No abstract

Unmanned aerial vehicles (UAVs) are widely used in wireless communication networks due to their rapid deployment and high mobility. However, in practical scenarios, the existence of obstacles and eavesdroppers will seriously interfere with the communication quality of the UAV network and produce a security risk. Thus, this paper combines reconfigurable intelligent surface (RIS) technology with UAVs to build a secure UAV communication network. Normally, a rotary-wing UAV (labeled as UAV-S) acting as a base station sends information signals to a legitimate user on the ground with RIS equipment. However, there is a passive eavesdropper on the ground who can steal the information. Therefore, a friendly UAV jammer (labeled as UAV-J) with a fixed location is introduced to send jamming signals to confuse the eavesdropper. The goal of this paper is to maximize the average secrecy rate of the communication network by jointly optimizing the flight trajectory, transmit power of the UAV-S and UAV-J, and phase shifter of the RIS. Since the constructed problem is highly nonconvex, an alternating optimization algorithm based on successive convex approximation techniques is proposed to solve the problem. Simulation results show that the proposed algorithm can achieve a higher secrecy rate in comparison with other schemes.

In this paper, we consider a ground terminal (GT) to an unmanned aerial vehicle (UAV) wireless communication system where data from GTs are collected by an unmanned aerial vehicle. We propose to use the ground terminal-UAV (G-U) region for the energy consumption model. In particular, to fulfill the data collection task with a minimum energy both of the GTs and UAV, an algorithm that combines optimal trajectory design and resource allocation scheme is proposed which is supposed to solve the optimization problem approximately. We initialize the UAV’s trajectory firstly. Then, the optimal UAV trajectory and GT’s resource allocation are obtained by using the successive convex optimization and Lagrange duality. Moreover, we come up with an efficient algorithm aimed to find an approximate solution by jointly optimizing trajectory and resource allocation. Numerical results show that the proposed solution is efficient. Compared with the benchmark scheme which did not adopt optimizing trajectory, the solution we propose engenders significant performance in energy efficiency.

Aiming at the characteristic of actual quasi-circular immune cell images, this paper presents the method of quasicircular immune cell images segmentation based on Otsu threshold and thinning algorithm. The image is first converted color space form RGB to YIQ. Then the image is segmented by Otsu threshold algorithm. And then the erosion and dilation of morphological filter are used to process the image. Finally, the Zhang-Suen thinning algorithm is employed to extract the cell's skeleton, which is the center of the quasi-circular immune cell. According to the thinning times, we can obtain the radius value of the quasi-circular immune cell, and the overlapping quasi-circular immune cells are separated. Experimental results show this method works successfully in the segmentation of quasi-circular immune cell images.

Construction of the virtual creature using computer hardware and software is an important aspect in computer simulation of life sciences. The paper provides a brief introduction of Object-oriented Biological modeling which used as a design methodology. The advantage of this method is a well consideration of specific purpose of building a model, that is to say, the user's needs.