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14th IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, CYBER 2024

作者： Zhang, Feng Jin, Zijian Jiang, Chaodi Yuan, Shuai Yang, Yongliang Wang, Xiaoduo School of Electrical & Control Engineering Shenyang Jianzhu University Liaoning Province Shenyang110168 China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Province Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798331506056

At present, it is still a great challenge to improve the observation accuracy of two-photon fluorescence microscope. A new method that using auxiliary microspheres as movable components on the sample is proposed to solve this challenge in this study, it can improve high-resolution imaging. In experiments using two-photon fluorescence microscopy, the half-width height (FWHM) of red fluorescent nanoparticles with a diameter of 20 nm was observed to be 296 nm using a primitive microscope system. In this paper by combining barium titanate microspheres with two-photon fluorescence microscopy, the accuracy of the point spread function of the nanoparticles can be improved by a factor of about 1.65, which results in a significant reduction of their half-width height measurements to 179 nm. The research is of great significance to improve the resolution of two-photon fluorescence microscope. This progress is very valuable for studying biological tissues and cell structures, it provides a new impetus for the sustainable development in the microscopic imaging field. © 2024 IEEE.

关键词： Microspheres

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Quantitative Electrostatic Potential Mapping in Dense Polycrystalline Functional Materials and Devices

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 280-281页

作者： Durham, Daniel B. Aabrar, Khandker Akif Ravindran, Prasanna Venkatesan Zaluzec, Nestor J. Stan, Liliana Khan, Asif Islam Datta, Suman Guha, Supratik Phatak, Charudatta Materials Science Division Argonne National Laboratory Lemont IL United States School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA United States Photon Sciences Directorate Argonne National Laboratory Lemont IL United States Center for Nanoscale Materials Argonne National Laboratory Lemont IL United States Pritzker School of Molecular Engineering University of Chicago Chicago IL United States

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Research on Biomimetic Design Methods for Humanoid Robot Thigh

Research on Biomimetic Design Methods for Humanoid Robot Thi...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Nie, Daming Xie, Anhuan Kong, Lingyu Zhang, Yu Zheng, Gang Fu, Yili Gu, Jason Zhejiang Laboratory Intelligent Robot Research Center Hangzhou311100 China Zhejiang University of Science and Technology School of Mechanical and Energy Engineering Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxB3M 1A2 Canada

ISBN: (纸本)9798350325706

Human bones have formed the preferred configuration for high-strength and lightweight after long-time evolution. Taking human's longest and strongest bone - the femur - as an example, it is consist of two characteristic layers, i.e. the substantia compacta and the substantia spongiosd. This article innovatively imitates the structural characteristics of human femur, the thigh of humanoid robot is designed in form of "variable thickness shell + variable density lattice". The thickness of shell and the density of lattice are adjusted by the initial stress distribution individually. Results show that the weight of shell and lattice of the thigh structure can be reduced by 20% under reasonable mapping relationship of "stress - shell thickness"and "stress - lattice rod diameter", while the structural stiffness meets the application requirements. Finally, the limiting factors of the "variable thickness shell + variable density lattice"structure designing approach are analyzed, and potential measures for optimizing the design method of the humanoid robot thigh in the future are described. © 2023 IEEE.

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A nano-sheet graphene-based enhanced thermal radiation composite for passive heat dissipation from vehicle batteries

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Nano Materials science 2024年第4期6卷 443-455页

作者： Ji-Xiang Wang Christopher Salmean Jiaxin Li Chaojie Lei Jun Li Mingliang Zhong Bo Qi Yufeng Mao Hebei Key Laboratory of Man-machine Environmental Thermal Control Technology and Equipment Hebei Vocational University of Technology and EngineeringHebei 054000PR China College of Electrical Energy and Power EngineeringYangzhou UniversityYangzhou225009PR China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and TechnologyKowloonHong Kong SARPR China China Academy of Launch Vehicle Technology Beijing100076PR China Beijing Sino-Spark Technology Co. Ltd.Beijing100191PR China School of Environmental Science and Engineering Suzhou University of Science and TechnologySuzhou215009PR China Institute of Optics and Electronics Chinese Academy of SciencesChengdu610209PR China National Key Laboratory of Optical Field Manipulation Science and Technology Chinese Academy of SciencesChengdu610209PR China Taizhou Wavexploration Energy Ltd. Taizhou225513PR China Department of Electrical and Computer Engineering University of TorontoTorontoM5S3G4Canada

