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10th IEEE Smart World Congress, SWC 2024

作者： Chen, Junyan Gao, Hui Wu, Xucheng University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Electronic Science and Technology of China Kash Institute of Electronics and Information Industry School of Computer Science and Engineering Chengdu China

ISBN: (纸本)9798331520861

Graph similarity computation is a critical task in various fields, including bioinformatics, social network analysis, and pattern recognition. Traditional methods, such as Graph Edit Distance, face challenges in computational complexity and accuracy. In this paper, we propose IASim, a method for computing graph similarity with information enhancement, leveraging Graph Neural Networks to enhance the accuracy and efficiency of graph similarity computation. IASim incorporates edge information and multi-level node information into the graph embedding process, utilizing a multi-layer neural tensor network architecture and a novel attention mechanism to capture the intricate relationships between nodes and edges. Our experiments on three diverse real datasets demonstrate that IASim outperforms existing methods in both accuracy and computational efficiency, exhibiting outstanding robustness and stability across a range of embedding dimensions. IASim emerges as a promising tool for a variety of applications demanding graph similarity computations. © 2024 IEEE.

关键词： Graph embeddings

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Hydrogel electrodes with conductive and substrate-adhesive layers for noninvasive long-term EEG acquisition

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Microsystems & Nanoengineering 2023年第3期9卷 357-370页

作者： Hailing Xue Dongyang Wang Mingyan Jin Hanbing Gao Xuhui Wang Long Xia Dong’ang Li Kai Sun Huanan Wang Xufeng Dong Chi Zhang Fengyu Cong Jiaqi Lin Key State Laboratory of Fine Chemicals School of BioengineeringDalian University of Technology116024 DalianChina School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of Technology116024 DalianChina Key Laboratory of Energy Materials and School of Materials Science and Engineering Dalian University of Technology116024 DalianChina

Noninvasive brain–computer interfaces (BCIs) show great potential in applications including sleep monitoring, fatigue alerts, neurofeedback training, etc. While noninvasive BCIs do not impose any procedural risk to users (as opposed to invasive BCIs), the acquisition of high-quality electroencephalograms (EEGs) in the long term has been challenging due to the limitations of current electrodes. Herein, we developed a semidry double-layer hydrogel electrode that not only records EEG signals at a resolution comparable to that of wet electrodes but is also able to withstand up to 12 h of continuous EEG acquisition. The electrode comprises dual hydrogel layers: a conductive layer that features high conductivity, low skin-contact impedance, and high robustness;and an adhesive layer that can bond to glass or plastic substrates to reduce motion artifacts in wearing conditions. Water retention in the hydrogel is stable, and the measured skin-contact impedance of the hydrogel electrode is comparable to that of wet electrodes (conductive paste) and drastically lower than that of dry electrodes (metal pin). Cytotoxicity and skin irritation tests show that the hydrogel electrode has excellent biocompatibility. Finally, the developed hydrogel electrode was evaluated in both N170 and P300 event-related potential (ERP) tests on human volunteers. The hydrogel electrode captured the expected ERP waveforms in both the N170 and P300 tests, showing similarities in the waveforms generated by wet electrodes. In contrast, dry electrodes fail to detect the triggered potential due to low signal quality. In addition, our hydrogel electrode can acquire EEG for up to 12 h and is ready for recycled use (7-day tests). Altogether, the results suggest that our semidry double-layer hydrogel electrodes are able to detect ERPs in the long term in an easy-to-use fashion, potentially opening up numerous applications in real-life scenarios for noninvasive BCI.

关键词： conductive electrode impedance

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Domain Contrastive Learning for Multi-Site Alzheimer's Disease Classification 20

Domain Contrastive Learning for Multi-Site Alzheimer's Disea...

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20th International Computer Conference on Wavelet Active Media technology and information Processing, ICCWAMTIP 2023

作者： Fiasam, Linda Delali Rao, Yunbo Sey, Collins Aggrey, Esther Stacy E. B. Kodjiku, Seth Larweh Browne, Judith Ayekai Danso, Juliana Mantebea Ukwuoma, Chiagoziem C. Gyarteng, Emmanuel S. A. School of Information and Software Engineering University of Electronic Science and Technology of China China School of Computer Science and Technology Zhejiang Gongshang University China School of Computer Science and Technology University of Electronic Science and Technology of China University China College of Nuclear Technology and Automation Engineering Chengdu University of Technology China

ISBN: (纸本)9798350318982

In the field of medical imaging, accurately classifying Alzheimer's Disease (AD) poses a substantial challenge, primarily due to the inherent variability in imaging data across different clinical sites. This paper introduces a novel approach, Domain Contrastive Learning (DCL), to address this challenge by enhancing the robustness and transferability of AD classification models using multi-site Magnetic Resonance Imaging (MRI) data. DCL leverages a unique contrastive learning technique within an autoencoder's latent space, enabling the extraction of domain-invariant features essential for accurate diagnosis. We rigorously evaluate the proposed network on brain images from three distinct imaging sites, employing a Domain Generalization (DG) training protocol to ensure robustness and generalizability across varying data sources. Our model is evaluated on three binary classification tasks: AD vs. Normal Control (NC), AD vs. Mild Cognitive Impairment (MCI), and MCI vs. NC. Results demonstrate that DCL outperforms existing methods, especially in AD vs. NC classification, achieving higher accuracy, sensitivity, and specificity with 0.51%, 1.54% and 1.68% increments respectively. This underscores DCL's potential as a robust and generalizable method for enhanced AD diagnosis, marking a significant step forward in medical imaging challenges in a multi-site context. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Performance analysis of UAV-based mixed underwater PLC-RF systems

