The As-prepared surfaces of C-axis-oriented Nd1Ba2Cu3Oy thin films characterized using scanning probe microscopes

Recently, superconducting Nd₁Ba₂Cu₃O_y (Ndl23) thin films with high superconducting transition temperature (T _c) have been successfully fabricated at our institute employing the standard laser ablation method. In this paper, we report the results of surface characterization of the Nd123 thin films using an ultrahigh vacuum scanning tunneling microscope/spectroscopy (UHV-STM/STS) and an atomic force microscope (AFM) system operated in air. Clear spiral pattern is observed on the surfaces of Nd123 thin films by STM and AFM, suggesting that films are formed by two-dimensional island growth mode. Contour plots of the spirals show that the step heights of the spirals are not always the integer or half-integer number of thec-axis parameter of the structure. This implies that the surface natural termination layer of the films may not be unique. This result is supported byI-V STS measurements. The surface morphology of the Nd123 thin films is compared with that of thec-axis-oriented Y₁Ba₂Cu₃S_y thin films. Surface atomic images of the as-prepared Nd123 thin films are obtained employing both STM and AFM. STS measurements show that most of the surfaces are semiconductive. The results of STS measurements together with the fact that we are able to see the surface atomic images using scanning probe microscopes suggest that exposure to air does not cause serious degradation to the as-prepared surfaces of Nd123 thin films.     

Martha J. Farah.

Recognizes Martha J. Farah for rigorous empirical and theoretical analysis of visual cognition, in which understanding of normal function and analysis of neurological deficits illuminate and strengthen one another. Applying diverse experimental techniques within an integrated approach to the study of mind and brain, she has sharpened and helped to answer fundamental questions about how humans generate and manipulate visual images, recognize objects, and attend to positions in space. Along with a citation, a biography is presented for Farah, as well as a bibliography of her works. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Blind omnidirectional image quality assessment with representative features and viewport oriented statistical features

With the development of information technologies, various types of streaming images are generated, such as videos, graphics, Virtual Reality (VR)/omnidirectional images (OIs), etc. Among them, the OIs usually have a broader view and a higher resolution, which provides human an immersive visual experience in a head-mounted display. However, the current image quality assessment works cannot achieve good performance without considering representative human visual features and visual viewing characteristics of OIs, which limited OIs’ further development. Motivated by the above problem, this work proposes a blind omnidirectional image quality assessment (BOIQA) model based on representative features and viewport oriented statistical features. Specifically, we apply the local binary pattern operator to encoder the cross-channel color information, and apply the weighted LBP to extract the structural features. Then the local natural scene statistics (NSS) features are extracted by using the viewport sampling to boost the performance. Finally, we apply support vector regression to predict the OIs’ quality score, and experimental results on CVIQD2018 and OIQA2018 Databases prove that the proposed model achieves better performance than state-of-the-art OIQA models.     

Horizontal Voting Ensemble Based Predictive Modeling System for ColonCancer

Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance according to the combined models from the last epochs of the proposed architecture. Ten thousand (10000) microscopic images are taken to test the classification performance of the proposed PMS with the HVE method. The microscopic images obtained from the colon tissues are classified into ACA or benign by the proposed PMS. Results prove that the proposed PMS has ~8% performance improvement over the architecture without using the HVE method. The proposed PMS for colon cancer reduces the misclassification rate and attains 99.2% of sensitivity and 99.4% of specificity. The overall accuracy of the proposed PMS is 99.3%, and without using the HVE method, it is only 91.3%.     

基于遗传算法的直线光流刚体运动重建

建立一种新的基于直线光流场从单目图像序列恢复刚体运动和结构的模型,推导出直线光流场与刚体的运动参数之间的关系,用2个二阶线性微分方程表达这种关系,并提出一种求解刚体运动参数的遗传算法,只需要获得图像平面的2条直线光流即可求解刚体的旋转参数,并用合成图像测试了该算法的有效性。     

Online face recognition system based on multi-view algorithm and Kernel PCA

An online face recognition system is presented in the paper. To online face recognition system, we should consider the recognition rate, the image compression and image size. In the paper we researched the innovation technologies for face recognition system, including Kernel Principal Component Analysis （Kernel PCA）, Delta low-pass wavelet filter, and face recognition algorithm using multiple images. Kernel PCA is derived to classify the characteristics of training images in the database. Delta low-pass wavelet filter is used to reduce the image size. A face recognition algorithm using multiple images is presented to improve the recognition rate. Simulation experiment shows that in the case of packet loss recognition rate is improved highly.     

数字虚拟图像与实拍影像的整合

数字虚拟图像与实拍影像的整合是现阶段动态影像创作的一种趋势,它突破了单一的影像形式,融会了两种不同形态的影像语言,不仅为创作者提供了无限的创作空间,并且开拓了新的审美情趣,使影像在创作观念与形式语言表现上发生了许多变化,值得我们思考与研究。本文通过对数字虚拟图像与实拍影像整合的含义、目的与价值三个方面的论述,希望可以引起对新的影像形式语言理论研究的思考,开拓影像形式语言的多元化。     

A Unified Theory of Uncalibrated Stereo for Both Perspective and Affine Cameras

This paper addresses the recovery of structure and motion from uncalibrated images of a scene under full perspective or under affine projection. Particular emphasis is placed on the configuration of two views, while the extension to $N$ views is given in Appendix. A unified expression of the fundamental matrix is derived which is valid for any projection model without lens distortion (including full perspective and affine camera). Affine reconstruction is considered as a special projective reconstruction. The theory is elaborated in a way such that everyone having knowledge of linear algebra can understand the discussion without difficulty. A new technique for affine reconstruction is developed, which consists in first estimating the affine epipolar geometry and then performing a triangulation for each point match with respect to an implicit common affine basis.