An artificial stent implantation is one of the most effective ways to treat coronary artery diseases. It is vital in vascular medical imaging, such as intravascular optical coherence tomography (IVOCT), to be able to track the position of stents in blood vessels effectively. We trained two models, the “You Only Look Once” version 3 (YOLOv3) and the Region-based Fully Convolutional Network (R-FCN), to detect metal support struts in IVOCT, respectively. After rotating the original images in the training set for data augmentation, and modifying the scale of the conventional anchor box in both two algorithms to fit the size of the target strut, YOLOv3 and R-FCN achieved precision, recall, and AP all above 95% in 0.4 IoU threshold. And R-FCN performs better than YOLOv3 in all relevant indicators.

Network security situation awareness is a critical basis for security solutions because it displays the target system’s security state by assessing actual or possible cyber-attacks in the target system. Aiming at the security and stability of global information flow, this paper studies the perception and measurement of the overall situation of network security. Through the Scrappy web crawler framework, data were collected from several Zhiming network security event websites, and based on the vulnerability database of China Computer Network Intrusion Prevention Center, the network security event database was designed and established, which enriched the data of situational awareness research. This study investigates the analysis and processing of network security events, a crucial parameter in the stage of security insight and perception, and builds and implements a text-based network security event analysis tool. By designing a network security event analysis tool based on text processing, the data cleaning of network security time text information is completed, and a set of network security event processing solutions with high applicability and comprehensiveness are formed. Statistical experimental results show that the network security event database built based on the crawler algorithm contains 43,848 pieces of data, which increases the capacity by 12.79% and 29.33% compared with the traditional algorithm, and reduces the reading time by 63.5% and 87.2%.

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5G wireless mobile communication system is faced with massive equipment access, information security and effective transmission is worth paying attention to. Wireless physical layer security mainly uses encryption principle to enhance the security of information transmission, while time reversal technology combines its electromagnetic characteristics and physical channel characteristics to improve the security performance of wireless communication system. In this paper, a signal transmission model of wireless multi-antenna communication system based on time reversal cavity is proposed and white Gaussian noise is introduced. The simulation results show that the space-time focusing characteristics of time reversal cavity can make the signal energy more concentrated on the target user, which can not only effectively alleviate the communication quality problems caused by multipath effect, but also ensure the security of information transmission process.

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