活性蓄冷器数学模型的研究进展

活性蓄冷器是室温磁制冷机的核心部分,它的性能直接影响整个磁制冷系统。了解其工作机理和热力学特性对制冷机的设计与优化具有重要意义。综述了近年来活性蓄冷器数学模型的研究进展,并对模型进行了比较分析。     

基于主动轮廓模型的EAST等离子体边界重建

通过分析等离子体边界的等磁通特性,利用主动轮廓模型进行边界重建,给出了主动轮廓的能量计算方法、重建算法、边界磁通和初始轮廓的确定方法。利用EAST实验数据对边界的重建测试表明,该算法具有良好的准确性和实时性。     

大口径薄型光学镜面支撑方案的优化设计

 针对薄型光学镜面支撑过程中的主动施力过程,建立了一个1维分析模型。利用该模型,采用有限元法对一个口径为300 mm、直径与厚度比为40的薄型光学镜面,利用离散支撑方案,针对4种镜面变形进行了计算,得到了实现变形要求所需施加力的大小。使用零阶优化方法中的子问题逼近法对施力位置、施力大小进行了具体优化。分析结果显示：优化后的镜面变形与目标形状更接近,最大平均差值比优化前减小了58%。     

Automatic detection of colloidal particles based on a shape regularized integrated active contour model

Manual segmentation of single colloidal particle in suspension encounters a bottleneck when a number of defocused particles simultaneously exist in an image. In this paper, we describe an image processing algorithm for extracting individual particle from digitized microscope images of colloidal suspensions. We propose a particle detection and location solution using a shape regularized integrated active contour model (ACM). Compared with existing methods where active contour models are not applied well to deal with multiple objects in complicated background, the proposed approach can automatically identify and locate multiple particles by combining characteristics of the particles such as shape, boundary and region. A regularization term is defined by prior information of specific shape, which is able to drive the shape of evolving curve toward the shape prior gradually. To locate the centers of the particles, the Hough transform is applied. Experimental results using polystyrene beads as sample particles reveal that the method has high efficiency and ability to deal with colloidal particles.     

A simplified adaptive feedback active noise control system

In the adaptive feedback active noise control system based on the internal model control (IMC) structure, the reference signal is regenerated by synthesizing the error signal and the secondary signal filtered with the estimation of the secondary path, hence more computation load and extra programming are required. Motivated by the engineering truth that the primary noise cannot be completely cancelled in most practical active noise control applications and the error signal still contains some portions of the primary noise, a simplified adaptive feedback active noise control system is proposed in this paper, which adopts the error signal directly as the reference signal in an adaptive feedforward control system and utilizes the leaky filtered-x LMS algorithm to update the controller. The convergence properties of the proposed system are investigated and its advantages are discussed by comparing with other feedback control systems as well as the weakness. Finally, simulations and experiments are carried out to demonstrate the effectiveness of the proposed system.     

不同处理工艺钢渣的X射线衍射和X射线荧光光谱分析及其活性指数预测模型

以不同处理工艺钢渣,即转炉热泼渣、转炉滚筒渣、铸余渣、铁水脱硫渣、电炉热泼渣和电炉滚筒渣作为研究对象。利用X射线衍射仪和X射线荧光光谱分析仪研究钢渣的化学成分与物相组成。利用BP神经网络模型建立钢渣活性指数预测模型,研究化学成分、物相组成与活性的关系。结果表明： 钢渣的处理工艺不同,其化学成分与物相组成存在明显差异;钢渣活性指数预测模型具有良好的符合性,即相对误差为2.42%和-2.54%,能充分反映输入层与输出层之间的映射关系。     

A video-rate range sensor based on depth from defocus

Recovering the depth information derived from dynamic scenes implies real-time range estimation. This paper addresses the implementation of a bifocal range sensor which estimates the depth by measuring the relative blurring between two images captured with different focal settings. To recover the depth accurately even in cases when the scene is textureless, one possible solution is to project a structured light on the scene. As a consequence, in the scene's spectrum a spatial frequency derived from illumination pattern is evident. The resulting algorithm involves only simple local operations, this assures the possibility of computing the depth at a rate of 10 frames per second. The experimental results indicate that the accuracy of this proposed sensor compares well with that offered by other methods such as stereo and motion parallax, while avoiding the problems caused by occlusion and missing parts.     

