schemes are robust to common signal-processing attacks, but show severe problems when faced with desynchronization attacks. To solve the problems associated with these approaches, we propose an audio-watermarking scheme based on support-vector-machine (SVM) theory to protect against desynchronization attacks by using audio statistics characteristics and a synchronization code technique. Experimental results with SVM show that our proposed scheme is inaudible, robust against common signal processing, and robust against desynchronization attacks.     

大豆及其加工食品转基因成分检测技术研究进展

随着基因工程技术在食用农产品领域的应用发展,形形色色的转基因食品应运而生。目前包括我国在内的许多国家为保护消费者的知情权和选择权,都建立了转基因食品标识管理制度。科学有效的转基因食品检测技术是实现我国转基因产品标识管理的前提。我国食品成分多样且基质复杂,针对初级农产品的转基因成分检测技术并不完全适用于工业加工食品尤其是深加工食品。这对食品监管及技术检测部门提出了新的要求。本文根据技术原理的不同分类介绍了目前几种主要的食品中转基因成分检测技术,除介绍现在已经成熟应用的技术方法外,本文还重点介绍了国内学者新近研发出的几种新技术,为研究人员进一步研发新技术提供重要参考。