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Recticoil for Efficient Compact Inductive Power Transfer

IEEE Transactions on Power Electronics 2025年第7期40卷 10154-10164页

作者： Yi, Zixuan Qin, Yuanyuan Yang, Xue-Xia Shao, Yaoxia Zeng, Dan Li, Meiling Shanghai University School of Communication and Information Engineering Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science Shanghai200444 China Hangzhou City University School of Information and Electrical Engineering Hangzhou310015 China

The MHz inductive power transfer (IPT) system has broad application prospects due to its high safety, longer transmission distance, and better tolerance for misalignment. However, the increase in frequency will lead to an increased loss of lumped components, such as inductors and capacitors, in peripheral circuits, thereby reducing efficiency. This is currently the bottleneck problem encountered by MHz IPT. To address this key challenge, researchers have tried to remove the lumped components in the peripheral circuit while ensuring the functions of the IPT system. One successful and beneficial attempt is the self-resonant coil, which replaces traditional lumped resonant capacitors with distributed capacitors formed by coil turn-to-turn capacitance, ensuring compensation for leakage inductance and eliminating reactive power. This innovative integration makes efficiency and integration greatly improved. In this article, the novel coil named Recticoil, on which the rectification function is integrated further, is proposed for efficient compact IPT. Recticoil can directly output dc power without additional compensation and rectification circuits. By analyzing a toroidal coil where two separate conductors generate a voltage differential, and incorporating two diodes, resulting in a dc output. Subsequently, the self-resonant coil replaces the toroidal coil to form Recticoil, and the equivalent circuits of Recticoil are given and analyzed. In addition, the analysis and test method of rectification efficiency is given. The experimental results show that the Recticoil achieves a rectification efficiency as high as 97.25% at 6.78 MHz, outperforming both the bridge rectifier and the Class E rectifier. Additionally, the compact construction of Recticoil eliminates the volume of traditional rectifiers. All of these advantages of Recticoil render it a promising candidate for applications in wearables and miniaturized devices. © 1986-2012 IEEE.

关键词： Equivalent circuits

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Application of meta-learning in cyberspace security:a survey

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Digital Communications and Networks 2023年第1期9卷 67-78页

作者： Aimin Yang Chaomeng Lu Jie Li Xiangdong Huang Tianhao Ji Xichang Li Yichao Sheng Hebei Key Laboratory of Data Science and Application North China University of Science and TechnologyTangshan063000China Hebei Engineering Research Center for the Intelligentization of Iron Ore Optimization and Ironmaking Raw Materials Preparation Processes North China University of Science and TechnologyTangshan063000China The Key Laboratory of Engineering Computing in Tangshan City North China University of Science and TechnologyTangshan063000China

In recent years,machine learning has made great progress in intrusion detection,network protection,anomaly detection,and other issues in ***,these traditional machine learning algorithms usually require a lot of data to learn and have a low recognition rate for unknown *** them,“one-shot learning”,“few-shot learning”,and“zero-shot learning”are challenges that cannot be ignored for traditional machine *** more intractable problem in cyberspace security is the changeable attack *** a new attack mode appears,there are few or even zero samples that can be ***-learning comes from imitating human problem-solving methods as humans can quickly learn unknown things based on their existing knowledge when *** purpose is to quickly obtain a model with high accuracy and strong generalization through less data *** article first divides the meta-learning model into five research directions based on different principles of *** are model-based,metric-based,optimization-based,online-learning-based,or stacked ***,the current problems in the field of cyberspace security are categorized into three branches:cyber security,information security,and artificial intelligence security according to different ***,the application research results of various meta-learning models on these three branches are *** the same time,based on the characteristics of strong generalization,evolution,and scalability of meta-learning,we contrast and summarize its advantages in solving ***,the prospect of future deep application of meta-learning in the field of cyberspace security is summarized.

