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Multi-parameter ultrasound imaging for musculoskeletal tissues based on a physics informed generative adversarial network

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Chinese Physics B 2025年第4期34卷 442-455页

作者： Pengxin Wang Heyu Ma Tianyu Liu Chengcheng Liu Dan Li Dean Ta Institute of Biomedical Engineering&Technology Academy for Engineering and TechnologyFudan UniversityShanghai 200433China State Key Laboratory of Integrated Chips and Systems Fudan UniversityShanghai 201203China Department of Electronic Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China Department of Biomedical Engineering School of Information Science and TechnologyFudan UniversityShanghai 200438China

Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal ***,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging *** inaccurate initial model may lead to local minima in the inversion and unexpected imaging results caused by cycle-skipping *** learning methods have been applied in musculoskeletal imaging,but need a large amount of data for *** by work related to generative adversarial networks with physical informed constrain,we proposed a method named as bone ultrasound imaging with physics informed generative adversarial network(BUIPIGAN)to achieve unsupervised multi-parameter imaging for musculoskeletal tissues,focusing on speed of sound(SOS)and *** the in-silico experiments using a ring array transducer,conventional FWI methods and BUIPIGAN were employed for multiparameter imaging of two musculoskeletal tissue *** results were evaluated based on visual appearance,structural similarity index measure(SSIM),signal-to-noise ratio(SNR),and relative error(RE).For SOS imaging of the tibia–fibula model,the proposed BUIPIGAN achieved accurate SOS imaging with best *** specific quantitative metrics for SOS imaging were SSIM 0.9573,SNR 28.70 dB,and RE 5.78%.For the multi-parameter imaging of the tibia–fibula and human forearm,the BUIPIGAN successfully reconstructed SOS and density distributions with SSIM above 94%,SNR above 21 dB,and RE below 10%.The BUIPIGAN also showed robustness across various noise levels(i.e.,30 dB,10 dB).The results demonstrated that the proposed BUIPIGAN can achieve high-accuracy SOS and density imaging,proving its potential for applications in musculoskeletal ultrasound imaging.

关键词： ultrasound image physics informed generative adversarial network musculoskeletal imaging

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An Intelligent Privacy Protection Scheme for Efficient Edge Computation Offloading in IoV

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Chinese Journal of Electronics 2024年第4期33卷 910-919页

作者： Liang YAO Xiaolong XU Wanchun DOU Muhammad Bilal School of Software Nanjing University of Information Science and Technology State Key Laboratory for Novel Software Technology Nanjing University Department of Computer and Electronics Systems Engineering Hankuk University of Foreign Studies

As a pivotal enabler of intelligent transportation system(ITS), Internet of vehicles(Io V) has aroused extensive attention from academia and industry. The exponential growth of computation-intensive, latency-sensitive,and privacy-aware vehicular applications in Io V result in the transformation from cloud computing to edge computing,which enables tasks to be offloaded to edge nodes(ENs) closer to vehicles for efficient execution. In ITS environment,however, due to dynamic and stochastic computation offloading requests, it is challenging to efficiently orchestrate offloading decisions for application requirements. How to accomplish complex computation offloading of vehicles while ensuring data privacy remains challenging. In this paper, we propose an intelligent computation offloading with privacy protection scheme, named COPP. In particular, an Advanced Encryption Standard-based encryption method is utilized to implement privacy protection. Furthermore, an online offloading scheme is proposed to find optimal offloading policies. Finally, experimental results demonstrate that COPP significantly outperforms benchmark schemes in the performance of both delay and energy consumption.

关键词： Industries Privacy Energy consumption Transportation Computational efficiency Encryption Protection

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Deep Learning Methods for Non-Contact Heart Rate Monitoring: A Review

Deep Learning Methods for Non-Contact Heart Rate Monitoring:...

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2024 World Conference on Complex systems, WCCS 2024

作者： El Boussaki, Hoda Latif, Rachid Saddik, Amine Ibn Zohr University Faculty of Applied Sciences Ait Melloul Morocco LISTI National School of Applied Sciences Ibn Zohr University Laboratory of Systems Engineering and Information Technology Agadir Morocco

ISBN: (纸本)9798331519131

Deep learning is a branch of machine learning that aims to teach computers to perform tasks that mimic human-like natural abilities. It has emerged as a pivotal technology contributing to advancements in the healthcare industry. This paper gives a thorough summary of the use of deep learning in non-contact heart rate assessment. Heart rate (HR) serves as a crucial vital sign for estimating the physiological condition of the body. Unlike conventional HR monitors, which typically necessitate skin contact, remote photoplethysmography (rPPG) allows for non-contact HR measurement by detecting minute variations in skin illumination through a video camera. © 2024 IEEE.

