基于安全域的Android系统内核安全增强机制研究

近年来,随着Android系统的迅猛发展,其安全面临着极大的挑战。Android的安全包括系统安全和软件安全,系统安全是整个安全的基石,对整体安全至关重要。以TOMOYO Linux 为基础,针对Android的特点,改进了域生成算法,实现了内核层面的安全增强机制。实验证明,所提安全增强方案能够有效增强Android系统的安全性。     

基于水下图像光学成像模型的清晰化算法

针对水下图像的纹理细节模糊、对比度低以及图像光照不均问题,通过分析水下图像的成像过程,提出一种水下图像清晰化算法。在小波域的低频子带上结合水下图像光学成像模型,先利用高斯模糊对介质散射光进行估计与去除,再采用基于局部复杂度的方法调整衰减因子,对衰减低频子图进行自适应增强;在高频子带上采用非线性变换的增强方法,进一步增强了高频信息并有效地抑制了噪声的放大。实验结果表明该算法对解决水下图像模糊和光照不均问题具有较好的效果,与基于小波变换的水下降质图像复原算法相比,具有较高的实时性。     

DTCWT域的红外与可见光图像融合算法

针对红外与可见光图像融合存在融合图像对比度和清晰度降低、噪声干扰等问题,提出一种DTCWT域的红外与可见光图像融合算法。首先对源图像进行预增强处理;然后通过DTCWT正变换得到低频子带图像和高频子带图像;再分别利用基于直觉模糊集的融合规则融合低频子带图像,基于信息反差对比度的融合规则融合高频子带图像;最后对融合后的低频子带图像和高频子带图像进行DTCWT逆变换得到融合图像。实验结果表明,本文算法能有效提高融合图像对比度和清晰度,降低噪声干扰,客观评价指标总体优于现有算法的,运行效率也有所提升。     

低档聚合原料开发高新差别化涤纶长丝的研究

结合企业的产业化试验及下游市场使用状况,对粗对苯二甲酸(QTA及EPTA)在三釜聚合工艺流程条件下,如何保障抗菌和阻燃涤纶长丝生产品质要求开展分析研究,确定了工艺优化调整、助剂添加、设备改进等若干措施,得到显著效果。最终单独使用低档原料,制得产品性能良好的聚酯,使高新差别化长丝新品顺利通过了产业化攻关。     

基于摇杆-转向架机构月球车机构运动学原理

基于摇杆-转向架机构月球车机构原理图建立相应的正向运动学坐标变换方程,得出各相应关节相对参考坐标原点的位姿,依此求出车体中心速度;再在各轮和铰相对右后轮高度差已知的情况下建立逆向运动学方程,给出求解相应关节相关参数的方法。     

Classification- and Regression-Assisted Differential Evolution for Computationally Expensive Problems

Differential Evolution (DE) has been well accepted as an effective evolutionary optimization technique. However, it usually involves a large number of fitness evaluations to obtain a satisfactory solution. This disadvantage severely restricts its application to computationally expensive problems, for which a single fitness evaluation can be highly timeconsuming. In the past decade, a lot of investigations have been conducted to incorporate a surrogate model into an evolutionary algorithm (EA) to alleviate its computational burden in this scenario. However, only limited work was devoted to DE. More importantly, although various types of surrogate models, such as regression, ranking, and classification models, have been investigated separately, none of them consistently outperforms others. In this paper, we propose to construct a surrogate model by combining both regression and classification techniques. It is shown that due to the specific selection strategy of DE, a synergy can be established between these two types of models, and leads to a surrogate model that is more appropriate for DE. A novel surrogate model-assisted DE, named Classification-and Regression-Assisted DE (CRADE) is proposed on this basis. Experimental studies are carried out on a set of 16 benchmark functions, and CRADE has shown significant superiority over DE-assisted with only regression or classification models. Further comparison to three state-of-the-art DE variants, i.e., DE with global and local neighborhoods (DEGL), JADE, and composite DE (CoDE), also demonstrates the superiority of CRADE.     

