Optimal Online Transmission Policy for Energy-Constrained Wireless-Powered Communication Networks

This work considers the design of online transmission policy in a wireless-powered communication system with a given energy budget. The system design objective is to maximize the long-term throughput of the system exploiting the energy storage capability at the wireless-powered node. We formulate the design problem as a constrained Markov decision process (CMDP) problem and obtain the optimal policy of transmit power and time allocation in each fading block via the Lagrangian approach. To investigate the system performance in different scenarios, numerical simulations are conducted with various system parameters. Our simulation results show that the optimal policy significantly outperforms a myopic policy which only maximizes the throughput in the current fading block. Moreover, the optimal allocation of transmit power and time is shown to be insensitive to the change of modulation and coding schemes, which facilitates its practical implementation.Comment: 7 pages, accepted by ICC 2019. An extended version of this paper is accepted by IEEE TW

Empirical Analysis of Vehicle Tracking Algorithms for Extracting Integral Trajectories from Consecutive Videos

This study introduces a novel methodological frame-work for extracting integral vehicle trajectories from several consecutive pictures automatically. The frame-work contains camera observation, eliminating image distortions, video stabilising, stitching images, identify-ing vehicles and tracking vehicles. Observation videos of four sections in South Fengtai Road, Nanjing, Jiangsu Province, China are taken as a case study to validate the framework. As key points, six typical tracking algorithms, including boosting, CSRT, KCF, median flow, MIL and MOSSE, are compared in terms of tracking reliability, operational time, random access memory (RAM) usage and data accuracy. Main impact factors taken into con-sideration involve vehicle colours, zebra lines, lane lines, lamps, guide boards and image stitching seams. Based on empirical analysis, it is found that MOSSE requires the least operational time and RAM usage, whereas CSRT presents the best tracking reliability. In addition, all tracking algorithms produce reliable vehicle trajecto-ry and speed data if vehicles are tracked steadily

Focal Sweep Camera for Space-Time Refocusing

A conventional camera has a limited depth of field (DOF), which often results in defocus blur and loss of image detail. The technique of image refocusing allows a user to interactively change the plane of focus and DOF of an image after it is captured. One way to achieve refocusing is to capture the entire light field. But this requires a significant compromise of spatial resolution. This is because of the dimensionality gap - the captured information (a light field) is 4-D, while the information required for refocusing (a focal stack) is only 3-D. In this paper, we present an imaging system that directly captures a focal stack by physically sweeping the focal plane. We first describe how to sweep the focal plane so that the aggregate DOF of the focal stack covers the entire desired depth range without gaps or overlaps. Since the focal stack is captured in a duration of time when scene objects can move, we refer to the captured focal stack as a duration focal stack. We then propose an algorithm for computing a space-time in-focus index map from the focal stack, which represents the time at which each pixel is best focused. The algorithm is designed to enable a seamless refocusing experience, even for textureless regions and at depth discontinuities. We have implemented two prototype focal-sweep cameras and captured several duration focal stacks. Results obtained using our method can be viewed at www.focalsweep.com

Monte Carlo Studies of Hydrogen Flouride Clusters: Cluster Size Distributions in Hydrogen Flouride Vapor

An investigation into the structure and composition of hydrogen flouride vapor is reported. Calculations are performed using a modified central force model potential developed by Klein and McDonald. Using a simulated annealing procedure, minimum energy structures for HF clusters are investigated ranging in size from n=2 to 7. Good agreement is found for the sturctural parameters obtained from the model potential and other theoretical and experimental information. The Monte Carlo method is used to determine the thermodynamic energy, entropy, and Gibbs free energy of the hydrogen flouride clusters at 1 atm pressure and 100 and 273 K. A minimum in the Gibbs free energy change is found at n-=4 implying that tetramers are very important in vapor

Robust neurooptimal control for a robot via adaptive dynamic programming

We aim at the optimization of the tracking control of a robot to improve the robustness, under the effect of unknown nonlinear perturbations. First, an auxiliary system is introduced, and optimal control of the auxiliary system can be seen as an approximate optimal control of the robot. Then, neural networks (NNs) are employed to approximate the solution of the Hamilton-Jacobi-Isaacs equation under the frame of adaptive dynamic programming. Next, based on the standard gradient attenuation algorithm and adaptive critic design, NNs are trained depending on the designed updating law with relaxing the requirement of initial stabilizing control. In light of the Lyapunov stability theory, all the error signals can be proved to be uniformly ultimately bounded. A series of simulation studies are carried out to show the effectiveness of the proposed control