基于平行活动围道模型的高分辨率遥感影像城区主干道路段提取

为了提取并表示高分辨率遥感影像中的主干道路段，提出了一种多分辨框架下的平行活动围道模型的算法.该算法在活动围道模型原理的基础上，重新定义各能量项:采用抛物线做为道路段的先验模型，增加了平行性能量，并采用多分辨框架下的梯度做为外部能量.该模型的优化过程实现了道路的定位，得到的结果是平行抛物线的参数，实现了道路的矢量表示.实验结果表明，能有效提取高分辨率遥感影像中的主干道路段.     

Region-based object and background extraction via active contours

In this paper, we propose a region-based model for the object and background extraction with application to the image with thick or complex boundary. Based on region information of the image, we employ two curves to extract the object and background, respectively, regardless of the boundary. The first curve is used to extract the object. Correspondingly, the second curve is used to extract the background. By employing two level set functions to represent the two curves, we propose a new region-based energy functional. In the proposed model, a distance constraint term is incorporated, which effectively avoid that the two level set functions too away from each other and keep their similar shapes well. Besides, we present a penalty term to maintain the accurate computation and stability evolution. Experiment results demonstrate the desirable performance of the proposed model with application to synthetic and real-world images.     

光在激活光纤中的传输

本文推导了连续光及宽脉冲在激活光纤中的运动方程,采用激活物质极化的量子理论,在零级近似及一级近似情况下,对其运动方程进行了求解,并讨论了激活物质对脉冲群速度的影响,定量地描述了连续光及宽脉冲的振幅与位相及群速度在激活光纤中的变化行为。     

Saliency Snake: A unified framework with adaptive initial curve

Active contour model also known as Snake, is a popular approach for contour extraction and image segmentation. However, some existing active contour models are sensitive to the initial curve, which is usually required to be placed near the true object contour. To address this problem, this paper proposes a novel active contour model with adaptive initial curve, namely Saliency Snake. Taking visual saliency into consideration, prior shape information of the interested object is incorporated explicitly into the energy functional of Saliency Snake. Such improvement facilitates active contour evolution and leads to fast and automatic segmentation. Experiment results demonstrate that the proposed Saliency Snake can achieve superior segmentation performance both in terms of accuracy and efficiency.     

A novel active contour model driven by local and global intensity fitting energies

In this paper, we propose a novel hybrid active contour model for image segmentation. In our model, we define a new region-scalable fitting (RSF) energy functional which combines the local and the global image information. The RSF energy functional can not only attract the contour toward object boundaries, but also improve the robustness to initialization of the contours. In order to segment the image fast and accurately, the length term and regularization term is incorporated into the variational level set formulation. Finally, by adopting gradient descent method, the minimization of the energy equation can be given. Due to the new kernel function we defined, our model can cope with intensity inhomogeneity images and less sensitive to the initialization of the contour when compared with the other models. Experimental results demonstrated that the proposed model can also segment both the real and medical images accurately.     

Randomly rattled ratchets

Summary Ratchets are anisotropic periodic potentials. Particles subject to ratchet forces and simultaneously to thermal and nonthermal fluctuations can rectify the nonequilibrium noise, thereby extracting energy from incoherent and otherwise symmetric random forces. In this paper I describe some simple models which illustrate this phenomenon, highlighting two particular mechanisms leading to fluctuation-induced current. Paper presented at the International Workshop ?Fluctuations in Physics and Biology: Stochastic Resonance, Signal Processing and Related Phenomena?, Elba, 5–10 June 1994. Address after July 1, 1994: Center for Nonlinear Studies, MS-B258, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.     

An automatic cerebellum extraction method in T1-weighted brain MR images using an active contour model with a shape prior

Purpose

The objective of this paper was to automatically segment the cerebellum from T1-weighted human brain magnetic resonance (MR) images.

Materials and Methods

The proposed method constructs a cerebellum template using five sets of 3-T MR imaging (MRI) data, which are used to determine the initial position and the shape prior of the cerebellum for the active contour model. Our formulation includes the active contour model with shape prior, which thereby maintains the shape of the template. The proposed active contour model is sequentially applied to sagittal-, coronal- and transverse-view images. To evaluate the proposed method, it is applied to BrainWeb data and a 3-T MRI data set and compared with FreeSurfer with respect to performance assessment metrics.