关键词： Meta-learning Cyberspace security Machine learning Few-shot learning

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Robust and Verifiable Privacy Federated Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1895-1908页

作者： Lu, Zhi Lu, Songfeng Tang, Xueming Wu, Junjun Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518063 China

Federated learning (FL) safeguards user privacy by uploading gradients instead of raw data. However, inference attacks can reconstruct raw data using gradients uploaded by users in FL. To mitigate this issue, researchers have combined privacy computing techniques with FL. However, these techniques may not ensure the Byzantine robustness of aggregation or the integrity of the aggregated outcomes. Most current robust privacy FL methods assess differences between gradients and benchmarks in the direction, allowing adversaries to poison the aggregation against the magnitude. Furthermore, these methods cannot ensure the integrity of the aggregation results. To overcome these challenges, this study proposes a novel algorithm, robust and verifiable privacy federated learning (RVPFL), which can more effectively eliminate the poisoning attack of the opponent by measuring the direction and magnitude of the gradient in the ciphertext state. The proposed algorithm guarantees the integrity of server aggregation results while safeguarding user privacy. In this study, comprehensive theoretical analysis and experimental validation of RVPFL are conducted to demonstrate its superiority. The proposed RVPFL algorithm solves the Byzantine robustness problem of aggregation and the integrity problem of aggregation results, which helps to research and develop more robust and effective privacy-preserving federal learning techniques. © 2020 IEEE.

关键词： Learning algorithms

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Evolution of vegetation phenology and its response to urbanisation in Shaanxi province, China: A fine-scale perspective

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Journal of Geographical Sciences 2025年第5期35卷 1024-1048页

作者： GAO Meiling MA Jingjing LI Zhenhong YANG Guijun College of Geological Engineering and Geomatics Chang'an University State Key Laboratory of Loess Science Key Laboratory of Ecological Geology and Disaster Prevention Ministry of Natural Resources Big Data Center for Geosciences and Satellites

Shaanxi province in China is rich in vegetation resources, making the study of vegetation phenology crucial for understanding climate change and ecological dynamics. Previous studies on Shaanxi have primarily focused on coarse-scale phenology, which results in the loss of essential spatial details due to the lack of finer-scale analyses. Moreover, the impact of rapid urbanisation on the phenology of various vegetation types in this region remains unclear. To address these gaps, we integrated Landsat and MODIS data to generate a daily 30 m NDVI sequence. Vegetation phenology across Shaanxi from 2000 to 2020 was then extracted and analysed, and the responses of different vegetation types to urbanisation were explored. Results indicated that accurate vegetation phenology can be obtained at a 30 m resolution, which is more precise than conventional coarse-scale investigations. The Start of Season(SOS) and End of Season(EOS) in the province advanced by-0.56 and-0.08 day/year, respectively, from 2000 to 2020. In general, the SOS gradually delays, and the EOS progressively advances with increasing latitude. However, anomalies were identified in regions south of 32.64°N and across the zone from 34.04°N to 37.56°N, which are primarily due to the effects of high elevation and rapid urbanisation, respectively. Further investigation into phenological differences among various vegetation types revealed that forests exhibit the earliest SOS, while grasslands present the latest. In addition, a significant negative correlation was found between the SOS difference and air temperature difference along the urban–rural gradient, with urbanisation having the most significant impact on cropland phenology. This study provides valuable insights into vegetation phenology and its response to urbanisation. These insights offer crucial information for ecological conservation and management strategies.

关键词： gap filling and Savitzky–Golay filtering Google Earth Engine spatiotemporal changes urbanisation vegetation phenology

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Acoustic Localization Method for Burst Point of Group Shot Projectile Based on Non-Parametric Estimation 2

Acoustic Localization Method for Burst Point of Group Shot P...

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2nd International Conference on Artificial Intelligence and Intelligent Information Processing, AIIIP 2023

作者： Zhang, Yahui Feng, Song Shang, Shuxian Tan, Weijie Wang, Yulong Zhang, Chunwei China Huayin Ordnance Test Center Huayin China State Key Laboratory of Public Big Data Guizhou Big Data Academy Guiyang China School of Mechanical Engineering State Key Laboratory for Manufacturing System Engineering Xi'an China

ISBN: (纸本)9798350371451

In the acoustic localization of mass projectiles, due to the large number of mass projectiles and short firing time, the traditional algorithm has some problems, such as waveform superposition and the order of explosion arrival at the sensor is not easy to distinguish. In order to solve this problem, an acoustic location method for burst point of mass projectile based on nonparametric estimation was proposed. The distribution of explosion probability function was calculated based on the measured acoustic waveform and regional explosion energy function. Then, the actual explosion point coordinates were obtained according to the extreme value. This method does not need to estimate the arrival time and arrival angle parameters, solves the problem that the order of arrival time is not easy to distinguish. Simulation and field tests show that the algorithm can effectively deal with 1∼32 projectiles fired in 2s, and solve the problem of explosion point location in the process of group gun surface attack exercise training and combat test. © 2023 IEEE.

