Application of fuzzy image restoration in criminal investigation

The advancement of science and technology has a positive effect on the development of law disciplines. The development of algorithms and artificial intelligence also has a certain impact on judicial practice. Image restoration is a significant technique in image processing. It aims to objectively restore the content or quality of the original image from the degraded image. Image degradation is always generated in image transmission, such as distortion, blur. In modern video surveillance system, image restoration is significant for criminal investigation. However, image restoration based on conventional filter algorithms cannot achieve satisfactory performance. Thus, we first introduce the image restoration algorithms based on different degradation model. Then, we propose some applications of fuzzy image restoration in criminal investigation. We conduct experiments on both degraded images and videos and experimental results have shown the effectiveness of fuzzy image restoration applying to the criminal investigation.     

Experimental investigation of multiphase flow behavior in drilling annuli using high speed visualization technique

Imaging with high definition video camera is an important technique to visualize the drilling conditions and to study the physics of complex multiphase flow associated with the hole cleaning process. The main advantage of visualizing multiphase flow in a drilling annulus is that the viewer can easily distinguish fluid phases, flow patterns and thicknesses of cutting beds. In this paper the hole cleaning process which involves the transportation of cuttings through a horizontal annulus was studied. The two-phase (solid-liquid) and the three-phase (solid-liquid-gas) flow conditions involved in this kind of annular transportation were experimentally simulated and images were taken using a high definition camera. Analyzing the captured images, a number of important parameters like velocities of different phases, heights of solid beds and sizes of gas bubbles were determined. Two different techniques based on an image analysis software and MATLAB coding were used for the determinations. The results were compared to validate the image analyzing methodology. The visualization technique developed in this paper has a direct application in investigating the critical conditions required for efficient hole cleaning as well as in optimizing the mud program during both planning and operational phases of drilling. Particularly, it would be useful in predicting the cuttings transport performance, estimating solid bed height, gas bubble size, and mean velocities of bubbles/particles.     

加热面朝下的池沸腾汽泡动态行为研究

基于Matlab软件开发了自动识别气液两相流界面程序，程序可获得气液界面变化、汽膜厚度、汽膜脱离周期和汽膜法向速度等特征。利用该程序对沟槽结构加热表面朝下布置时，在不同倾角、不同热流密度下的汽泡动态数据进行了处理和分析。结果表明：加热表面朝下发生核态沸腾时，汽膜厚度随热流密度的增大而增大，汽泡脱离周期随热流密度的增大先减小，而后维持在一稳定值；汽膜脱离周期随倾角的增大而减小，倾角为5°时的汽膜脱离周期稳定在0.27 s左右。当发生沸腾危机时，汽膜厚度迅速减小，这可作为动态监测加热表面沸腾状态的依据。     

一种用于平面的电火花强化修复装置

研究了一种用于金属平面的电火花强化修复装置。经过SEM照片分析,MM200磨损试验,以及硬度梯度分布综合判断,该装置生成的强化修复层比较完整、有一定厚度,极大改善了零件表面的硬度和耐磨性。     

自适应天牛须优化与K均值聚类的图像分割算法研究

在机器识别中,图像分割是重要的一个步骤,传统分割手段存在一定缺陷。针对传统K均值聚类分割的初始聚类中心敏感的缺陷进行了优化,利用自适应天牛须优化算法,避免了这一问题。通过实验结果表明,该算法(ABASK)对图像进行分割,既可以保证图像轮廓的分割,同时还可以更多地保留图像细节。     

A novel region-based multimodal image fusion technique using improved dictionary learning

Recently, the sparse representation (SR) based algorithms have gained much attention from the researchers in the area of image fusion (IF). The building of a compact discriminative dictionary plays a vital role in the sparse-based IF techniques. In this context, an efficient multimodal IF method based on improved dictionary learning is investigated. The key contributions of this paper are: (a) An improved KSVD algorithm is suggested for the dictionary learning process, (b) to reduce the computational time, only the informative patches are selected using energy feature, and (c) a novel region-based fusion scheme is suggested for the first time for the problem on hand. The suggested technique is tested with a number of multimodal images from Harvard Medical School brain database. The results are compared with state-of-the-art multiscale transform-based methods and modified SR-based methods. Unlike earlier methods, our proposed technique generates an adaptive dictionary through selection of informative patches only. This results in a compact dictionary with improved computational efficiency. The experimental results reveal that our approach outperforms other methods. The potential application of the suggested method could be in pathological images for follow-up study and better treatment planning.     

