基于CMYK空间的火灾区域粒子群优化快速定位方法

将CMYK彩色模型下的火焰颜色特征与粒子群优化(Particle swarm optimization,PSO)算法求最优适应度函数相结合,通过合理配置检测窗口邻域中颜色的M,y各低阶矩的特征在欧氏距离分类适应度函数中的因子及PSO中各参数,使森林监测图像的可疑火灾着火点的初定位控制在0.05s以内,最后通过对火灾样本关键图与初定位可疑着火点的颜色互信息的计算而得到进一步的校验和确定.实验表明改进的PSO算法具有良好的火焰区域定位效果及运算效率,易于移植到前端探测的嵌入式火灾探测系统.     

Importance sampling for volumetric illumination of flames

Physically based rendering of scenes with volumetric illumination of flames remains a challenging problem due to the complexity of their heterogeneous radiative properties. Current bidirectional importance sampling strategies have been focusing on emissive light sources without anisotropic extinction. In this paper, we present an efficient importance sampling method for volumetric light sources with anisotropic extinction. According to the radiative properties of flames, we separate the computation of anisotropic extinction from the evaluation of illumination inside flames and utilize cluster-based hierarchies to rapidly estimate them. To exploit the coherence of radiative voxels, we also propose a new similarity metric to aggregate voxels into clusters. For each pixel to be shaded, we use these clusters to rapidly approximate the importance function of voxels, and draw final illumination samples from clusters. Our results show that this approach substantially reduces the variance of images when rendering scenes with flames.     

RMPCT技术在连续重整装置上的应用

催化连续重整是石油加工中极其重要的工艺过程。由于反应复杂,过程变量多,变量之间耦合严重,存在许多重要不易测量变量,使过程控制难度大,采用常规的PID单回路控制有很大的局限性。多变量模型预估控制MPC是石油化工生产中广泛应用的1种先进控制策略。霍尼韦尔公司在MPC的基础上开发出了鲁棒多变量模型预测控制技术RMPCT。将R...     

离心压缩机自动控制系统的设计和应用

介绍以ＰＣ－ＢＵＳ工控机为中心构成离心压缩机自动控制系统的设计及在化工生产中的应用,实践证明,该系统工作可靠,经济效益显著,达到了设计目的。     

一种快速模板匹配目标识别算法

该文拟将计算机视觉中传统模板匹配方法与对场景物体的中心矩描述方法相结合,提出了一种效率较高的匹配算法。算法在匹配识别上不仅不受物体方位旋转及尺寸缩放变化影响,而且能较精确地求出物体相对于模板的缩放比例和偏转角度。文中给出了与传统模板匹配算法对照的实验结果。     

一种基于PC机的高速16位并行数据采集接口

介绍了一种在PC机上实现的高速16位并行数据采集接口。该接口由高速光电隔离电路,双端口FIFO存储缓冲器电路及由FPGA芯片构成的计算机接口逻辑与控制电路等组成。该接口电路将终端显示处理系统与前端数据处理系统通过光电耦合器隔离开来,避免了它们之间的相互干扰,较好地解决了16位并行数据高速传输中存在的电磁干扰问题和大数据量实时有效传输问题。采用现场可编码门阵列FPGA芯片,使硬件设计软件化,既实现了复杂逻辑功能设计,又减少了硬件电路规模,提高了系统的可靠性,在雷达、声纳等复杂系统中具有良好的应用价值。     

基于正交小波变换的信号降噪算法研究

提出了一种基于正交小波变换的信号降噪方法,深入研究了小波变换中的信号分解与重构的Mallat算法,详细介绍了正交小波变换中阈值的选取,并进行了实验研究。实验结果表明,该方法可以取得较好的去噪效果。     

An overview of quantum computation models: quantum automata

Quantum automata, as theoretical models of quantum computers, include quantum finite automata (QFA), quantum sequential machines (QSM), quantum pushdown automata (QPDA), quantum Turing machines (QTM), quantum cellular automata (QCA), and the others, for example, automata theory based on quantum logic (orthomodular lattice-valued automata). In this paper, we try to outline a basic progress in the research on these models, focusing on QFA, QSM, QPDA, QTM, and orthomodular lattice-valued automata. Also, other models closely relative to them are mentioned. In particular, based on the existing results in the literature, we finally address a number of problems to be studied in future.     

Clustering and embedding using commute times

This paper exploits the properties of the commute time between nodes of a graph for the purposes of clustering and embedding, and explores its applications to image segmentation and multi-body motion tracking. Our starting point is the lazy random walk on the graph, which is determined by the heatkernel of the graph and can be computed from the spectrum of the graph Laplacian. We characterize the random walk using the commute time (i.e. the expected time taken for a random walk to travel between two nodes and return) and show how this quantity may be computed from the Laplacian spectrum using the discrete Green's function. Our motivation is that the commute time can be anticipated to be a more robust measure of the proximity of data than the raw proximity matrix. In this paper, we explore two applications of the commute time. The first is to develop a method for image segmentation using the eigenvector corresponding to the smallest eigenvalue of the commute time matrix. We show that our commute time segmentation method has the property of enhancing the intra-group coherence while weakening inter-group coherence and is superior to the normalized cut. The second application is to develop a robust multi-body motion tracking method using an embedding based on the commute time. Our embedding procedure preserves commute time, and is closely akin to kernel PCA, the Laplacian eigenmap and the diffusion map. We illustrate the results both on synthetic image sequences and real world video sequences, and compare our results with several alternative methods.     

向日葵菌核病菌毒素的生产及其生物活性的测定

首次报道了向日葵核病菌[Sclerotinia sclerotiorum (Lib.) de Bary]在离体,活体培养条件下均能产生草酸毒素,研究表明,在扫描电镜下,Ca^2 离子结晶可形成草酸钙晶体,且多分布在孔及表皮毛周围;该菌的培养滤波及粗毒素对种子萌发胚轴伸长和幼草生长等都有毒害或抑制作用。