Localization of Distributed Fiber Sensor Employing a Sub-Ring

A simple distributed optical fiber sensing system used to monitor vibration signal has an additional sub-loop eoupled with main ring by a 3 dB coupler. This paper compares three outputting interfered beams, each of them travels in the sub-ring 0, 1, 2 times, separately. Using the simultaneous equations produced by those three outputs, we find the relation between the interference lights and vibration signal＇s characteristics, such as frequency, amplitude and position. Through simplifying and calculating, the vibration position can be obtained finally.

Reinforcement Learning-Based Optimization for Drone Mobility in 5G and Beyond Ultra-Dense Networks

Drone applications in 5th generation(5G)networks mainly focus on services and use cases such as providing connectivity during crowded events,human-instigated disasters,unmanned aerial vehicle traffic management,internet of things in the sky,and situation awareness.4G and 5G cellular networks face various challenges to ensure dynamic control and safe mobility of the drone when it is tasked with delivering these services.The drone can fly in three-dimensional space.The drone connectivity can suffer from increased handover cost due to several reasons,including variations in the received signal strength indicator,co-channel interference offered to the drone by neighboring cells,and abrupt drop in lobe edge signals due to antenna nulls.The baseline greedy handover algorithm only ensures the strongest connection between the drone and small cells so that the drone may experience several handovers.Intended for fast environment learning,machine learning techniques such as Q-learning help the drone fly with minimum handover cost along with robust connectivity.In this study,we propose a Q-learning-based approach evaluated in three different scenarios.The handover decision is optimized gradually using Q-learning to provide efficient mobility support with high data rate in time-sensitive applications,tactile internet,and haptics communication.Simulation results demonstrate that the proposed algorithm can effectively minimize the handover cost in a learning environment.This work presents a notable contribution to determine the optimal route of drones for researchers who are exploring UAV use cases in cellular networks where a large testing site comprised of several cells with multiple UAVs is under consideration.

Detection of loop closure in visual SLAM:a stacked assorted auto-encoder based approach

The current mainstream methods of loop closure detection in visual simultaneous localization and mapping(SLAM)are based on bag-of-words(Bo W).However,traditional Bo W-based approaches are strongly affected by changes in the appearance of the scene,which leads to poor robustness and low precision.In order to improve the precision and robustness of loop closure detection,a novel approach based on stacked assorted auto-encoder(SAAE)is proposed.The traditional stacked auto-encoder is made up of multiple layers of the same autoencoder.Compared with the visual Bo W model,although it can better extract the features of the scene image,the output feature dimension is high.The proposed SAAE is composed of multiple layers of denoising auto-encoder,convolutional auto-encoder and sparse auto-encoder,it uses denoising auto-encoder to improve the robustness of image features,convolutional auto-encoder to preserve the spatial information of the image,and sparse auto-encoder to reduce the dimensionality of image features.It is capable of extracting low to high dimensional features of the scene image and preserving the spatial local characteristics of the image,which makes the output features more robust.The performance of SAAE is evaluated by a comparison study using data from new college dataset and city centre dataset.The methodology proposed in this paper can effectively improve the precision and robustness of loop closure detection in visual SLAM.

An investigation on dysphotopsia of a sigma-edged intraocular lens

A sigma-edged design of intraocular lens （IOL） is proposed to minimize the reflected glare images associated with the edge. The optimal sigma inverse edge is investigated when pupil diameter is 5.0 mm by the established Escudero-Sanz＇s wide angle model. The non-sequential ray tracing program of Zemax-EE （Zemax Development Corp., San Diego, USA） is used to investigate the sigma edge of reducing the potential for edge glare phenomena. The results show that sigma-edged design can significantly reduce the reflected glare intensity on retina if the angle of its inverse edge is taken from 20 to 70 degrees.