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Flexible Capacitive Pressure Sensors and Their Applications in Human-Machine Interactions

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Flexible Capacitive Pressure Sensors and Their Applications ...

Sensor Technology and Control (ISSTC), International Symposium on

作者： Chenyu Fang Tianli Fu Yao Shi Changzhou No.1 High School Changzhou China School of Mechanical and Electronic Engineering Wuhan University of Technology Wuhan China College of Computer and Information Science College of Software Southwest University Chongqing China

Flexible capacitive pressure sensors have shown excellent application potential in human-machine interactions, wearable electronic devices, biological and medical, and electronic skin. Compared with piezoresistive and piezoelectric pressure sensors, capacitive pressure sensors with advantages such as high flexibility, high stability, low consumption, and simple construction. Because of these advantages, flexible capacitive pressure sensors have become the key research direction of pressure sensors in recent years. This paper introduces the working principle of flexible capacitive pressure sensors and discusses numerous research on improving the performance of flexible capacitive pressure sensors. Then two methods of improving the dielectric layer structures to improve the sensitivity of the sensor and some related works are reviewed. Finally, the flexible capacitive pressure sensors' huge potential for advances in human-machine interactions areas such as health care and motion monitoring is also discussed. The paper concludes with an overview of future research directions of improving the performance of flexible capacitive pressure sensors.

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Evolutionary Multitasking With Adaptive Knowledge Transfer for Expensive Multiobjective Optimization

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IEEE Transactions on Evolutionary Computation 2024年

作者： Wu, Xunfeng Liu, Songbai Lin, Qiuzhen Tan, Kay Chen Leung, Victor C. M. The Hong Kong Polytechnic University Department of Data Science and Artificial Intelligence Hong Kong Hong Kong Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Surrogate-assisted evolutionary algorithms (SAEAs) have shown promising performance in tackling expensive multiobjective optimization problems (EMOPs). However, existing SAEAs solve EMOPs separately, which ignore their optimization experiences earned before. Inspired by multitasking optimization paradigm for multitasking multiobjective optimization problems (MTMOPs), this article designs the first SAEA for tackling expensive MTMOPs (EMTMOPs) with adaptive knowledge transfer. First, a competitive surrogate selection is proposed to improve the generalization ability of approximating various EMOP tasks, where two types of surrogate models are trained and then compete for use to replace real expensive evaluations. Then, an adaptive solution selection is designed, which identifies promising transfer solutions to accelerate the solving of target task and selects promising infill solutions for real expensive evaluations to refine the surrogate models. The performance of our algorithm is validated on three commonly used benchmark suites and some real-world EMTMOPs. The experiments vali-date our superiority over several state-of-the-art SAEAs on most test cases. © 1.97-201. IEEE.

关键词： Multiobjective optimization

Rapid processing of frames refreshment with viewpoint movement based on openGL for 3D walkthrough system

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Sensors and Transducers 2014年第5期171卷 157-161页

作者： Shi, Guoyou Chen, Peng Liu, Shuang College of Navigation Dalian Maritime University 1 Linghai Road China Department of Computer Science & Technology Dalian Neusoft Institute of Information 8 Software Park Road China School of Computer Science & Engineering Dalian Nationalities University 18 Liaohe West Road Dalian Development Zone China

How to refresh frames for 3D scenes efficiently with viewpoint movement is very important for a 3D walkthrough system. Detailed calculation process of movement position and destination position for the viewpoint in virtual 3D scenes is described, thus implementing controlling scenes through the application of an external device. Moreover, OpenGL Performer pfLOD node is utilized to process LOD (Level of Detail) display for improving scenes refreshment performance. With OpenGL's powerful interaction functions, 3D scenes are rendered with a fixed frame rate over 50 Hz. Then, details of MFC framework initialization and OpenGL initialization are given for Dalian nationalities university 3D walkthrough system. Running results of the software show the algorithm designed in this paper is feasible and effective and can meet requirements of real application. © 201. IFSA Publishing, S. L.