关键词： Photoplethysmography

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Color-conversion displays:current status and future outlook

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Light(Science & Applications) 2024年第12期13卷 2941-2961页

作者： Guijun Li Man-Chun Tseng Yu Chen Fion Sze-Yan Yeung Hangyu He Yuechu Cheng Junhu Cai Enguo Chen Hoi-Sing Kwok Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer EngineeringThe Hong Kong University of Science and TechnologyHong KongChina National and Local United Engineering Laboratory of Flat Panel Display Technology College of Physics and Information EngineeringFuzhou UniversityCollege of Physics and Information Engineering 350108FuzhouChina Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou 350108China

The growing focus on enhancing color quality in liquid crystal displays(LCDs)and organic light-emitting diodes(OLEDs)has spurred significant advancements in color-conversion ***,color conversion is also important for the development and commercialization of *** article provides a comprehensive review of different types of color conversion methods as well as different types of color conversion *** summarize the current status of patterning process,and discuss key strategies to enhance display ***,we speculate on the future prospects and roles that color conversion will play in ultra-high-definition micro-and projection displays.

关键词： materials projection outlook

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Air Combat Agent Construction Based on Hybrid Self-play Deep Reinforcement Learning 1

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11th China Conference on Command and Control, C2 2023

作者： Xia, Zhijie Mao, Yiming He, Jiafan Chen, Jiaxin Li, Qingwei Science and Technology On Information Systems Engineering Laboratory Nanjing210023 China

ISBN: (数字)9789819990214

ISBN: (纸本)9789819990207

In increasingly complex air combat, machine learning method such as deep reinforcement learning (DRL) for air combat decision-making control has become a research hotspot. In order to prevent air combat agents from falling into local optimum and enable the agents to gain advantages over diversified opponents, this paper proposes an air combat agent construction method based on hybrid self-play deep reinforcement learning. Before each game in training, DRL agent selects the opponent randomly from a strategy pool that includes multiple expert system agents and DRL self-play agent with delayed updates. Agents gain experience in confronting multiple opponents, and keeping exploring new air combat skills when confronting self-play agent with delayed updates. The experimental results showed that the trained agent achieved a very high winning rate against expert system agents. This demonstrates that this method is effective in improving the winning rate and preventing the agent from falling into the local optimum. © Chinese Institute of Command and Control 2024.

关键词： Reinforcement learning

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A framework of force of information influence and application for C4KISR system

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Journal of systems engineering and Electronics 2024年第2期35卷 430-443页

作者： MAO Shaojie DIAO Lianwang SUN Yu WANG Heng YI Kan XU Xin MAO Xiaobin ZHANG Kecheng SHENG Long Science and Technology on Information Systems Engineering Laboratory The 28th Research Institute of China Electronics Technology Group CorporationNanjing 210007China Unit 94860 of the PLA Nanjing 210008China

The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.

关键词： information warfare command control communications computer kill intelligence surveillance reconnaissance(C4KISR)system information circulation force of information influence information entropy

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Boosting for Distributed Online Convex Optimization

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Tsinghua Science and technology 2023年第4期28卷 811-821页

作者： Yuhan Hu Yawei Zhao Lailong Luo Deke Guo Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410073China Medical Engineering Laboratory of Chinese PLA General Hospital and also with the School of Cyberspace SecurityDongguan University of TechnologyDongguan 523000China

Decentralized Online Learning(DOL)extends online learning to the domain of distributed ***,limitations of local data in decentralized settings lead to a decrease in the accuracy of decisions or models compared to centralized *** the increasing requirement to achieve a high-precision model or decision with distributed data resources in a network,applying ensemble methods is attempted to achieve a superior model or decision with only transferring gradients or models.A new boosting method,namely Boosting for Distributed Online Convex Optimization(BD-OCO),is designed to realize the application of boosting in distributed ***-OCO achieves the regret upper bound O(M+N/MNT)where M measures the size of the distributed network and N is the number of Weak Learners(WLs)in each *** core idea of BD-OCO is to apply the local model to train a strong global ***-OCO is evaluated on the basis of eight different real-world *** results show that BD-OCO achieves excellent performance in accuracy and convergence,and is robust to the size of the distributed network.

关键词： distributed Online Convex Optimization(OCO) online boosting Online Gradient Boosting(OGB)

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Operational System of systems Capability Evaluation: A information Granule-Based Capability Representation and Evaluation Method 3

Operational System of Systems Capability Evaluation: A Infor...

