Adaptive reversible data hiding for JPEG images with multiple two-dimensional histograms

Joint photographic experts group (JPEG) can provide good quality with small file size but also eliminate extensively the redundancies of images. Therefore, hiding data into JPEG images in terms of maintaining high visual quality at small file sizes has been a great challenge for researchers. In this paper, an adaptive reversible data hiding method for JPEG images containing multiple two-dimensional (2D) histograms is proposed. Adaptability is mainly reflected in three aspects. The first one is to preferentially select sharper histograms for data embedding after $K$ histograms are established by constructing the $k$th ($k\in \{1,2,\dots ,K\}$) histogram using the $k$th non-zero alternating current (AC) coefficient of all the quantized discrete cosine transform blocks. On the other hand, to fully exploit the strong correlation between coefficients of one histogram, the smoothness of each coefficient is estimated by a block smoothness estimator so that a sharply-distributed 2D-histogram is constructed by combining two coefficients with similar smoothness into a pair. The pair corresponding to low complexity is selected priorly for data embedding, leading to high embedding performance while maintaining low file size. Besides, we design multiple embedding strategies to adaptively select the embedding strategy for each 2D histogram. Experimental results demonstrate that the proposed method can achieve higher rate–distortion performance which maintaining lower file storage space, compared with previous studies.     

Probing the effect of R-cation radii on structural,vibrational, optical,and dielectric properties of rare earth (R=La,Pr, Nd) aluminates

The present study correlates the effect of R-cation radii on structural, vibrational, optical, and dielectric properties of rhombohedral rare earth aluminates RAlO₃ (R = La, Pr, Nd). The polycrystalline samples of RAlO₃ have been synthesized using sol-gel synthesis technique. Pure rhombohedral phase of RAlO₃ samples has been confirmed with X-ray diffraction. Systematic decrements in the lattice parameter, bond length, and bond angle have been observed, giving rise to structural distortion due to decrease in ionic radii of R-cation. The phononic properties of RAlO₃ have been investigated through Raman spectroscopy, where the degree of distortion of AlO₆ octahedra can be analyzed with the peak position of E_g and A_1g modes. An increase in the energy bandgap with decreasing R-cation radii shows an interconnection with the decrease in Al–O bond length. Interestingly, the decreasing dielectric constant with decreasing ionic radii of R-cation has been correlated with the difference in electronegativity of cation(R³⁺)-anion(O^2?) pair. Also, a positive linear relationship between dielectric constant and energy bandgap has been investigated using Penn model.     

聚类混合型数据的密度峰值改进算法

聚类混合型数据，通常是依据样本属性类别的不同分别进行评价。但这种将样本属性划分到不同子空间中分别度量的方式，割裂了样本属性原有的统一性；导致对样本个体的相似性评价产生了非一致的度量偏差。针对这一问题，提出以二进制编码样本属性，再由海明差异对属性编码施行统一度量的新的聚类算法。新算法通过在统一的框架内对混合型数据实施相似性度量，避免了对样本属性的切割，在此基础上又根据不同属性的性质赋予其不同的权重，并以此评价样本个体之间的相似程度。实验结果表明，新算法能够有效地聚类混合型数据；与已有的其他聚类算法相比较，表现出更好的聚类准确率及稳定性。     

镜头成像畸变的MTF像高测试法研究

为了解决传统标板拍摄测试广角镜头成像畸变的不准确、复现性差问题,提出了基于调制传递函数(MTF)理论的成像畸变测试方法。通过研究镜头畸变测试国内外的研究现状,重点分析了成像镜头特别是广角镜头采用传统标板拍摄测试成像畸变的缺陷。提出了一种通过测试镜头轴上有效焦距和不同角度的离轴有效焦距,并导入畸变计算公式从而得到镜头成像相对畸变的MTF测试方法。研究结果表明,采用MTF测试方法可以实现对镜头成像畸变的快速、准确的测量。     

Control Model for Large‐Sized Gantry Type Linear Motor Slider

At present, many industrial carrier devices utilize linear motor sliders. However, a heavier load requires a linear motor (which is an example of a direct drive device) to get higher power, compared with a rotary motor with a ball screw slider (which is an example of an indirect drive device). In order to obtain higher power at a lower cost, a linear slider with multiple motors can be utilized, for example, a gantry type linear motor slider. Moving the gantry type slider requires two linear motors that are set up in parallel to enable synchronization control. Some conventional synchronization control methods have been proposed for the parallel twin linear slider; however, a large‐scaled gantry type linear motor slider has two unique problems: mechanical distortion caused by the limitations of installation environment and coupling caused by joints with low stiffness. This paper proposes a control model to solve these problems, and an identification method of each parameter. Furthermore, the effectiveness of the control model is verified by comparison with simulation results and experimental results.     

