A sequencing problem for a mixed-model assembly line in a JIT production system

In an assembly line of a just-in-time (JIT) production system, workers have the power and the responsibility to stop the line when they fail to complete their operations within their work zones. This paper deals with a sequencing problem for the mixed-model assembly conveyor line in the JIT production system. In some environment, the most important criterion is the line stoppage rather than the variation of production rates. The problem is to find an optimal sequence of units that minimizes the total line stoppage time. Lower and upper bounds of the total line stoppage time are derived and the branch-and-bound method is applied to the problem. A numerical example is given.     

小波域最小嵌入失真函数设计及其在隐写中的应用

为了提高隐写方案的安全性,提出一种基于最小嵌入失真原理和网格码的图像隐写算法。首先在离散小波域结合人眼视觉特性和整数提升小波变换设计了失真测度函数,主要考虑了亮度、频率和纹理掩蔽因子对载体失真的影响。然后结合网格码设计了隐写算法,将嵌入信息对载体的修改最小化并且集中在人眼不敏感区域。实验结果显示,方案具有良好的视觉不可见性,且能抵抗空域、小波域等隐写分析的攻击,安全容量达到0.4 bits/pixel。     

Fast Object Segmentation by Growing Minimal Paths from a Single Point on 2D or 3D Images

In this paper, we present a new method for segmenting closed contours and surfaces. Our work builds on a variant of the minimal path approach. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal paths allows us to extract a closed contour from a 2D image. This approach can also be used for finding an open curve giving extra information as stopping criteria. Detection of a variety of objects on real images is demonstrated. Using a similar idea, we can extract networks of minimal paths from a 3D image called Geodesic Meshing. The proposed method is applied to 3D data with promising results.

Optimal cooperative beamforming design schemes  for AF MOMO two way relay channels

In this paper,beamforming parameters in multiple input multiple output (MIMO) two-way relay channels (TWRCs) are designed.We investigate three communicating scenarios,in which,the source nodes are all ...     

Model reduction for nonlinear multiscale parabolic problems using dynamic mode decomposition

In this article, a model reduction technique is presented to solve nonlinear multiscale parabolic problems using dynamic mode decomposition. The multiple scales and nonlinearity bring great challenges for simulating the problems. To overcome this difficulty, we develop a model reduction method for the nonlinear multiscale dynamic problems by integrating constraint energy minimizing generalized multiscale finite element method (CEM-GMsFEM) with dynamic mode decomposition (DMD). CEM-GMsFEM has shown great efficiency to solve linear multiscale problems in a coarse space. However, using CEM-GMsFEM to directly solve multiscale nonlinear parabolic models involves dynamically computing the residual and the Jacobian on a fine grid. This may be very computationally expensive because the evaluation of the nonlinear term is implemented in a high-dimensional fine scale space. As a data-driven method, DMD can use observation data and give an explicit expression to accurately describe the underlying nonlinear dynamic system. To efficiently compute the multiscale nonlinear parabolic problems, we propose a CEM-DMD model reduction by combing CEM-GMsFEM and DMD. The CEM-DMD reduced model is a coarsen linear model, which avoids the nonlinear solver in the fine space. It is crucial to judiciously choose observation in DMD. Only proper observation can render an accurate DMD model. In the context of CEM-DMD, we introduce two different observations: fine scale observation and coarse scale observation. In the construction of DMD model, the coarse scale observation requires much less computation than the fine scale observation. The CEM-DMD model using the coarse scale observation gives a complete coarse model for the nonlinear multiscale dynamic systems and significantly improves the computation efficiency. To show the performance of the CEM-DMD using the different observations, we present a few numerical results for the nonlinear multiscale parabolic problems in heterogeneous porous media.     

开放式基金规模变化系统净投资变化率同定问题

讨论了开放式基金规模变化系统中的基金净投资变化率同定问题,利用Banach空间理论得到了同定问题的解的存在惟一性.     

使用LR分析表的词法分析器与分析表最小化

以一个模型语言为例,系统地介绍了使用LR分析表的词法分析器工作原理,以及词法分析器所使用的LR分析表最小化方法。使用LR分析表的词法分析器,统一了词法分析器和语法分析器的构造方法,简化了编译程序的设计和构造。分析表的最小化是通过编码压缩来实现的,分析表的最小化减少了编译程序运行所需的内存空间。     

基于对数极坐标变换的景像匹配算法研究

针对成像制导过程中对实时性和准确性的要求,对存在旋转和尺度变化的航拍照片的匹配进行研究,提出了一种基于对数极坐标变换的匹配和跟踪算法.匹配时先对基准图和实时图按多分辨率金字塔法进行对数极坐标变换,利用对数极坐标的旋转和尺度不变性进行匹配.匹配后,用相对运动时目标的对数极坐标变换图像梯度下降最小相异评估方法对目标进行跟踪,通过对航拍照片进行匹配测试,证明了这种方法的有效性.     

Low Power Encoding Techniques for Dynamically Reconfigurable Hardware

In this paper, an approach to the implementation of digital systems is presented which utilizes dynamic hardware reconfiguration in order to automatically minimize the power dissipated on module interconnections such as system buses during system run time. Reduction of power dissipation is achieved by means of an activity-reducing system bus encoding technique. Encoder and decoder are implemented with dynamically reconfigured code tables which contain a transition minimizing code that is periodically recomputed during run time of the system in order to adapt to variations in the statistical parameters of the encoded data stream. We present the theoretical basics and an efficient implementation of a corresponding coder-decoder system. Experimental results showed a reduction in bus transition activity of up to 41%.