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Digital Communications and Networks 2024年第5期10卷 1332-1340页

作者： Shenghai Chen Liang Yang Xianfu Lei College of Computer Science and Electronic Engineering Hunan UniversityChangsha410082China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua418000China School of Information Science and Technology Southwest Jiaotong UniversityChengdu610031China

In this study,we analyzed the performance of an Unmanned Aerial Vehicle(UAV)-based mixed Underwater Power Line Communication-Radio Frequency(UPLC-RF)*** this network,a buoy located at the sea is used as a relay to transmit signals from the underwater signal source to the UAV through the PLC *** assume that the UPLC channel obeys a log-normal distribution and that the RF link follows the Rician *** this model,we obtained the closed-form expressions for the Outage Probability(OP),Average Bit-error-rate(ABER),and Average Channel Capacity(ACC).In addition,the asymptotic analysis of the OP and ABER was performed,and an upper bound for the average capacity was ***,the analytical results were verified by Monte Carlo simulation thereby demonstrating the effect of impulse noise and the altitude of the UAV on network performance.

关键词： ABER Average bit-error-rate ACC Average channel capacity OP Outage probability UAV Unmanned aerial vehicle UPLC Underwater power line communication

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A Sequential Rotation Filtering Network for High Circular Polarization Purity Antenna Array

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IEEE Microwave and Wireless technology Letters 2025年第4期35卷 428-431页

作者： Wu, Sifan Li, Jianxing Yao, Jiahui Cao, Yuanxi Xu, Kai-Da Xi'an Jiaotong University Shaanxi Key Laboratory of Deep Space Exploration Intelligent Information Technology School of Information and Communications Engineering Xi'an710049 China University of Electronic Science and Technology of China Zhejiang Quzhou324000 China

This letter introduces a sequential rotation filtering network (SRFN), enabling a 16×16 antenna array to achieve high circular polarization (CP) purity and enhanced frequency selectivity. The proposed SRFN integrates filtering, power dividing, and phase shifting functions, providing phase states of 0°, 90°, 180°, and 270° at the four output ports with 7th-order filtering response. Moreover, four sets of 8×8 subarrays are arranged orthogonally and connected to the outputs of the SRFN. Finally, a 16×16 antenna array is monolithically fabricated using the 3-D printing technology. Measurement results demonstrate an operating bandwidth (return loss >10 dB) of 27.7-29.6 GHz, with the radiation gain ranging from 29.5 to 30.5 dBic. Due to the proposed SRFN, the in-band axial ratio (AR) remains lower than 0.5 dB, while the out-of-band realized gain suppression exceeds 30 dB/GHz. The proposed SRFN methodology serves as an integrated feeding network for antenna arrays requiring high CP purity and frequency selectivity. © 2023 IEEE.

关键词： Circular polarization

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DeepOCL:A deep neural network for Object Constraint Language generation from unrestricted nature language

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CAAI Transactions on Intelligence technology 2024年第1期9卷 250-263页

作者： Yilong Yang Yibo Liu Tianshu Bao Weiru Wang Nan Niu Yongfeng Yin School of Software Beihang UniversityBeijingChina College of Computer Science and Technology Guizhou UniversityGuiyangGuizhouChina Faculty of Information Technology Beijing University of TechnologyBeijingChina Department of Electrical Engineering and Computer Sciences University of CincinnatiCincinnatiOhioUSA

Object Constraint Language(OCL)is one kind of lightweight formal specification,which is widely used for software verification and validation in NASA and Object Management Group *** OCL provides a simple expressive syntax,it is hard for the developers to write correctly due to lacking knowledge of the mathematical foundations of the first-order logic,which is approximately half accurate at the first stage of devel-opment.A deep neural network named DeepOCL is proposed,which takes the unre-stricted natural language as inputs and automatically outputs the best-scored OCL candidates without requiring a domain conceptual model that is compulsively required in existing rule-based generation *** demonstrate the validity of our proposed approach,ablation experiments were conducted on a new sentence-aligned dataset named *** experiments show that the proposed DeepOCL can achieve state of the art for OCL statement generation,scored 74.30 on BLEU,and greatly outperformed experienced developers by 35.19%.The proposed approach is the first deep learning approach to generate the OCL expression from the natural *** can be further developed as a CASE tool for the software industry.

关键词： deep learning OCL software engineering

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Adaptive Climbing Strategy of Snake Robot Based on Compliance Control 4

Adaptive Climbing Strategy of Snake Robot Based on Complianc...

