The tracking of a particular pedestrian is an important issue in computer vision to guarantee societal safety. Due to the limited computing performances of unmanned aerial vehicle (UAV) systems, the Correlation Filter (CF) algorithm has been widely used to perform the task of tracking. However, it has a fixed template size and cannot effectively solve the occlusion problem. Thus, a tracking-by-detection framework was designed in the current research. A lightweight YOLOv3-based (You Only Look Once version 3) mode which had Efficient Channel Attention (ECA) was integrated into the CF algorithm to provide deep features. In addition, a lightweight Siamese CNN with Cross Stage Partial (CSP) provided the representations of features learned from massive face images, allowing the target similarity in data association to be guaranteed. As a result, a Deep Feature Kernelized Correlation Filters method coupled with Siamese-CSP(Siam-DFKCF) was established to increase the tracking robustness. From the experimental results, it can be concluded that the anti-occlusion and re-tracking performance of the proposed method was increased. The tracking accuracy Distance Precision (DP) and Overlap Precision (OP) had been increased to 0.934 and 0.909 respectively in our test data.

Helical tube steam generators are often used in nuclear power plants because of their compact structure and high heat transfer efficiency. The impact of the internal fluid causes the vibration of the tube bundle, which leads to the failure of the integrity of the safety structure. Aiming at flow-induced vibration (FIV) of helical tube arrays, a finite element model of the helical tube was established to consider the constraint of the support structure. The computational fluid dynamics (CFD)/computational structural dynamics (CSD) coupling calculation method based on the superposition of three modes was used to study the FIV characteristics of helical tube arrays at different flow velocities. The influence of adjacent helical tubes’ vibration on the vibration of the target tube was also investigated. The results show that when FIV occurs in the helical tube, with the increase of inlet velocity, the axial amplitude will be greater than the radial at the same velocity. When some tubes vibrate, the vibration of the target tube will be enhanced; while adjacent tubes vibrate, it will weaken the impact of the fluid on the target tube and obviously weaken the vibration of the target tube.

Lossy dielectric bars have potential applications in high power microwave (HPM) radiation-effect experiments performed in wind tunnels. Under plane excitation, beat wave patterns are observed along lossy and lossless dielectric bars in 3-D electromagnetic simulation results. Mode analysis is performed to clarify the two main modes in the beat waves—the leaky and guided modes. Comparisons are made between the theoretical and simulated results and acceptable agreements are obtained. The absorbing array of lossy dielectric bars is further investigated. The array can attenuate 90% of the microwave power at 10 GHz when a ten-meter series of such arrays is arranged. It is expected that the proposed absorbing array can achieve the required attenuation, considering that the testing object under microwave radiation is also an absorbing structure itself.