The infant-size humanoid robot THBIP-II, Tsinghua University biped robot II, is the second generation prototype of Tsinghua biped robots. THBIP-II is 75 cm tall, weighs 18 Kg, and has 24 degrees of freedom (DOF). This paper addresses the design, mechanical modeling, gait planning method, and global footstep planning method of the robot. First the humanoid mechatronics system and its kinematics and dynamics modeling are prescribed. Second, the gait planning algorithm developed for human-like walking is presented. Third, a footstep planning method for global navigation is addressed. Finally, the walking experiments are given to verify the validity of the above aspects.

All-inorganic perovskites have emerged in the field of optoelectronic devices for their excellent light absorption and energy conversion efficiencies, as well as their superior stability compared to organic−inorganic perovskites. The two-dimensional (2D) all-inorganic perovskites have a higher exciton binding energy and carrier recombination efficiency than their bulk counterparts due to the quantum confinement effect, which indicts high strong light−matter interactions and is suitable for special integrated optoelectronics such as a micro laser or quick-response photodetector. However, it is difficult to fabricate a 2D large-sized sample with high crystal quality due to the nonlayered structure, which limits its further research and practical application. In this work, based on an atmospheric pressure chemical vapor deposition strategy combining a space-confined method and van der Waals epitaxy, the synergistic effect of these two techniques results in large-sized ultrathin all-inorganic CsPbI 3 perovskite nanosheets for which the lateral dimension can exceed 50 μm while the smallest thickness can reach 3 nm. The high crystal quality of the square-like samples has been confirmed by a microstructure characterization, while the corresponding performances like long carrier life (360 ns), high resistivity, and good stability were also verified, implying great promise for their applications in high-performance integrated optoelectronics. This method may pave the way for a uniform fabrication of other 2D nonlayered materials as well.

Reforming methane to produce syngas is a subject that generates considerable interest. The process requires catalysts that possess high-performance active sites to activate stable C–H bonds. Herein, we report a facile synthetic strategy to prepare Ni-based catalysts by complexation–impregnation (Ni-G/SiO2-C) and precipitation–impregnation (Ni-G/SiO2-P) methods using glycine as a complexing agent. The particle size of Ni in both types of catalysts is decreased by adding glycine in the preparation process. Nevertheless, the preparation methods and amount of glycine play a significant role in the particle size and distribution of Ni over the Ni-based catalysts. The smaller particle size and narrower distribution of Ni were obtained in the Ni-G/SiO2-P catalyst. The catalysts were comparatively tested for carbon-dioxide reforming of methane (CDR). Ni-G/SiO2-P showed better CDR performance than Ni-G/SiO2-C and Ni/SiO2 and increased stability because of the smaller particle size and narrower distribution of Ni. Moreover, a high-performance Ni-based catalyst was prepared by optimizing the amount of glycine added. An unobservable deactivation was obtained over Ni-G-2/SiO2-P and Ni-G-3/SiO2-P for CDR during TOS = 20 h. Thus, a new promising method is described for the preparation of Ni-based catalysts for CDR.

In this paper, we proposed a new video quality metric model, which describe the video quality feature using quaternion matrix. The four parts of the quaternion are brightness, chrominance, contour, and inter frame residual, respectively. The feature value of each block is computed from quaternion model by singular value decomposition. In addition we extract gray-level co-occurrence matrix (GLCM) of each block, then calculate differential entropy of GLCM as the weight of the block. The algorithm is tested on the video quality expert group (VQEG) Phase I FR-TV test data set.Experiments show that it has good correlation with perceived video quality. Keywords:Video quality assessment; quaternion; Gray-Level Co-occurrence Matrix; video quality expert group (VQEG) IntroductionDigital videos are increasingly using in people's day-to-day lives. There are many applications of videos such as internet videos, digital television, video conferencing, and so on. Methods for evaluating video quality are become more and more important to maintain the quality of internet service, or to evaluate the perfonnance of the compression. The best method to evaluate quality of videos is subject evaluation, but it is complex and much time cost. The objective evaluation methods become a focus of the video evaluation.In this paper, we describe the quality information of videos using quaternion matrix, which include four parts to represent main features of the video. According to human visual theory, contour information and surface infonnation are important in distinguishing objects[ I ] [2]. In the quaternion model, chrominance information also used to describe contour and surface feature in three parts, not only luminance infonnation. inter-trame-difference (TFD) is used to describe temporal domain feature of the videos. In 978-1-4673-4685-6/12/$31.00 ©2012 IEEE 193 addition, we calculate differential entropy of the gray-level co-occurrence matrix [3] [4] as the weight of the block, to evaluate level of surface detail of blocks. Finally, The quaternion is calculated by singular value decomposition to measure the the quality value of the video. Experiments show this evaluation model is superior to the traditional method, such as MSE, PSNR and VSSIM [5] .The rest of the paper is organized as follows. In section 2, we give a brief introduction about Quaternion matrix and singular value decomposition (SVD); in section 3, we describe how to build quaternion matrix for video quality assessment; section 4 describes how to compute differential entropy of the gray-level co-occurrence matrix as the weight of a block; section 5 gives out the steps to calculate feature value of the videos; in section 6, we compare the results of different video quality assessment models tested on the video quality experts group (VQEG) Phase I FR-TV video dataset; finally, Section 7 draws conclusions. Quaternion and singular value decompositionA quaternion matrix Q is made of one real part and three imaginary parts: Q = a + bi + cj + dk (I) Where i, j, k obey the rules ...