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3rd International Conference on Artificial Intelligence and Computer information technology, AICIT 2024

作者： Yan, Jingjing Xiao, Weidong Zhang, Weiming Fu, Chen College of Systems Engineering National University of Denfense Technology Changsha China National Key Laboratory of Information Systems Engineering Nanjing China College of Systems Engineering National University of Denfense Technology National Key Laboratory of Information Systems Engineering Changsha China Nanjing Research Institute of Electronic Engineering National Key Laboratory of Information Systems Engineering Nanjing China

ISBN: (纸本)9798350365443

The modern military confrontations often involve simultaneous activities such as electromagnetic warfare, network information warfare, and weapon firepower confrontation. These confrontations typically take the form of a system of systems (SoS), which is a complex system with diverse data types, large volumes of data, and intricate data transmission networks. To ensure absolute superiority in military confrontations, combat commanders must be able to extract knowledge from the complex SoS data and intuitively understand and evaluate its various capabilities in order to promptly implement appropriate command measures. This study proposes a granular description-based method for evaluating SoS capabilities to achieve rapid and intuitive cognition of SoS capabilities. The method aims to transform the problem of evaluating SoS capabilities into a granular modeling problem consisting of three stages: the first stageinvolveso rganizing t he S oS data a nd constructing a dataset encompassing SoS capability;the second stage focuses on constructing capability information granules;the third stage develops an information granule-based model using historical SoS data. Based on the SoS capability dataset generated by the constructed SoS-level combat confrontation simulation environment, a series of experiments concerning the generated dataset are implemented to exhibit the process and effect of the proposed granular-based evaluation method. © 2024 IEEE.

关键词： information granules

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Compact TE-pass polarizer based on lithium-niobate-on-insulator assisted by indium tin oxide and silicon nitride

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Chinese Physics B 2023年第6期32卷 284-289页

作者：刘家敏张德龙 Department of Opto-electronics and Information Engineering School of Precision Instruments and Opto-electronics EngineeringKey Laboratory of Optoelectronic Information Technology(Ministry of Education)and Key Laboratory of Micro-Opto-Electro-Mechanical Systems(MOEMS)Technology(Ministry of Education)Tianjin UniversityTianjin 300072China

An indium tin oxide(ITO) and silicon nitride(Si_(3)N_(4)) assisted compact TE-pass waveguide polarizer based on lithiumniobate-on-insulator is proposed and numerically *** properly designing the ITO and Si_(3)N_(4) assisted structure and utilizing the epsilon-near-zero effect of ITO,the TM mode is strongly confined in the ITO layer with extremely high loss,while the TE mode is hardly affected and passes through the waveguide with low *** simulation results show that the polarizer has an extinction ratio of 22.5 dB and an insertion loss of 0.8 dB at the wavelength of 1.55 μm,and has an operating bandwidth of about 125 nm(from 1540 nm to 1665 nm) for an extinction ratio of>20 dB and an insertion loss of<0.95 ***,the proposed device exhibits large fabrication *** notably,the device is compact,with a length of only 7.5 μm,and is appropriate for on-chip applications.

关键词： polarizer lithium-niobate-on-insulator integrated optics devices optical waveguide

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A Novel Multi-Objective Synchronous Optimal Subarray Partition Method for Transmitting Array in Microwave Wireless Power Transmission

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Progress In Electromagnetics Research C 2024年 142卷 195-206页

作者： Li, Jianxiong Wang, Chen School of Electronic and Information Engineering Tiangong University Tianjin China Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems Tianjin China

To improve the beam collection efficiency (BCE) of the microwave wireless power transmission (MWPT) system while reducing the peak sidelobe level outside the receiving area (CSL) and system cost, this paper proposes a new subarray partition technique and a nonuniform sparsely distributed quadrant symmetric planar array (NSDQSPA) model. A particle swarm optimization algorithm based on multiple-objective with nonlinear time-variant inertia and learning factor improved particle swarm optimization (MO-NTVILFIPSO) is also proposed. The one-step multi-objective subarray partition algorithm adopts dynamic weight and dynamic learning factor to carry out one-step optimization on the array element arrangement of the transmitting array. The optimization algorithm simultaneously optimizes two performance indicators: the ∆BCE, which represents the optimization accuracy for the BCE, and the αref, which represents the mean square error of the excitation amplitude before and after the subarray partition. Many simulation results show that the BCE is 94.91%, and the CSL is −13.41 dB when the transmitting array with an aperture of 4.5λ × 4.5λ is divided into six subarrays. The simulation results further demonstrate that the proposed subarray division method is appropriate for the MWPT system and that the algorithm in this paper, when the array elements with the same excitation amplitude are divided for the planar transmitting array on the array model, and can guarantee relatively high BCE and relatively low complexity of the system feed network. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Mean square error

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