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4th International Symposium on Intelligent Robotics and Systems, ISoIRS 2024

作者： Yang, Huizhuo Dong, Jiyuan Wang, Meng Meng, Shiyong Yang, Lei Xue, Jiashuo Tiangong University School of Electronic and Information Engineering Tianjin China Tiangong University Department of Computer Science and Technology Tianjin China Tiangong University Department of Software Engineering Tianjin China

ISBN: (纸本)9798350364798

Snake robots, exhibiting a high degree of redundancy, are a class of biomimetic robots capable of forming a helical rolling gait for climbing trees and pipes. The surface structure of naturally grown trees is irregular, which may hinder the snake robots from achieving optimal surface conformation. Additionally, the presence of numerous branching structures in pipes introduces unpredictability in pipe climbing. To address these challenges, we propose an adaptive climbing strategy for snake robots based on compliant control. By adjusting a pre-set elasticity coefficient, the snake robot modulates the output torque of each joint, thereby altering the target angle of the joint. This adjustment enables the snake robot to adapt to unstructured environments. We conducted an experiment on climbing curved pipes to verify the effectiveness of this method. The result demonstrate that under unknown conditions, the robustness of the snake robot's climbing motion is enhanced by modifying the pre-set elasticity coefficient based on compliant control. This finding underscores the potential of compliant control in improving the adaptability and performance of Snake robots in complex environments. © 2024 IEEE.

关键词： Microrobots

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Remote entangling gate between a quantum dot spin and a transmon qubit mediated by microwave photons

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Chinese Physics B 2024年第2期33卷 52-59页

作者：朱行宇朱乐天涂涛李传锋 Key Laboratory of Quantum Information Chinese Academy of SciencesUniversity of Science and Technology of ChinaHefei 230026China School of Mechanical and Electronic Engineering Suzhou UniversitySuzhou 234000China Hefei National Laboratory University of Science and Technology of ChinaChinese Academy of SciencesHefei 230088China

Spin qubits and superconducting qubits are promising candidates for realizing solid-state quantum information *** a hybrid architecture that combines the advantages of different qubits on the same chip is a highly desirable but challenging *** we propose a hybrid architecture that utilizes a high-impedance SQUID array resonator as a quantum bus,thereby coherently coupling different solid-state *** employ a resonant exchange spin qubit hosted in a triple quantum dot and a superconducting transmon *** this hybrid system is highly tunable,it can operate in a dispersive regime,where the interaction between the different qubits is mediated by virtual *** utilizing such interactions,entangling gate operations between different qubits can be realized in a short time of 30 ns with a fidelity of up to 96.5%under realistic parameter *** utilizing this interaction,remote entangled state between different qubits can be prepared and is robust to perturbations of various *** results pave the way for exploring efficient fault-tolerant quantum computation on hybrid quantum architecture platforms.

关键词： hybrid quantum architectures circuit quantum electrodynamics entangling gate

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Application of a class of density peak clustering algorithm in short-term smart grid 8

Application of a class of density peak clustering algorithm ...

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8th International Conference on Energy System, Electricity, and Power, ESEP 2023

作者： Wang, Chenyu Zhang, Zhao Zhu, Zhipeng Zhou, Hongyan School of Computer Science and Software Engineering University of Science and Technology Liaoning 185 Qianshanzhong Road Liaoning Anshan114051 China School of Electronic and Information Engineering University of Science and Technology Liaoning 185 Qianshanzhong Road Liaoning Anshan114051 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

The classification of short-term power load data by clustering algorithm can lay a good foundation for the subsequent power load forecasting work and provide a more efficient, safe and reliable direction for the operation of power system. Density peaks clustering algorithm with k-nearest neighbors and weighted similarity can reduce the negative impact of global data on local data, avoid the collateral effect of errors and improve the accuracy of the model. It has better effect on local peak power change and global power forecast. In this paper, the density peaks clustering algorithm with k-nearest neighbors and weighted similarity are compared with DPC clustering method through simulation examples, and the effectiveness of this method is verified. © 2024 SPIE.

关键词： Clustering algorithms

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Event-Triggered Control for Obstacle Avoidance in Second-Order Nonlinear Multi-Agent Systems with Directed Graph 8

Event-Triggered Control for Obstacle Avoidance in Second-Ord...

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8th International Conference on Energy System, Electricity, and Power, ESEP 2023

作者： Zhu, Zhipeng Zhang, Zhao Wang, Chenyu Zhou, Hongyan School of Computer Science and Software Engineering University of Science and Technology Liaoning 185 Qianshanzhong Road Liaoning Anshan114051 China School of Electronic and Information Engineering University of Science and Technology Liaoning 185 Qianshanzhong Road Liaoning Anshan114051 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

In this paper, we study the obstacle avoidance problem of second-order nonlinear multi-agent systems (MASs) with directed graph based on event-triggered control. Firstly, the consensus requirement is accomplished by using the event-triggered consensus algorithm, and experiments are given for verification. Secondly, an improved artificial potential field (IAPF) method is proposed to solve the obstacle avoidance problem, and comparison experiments are made, from which the experimental results show that the IAPF method is significantly better than the traditional artificial potential field (TAPF) method under the same conditions. © 2024 SPIE.

关键词： Directed graphs

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