Beijing University of Technology

About: Beijing University of Technology is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: Microstructure & Computer science. The organization has 31929 authors who have published 31987 publications receiving 352112 citations. The organization is also known as: Běijīng Gōngyè Dàxué & Beijing Polytechnic University.

Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data

Abstract: In this paper, we investigate into the problem of image quality assessment (IQA) and enhancement via machine learning. This issue has long attracted a wide range of attention in computational intelligence and image processing communities, since, for many practical applications, e.g., object detection and recognition, raw images are usually needed to be appropriately enhanced to raise the visual quality (e.g., visibility and contrast). In fact, proper enhancement can noticeably improve the quality of input images, even better than originally captured images, which are generally thought to be of the best quality. In this paper, we present two most important contributions. The first contribution is to develop a new no-reference (NR) IQA model. Given an image, our quality measure first extracts 17 features through analysis of contrast, sharpness, brightness and more, and then yields a measure of visual quality using a regression module, which is learned with big-data training samples that are much bigger than the size of relevant image data sets. The results of experiments on nine data sets validate the superiority and efficiency of our blind metric compared with typical state-of-the-art full-reference, reduced-reference and NA IQA methods. The second contribution is that a robust image enhancement framework is established based on quality optimization. For an input image, by the guidance of the proposed NR-IQA measure, we conduct histogram modification to successively rectify image brightness and contrast to a proper level. Thorough tests demonstrate that our framework can well enhance natural images, low-contrast images, low-light images, and dehazed images. The source code will be released at https://sites.google.com/site/guke198701/publications .

Single-atomic cobalt sites embedded in hierarchically ordered porous nitrogen-doped carbon as a superior bifunctional electrocatalyst.

Abstract: Exploring efficient and cost-effective catalysts to replace precious metal catalysts, such as Pt, for electrocatalytic oxygen reduction reaction (ORR) and hydrogen evolution reaction (HER) holds great promise for renewable energy technologies. Herein, we prepare a type of Co catalyst with single-atomic Co sites embedded in hierarchically ordered porous N-doped carbon (Co-SAS/HOPNC) through a facile dual-template cooperative pyrolysis approach. The desirable combination of highly dispersed isolated atomic Co-N4 active sites, large surface area, high porosity, and good conductivity gives rise to an excellent catalytic performance. The catalyst exhibits outstanding performance for ORR in alkaline medium with a half-wave potential (E1/2) of 0.892 V, which is 53 mV more positive than that of Pt/C, as well as a high tolerance of methanol and great stability. The catalyst also shows a remarkable catalytic performance for HER with distinctly high turnover frequencies of 0.41 and 3.8 s−1 at an overpotential of 100 and 200 mV, respectively, together with a long-term durability in acidic condition. Experiments and density functional theory (DFT) calculations reveal that the atomically isolated single Co sites and the structural advantages of the unique 3D hierarchical porous architecture synergistically contribute to the high catalytic activity.

Emerging Nonaqueous Aluminum-Ion Batteries: Challenges, Status, and Perspectives.

Abstract: Aluminum-ion batteries (AIBs) are regarded as viable alternatives to lithium-ion technology because of their high volumetric capacity, their low cost, and the rich abundance of aluminum. However, several serious drawbacks of aqueous systems (passive film formation, hydrogen evolution, anode corrosion, etc.) hinder the large-scale application of these systems. Thus, nonaqueous AIBs show incomparable advantages for progress in large-scale electrical energy storage. However, nonaqueous aluminum battery systems are still nascent, and various technical and scientific obstacles to designing AIBs with high capacity and long cycling life have not been resolved until now. Moreover, the aluminum cell is a complex device whose energy density is determined by various parameters, most of which are often ignored, resulting in failure to achieve the maximum performance of the cell. The purpose here is to discuss how to further develop reliable nonaqueous AIBs. First, the current status of nonaqueous AIBs is reviewed based on statistical data from the literature. The influence of parameters on energy density is analyzed, and the current situation and existing problems are summarized. Furthermore, possible solutions and concerns regarding the construction of reliable nonaqueous AIBs are comprehensively discussed. Finally, future research directions and prospects in the aluminum battery field are proposed.