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IEEE Conference on Decision and Control

作者： Sunil Kumar Rajendran Qi Wei Ningshi Yao Feitian Zhang Department of Electrical and Computer Engineering George Mason University Fairfax VA USA Department of Bioengineering George Mason University Fairfax VA USA Department of Advanced Manufacturing and Robotics and the State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing China

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

With the aid of a robotic eye platform, several ocular motor disorders such as strabismus can be studied by ophthalmologists and biomedical researchers to better under-stand the biomechanisms of the human eye. Our previous work modeled a 2-DOF robotic eye driven by Super-Coiled Polymer (SCP) artificial muscles and presented a Deep Deterministic Policy Gradient (DDPG) learning-based controller. The control policy requires access to the full system states that include the orientation of the robotic eye and temperature changes of the SCPs. While the angular orientations of the robotic eye can be determined using embedded sensors or image-processing of the visual feed, it is quite laborious and expensive to measure the temperatures of the slender SCP muscles without affecting robot dynamics. To address this problem, this paper designs a linear reduced-order state observer based on the linearization of the nonlinear dynamics of the robotic eye. The linearized model is analytically shown to be fully observable along any trajectory within the operation range. To quantify the local observability of the dynamical system, local unobservability indices and local estimation condition numbers are determined along trajectories of the system states. The performance of the designed observer is tested through simulation in both open-loop and closed-loop foveation control of the robotic eye.

关键词： Temperature sensors Temperature measurement Visualization Observers Robot sensing systems Trajectory Nonlinear dynamical systems

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Dynamic State Estimation-Based Protection for Induction Motor Loads

arXiv

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arXiv 2022年

作者： Barnes, Arthur K. Basu, Sarbajit Mate, Adam The Advanced Network Science Initiative Los Alamos National Laboratory Los AlamosNM87545 United States The Klipsch School of Electrical and Computer Engineering The New Mexico State University Las CrucesNM88003 United States

Ensuring protective device coordination is critical to maintain the resilience and improve the reliability of large microgrids. Inverter-interfaced generation, however, poses significant challenges when designing protection systems. Traditional time-overcurrent protective devices are unsuitable on account of the lack of fault current. Present industry practice is to force all inverters to shut down during faults, which prevents large microgrids from operating in a resilient and reliable manner. Dynamic state estimation (DSE) has been proposed for line protection, and more recently for the protection of load buses or downstream radial portions of microgrids. However, only passive loads with series resistive-inductive loads have been tested with DSE, even though the behavior of dynamic loads – such as induction motors or power electronics – may differ significantly during faults. This paper considers the case of applying DSE to protecting a load bus serving a three-phase induction motor. © 2022, CC BY.

关键词： Electric power distribution

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Gesture Control Method for Oral Blood Mixed Liquid Removal Robot∗ 5

Gesture Control Method for Oral Blood Mixed Liquid Removal R...

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5th World Robot Conference Symposium on advanced Robotics and Automation, WRC SARA 2023

作者： Ma, Xudong Kuang, Ziao Li, Han Chen, Anqi Li, Changsheng Liu, Wenyong Wang, Junchen Hu, Yida David Gao, Li Su, Bai-Quan Beijing University of Posts and Tele-communications Medical Robotics Laboratory School of Automation Beijing100876 China Beijing University of Posts and Tele-communications School of Computer Beijing100876 China Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beihang University Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beijing100083 China Beihang University School of Mechanical Engineering and Automation Beijing100083 China Brigham and Women's Hospital Harvard Medical School BostonMA02115 United States Peking University School and Hospital of Stomatology National Clinical Research Center for Oral Diseases National Stomatological Center Department of Periodontology Beijing China

ISBN: (纸本)9798350307320

All of oral surgeries are accompanied by bleeding. Manual removal of blood is carried out by a nurse and dozens of repetitive blood suction operations are implemented by the nurse during a single oral surgery. In our previous work, a robot for removal of blood-water mixed liquid is designed. However, the robot requires an initial order to autonomous removal of blood mixed liquid. In this paper, a hand gesture control method for typical operations of the robot is developed. Gesture dataset are developed at first and a deep learning neural network is trained for detection of hand gesture. The gesture control procedures for four typical operations are provided in detail. In a group of experiments, it's demonstrated that an oral surgeon controls the robot's motion by presenting prescribed hand gesture. The proposed method could be an alternative manner for blood mixed liquid removal. © 2023 IEEE.