关键词： Application programming interfaces (API)

Optimizing Mobile-Friendly Viewport Prediction for Live 360-Degree Video Streaming

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arXiv 2024年

作者： Zhang, Lei Long, Tao Xu, Weizhen Cui, Laizhong Liu, Jiangchuan The College of Computer Science and Software Engineering Shenzhen University Guangdong Shenzhen518060 China The School of Computing Science Simon Fraser University BurnabyBCV5A 1S6 Canada

Viewport prediction is the crucial task for adaptive 360-degree video streaming, as the bitrate control algorithms usually require the knowledge of the user’s viewing portions of the frames. Various methods are studied and adopted for viewport prediction from less accurate statistic tools to highly calibrated deep neural networks. Conventionally, it is difficult to implement sophisticated deep learning methods on mobile devices, which have limited computation capability. In this work, we propose an advanced learning-based viewport prediction approach and carefully design it to introduce minimal transmission and computation overhead for mobile terminals. We also propose a model-agnostic meta-learning (MAML) based saliency prediction network trainer, which provides a few-sample fast training solution to obtain the prediction model by utilizing the information from the past models. We further discuss how to integrate this mobile-friendly viewport prediction (MFVP) approach into a typical 360-degree video live streaming system by formulating and solving the bitrate adaptation problem. Extensive experiment results show that our prediction approach can work in real-time for live video streaming and can achieve higher accuracies compared to other existing prediction methods on mobile end, which, together with our bitrate adaptation algorithm, significantly improves the streaming QoE from various *** observe the accuracy of MFVP is 8.1. to 28.7% higher than other algorithms and achieves 3.73% to 1..96% higher average quality level and 49.6% to 74.97% less quality level change than other algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Forecasting

End-to-End Delay Performance for Mobile Cyber-Physical Systems with Edge Computing 11

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End-to-End Delay Performance for Mobile Cyber-Physical Syste...

1.th International Conference on Networks, Communication and Computing, ICNCC 2022

作者： Wu, Yan Yang, Qinghai Qiao, Feiyu Kwak, K.S. Leung, C.M. Pan, Guangchuan State Key Laboratory of ISN School of Telecommunications Engineering Xidian University No.2 South Taibai Road Shaanxi Xi'an710071 China Communication Engineering Inha University #100 Inha-Ro Nam-gu Incheon22212 Korea Republic of College of Computer Science and Software Engineering Shenzhen University 518060 China The Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Xidian University No.2 South Taibai Road Shaanxi Xi'an710071 China

ISBN: (纸本)9781450398039

In this letter, we investigate the end-to-end (E2E) delay performance for mobile cyber-physical systems (M-CPS) with edge computing. The traditional delay analysis is based on flow conservation law, whereas the flow is not conserved in the M-CPS with edge computing due to the existence of edge computing node and remote controller. To tackle this problem, we introduce two scaling factors to ensure the flow conservation, then the E2E delay bound of M-CPS with edge computing is derived via stochastic network calculus. In addition, to cater for the delay demand for M-CPS stability, the stable-aware delay bound is obtained. Numerical results show the gap between the analytic bound and simulation can be narrower as the average signal-to-noise (SNR) growing. © 2022 ACM.

关键词： Cyber Physical System

A new Technique in Protein Structure Quantitative Identification 9th

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A new Technique in Protein Structure Quantitative Identifica...

9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Guo, Mengjiao Cao, Haobin He, Jing Ji, Tengfei Department of Computer Science and Software Engineering Swinburne University of Technology Melbourne3122 Australia Department of Mechanical Engineering University College London LondonWC1E 6BT United Kingdom Department of Neuroscience University of Oxford OxfordOX39DU United Kingdom State Key Laboratory of Bioactive Substance and Function of Natural Medicines Institute of Materia Medica Peking Union Medical College Chinese Academy of Medical Sciences Beijing100050 China

Graph distance is also named approximate graph isomorphism, error-tolerant graph matching, it is a measure of similarity (or dissimilarity) between two graphs. The graph distance function is an elusive question remaining a pressing problem in a wide range of fields. In general, graphs are usually enriched with node and edge attributes, namely, heterogeneous graphs, our focus is encapsulating node and edge identities in a graph. In addition, an adequate representation of the graph-adjacency matrix can capture the connectivity of the graph structure, while an adjacency matrix bears high-order combinatorial nature. Solving these challenges in the effective analysis of these graphs is of utmost importance. In this paper, structural and semantic features are both preserved by graphs, so the analysis of row sum and eigenspectra for vertex and edge adjacency matrix has captured the affinity interactions within graphs locally and globally. Therefore, we estimate the geometrical and semantic dissimilarities/distances between graphs extensively and systemically. Several illustrative chemical compound cases implement in practical scenarios, thus, the theory could be easily understood. Our method defines a quantitative distance (or dissimilarity) measure for comparing graphs, it has a good measure of expressiveness and a suited polynomial computation complexity, which paves the way for graph analysis. © 2022 The Authors. Published by Elsevier B.V.