基于算子的图像分解

图像的形态学卡通纹理分解与图像层级分解是近年来图像分析领域的研究热点.针对现有图像分解算法求解过程复杂且不易对图像层级分解的问题,提出了一种基于算子的快速图像分解算法.在该方法中,由局部奇异线性算子来刻画图像的纹理成分,剩余图像信号则被描述为卡通成分;同时通过引入自适应参数调节的方法来实现对剩余信号的分解,进而实现图像的层级分解.其中,自适应参数由图像局部全变差变化率来确定.实验结果表明,该算法具有较好的运行效率,同时具有较好的分解视觉效果.     

无线传感器网络中声震信号的特征提取算法

面向无线传感器网络在地面目标声震信号识别方面的应用需求,提出基于局域判别基(Local Discriminant Bases,LDB)算法的特征提取方法.并且,针对现有的基于时频能量图的可分性测度的缺点,提出新的基于概率密度估计的相对微分熵的可分性测度.基于实地采集到的信号的仿真实验表明,该方法在一定程度上提高了目标的正确识别率,降低了特征维数,具有实际的应用价值.     

Mammogram Enhancement Using Lifting Dyadic Wavelet Transform and Normalized Tsallis Entropy

In this paper, we present a new technique for mammogram enhancement using fast dyadic wavelet transform （FDyWT） based on lifted spline dyadic wavelets and normalized Tsallis entropy. First, a mammogram image is decom- posed into a multiscale hierarchy of low-subband and high-subband images using FDyWT. Then noise is suppressed using normalized Tsallis entropy of the local variance of the modulus of oriented high-subband images. After that, the wavelet coefficients of high-subbands are modified using a non-linear operator and finally the low-subband image at the first scale is modified with power law transformation to suppress background. Though FDyWT is shift-invariant and has better poten- tial for detecting singularities like edges, its performance depends on the choice of dyadic wavclcts. On the other hand, the nulnber of vanishing moments is an important characteristic of dyadic wavelets for singularity analysis because it provides an upper bound measurement for singularity characterization. Using lifting dyadic schemes, we construct lifted spline dyadic wavelets of different degrees with increased number of vanishing moments. We also examine the effect of these wavelets on mammogram enhancement. The method is tested on mammogram images, taken from MIAS （Mammographic Image Analysis Society） database, having various background tissue types and containing different abnormalities. The comparison with tile state-of-the-art contrast enhancement methods reveals that the proposed method performs better and the difference is statistically significant.     

基础信息保持和细节强化的胸部CT图像增强

目的 清晰的胸部计算机断层扫描(computed tomography, CT)图像有助于医生准确诊断肺部相关疾病,但受成像设备、条件等因素的限制,扫描得到的CT图像质量有时会不尽如人意。因此,本文提出一种简单有效的基于基础信息保持和细节强化的胸部CT图像增强算法。方法 利用多尺度引导滤波器将胸部CT图像分解为一个基础信息层和多个不同尺度的细节层。基于熵的权重将胸部CT图像的多个细节层进行融合,并乘以强化系数进一步增强纹理细节。将强化的细节层和原始的基础信息层重新组合即可生成细节强化的胸部CT图像。通过此种增强方式,本文算法既能显著增强胸部CT图像的纹理细节,又能将大部分原始的基础结构信息保留到增强图像中。结果 为了验证算法的有效性,将本文算法与5种优秀的图像增强算法在由3 209幅胸部CT图像组成的数据集上进行测试评估。定性和定量实验结果表明,本文算法得到的增强图像保持了更多原始胸部CT图像中的基础结构信息,并更显著地强化了其中的纹理细节信息。在定量结果中,本文算法的标准差、结构相似性和峰值信噪比指标值均优于对比的5种方法,相比于性能第2的方法分别提高了4.95、0.16和4.47,...