关键词： Blood

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Tenacity Prediction of Polyester Materials Based on an Ensemble Soft Measurement Model

Tenacity Prediction of Polyester Materials Based on an Ensem...

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Chinese Automation Congress (CAC)

作者： Jiaxu Duan Jun Wang Youji Tao Zhiping Ma Xin Wu Zhou Hu State Key Laboratory of Environmental Adaptability for Industrial Products China National Electric Apparatus Research Institute Co. Ltd Guangzhou China Kinte Materials Science and Technology Co. Ltd Guangzhou China Department of Computer Science Hunan University of Technology and Business Changsha China School of electronic information and electrical engineering Yangtze University Jingzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In the development process of polyester powder coating materials, it has great guiding significance for the development of new materials as the polyester material properties can be predicted through the given monomer structure and formula. In order to meet the requirements of rapid development of polyester materials, this paper establishes a prediction method based on an ensemble soft measurement model (ESM) for one key property--tenacity in prompting the acceleration of development cycle of polyester products. The processed data employed to train and test the model were collected from a local material company, and it covers over 100 kinds of polymerized resins. Firstly, the molecular expressions of monomers are converted to SMILES codes and further translated to ECFP fingerprints. Then, the principal component analysis (PCA) method is adopted to extract the elements with higher importance in each fingerprint. Finally, the ensemble model that consists of 4 machine learning models was established to make the multiclassification decision in tenacity prediction. The effectiveness of the prediction model is evaluated by comparing the predicted and the practical tensile test results. The results demonstrate that this approach achieves better performance in the material property prediction as well as generalization capability.

关键词： Weight measurement Soft sensors Predictive models Fingerprint recognition Data models Mathematical models Polymers Resins Material properties Principal component analysis

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Exploring coupling flip mechanisms via plasmon-induced transparency in active metamaterials

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Chinese Optics Letters 2025年第2期 156-161页

作者：武志强高靖翔杨清秀池家豪王桂芳庄松林程庆庆 School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Department of Respiratory Diseases and Critical Medicine Quzhou Hospital Affiliated with Wenzhou Medical University State Key Laboratory of Terahertz and Millimeter Waves City University of Hong Kong

Comparing the coupling strength with both the mean and the product of the square roots of the respective damping rates for the bright and dark modes is a crucial metric in the study of plasmon-induced transparency(PIT). The flip in the ratio determines whether the coupling state between the structural units is strong or weak and also applies to the group *** study explores two primary coupling channels within PIT structures: the inter-resonator distance(d) between the splitring resonators(SRRs) and the cut wire(CW) and the spacing(g) between the SRRs. In the simulations, photosensitive silicon is embedded in the openings of the dark mode SRR resonator, actively modulating the dispersion characteristics and the coupling strength. Furthermore, we methodically examine the influence of these coupling channels on the transition between the coupling states, as well as on the maximal group delay in the PIT effect. Theoretically, leveraging the parameter fitting via the Lorentz coupling resonator model identifies the dominant parameters governing coupling state flips and differential regulation mechanisms. Our findings contribute to a deeper understanding of PIT phenomena and offer insights into optimizing PIT structures for diverse applications.

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Toward Ultra-Low-Power Remote Health Monitoring: An Optimal and Adaptive Compressed Sensing Framework for Activity Recognition

arXiv

引用

arXiv 2023年

作者： Pagán, Josué Fallahzadeh, Ramin Pedram, Mahdi Risco-Martín, José L. Moya, José M. Ayala, José L. Ghasemzadeh, Hassan Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid28040 Spain School of Electrical Engineering and Computer Science Washington State University PullmanWA99164 United States Universidad Politécnica de Madrid Madrid28040 Spain Center for Computational Simulation Universidad Politécnica de Madrid Campus de Montegancedo Boadilla del Monte Madrid28660 Spain