关键词： Graphic methods

Secure distributed on-device learning networks with byzantine adversaries

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arXiv 2019年

作者： Dong, Yanjie Cheng, Julian Hossain, Md. Jahangir Leung, Victor C. M. Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada School of Engineering University of British Columbia KelownaBCV1V 1V7 Canada College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China

The privacy concern exists when the central server has the copies of datasets. Hence, there is a paradigm shift for the learning networks to change from centralized in-cloud learning to distributed on-device learning. Benefit from the parallel computing, the on-device learning networks have a lower bandwidth requirement than the in-cloud learning networks. Moreover, the on-device learning networks also have several desirable characteristics such as privacy preserving and flexibility. However, the on-device learning networks are vulnerable to the malfunctioning terminals across the networks. The worst-case malfunctioning terminals are the Byzantine adversaries, that can perform arbitrary harmful operations to compromise the learned model based on the full knowledge of the networks. Hence, the design of secure learning algorithms becomes an emerging topic in the on-device learning networks with Byzantine adversaries. In this article, we present a comprehensive overview of the prevalent secure learning algorithms for the two promising on-device learning networks: Federated-Learning networks and decentralized-learning networks. We also review several future research directions in the Federated-Learning and decentralized-learning networks. Copyright © 201., The Authors. All rights reserved.

关键词： Learning algorithms

Evaluating and Improving the Depth Accuracy of Kinect for Windows v2

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arXiv 2022年

作者： Yang, Lin Zhang, Longyu Dong, Haiwei Alelaiwi, Abdulhameed Saddik, Abdulmotaleb El School of Electrical Engineering and Computer Science University of Ottawa 800 King Edward OttawaONK1N 6N5 Canada Software Engineering Department College of Computer and Information Sciences King Saud University Riyadh12372 Saudi Arabia

Microsoft Kinect sensor has been widely used in many applications since the launch of its first version. Recently, Microsoft released a new version of Kinect sensor with improved hardware. However, the accuracy assessment of the sensor remains to be answered. In this paper, we measure the depth accuracy of the newly released Kinect v2 depth sensor, and obtain a cone model to illustrate its accuracy distribution. We then evaluate the variance of the captured depth values by depth entropy. In addition, we propose a trilateration method to improve the depth accuracy with multiple Kinects simultaneously. The experimental results are provided to ascertain the proposed model and method. Copyright © 2022, The Authors. All rights reserved.

关键词： Entropy

Multiobjective Vehicle Routing Optimization with Time Windows: A Hybrid Approach Using Deep Reinforcement Learning and NSGA-II

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arXiv 2024年

作者： Wu, Rixin Wang, Ran Hao, Jie Wu, Qiang Wang, Ping Niyato, Dusit The College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China The Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing Jiangsu210038 China The Department of Electrical Engineering and Computer Science Lassonde School of Engineering York University M3J 1P3 Canada The School of Computer Science and Engineering Nanyang Technological University 639798 Singapore

This paper proposes a weight-aware deep reinforcement learning (WADRL) approach designed to address the multiobjective vehicle routing problem with time windows (MOVRPTW), aiming to use a single deep reinforcement learning (DRL) model to solve the entire multiobjective optimization problem. The Non-dominated sorting genetic algorithm-II (NSGA-II) method is then employed to optimize the outcomes produced by the WADRL, thereby mitigating the limitations of both approaches. Firstly, we design an MOVRPTW model to balance the minimization of travel cost and the maximization of customer satisfaction. Subsequently, we present a novel DRL framework that incorporates a transformer-based policy network. This network is composed of an encoder module, a weight embedding module where the weights of the objective functions are incorporated, and a decoder module. NSGA-II is then utilized to optimize the solutions generated by WADRL. Finally, extensive experimental results demonstrate that our method outperforms the existing and traditional methods. Due to the numerous constraints in VRPTW, generating initial solutions of the NSGA-II algorithm can be time-consuming. However, using solutions generated by the WADRL as initial solutions for NSGA-II significantly reduces the time required for generating initial solutions. Meanwhile, the NSGA-II algorithm can enhance the quality of solutions generated by WADRL, resulting in solutions with better scalability. Notably, the weight-aware strategy significantly reduces the training time of DRL while achieving better results, enabling a single DRL model to solve the entire multiobjective optimization problem. © 2024, CC BY.

关键词： Reinforcement learning