Results

The segmented cerebellum was compared with the results from FreeSurfer. Using the manually segmented cerebellum as reference, we measured the average Jaccard coefficients of the proposed method, which were 0.882 and 0.885 for the BrainWeb data and 3-T MRI data set, respectively.

Conclusion

We presented the active contour model with shape prior for extracting the cerebellum from T1-weighted brain MR images. The proposed method yielded a robust and accurate segmentation result.     

Soil radon response around an active volcano

Soil radon behavior related to the volcanic eruptive period 1997–1999 of Popocatepetl volcano has been studied as a function of the volcanic activity. Since the volcano is located 60 km from Mexico City, the risk associated with an explosive eruptive phase is high and an intense surveillance program has been implemented. Previous studies in this particular volcano showed soil radon pulses preceding the initial phase of the eruption. The radon survey was performed with LR-115 track detectors at a shallow depth and the effect of the soil moisture during the rainy season has been observed on the detectors response. In the present state of the volcanic activity the soil radon behavior has shown more stability than in previous eruptive stages.     

有源半导体双稳放大器稳定性分析

本文从半经典理论出发,对有源双稳放大器进行了稳定性分析,其结果表明:有源双稳器件远较无源器件易产生正沿不稳定性。在此基础上,我们讨论了有源E-P型双稳开关器件的实用开关速度的极限,实验中我们采用两个InGaAsP/InP双异质结单纵模激光器观察到了全光型开关现象。     

Design optimization of all-optical actively mode-locked ring laser based on cross-gain modulation in a semiconductor optical amplifier

A complete and detailed model is presented that describes the main physical phenomena that occur in an actively mode-locked fiber ring laser based on cross-gain modulation in a semiconductor optical amplifier employed as both the gain medium and mode-locking element. The relationship between key laser parameters and the output pulse characteristics is numerically analyzed to provide simple design rules and derive a set of necessary operational conditions. The adoption of these rules and the satisfaction of these conditions enables the optimization of the laser performance and the generation of short and high energy mode-locked output pulses.     

A robust level set method based on local statistical information for noisy image segmentation

The paper presents an improved local region-based active contour model for image segmentation, which is robust to noise. A data fitting energy functional is defined in terms of curves and the energy terms which are based on the differences between the local average intensity and the global intensity means. Then the energy is incorporated into a level set variational formulation, from which a curve evolution equation is derived for energy minimization. And then the level set function is regularized by Gaussian filter to keep smooth and eliminate the re-initialization. By using the local statistical information, the proposed model can handle with noisy images. The proposed model is first presented as a two-phase level set formulation and then extended to a multi-phase one. Experimental results show desirable performances of the proposed model for both noisy synthetic and real images, especially with high level noise.     

Arbitrary initialization for Chan–Vese model

Three problems about initialization of Chan–Vese model impeding its applications of Chan–Vese model, are discussed in this paper first by various experiments. Then, a novel method to solve these badly initialization problems is proposed, which can be divided into three parts: a hypothesis that image boundaries do not contain any feature of the objects; an examination criterion to check whether the current contour is suitable for continuing or not; and a method to revise the unsuitable current contour into a new one. The most important advantage of our proposed method is that it realizes the arbitrary initialization which can release the manual work in essence. Extensive experiments on synthetic and real images demonstrate the advantages of the proposed method.     

A joint shape evolution approach to medical image segmentation using expectation-maximization algorithm

This study proposes an expectation–maximization (EM)-based curve evolution algorithm for segmentation of magnetic resonance brain images. In the proposed algorithm, the evolution curve is constrained not only by a shape-based statistical model but also by a hidden variable model from image observation. The hidden variable model herein is defined by the local voxel labeling, which is unknown and estimated by the expected likelihood function derived from the image data and prior anatomical knowledge. In the M-step, the shapes of the structures are estimated jointly by encoding the hidden variable model and the statistical prior model obtained from the training stage. In the E-step, the expected observation likelihood and the prior distribution of the hidden variables are estimated. In experiments, the proposed automatic segmentation algorithm is applied to multiple gray nuclei structures such as caudate, putamens and thalamus of three-dimensional magnetic resonance imaging in volunteers and patients. As for the robustness and accuracy of the segmentation algorithm, the results of the proposed EM-joint shape-based algorithm outperformed those obtained using the statistical shape model-based techniques in the same framework and a current state-of-the-art region competition level set method.