In response to thermal runaway(TR)of electric vehicles,recent attention has been focused on mitigation strategies such as efficient heat dredging in battery thermal *** management with particular focus on battery cooling has been becoming increasingly *** usually happened when an electric vehicle is unpowered and *** this state,traditional active battery cooling schemes are disabled,which can easily lead to dangerous incidents due to loss of cooling ability,and advanced passive cooling strategies are therefore gaining ***,we developed an enhanced thermal radiation material,consisting of~1μm thick multilayered nano-sheet graphene film coated upon the heat dissipation surface,thereby enhancing thermal radiation in the *** surface was characterized on the nanoscale,and tested in a battery-cooling *** found that the graphene-based coating's spectral emissivity is between 91% and 95% in the mid-infrared region,and thermal experiments consequently illustrated that graphene-based radiative cooling yielded up to15.1% temperature reduction when compared to the uncoated *** the novel graphene surface to augment a heat pipe,the temperature reduction can be further enlarged to 25.6%.The new material may contribute to transportation safety,global warming mitigation and carbon neutralization.

关键词： Battery thermal management Nano-sheet graphene Functional material Passive cooling Thermal radiation

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Protein-Folding Inspired Programmable Control System for Robot Swarms

Protein-Folding Inspired Programmable Control System for Rob...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Zhang, Feng Gu, Yuping Wang, Zebin Yuan, Shuai Yang, Yongliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110106 China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China

ISBN: (纸本)9781665481090

In swarm robotics, most of the control algorithms are inspired by the behaviors of animal swarms. The capability gap between robots and animals, however, hinders the reliability of these algorithms. Toward developing reliable algorithms of robot swarms, a promising solution is learning from the collective behaviors of low-intelligent natural swarms, such as cell collectives and molecular assemblies. Here, we proposed a programmable control system inspired by protein folding. Using our homemade RoboFold platform, we demonstrated a protein-folding inspired programmable control method for robot swarms. By programming and designing the sequence of a thread of protein-like robots, the developed system can mimic the formation of hierarchical structures in robot swarms as the three-level of protein structures. We quantitatively characterized the specific features of self-organized morphologies. The experimental results together demonstrated the feasibility of this method. To summarize, this work successfully translated the principles of protein-folding into programming methods to control the morphology of robot swarms. Considering that the protein folding problem is essentially a physicochemical problem, this system is not only beneficial for the control of swarm robots but also has the potential to develop into a tool for studying the protein folding problem. © 2024 IEEE.

关键词： Robot programming

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Online Self-distillation and Self-modeling for 3D Brain Tumor Segmentation

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Pang, Yan Li, Yunhao Huang, Teng Liang, Jiaming Wang, Zhen Dong, Changyu Kuang, Dongyang Hu, Ying Chen, Hao Lei, Tim Wang, Qiong The Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China The School of Artificial Intelligence Guangzhou University China The Zhejiang Lab Hangzhou China Sun Yat-sen University China The Department of Computer Science and Engineering The Department of Chemical and Biological Engineering Hong Kong University of Science and Technology China The Department of Electrical Engineering University of Colorado Denver United States

In the specialized domain of brain tumor segmentation, supervised segmentation approaches are hindered by the limited availability of high-quality labeled data, a condition arising from data privacy concerns, significant costs, and ethical issues. In response to this challenge, this paper presents a training framework that adeptly integrates a plug-and-play component, MOD, into current supervised learning models, boosting their efficacy in scenarios with limited data. The MOD consists of an Online Tokenizer and a Dense Predictor, which employs self-distillation and self-modeling on masked patches, promoting swift convergence and efficient representation learning. During the inference phase, the plug-and-play MOD component is excluded, preserving the computational efficiency of the original model without incurring extra processing costs. We substantiated the value of our approach through experiments on leading 3D brain tumor segmentation baselines. Remarkably, models augmented with the MOD consistently showcased superior results, achieving elevated Dice coefficients and HD95 scores on two datasets: BraTS 2021 and MSD 2019 Task-01 Brain Tumor. Code: https://***/aigzhusmart/MOD © 2013 IEEE.

