Harbin Institute of Technology

About: Harbin Institute of Technology is a education organization based out in Harbin, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 88259 authors who have published 109297 publications receiving 1603393 citations. The organization is also known as: HIT.

Review on cyber-physical systems

Abstract: Cyber-physical systems U+0028 CPS U+0029 are complex systems with organic integration and in-depth collaboration of computation, communications and control U+0028 3C U+0029 technology. Subject to the theory and technology of existing network systems and physical systems, the development of CPS is facing enormous challenges. This paper first introduces the concept and characteristics of CPS and analyzes the present situation of CPS researches. Then the development of CPS is discussed from perspectives of system model, information processing technology and software design. At last it analyzes the main obstacles and key researches in developing CPS.

Z-scheme mesoporous photocatalyst constructed by modification of Sn3O4 nanoclusters on g-C3N4 nanosheets with improved photocatalytic performance and mechanism insight

Abstract: Antibiotic drugs have become the important organic pollutants in the water resources, the high-efficient removal of which is one of the foremost works for protecting water environment. The new Z-scheme mes-Sn3O4/g-C3N4 heterostructure was obtained in present work, compared with single g-C3N4, which exhibits more superior photocatalytic performance for degrading and mineralizing tetracycline hydrochloride in water. The investigations of microstructure, physical properities and photoelectrochemical behaviors indicate that the modification effect mesoporous Sn3O4 on the surface of g-C3N4 nanosheets fabricates close heterostructure, which enlarges distinctly the specific surface area and improves dramatically the separation efficiency of charge carriers. Furthermore, the possible photocatalytic reaction mechanisms including transfer behaviors of charge carriers, generation of reactive species, degradation intermediate products of TC-HCl are also revealed in depth.

Edge-Enhanced GAN for Remote Sensing Image Superresolution

Abstract: The current superresolution (SR) methods based on deep learning have shown remarkable comparative advantages but remain unsatisfactory in recovering the high-frequency edge details of the images in noise-contaminated imaging conditions, e.g., remote sensing satellite imaging. In this paper, we propose a generative adversarial network (GAN)-based edge-enhancement network (EEGAN) for robust satellite image SR reconstruction along with the adversarial learning strategy that is insensitive to noise. In particular, EEGAN consists of two main subnetworks: an ultradense subnetwork (UDSN) and an edge-enhancement subnetwork (EESN). In UDSN, a group of 2-D dense blocks is assembled for feature extraction and to obtain an intermediate high-resolution result that looks sharp but is eroded with artifacts and noises as previous GAN-based methods do. Then, EESN is constructed to extract and enhance the image contours by purifying the noise-contaminated components with mask processing. The recovered intermediate image and enhanced edges can be combined to generate the result that enjoys high credibility and clear contents. Extensive experiments on Kaggle Open Source Data set , Jilin-1 video satellite images, and Digitalglobe show superior reconstruction performance compared to the state-of-the-art SR approaches.