Activity recognition, as an important component of behavioral monitoring and intervention, has attracted enormous attention, especially in Mobile Cloud Computing (MCC) and Remote Health Monitoring (RHM) paradigms. While recently resource constrained wearable devices have been gaining popularity, their battery life is limited and constrained by the frequent wireless transmission of data to more computationally powerful back-ends. This paper proposes an ultra-low power activity recognition system using a novel adaptive compressed sensing technique that aims to minimize transmission costs. Coarse-grained on-body sensor localization and unsupervised clustering modules are devised to autonomously reconfigure the compressed sensing module for further power saving. We perform a thorough heuristic optimization using Grammatical Evolution (GE) to ensure minimal computation overhead of the proposed methodology. Our evaluation on a real-world dataset and a low power wearable sensing node demonstrates that our approach can reduce the energy consumption of the wireless data transmission up to 81.2% and 61.5%, with up to 60.6% and 35.0% overall power savings in comparison with baseline and a naive state-of-the-art approaches, respectively. These solutions lead to an average activity recognition accuracy of 89.0%—only 4.8% less than the baseline accuracy—while having a negligible energy overhead of on-node computation. © 2023, CC BY-SA.

关键词： Optimization

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Human body odour modulates neural processing of faces: effective connectivity analysis using EEG

Human body odour modulates neural processing of faces: effec...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Saideh Ferdowsi Dimitri Ognibene Tom Foulsham Alberto Greco Alejandro Luis Callara Sergio Cervera-Torres Mariano Alcañiz Nicola Vanello Luca Citi School of computer science and electrical engineering University of Essex Colchester UK Department of Psychology University of Milan-Bicocca Milan Italy Department of Psychology University of Essex Colchester UK Department of Information Engineering University of Pisa Pisa Italy Laboratory of Immersive Neurotechnologies (LabLENI) Human-Centered Technology Institute (Human-Tech) Polytechnic University of Valencia Spain

Facial emotion processing by the brain plays a decisive role in human social interactions. This signal helps us interpret and predict people's behaviours. However, other social signals such as human voices or human body odours may facilitate or impair the identification of facial expressions. Here we studied the effects of emotional human body odours on face processing by measuring evoked neural responses and brain connectivity using the electroencephalogram (EEG). We used an emotion recognition task in which the participants attributed an emotion (i.e. happy vs fearful) to a presented face image while simultaneously exposed to emotional body odours. First, we measured face related potentials (FRP)s including P100 and N170 components. Statistical analyses revealed significant differences among FRPs recorded in different odour conditions. Second, we used a hierarchical Bayesian approach including a group dynamic causal model (DCM) followed by parametric empirical Bayes (PEB) to characterize the brain network explaining differences between FRPs. Our preliminary results suggested that different brain networks contribute to neutral face processing in the presence of different emotional body odours.

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Sensing With Communication Signals: From Information Theory to Signal Processing

arXiv

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arXiv 2025年

作者： Liu, Fan Liu, Ya-Feng Cui, Yuanhao Masouros, Christos Xu, Jie Han, Tony Xiao Buzzi, Stefano Eldar, Yonina C. Jin, Shi National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematicsand Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom Guangdong518172 China Huawei Technologies Co. Ltd China Department of Electrical and Information Engineering University of Cassino and Southern Lazio CassinoI-03043 Italy Department of Electronics Information and Bioengineering Politecnico di Milano MilanoI-20133 Italy ParmaI-43124 Italy Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel

The Integrated Sensing and Communications (ISAC) paradigm is anticipated to be a cornerstone of the upcoming 6G networks. In order to optimize the use of wireless resources, 6G ISAC systems need to harness the communication data payload signals, which are inherently random, for both sensing and communication (S&C) purposes. This tutorial paper provides a comprehensive technical overview of the fundamental theory and signal processing methodologies for ISAC transmission with random communication signals. We begin by introducing the deterministic-random tradeoff (DRT) between S&C from an information-theoretic perspective, emphasizing the need for specialized signal processing techniques tailored to random ISAC signals. Building on this foundation, we review the core signal models and processing pipelines for communication-centric ISAC systems, and analyze the average squared auto-correlation function (ACF) of random ISAC signals, which serves as a fundamental performance metric for multi-target ranging tasks. Drawing insights from these theoretical results, we outline the design principles for the three key components of communication-centric ISAC systems: modulation schemes, constellation design, and pulse shaping filters. The goal is to either enhance sensing performance without compromising communication efficiency or to establish a scalable tradeoff between the two. We then extend our analysis from a single-antenna ISAC system to its multi-antenna counterpart, discussing recent advancements in multiinput multi-output (MIMO) precoding techniques specifically designed for random ISAC signals. We conclude by highlighting several open challenges and future research directions in the field of sensing with communication signals. Copyright © 2025, The Authors. All rights reserved.