关键词： Self-supervised learning

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Graphene Bridge Heterostructure Devices for Negative Differential Transconductance Circuit Applications

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Nano-Micro Letters 2023年第2期15卷 161-171页

作者： Minjong Lee Tae Wook Kim Chang Yong Park Kimoon Lee Takashi Taniguchi Kenji Watanabe Min‑gu Kim Do Kyung Hwang Young Tack Lee Department of Electrical and Computer Engineering Inha UniversityIncheon 22212Republic of Korea Department of Materials Science and Engineering The University of Texas at DallasRichardsonTX 75080USA Center for Opto‑Electronic Materials and Devices Post‑Silicon Semiconductor InstituteKorea Institute of Science and Technology(KIST)Seoul 02792Republic of Korea Department of Physics Kunsan National UniversityGunsan 54150Republic of Korea Advanced Materials Laboratory National Institute for Materials ScienceTsukuba 305‑0044Japan Department of Information and Communication Engineering Inha UniversityIncheon 22212Republic of Korea Division of Nanoscience and Technology KIST SchoolUniversity of Science and Technology(UST)Seoul 02792Republic of Korea Department of Electronic Engineering Inha UniversityIncheon 22212Republic of Korea

Two-dimensional van der Waals(2D vdW)material-based heterostructure devices have been widely studied for high-end electronic applications owing to their heterojunction *** this study,we demonstrate graphene(Gr)-bridge heterostructure devices consisting of laterally series-connected ambipolar semiconductor/Gr-bridge/n-type molybdenum disulfide as a channel material for field-effect transistors(FET).Unlike conventional FET operation,our Gr-bridge devices exhibit nonclassical transfer characteristics(humped transfer curve),thus possessing a negative differential *** phenomena are interpreted as the operating behavior in two series-connected FETs,and they result from the gate-tunable contact capacity of the Gr-bridge ***-value logic inverters and frequency tripler circuits are successfully demonstrated using ambipolar semiconductors with narrow-and wide-bandgap materials as more advanced circuit applications based on non-classical transfer ***,we believe that our innovative and straightforward device structure engineering will be a promising technique for future multi-functional circuit applications of 2D nanoelectronics.

关键词： Graphene bridge Heterostructure device Non-classical transfer characteristics Multi-value logic inverter Frequency tripler

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Ionic liquid multistate resistive switching characteristics in two terminal soft and flexible discrete channels for neuromorphic computing

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Microsystems & Nanoengineering 2022年第3期8卷 153-161页

作者： Muhammad Umair Khan Jungmin Kim Mahesh Y.Chougale Chaudhry Muhammad Furqan Qazi Muhammad Saqib Rayyan Ali Shaukat Nobuhiko P.Kobayashi Baker Mohammad Jinho Bae Hoi-Sing Kwok Department of Ocean System Engineering Jeju National University102 JejudaehakroJeju 63243Republic of Korea Department of Electrical Engineering and Computer Science Khalifa UniversityAbu Dhabi 127788UAE System on Chip Center Khalifa UniversityAbu Dhabi 127788UAE Department of Electronics and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina State Key Laboratory on Advanced Displays and Optoelectronics Technologies The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina Baskin School of Engineering Univerity of California Santa Cruz1156 High StreetSanta CruzCA 95064USA

By exploiting ion transport phenomena in a soft and flexible discrete channel,liquid material conductance can be controlled by using an electrical input signal,which results in analog neuromorphic *** paper proposes an ionic liquid(IL)multistate resistive switching device capable of mimicking synapse analog behavior by using IL BMIM FeCL_(4) and H_(2)O into the two ends of a discrete polydimethylsiloxane(PDMs)*** spike rate-dependent plasticity(SRDP)and spike-timing-dependent plasticity(STDP)behavior are highly stable by modulating the input ***,the discrete channel device presents highly durable performance under mechanical bending and *** the obtained parameters from the proposed ionic liquid-based synaptic device,convolutional neural network simulation runs to an image recognition task,reaching an accuracy of 84%.The bending test of a device opens a new gateway for the future of soft and flexible brain-inspired neuromorphic computing systems for various shaped artificial intelligence applications.

