Improved Actor Relation Graph based Group Activity Recognition

Video understanding is to recognize and classify different actions or activities appearing in the video. A lot of previous work, such as video captioning, has shown promising performance in producing general video understanding. However, it is still challenging to generate a fine-grained description of human actions and their interactions using state-of-the-art video captioning techniques. The detailed description of human actions and group activities is essential information, which can be used in real-time CCTV video surveillance, health care, sports video analysis, etc. This study proposes a video understanding method that mainly focused on group activity recognition by learning the pair-wise actor appearance similarity and actor positions. We propose to use Normalized cross-correlation (NCC) and the sum of absolute differences (SAD) to calculate the pair-wise appearance similarity and build the actor relationship graph to allow the graph convolution network to learn how to classify group activities. We also propose to use MobileNet as the backbone to extract features from each video frame. A visualization model is further introduced to visualize each input video frame with predicted bounding boxes on each human object and predict individual action and collective activity

A Survey of Multimedia Technologies and Robust Algorithms

Multimedia technologies are now more practical and deployable in real life, and the algorithms are widely used in various researching areas such as deep learning, signal processing, haptics, computer vision, robotics, and medical multimedia processing. This survey provides an overview of multimedia technologies and robust algorithms in multimedia data processing, medical multimedia processing, human facial expression tracking and pose recognition, and multimedia in education and training. This survey will also analyze and propose a future research direction based on the overview of current robust algorithms and multimedia technologies. We want to thank the research and previous work done by the Multimedia Research Centre (MRC), the University of Alberta, which is the inspiration and starting point for future research.Comment: arXiv admin note: text overlap with arXiv:2010.1296

A Simple Strategy for the Simultaneous Determination of Dopamine, Uric Acid, L-Tryptophan and Theophylline Based on a Carbon Nano-Onions Modified Electrode

In this work, carbon nano-onions (CNOs) with particle sizes of 5–10 nm were prepared by the multi-potential step method. High-resolution transmission electron microscopy, infrared spectroscopy and Raman spectroscopy characterize the effective synthesis of CNOs. CNOs/GCEs were prepared by depositing the prepared CNOs onto glassy carbon electrodes (GCEs) by a drop-coating method. Examination of the electrocatalytic activity of the CNOs/GCE sensor by simultaneously detecting dopamine (DA), uric acid (UA), L-tryptophan (Trp) and theophylline (TP) using a differential pulse voltammetry technique. The results showed that the linear ranges of DA, UA, Trp and TP were DA 0.01–38.16 μM, UA 0.06–68.16 μM, Trp 1.00–108.25 μM, and TP 8.16–108.25 μM, and the detection limits (S/N = 3) were 0.0039 μM, 0.0087 μM, 0.18 μM and 0.35 μM, respectively. The CNOS/GCE sensor had good stability and could be used for the detection of actual samples

Vanadium Dioxide-Based Terahertz Metamaterial Devices Switchable between Transmission and Absorption

Terahertz metamaterial plays a significant role in the development of imaging, sensing, and communications. The function of conventional terahertz metamaterials was fixed after fabrication. They can only achieve a single function and do not have adjustable characteristics, which greatly limits the scalability and practical application of metamaterial. Here, we propose a vanadium dioxide-based terahertz metamaterial device, which is switchable between being a transmitter and an absorber. The transmission and absorption characteristics and temperature tunable properties of phase change metamaterials in the terahertz band were investigated. As the temperature of vanadium dioxide is varied between 20 °C and 80 °C, the device can switch between transmission and quad-band resonance absorption at the terahertz frequency range, with a high transmission rate of over 80% and a peak absorbance of 98.3%, respectively. In addition, when the device acts as an absorber, the proposed metamaterial device is tunable, and the modulation amplitude can reach 94.3%; while the device is used as a transmissive device, the modulation amplitude of the transmission peak at 81%. The results indicate that the proposed metamaterial device can promote the applications of terahertz devices, such as switching, modulation, and sensing

3D printed hierarchical spinel monolithic catalysts for highly efficient semi-hydrogenation of acetylene

Porous monolithic catalysts with high specific surface areas, which can not only facilitate heat/mass transfer, but also help to expose active sites, are highly desired in strongly exothermic or endothermic gas-solid phase reactions. In this work, hierarchical spinel monolithic catalysts with a porous woodpile architecture were fabricated via extrusion-based three-dimensional (3D) printing (direct ink writing, DIW in brief) of aluminate-intercalated layered double hydroxide (AI-LDH) followed by low temperature calcination. The intercalation of aluminate in LDH is found crucial to tailor the M2+/Al3+ ratio, integrate LDH nanosheets into monolithic catalyst, and enable the conversion of LDH to spinel at the temperature as low as 500 °C with high specific surface areas (> 350 m2/g). The rapid mass/heat transfer resulted from the versatile 3D network at macroscale and the highly dispersed and fully exposed active sites benefited from the porous structure at microscale endow the 3D-printed Pd loaded spinel MgAl-mixed metal oxide (3D-AI-Pd/MMO) catalyst with excellent catalytic performance in semi-hydrogenation of acetylene, achieving 100% conversion at 60 °C with more than 84% ethylene selectivity.This research was supported by the National Natural Science Foundation of China (Nos. 21935001, 22005022 and 22175012), the program for Changjiang Scholars and Innovation Research Team in the University (No. IRT1205), the starting-up foundation from Beijing University of Chemical Technology (No. BUCTRC202025), the fellowship of China Postdoctoral Science Foundation (No. 2020M670107), the Natural Science Foundation of Beijing, China (No. 2214062), the Fundamental Research Funds for the Central Universities, and the long-term subsidy mechanism from the Ministry of Finance and the Ministry of Education of PRC