关键词： Projectiles

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Multi-agent Reinforcement Learning for a Special Formation Problem 5th

Multi-agent Reinforcement Learning for a Special Formation P...

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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Qu, Changsheng Ke, Liangjun Xuan, Shuzhe Wang, Zhigang State Key Laboratory for Manufacturing Systems Engineering School of Automation Science and Engineering Xi’an Jiaotong University 710049 Xi’an China CETC Key Laboratory of Data Link Technology Xi’an China

ISBN: (纸本)9789811939976

For a long time, the formation control problem has been one of the core problems in the field of multi-agent collaboration. It’s goal is to make multiple agents form a formation in the tasks and move to a designated target point. In this paper, the reinforcement learning method is used to deal with a special formation problem, and the mean field theory is applied to Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to make it effective in large-scale multi-agent formation problems. The algorithm is compared with MADDPG and Deep Deterministic Policy Gradient (DDPG) algorithm. In the simulation experiment, a team of UAVs are initialized at random positions in the two-dimensional space. The goal is to make the UAVs form an equilateral triangle with the shortest total displacement. We model the formation problem. In our algorithm, a reward function is designed based on the goal of making equilateral triangle formation and requirement of the shortest total displacement;Moreover, we define the equilateral triangle criterion and use it to evaluate the formation effect of multi-agent reinforcement learning. The results show that, compared with DDPG and MADDPG algorithms, MADDPG algorithm using the mean field method has obvious advantages over MADDPG and DDPG in terms of convergence speed and success rate in the formation problem. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mean field theory

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Predicting Lactobacillus delbrueckii ***-Streptococcus thermophilus interactions based on a highly accurate semi-supervised learning method

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Science China(Life Sciences) 2025年第2期68卷 558-574页

作者： Shujuan Yang Mei Bai Weichi Liu Weicheng Li Zhi Zhong Lai-Yu Kwok Gaifang Dong Zhihong Sun Key Laboratory of Dairy Biotechnology and Engineering Ministry of EducationInner Mongolia Agricultural UniversityHohhot 010018China Key Laboratory of Dairy Products Processing Ministry of Agriculture and Rural AffairsInner Mongolia Agricultural UniversityHohhot 010018China Inner Mongolia Key Laboratory of Dairy Biotechnology and Engineering Inner Mongolia Agricultural UniversityHohhot 010018China Collaborative Innovative Center for Lactic Acid Bacteria and Fermented Dairy Products Ministry of EducationInner Mongolia Agricultural UniversityHohhot 010018China College of Computer and Information Engineering Inner Mongolia Agricultural UniversityHohhot 010018China Inner Mongolia Autonomous Region Key Laboratory of Big Data Research and Application of Agriculture and Animal Husbandry Hohhot 010018China

Lactobacillus delbrueckii ***(***)and Streptococcus thermophilus(***)are commonly used starters in milk *** experiments revealed that *** interactions(Lb St I)substantially impact dairy product quality and *** biological humidity experiments are time-consuming and labor-intensive in screening interaction combinations,an artificial intelligence-based method for screening interactive starter combinations is ***,in the current research on artificial intelligence based interaction prediction in the field of bioinformatics,most successful models adopt supervised learning methods,and there is a lack of research on interaction prediction with only a small number of labeled ***,this study aimed to develop a semi-supervised learning framework for predicting Lb St I using genomic data from 362 isolates(181per species).The framework consisted of a two-part model:a co-clustering prediction model(based on the Kyoto Encyclopedia of Genes and Genomes(KEGG)dataset)and a Laplacian regularized least squares prediction model(based on K-mer analysis and gene composition of all isolates datasets).To enhance accuracy,we integrated the separate outcomes produced by each component of the two-part model to generate the ultimate Lb St I prediction results,which were verified through milk fermentation *** through milk fermentation experiments confirmed a high precision rate of 85%(17/20;validated with 20 randomly selected combinations of expected interacting isolates).Our data suggest that the biosynthetic pathways of cysteine,riboflavin,teichoic acid,and exopolysaccharides,as well as the ATP-binding cassette transport systems,contribute to the mutualistic relationship between these starter bacteria during milk ***,this finding requires further experimental *** presented model and data are valuable resources for academics an

关键词： Lactobacillus delbrueckii subsp.bulgaricus and Streptococcus thermophilus interaction prediction semi-supervised learning dairy starter artificial intelligence milk fermentation