关键词： Signal modulation

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Regulating Water Molecules via Bioinspired Covalent Organic Framework Membranes for Zn Metal Anodes

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Angewandte Chemie - International Edition 2025年第14期64卷 e202424184页

作者： Zhang, Sida Chen, Jiashu Chen, Weigen Su, Yiwen Gou, Qianzhi Yuan, Ruduan Wang, Ziyi Wang, Kaixin Zhang, Wentao Hu, Xiqian Zhang, Zhixian Wang, Pinyi Wan, Fu Liu, Jie Li, Beibei Wang, Yifei Zheng, Guangping Li, Meng Sun, Jingyu State Key Laboratory of Power Transmission Equipment Technology School of Electrical Engineering National Innovation Center for Industry-Education Integration of Energy Storage Chongqing University Chongqing400044 China Soochow Institute for Energy and Materials Innovation Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow University Suzhou215006 China Department of Mechanical Engineering Hong Kong Polytechnic University Hung Hom Kowloon999077 Hong Kong MOE Key Laboratory of Low-grade Energy Utilization Technologies and Systems CQU-NUS Renewable Energy Materials & Devices Joint Laboratory School of Energy and Power Engineering National Innovation Center for Industry-Education Integration of Energy Storage Chongqing University Chongqing400044 China School of Building Services Science and Engineering Xi'an University of Architecture and Technology Xi'an710055 China School of Electrical and Electronic Engineering Chongqing University of Technology Chongqing400054 China Hunan University Changsha410082 China College of Environmental Science and Engineering National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology Beijing University of Technology Beijing100124 China

The Zn metal anode in aqueous zinc-ion batteries (AZIBs) faces daunting challenges including undesired water-induced parasitic reactions and sluggish ion migration kinetics. Herein, we develop three-dimensional covalent organic framework (COF) membranes with bioinspired ion channels toward stabilized Zn anodes. These COFs, featured by zincophilic pyridine-N sites, enable effective regulation of water molecules at the anode-electrolyte interphase. Systematic experimental analysis and theoretical simulations reveal the optimized COF-320N membrane functions as ion pumps, accordingly facilitating Zn2+ transport and inhibiting direct contact between Zn anode and free water molecules. Consequently, the bio-inspired strategy achieves improved Zn2+ transference number (0.61), rapid de-solvation kinetics, and suppressed hydrogen evolution. The assembled Zn||MnO2 pouch cell integrated with COF-320N membrane exhibits favorable electrochemical performances. Such a bioinspired concept for optimizing Zn anodes opens new pathways in developing advanced energy storage devices. © 2025 Wiley-VCH GmbH.

关键词： Manganese oxide

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Multi-Weather Full-Body Triboelectric Garments for Personalized Moisture Management and Water Energy Acquisition

SSRN

引用

SSRN 2023年

作者： Kang, Tian Ma, Wanwan Guo, Yinben Zhou, Jie Zhang, Yihe Ji, Tianyi Gong, Wei School of Materials Science and Engineering Shanghai University of Engineering Science Shanghai201620 China Key Laboratory of Textile Science & Technology Ministry of Education College of Textiles Donghua University Shanghai201620 China College of Electronics and Information Engineering Sichuan University Chengdu610064 China State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and Engineering Donghua University Shanghai201620 China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore117583 Singapore

The occurrence of extreme events (such as heatwaves, heavy precipitation) is unprecedented in the observed record and will increase with increasing global warming, leading to severe human health issues. Wearing suitable garments in different weather is one of the solutions for people to ease their physical discomfort in an energy-saving way. However, only one piece of traditional clothes hardly satisfies the demand of the changing weather. Herein, a multi-weather full-body triboelectric garment with a one-way moisture transport structure is presented to keep people feeling cool in the scorching weather while capturing droplet energy in rainy situations. A trilayer progressive wetting structure was designed to effectively transport sweat from the inner layer near the skin to the outer layer to keep the skin dry and comfortable in the muggy air, with a unidirectional transmission index of 1025%. When it starts to rain, the rain droplets quickly roll down the textile surface and generate triboelectric energy with the hydrophobic surface and conductive MXene layer inside. More than that, the scalable fabrication process makes it possible to obtain the textile with enough areas for making a whole garment, which is much more practical in real application scenarios. © 2023, The Authors. All rights reserved.

关键词： Fabrication

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