Three principles for preparing Al wire with high strength and high electrical conductivity

The trade-off relation between the strength and the electrical conductivity has been a long-standing dilemma in metallic materials. In the study, three key principles, i.e. elongated grains, sharp texture and nano-scale precipitates, were presented for preparing Al wire with high strength and high electrical conductivity based on the specially designed experiments for breaking the mutually exclusive relation between the strength and the electrical conductivity. The results show that the elongated grains could lead to a higher electrical conductivity in Al wire without sacrificing the strength; while, the 111 sharp texture can efficiently strengthen the Al wire without influencing the electrical conductivity. Furthermore, nano-scale precipitates with proper size can simultaneously improve the strength and electrical conductivity of Al alloy wire. Under the guidance of the above three key principles, Al wires with high strength and high conductivity were prepared.     

Temperature-gradient induced microstructure evolution in heat-affected zone of electron beam welded Ti-6Al-4V titanium alloy

The heat-affected zone (HAZ) of electron beam welded (EBW) joint normally undergoes a unique heat-treating process consisting of rapid temperature rising and dropping stages, resulting in temperature-gradient in HAZ as a function of the distance to fusion zone (FZ). In the current work, microstructure, elements distribution and crystallographic orientation of three parts (near base material (BM) zone, mid-HAZ and near-FZ) in the HAZ of Ti-6Al-4V alloy were systematically investigated. The microstructure observation revealed that the microstructural variation from near-BM to near-FZ included the reduction of primary α (α_p) grains, the increase of transformed β structure (β_t) and the formation of various α structures. The rim-α, dendritic α and abnormal secondary α (α_s) colonies formed in the mid-HAZ, while the “ghost” structures grew in the near-FZ respectively. The electron probe microanalyzer (EPMA) and electron back-scattered diffraction (EBSD) technologies were employed to evaluate the elements diffusion and texture evolution during the unique thermal process of welding. The formation of the various α structures in the HAZ were discussed based on the EPMA and EBSD results. Finally, the nanoindentation hardness of “ghost” structures was presented and compared with nearby β_t regions.     

由文本至口形的媒体变换技术的研究

本文根据汉语的发音特点,提出了由基本音素口形参数和预先建立的口形模型来生成各种音节相应的正面口形图象的方法,从而完成由文本至口形的媒体变换,首先我们建立变形物体运动模型,然后由此构造一个口唇的动态发音模型,最后采用纹理映射技术,由基本音素口形参数和动态发音模型合成正面发音口形的图象。     

Weighted and extended total variation for image restoration and decomposition

In various information processing tasks obtaining regularized versions of a noisy or corrupted image data is often a prerequisite for successful use of classical image analysis algorithms. Image restoration and decomposition methods need to be robust if they are to be useful in practice. In particular, this property has to be verified in engineering and scientific applications. By robustness, we mean that the performance of an algorithm should not be affected significantly by small deviations from the assumed model. In image processing, total variation (TV) is a powerful tool to increase robustness. In this paper, we define several concepts that are useful in robust restoration and robust decomposition. We propose two extended total variation models, weighted total variation (WTV) and extended total variation (ETV). We state generic approaches. The idea is to replace the TV penalty term with more general terms. The motivation is to increase the robustness of ROF (Rudin, Osher, Fatemi) model and to prevent the staircasing effect due to this method. Moreover, rewriting the non-convex sublinear regularizing terms as WTV, we provide a new approach to perform minimization via the well-known Chambolle's algorithm. The implementation is then more straightforward than the half-quadratic algorithm. The behavior of image decomposition methods is also a challenging problem, which is closely related to anisotropic diffusion. ETV leads to an anisotropic decomposition close to edges improving the robustness. It allows to respect desired geometric properties during the restoration, and to control more precisely the regularization process. We also discuss why compression algorithms can be an objective method to evaluate the image decomposition quality.     

Associating visual textures with human perceptions using genetic algorithms

This paper deals with an approach allowing to associate visual textures with given human perceptions. Hereby, based on a forward model associating human perceptions for given visual textures, the deduction of an reverse process is presented which is able to associate and characterize visual textures for given human perceptions. For doing so, we propose a constraint-based genetic algorithm approach, which is able to minimize a specific optimization problem containing constraints in form of band-widths for valid individuals (low level features extracted from textures) in a population. The constraints are determined by relationships between (low level) features characterizing textures in form of high-dimensional approximation models. Additionally, in each iteration step checking for valid individuals is carried out with a texture/non-texture classifier or by using a convex hull over a set of valid textures. The whole approach is evaluated based on a real-world texture set used as a start population in the genetic algorithm and by defining various kinds of human perceptions (for which textures are sought) represented by adjective vectors in the aesthetic space. The generated individuals (low level feature vectors) have a high level of fitness (they are quite close to the pre-defined adjective vectors) and a small distance to the initial population. The textures synthesized based on the generated individuals are visualized and compared with textures synthesized by a time-intensive direct texture mixing and re-combination method based on a real-world texture data base.     

论Photoshop中三维立体效果的营造

该文探讨了在Photoshop中如何通过作品构成元素的变化关系、光线阴影效果和肌理材质的应用营造三维立体效果,从而创造出更富有吸引力、感染力和想象力的作品.     

Automatic joint classification and segmentation of whole cell 3D images

We present a machine learning tool for automatic texton-based joint classification and segmentation of mitochondria in MNT-1 cells imaged using ion-abrasion scanning electron microscopy (IA-SEM). For diagnosing signatures that may be unique to cellular states such as cancer, automatic tools with minimal user intervention need to be developed for analysis and mining of high-throughput data from these large volume data sets (typically ). Challenges for such a tool in 3D electron microscopy arise due to low contrast and signal-to-noise ratios (SNR) inherent to biological imaging. Our approach is based on block-wise classification of images into a trained list of regions. Given manually labeled images, our goal is to learn models that can localize novel instances of the regions in test datasets. Since datasets obtained using electron microscopes are intrinsically noisy, we improve the SNR of the data for automatic segmentation by implementing a 2D texture-preserving filter on each slice of the 3D dataset. We investigate texton-based region features in this work. Classification is performed by k-nearest neighbor (k-NN) classifier, support vector machines (SVMs), adaptive boosting (AdaBoost) and histogram matching using a NN classifier. In addition, we study the computational complexity vs. segmentation accuracy tradeoff of these classifiers. Segmentation results demonstrate that our approach using minimal training data performs close to semi-automatic methods using the variational level-set method and manual segmentation carried out by an experienced user. Using our method, which we show to have minimal user intervention and high classification accuracy, we investigate quantitative parameters such as volume of the cytoplasm occupied by mitochondria, differences between the surface area of inner and outer membranes and mean mitochondrial width which are quantities potentially relevant to distinguishing cancer cells from normal cells. To test the accuracy of our approach, these quantities are compared against manually computed counterparts. We also demonstrate extension of these methods to segment 3D images obtained using electron tomography.