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Three-Dimensional Collision Avoidance Method for Robot-Assisted Minimally Invasive Surgery

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Cyborg and Bionic Systems 2023年第1期4卷 121-135页

作者： Ling Li Xiaojian Li Bo Ouyang Hangjie Mo Hongliang Ren Shanlin Yang School of Management Hefei University of TechnologyHefeiChina Key Laboratory of Process Optimization and Intelligent Decision-Making(Ministry of Education) Hefei University of TechnologyHefeiChina Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance(Ministry of Education) Hefei University of TechnologyHefeiChina Department of Biomedical Engineering Faculty of EngineeringNational University of SingaporeSingaporeSingapore Department of Electronic Engineering Shun Hing Institute of Advanced EngineeringThe Chinese University of Hong KongHong KongChina National Engineering Laboratory for Big Data Distribution and Exchange Technologies ShanghaiChina

In the robot-assisted minimally invasive surgery,if a collision occurs,the robot system program could be damaged,and normal tissues could be *** avoid collisions during surgery,a 3-dimensional collision avoidance method is proposed in this *** proposed method is predicated on the design of 3 strategic vectors:the collision-with-instrument-avoidance(CI)vector,the collision-with-tissues-avoidance(CT)vector,and the constrained-control(CC)*** CI vector demarcates 3 specific directions to forestall collision among the surgical *** CT vector,on the other hand,comprises 2 components tailored to prevent inadvertent contact between the robot-controlled instrument and nontarget ***,the CC vector is introduced to guide the endpoint of the robot-controlled instrument toward the desired position,ensuring precision in its movements,in alignment with the surgical *** results verify the proposed collision avoidance method for robot-assisted minimally invasive *** code and data are available at https://***/cynerelee/collision-avoidance.

关键词： collision desired verify

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A numerical magnitude aware multi-channel hierarchical encoding network for math word problem solving

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Neural Computing and Applications 2025年第3期37卷 1651-1672页

作者： Xu, Junjie Chen, Yuzhong Xiao, Lingsheng Liao, Hongmiao Zhong, Jiayuan Dong, Chen College of Computer and Data Science Fuzhou University Fujian Province Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fujian Province Fuzhou350108 China

Math word problem (MWP) represents a critical research area within reading comprehension, where accurate comprehension of math problem text is crucial for generating math expressions. However, current approaches still grapple with unresolved challenges in grasping the sensitivity of math problem text and delineating distinct roles across various clause types, and enhancing numerical representation. To address these challenges, this paper proposes a Numerical Magnitude Aware Multi-Channel Hierarchical Encoding Network (NMA-MHEA) for math expression generation. Firstly, NMA-MHEA implements a multi-channel hierarchical context encoding module to learn context representations at three different channels: intra-clause channel, inter-clause channel, and context-question interaction channel. NMA-MHEA constructs hierarchical constituent-dependency graphs for different levels of sentences and employs a Hierarchical Graph Attention Neural Network (HGAT) to learn syntactic and semantic information within these graphs at the intra-clause and inter-clause channels. NMA-MHEA then refines context clauses using question information at the context-question interaction channel. Secondly, NMA-MHEA designs a number encoding module to enhance the relative magnitude information among numerical values and type information of numerical values. Experimental results on two public benchmark datasets demonstrate that NMA-MHEA outperforms other state-of-the-art models. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Semantics

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data-Driven Design of Fault Detection Approach for Dynamic Systems Based on Subspace Identification Method 13

Data-Driven Design of Fault Detection Approach for Dynamic S...

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13th IEEE data Driven Control and Learning Systems Conference, DDCLS 2024

作者： Yating, Lyu Jingjing, Gao Xu, Yang Jian, Huang Jiarui, Cui School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education Beijing100083 China

ISBN: (纸本)9798350361674

In the context of continuous advancements in modern industry and the escalating demands for the safety and reliability of control systems, timely fault diagnosis of control systems becomes paramount. Driven by this imperative, this article devotes to data-driven design of fault detection systems based on subspace identification method. For this purpose, a fault detection approach based on Subspace State Space System Identification and model-based full-dimensional observer design is firstly designed. It is followed by a data-driven fault detection approach based on one-step identification of stable kernel representation and direct design of the residual generator. Finally, the effectiveness and performance of the two proposed approaches have been verified through a case study on the laboratory threetank system. © 2024 IEEE.

关键词： State space methods

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