关键词： computing gateway state

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DDPS: Dynamic Differential Pricing-Based Edge Offloading System With Energy Harvesting Devices

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IEEE Transactions on Network science and engineering 2025年

作者： Xue, Hai Xia, Yun Xiong, Neal N. Zhang, Di Pei, Songwen University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Sul Ross State University Department of Computer Science and Mathematics AlpineTX79830 United States Zhengzhou University School of Electrical and Information Engineering Zhengzhou450001 China Zhengzhou University Henan International Joint Laboratory of Intelligent Health Information System Zhengzhou450001 China Zhengzhou University National Engineering Laboratory for Internet Medical Systems and Applications Zhengzhou450001 China

Mobile edge computing (MEC) mitigates the energy and computation burdens on mobile users (MUs) by offloading tasks to the network edge. To optimize MEC server utilization through effective resource allocation, a well-designed pricing strategy is indispensable. In this paper, we propose a dynamic differential pricing scheme (DDPS) for an edge offloading scenario with energy harvesting devices, which determines prices based on computing resource usage to enhance edge server (ES) utilization. First, an offloading decision algorithm is proposed to balance harvested and consumed energy, determining whether and how much data to offload. Second, a Stackelberg game-based differential pricing algorithm is proposed to optimize computing resource allocation for MUs and reallocate surplus resources to delay-sensitive devices. Extensive simulations are conducted to demonstrate the effectiveness of the proposed DDPS scheme. Specifically, in comparison to the existing best-performing pricing scheme, for different task arrival rates, DDPS can achieve a 5.3% decrease in average execution delay, a 1.7% increase in ES utility (Userver, which represents the payment from MUs minus penalties for discarded tasks), and a 2.1% increase in the average ratio of service for MUs. In addition, DDPS also improves 2.8% Userver on average with different ES computation capacities. © 2025 IEEE. All rights reserved.

关键词： Mobile edge computing

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Joint Beamforming and Power Allocation Design for Wirelessly Charged Unmanned Inspecting Vehicles in Power Transmission Systems

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2025年

作者： Huang, Yingjie Abdelhady, Amr M. Wang, Qianggang Ye, Jia Chi, Yuan Eltawil, Ahmed M. El-Sherif, Amr A. ElBatt, Tamer Chongqing University State Key Laboratory of Power Transmission Equipment Technology School of Electrical Engineering Chongqing400044 China King Abdullah University of Science and Technology Computer Electrical and Mathematical Science and Engineering Division Province Makkah23955-6900 Saudi Arabia Electronics and Communications Department Egypt University of Informatics Cairo Governorate Egypt Department of Computer Science and Engineering The American University Cairo Governorate Cairo Egypt

The rapid development of the smart grid has intensified research efforts towards automating power transmission system inspections using unmanned intelligent vehicles (UIVs). A major challenge hindering their large-scale deployment is the short operational endurance of these vehicles. This paper addresses this limitation by proposing the use of an energy transmitter (ET) and a reconfigurable intelligent surface for wirelessly charging the vehicles through radio frequency (RF) signals. Additionally, we tackle the nonlinearity of RF-to-direct current (DC) conversion, which shows efficiency saturation at high power levels, by introducing a novel power-splitting (PS) energy harvesting (EH) receiver architecture in the inspection vehicles. The inspection tasks are divided into multiple time slots, and a power transfer efficiency (PTE) maximization problem is formulated to jointly optimize the beamforming design at both the transmitter and the RIS, as well as the transmit power allocation and receiving power splitter settings for each time slot. This approach aims to meet the energy requirements of the unmanned inspection vehicles while adhering to the total available power constraint at the ET. To solve the non-convex PTE maximization problem, we propose an efficient solution utilizing alternating optimization, the Dinkelbach’s method, and successive convex approximation, considering the unique properties of channel structure and finite phase resolution. Numerical results demonstrate that our proposed system and design significantly extend the lifespan of inspection vehicles and achieve high energy efficiency in a low-complexity manner. © 2017 IEEE.

关键词： Inductive power transmission

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