基于修正等速运动规律的自由曲面多轴加工刀轴序列优化方法

针对自由曲面多轴加工中起始位置处刀具相对工件速度、加速度不为零导致的一定程度刚性冲击现象,提出了一种基于修正等速运动规律的刀轴序列优化方法,通过控制工件坐标系中决定刀具姿态的两个约束角,使之变化遵循修正等速运动规律,获得了切削行上平稳变化的刀轴序列,避免了由于起始位置处刀具相对工件速度、加速度不为零导致刀具不能精准到达后续加工位置的现象。算例分析表明,该方法能产生平稳且光滑的刀轴序列,可一定程度改善机床运动性能,提高加工表面质量。     

Discriminative graph convolution networks for hyperspectral image classification

Recently, the proposal of graph convolutional networks (GCN) has successfully implemented into hyperspectral image data representation and analysis. In spite of the great success, there are still several major challenges in hyperspectral image classification, including within-class diversity, and between-class similarity, which generally degenerate hyperspectral image classification performance. To address the problems, we propose a discriminative graph convolution networks (DGCN) for hyperspectral image classification. This method introduces the concepts of within-class scatter and between-class scatter, which respectively reflect the global geometric structure and discriminative information of the input space. The experimental results on the hyperspectral data sets show that the proposed method has good classification performance.     

Disassembly sequence planning using a Flatworm algorithm

Disassembly Sequence Planning (DSP) refers to a disassembly sequence based on the disassembly properties and restrictions of the product parts that meets the benefit goal. This study aims to reduce the number of changes in disassembly direction and disassembly tools so as to reduce the disassembly time. This study proposes a novel Flatworm algorithm that evolves through the regenerative properties of the flatworm. It is similar to the evolutionary concept of genetic algorithms, with evolution as the main idea, but without crossover, mutation or replication mechanisms in the evolutionary processes. Instead, it is based upon the characteristics of the growth, fracture and regeneration mechanisms of the flatworm. The Flatworm algorithm features a variety of disassembly combinations and excellent mechanisms to avoid the local optimal solution. In particular, it has the advantage of keeping a good disassembly combination from being destroyed. In this study, it is compared with two genetic algorithms and two ant colony algorithms and tested in three examples of different complexity: a ceiling fan, a printer, and 150 simulated parts. The solution searching ability and execution time are compared upon the same evaluation standard. The test results demonstrate that the novel Flatworm algorithm proposed in this study is superior to the two genetic algorithms and ant colony algorithms in solution quality.     

Inverse identification of constitutive parameters from heat source fields: A local approach applied to hyperelasticity

In this paper, a new inverse identification method of constitutive parameters is developed from full kinematic and thermal field measurements. It consists in reconstructing the heat source field from two different approaches by using the heat diffusion equation. The first one requires the temperature field measurement and the value of the thermophysical parameters. The second one is based on the kinematic field measurement and the choice of a thermo-hyperelastic model that contains the parameters to be identified. The identification is carried out at the local scale, ie, at any point of the heat source field, without using the boundary conditions. In the present work, the method is applied to the challenging case of hyperelasticity from a heterogeneous test. Due to large deformations undergone by the rubber specimen tested, a motion compensation technique is developed to plot the kinematic and the thermal fields at the same points before reconstructing the heterogeneous heat source field. In the present case, the constitutive parameter of the Neo-Hookean model has been identified, and its distribution has been characterized with respect to the strain state at the surface of a cross-shaped specimen.