管内插新型自旋转子的流阻及抑垢特性

提出了一种新型自旋转子,并通过数值及实验方法研究了其流动阻力及抑垢特性.实验结果表明,在流速为0.76 m/s时转子转速仍可达100r/min,内插该转子的流动阻力比光管增加2倍左右,正反旋向转子组(每组4个转子)相问布置可防止沿流向转子转速递减,使转子转速基本恒定.数值分析表明,通过减小转子的旋转轴套外径并加前端导流...     

Night vision dense crowd counting based on mid-term fusion of thermal imaging features北大核心CSCD

为了提高人群计数模型对尺度和光噪声的鲁棒性,设计了一种多模态图像融合网络。提出了一种针对夜间人群统计模型,并设计了一个子网络Rgb-T-net,网络融合了热成像特征和可见光图像的特征,增强了网络对热成像和夜间人群特征的判断能力。模型采用自适应高斯核对密度图进行回归,在Rgb-T-CC数据集上完成了夜视训练和测试。经验证网络平均绝对误差为18.16,均方误差为32.14,目标检测召回率为97.65%,计数性能和检测表现优于当前最先进的双峰融合方法。实验结果表明,所提出的多模态特征融合网络能够解决夜视环境下的计数与检测问题,消融实验进一步证明了融合模型各部分参数的有效性。     

基于改进U-Net的量子点STM图像分割

为提升量子点图像分割精度,降低特征识别误差,提出一种基于改进U-Net的量子点图像分割方法.首先,在预处理阶段,设计了以色彩通道为权值的灰度化算法,以提升后续分割效果.其次,在STM图像分割部分,在原始U-Net结构上引入中间过渡层以均衡网络各层特征.而后,建立数据集,并通过实验对比不同分割算法的精确度、召回率、F-measure.最后,将分割算法应用于量子点的特征识别,并测试了不同分割方式对应用的影响.实验结果显示,改进灰度化方法保留细节信息丰富,明显提升了量子点分割精度;改进U-Net的平均精确率、召回率、F-measure相较原始网络分别提升了13.83%、2.16%、8.13%.同时,实验数据表明由于分割精度的提升,量子点数量、纵横比等特征参数的识别更加精确.     

Security analysis of a spatiotemporal-chaos-based cryptosystem

An S-box modified one-way coupled map lattice is applied as a chaotic cryptograph. The security of the system is evaluated from various attacks currently used, including those based on error function analysis, statistical property analysis, and known-plaintext and chosen-ciphertext analytical computations. It is found that none of the above attacks can be better than the brute force attack of which the cost is exhaustively quantitated by the key number in the key space. Also, the system has fairly fast encryption (decryption) speed, and has extremely long period for finite-precision computer realization of chaos. It is thus argued that this chaotic cryptosystem can be a hopeful candidate for realistic service of secure communications.     

Infrared image enhancement through saliency feature analysis based on multi-scale decomposition

To improve contrast between dim target region and background in infrared (IR) long-range surveillance, this paper proposes a fast image enhancement approach using saliency feature extraction based on multi-scale decomposition. Firstly, a smooth based multi-scale decomposition is designed and applied to original infrared image, generating sub-images with various frequency components at different decomposition levels. The dim target regions of sub-images are extracted by a local frequency-tuned based saliency feature detection method, secondly. With saliency maps created by saliency extraction using multi-scale local windows with different sizes, the sub-images are enhanced at different decomposition scales. Finally, the enhanced result is reconstructed by synthesizing the all sub-images with adjustable synthetic weights. Since salient areas are analyzed based on fast multi-scale image decomposition, IR image can be s enhanced with good contrast successfully and rapidly. Compared with other algorithms, the experimental results prove that the proposed method is robust and efficient for IR image enhancement.     

Diffusion in fluids with large mean free paths: Non-classical behavior between Knudsen and Fickian limits

Diffusion in fluids is analyzed at non-classical conditions, intermediate between the Knudsen and Fickian limits. The fluid is considered in the framework of the Einstein’s diffusion evolution equation involving expansions of the density distribution in powers of displacement and time. The standard truncation of these expansions results in the classical model of diffusion; however, higher-order terms lead to a departure from classical behavior. This has not been studied or discussed adequately in the literature previously.Here, we present an exact solution of the Einstein’s diffusion evolution equation without truncation of the density expansions. This solution illustrates limitations in the classical truncations and demonstrates non-classical effects due to large mean free paths, λ. In particular, this new solution shows that, at large λ, there are significant quantitative deviations from classical diffusion profiles. In addition, this solution demonstrates a dramatic change in the diffusion mechanism from the state where the molecular motions are predominantly ballistic to one of molecular chaos. This has implications for fundamentals of fluids between the Knudsen and Fickian limits, and for a variety of fields where evolution of a system includes random, multi-scale displacement of particles, such as nanotechnology, vacuum techniques, turbulence, and astrophysics.     

Adaptive synchronization of weighted complex dynamical networks through pinning

This paper considers the problem of controlling weighted complex dynamical networks by applying adaptive control to a fraction of network nodes. We investigate the local and global synchronization of the controlled dynamical network through the construction of a master stability function and a Lyapunov function. Analytical results show that a certain number of nodes can be controlled by using adaptive pinning to ensure the synchronization of the entire network. We present numerical simulations to verify the effectiveness of the proposed scheme. In comparison with feedback pinning, the proposed pinning control scheme is robust when tested by noise, different weighting and coupling structures, and time delays.     

Synchronization of different chaotic systems via active radial basis functions sliding mode controller

This paper presents a new method to synchronize different chaotic systems with disturbances via an active radial basis function （RBF） sliding controller. This method incorporates the advantages of active control, neural network and sliding mode control. The main part of the controller is given based on the output of the RBF neural networks and the weights of these single layer networks are tuned on-line based on the sliding mode reaching law. Only several radial basis functions are required for this controller which takes the sliding mode variable as the only input. The proposed controller can make the synchronization error converge to zero quickly and can overcome external disturbances. Analysis of the stability for the controller is carried out based on the Lyapunov stability theorem. Finally, five examples are given to illustrate the robustness and effectiveness of the proposed synchronization control strategy.     

Hash function based on the generalized Henon map

A new Hash function based on the generalized Henon map is proposed. We have obtained a binary sequence with excellent pseudo-random characteristics through improving the sequence generated by the generalized Henon map, and use it to construct Hash function. First we divide the message into groups, and then carry out the Xor operation between the ASCII value of each group and the binary sequence, the result can be used as the initial values of the next loop. Repeat the procedure until all the groups have been processed, and the final binary sequence is the Hash value. In the scheme, the initial values of the generalized Henon map are used as the secret key and the messages are mapped to Hash values with a designated length. Simulation results show that the proposed scheme has strong diffusion and confusion capability, good collision resistance, large key space, extreme sensitivity to message and secret key, and it is easy to be realized and extended.     

Controlling bifurcations and chaos in discrete small-world networks

We propose an impulsive hybrid control method to control the period-doubling bifurcations and stabilize unstable periodic orbits embedded in a chaotic attractor of a small-world network. Simulation results show that the bifurcations can be delayed or completely eliminated. A periodic orbit of the system can be controlled to any desired periodic orbit by using this method.