Features of crystal structures and thermo-mechanical properties of weberites RE3NbO7 (RE=La,Nd, Sm,Eu, Gd) ceramics

The features of crystal structures, thermo-mechanical properties and their dominant mechanisms of weberites RE₃NbO₇ were studied as high-temperature oxides. We concentrated on connections between structures and thermo-mechanical properties, the influences of bond lengths, lattice distortion degrees and microstructures on these properties were estimated. The shortening of bond length and increment of bonding strength would lead to the increase of mechanical properties. The Vickers hardness (4.5-7.8 GPa) and toughness (0.5-1.6 MPa·m^1/2) of weberites RE₃NbO₇ are enhanced by grain refinement and increment of bond strength, while crystal structures, bond lengths, and lattice distortion degrees influenced their Young's modulus (100-170 GPa). Nano-indentation was applied to test the influence of microstructures on modulus and hardness. The dominant mechanisms for mechanical properties and thermal conductivity were proposed, which was conducive to properties tailoring and engineering applications of weberites RE₃NbO₇ oxides.     

限制失真的网格参数化方法

针对当前网格参数化效率较低、映射失真较严重的问题，提出一种限制失真的网格参数化方法。首先，预处理原始网格模型。输入原3D网格模型，采用Half-Edge数据结构来重新组织网格并切割网格模型产生相应的切缝；构建Tutte映射把3D网格映射到一个2D凸多边形域，即构建2D网格模型。然后，进行限制失真的网格参数化计算。将Tutte映射后的2D网格模型作为限制失真计算的初始数据，建立相对于原3D模型网格的失真度量函数；求得该度量函数的最小值点，即为映射后的网格坐标集合；将映射后的网格作为限制失真映射的输入网格，设定迭代终止条件，循环迭代直至迭代结束，得到收敛的最优网格坐标；在计算映射失真度时，针对等距映射失真采用Dirichlet能量函数度量，针对共形映射失真采用尽可能等距（MIPS）能量函数度量；在求解映射失真度量函数的最小值点时采用代理函数法结合组合牛顿法的最优解方法。最终，实现了该方法并开发了一个原型系统。在原型系统中，分别设计了限制等距失真和限制共形失真的网格参数化实验，对程序执行时间和失真能量下降情况进行了统计和对比，提供了相应的纹理映射效果展示。实验数据表明，所提出的方法执行效率高、映射失真能量下降快，最优值收敛质量稳定；纹理映射时纹理着色均匀、布局紧致、线条均匀，符合实际应用的标准。     

Distance and similarity measures of Pythagorean fuzzy sets based on the Hausdorff metric with application to fuzzy TOPSIS

Pythagorean fuzzy sets (PFSs) were proposed by Yager in 2013 to treat imprecise and vague information in daily life more rigorously and efficiently with higher precision than intuitionistic fuzzy sets. In this paper, we construct new distance and similarity measures of PFSs based on the Hausdorff metric. We first develop a method to calculate a distance between PFSs based on the Hasudorff metric, along with proving several properties and theorems. We then consider a generalization of other distance measures, such as the Hamming distance, the Euclidean distance, and their normalized versions. On the basis of the proposed distances for PFSs, we give new similarity measures to compute the similarity degree of PFSs. Some examples related to pattern recognition and linguistic variables are used to validate the proposed distance and similarity measures. Finally, we apply the proposed methods to multicriteria decision-making by constructing a Pythagorean fuzzy Technique for Order Preference by Similarity to an Ideal Solution and then present a practical example to address an important issue related to social sector. Numerical results indicate that the proposed methods are reasonable and applicable and also that they are well suited in pattern recognition, linguistic variables, and multicriteria decision-making with PFSs.     

Research on the parallelization of image quality analysis algorithm based on deep learning

Image quality assessment is an indispensable in computer vision applications, such as image classification, image parsing. With the development of Internet, image data acquisition becomes more conveniently. However, image distortion is inevitable due to imperfect image acquisition system, image transmission medium and image recording equipment. Traditional image quality assessment algorithms only focus on low-level visual features such as color or texture, which could not encode high-level features effectively. CNN-based methods have shown satisfactory results in image quality assessment. However, existing methods have problems such as incomplete feature extraction, partial image block distortion, and inability to determine scores. So in this paper, we propose a novel framework for image quality assessment based on deep learning. We incorporate both low-level visual features and high-level semantic features to better describe images. And image quality is analyzed in a parallel processing mode. Experiments are conducted on LIVE and TID2008 datasets demonstrate the proposed model can predict the quality of the distorted image well, and both SROCC and PLCC can reach 0.92 or higher.