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Machine learning-assisted multi-stage highly sensitive electronic skin tactile sensing tracking platform

Science China Materials 2025年

作者： Shun Liu Ziqi Wang Duo Pan Hu Liu State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment National Engineering Research Center for Advanced Polymer Processing Technology Zhengzhou University

Human skin sensory system, featuring a sophisticated threedimensional(3D) distribution of mechanoreceptors within the skin, possesses an exceptional ability to perceive a diverse range of external mechanical stimuli a...

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Detecting Double Mixed Compressed Images Based on Quaternion Convolutional Neural Network

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Chinese Journal of Electronics 2024年第3期33卷 657-671页

作者： Hao WANG Jinwei WANG Xuelong HU Bingtao HU Qilin YIN Xiangyang LUO Bin MA Jinsheng SUN Department of Automation Nanjing University of Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Department of Computer and Software Nanjing University of Information Science and Technology School of Management Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University State Key Laboratory of Mathematical Engineering and Advanced Computing Qilu University of Technology

Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression *** particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing *** tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is *** QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion *** relationships between the color channels of the image are preserved,and the utilization of color information is ***,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double *** results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.

关键词： Color image forensics JPEG JPEG2000 Mixed double compression Quaternion convolutional neural network

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A quantum federated learning framework for classical clients

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Science China(Physics,Mechanics & Astronomy) 2024年第5期67卷 1-10页

作者： Yanqi Song Yusen Wu Shengyao Wu Dandan Li Qiaoyan Wen Sujuan Qin Fei Gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 00876China Department of Physics The University of Western AustraliaPerthWA 6009Australia School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijing100876China

Quantum federated learning(QFL)enables collaborative training of a quantum machine learning(QML)model among multiple clients possessing quantum computing capabilities,without the need to share their respective local ***,the limited availability of quantum computing resources poses a challenge for each client to acquire quantum computing *** raises a natural question:Can quantum computing capabilities be deployed on the server instead?In this paper,we propose a QFL framework specifically designed for classical clients,referred to as CC-QFL,in response to this *** each iteration,the collaborative training of the QML model is assisted by the shadow tomography technique,eliminating the need for quantum computing capabilities of ***,the server constructs a classical representation of the QML model and transmits it to the *** clients encode their local data onto observables and use this classical representation to calculate local *** local gradients are then utilized to update the parameters of the QML *** evaluate the effectiveness of our framework through extensive numerical simulations using handwritten digit images from the MNIST *** framework provides valuable insights into QFL,particularly in scenarios where quantum computing resources are scarce.

关键词： client server quantum

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Application of fractal theory to study morphology of manganese sulfide inclusion in resulfurized free-cutting steels

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Journal of Iron and Steel Research International 2023年第1期30卷 137-149页

作者： Xiang-yu Xu Zhi-qi Zeng Qian-ren Tian Chen-wei Cao Ping Shen Jian-xun Fu Center for Advanced Solidification Technology(CAST) State Key Laboratory of Advanced Special SteelSchool of Materials Science and EngineeringShanghai UniversityShanghai 200444China Baosight Software Co. Ltd.Information Service HeadquartersShanghai 201203China

The morphology and distribution of manganese sulfide(MnS)inclusions have a significant influence on the comprehensive performance,which is an important research field for resulfurized *** on the experiments of non-aqueous electrolyte and scanning electron microscope observation,the fractal theory was employed to study the three-dimensional morphologies of MnS *** results showed that the edge fractal dimension of MnS inclusions was between 1.59 and *** addition,similar morphology of MnS inclusions had a close fractal *** MnS edge fractal dimension is highly positively correlated with the morphological *** multifractal spectrums of MnS inclusions on two-dimensional plane of as-cast and as-rolled resulfurized free-cutting steels were *** large-size MnS inclusions belong to large probability subset,while the small-size MnS inclusions belong to small probability *** multifractal spectrum can truly and effectively reflect the difference and non-uniformity of distribution of MnS inclusions on 2D *** the premise of similar content of MnS,with the refinement of MnS inclusions,the multifractal spectrum width and the multifractal spectrum symmetry parameter were *** multifractal spectrum provides a new method for studying the second phase in materials.

关键词： MnS inclusion Morphology Fractal dimension Multifractal Resulfurized steel

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Data-driven modeling on anisotropic mechanical behavior of brain tissue with internal pressure

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Defence Technology（防务技术） 2024年第3期33卷 55-65页

作者： Zhiyuan Tang Yu Wang Khalil I.Elkhodary Zefeng Yu Shan Tang Dan Peng State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of Technology116023DalianPR China The Department of Mechanical Engineering The American University in CairoNew Cairo11835Egypt Department of Neurology The Second Hospital of Dalian Medical UniversityDalian116023PR China

Brain tissue is one of the softest parts of the human body,composed of white matter and grey *** mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain ***,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical *** white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical *** such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional *** a constitutive law for multiscale brain tissue using traditional function-based approaches can be very ***,this paper proposes a data-driven approach to establish the desired mechanical model of brain *** focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our *** matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading *** generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal ***,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body *** with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling *** predictions made by our trained model demonstrate sufficient ***,we find that the level of internal blood pressur

关键词： Data driven Constitutive law Anisotropy Brain tissue Internal pressure

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Blockchain-Enabled Secure, Fair and Scalable Data Sharing in Zero-Trust Edge-End Environment

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IEEE Journal on Selected Areas in Communications 2025年第6期43卷 2056-2069页

作者： Xu, Xiaolong Meng, Ke Xiang, Haolong Cui, Guangming Xia, Xiaoyu Dou, Wanchun Nanjing210044 China Nanjing University of Information Science and Technology School of Software and the Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services Nanjing210044 China RMIT University School of Computing Technologies MelbourneVIC3000 Australia Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China

In edge computing, the Zero-Trust Security Model (ZTSM), as a key enabling technology for next-generation networks, plays a crucial role in providing authentication for addressing data sharing concerns, such as frequent data breaches, data misuse, and cyberattacks. However, due to the complexity and diversity of edge environments, ZTSM struggles to meet the security requirements of data sharing frameworks solely through enhanced authentication. Consequently, such frameworks with ZTSM still face challenges in ensuring data integrity, evaluating various node behaviors, and coping with the increasing complexity of node attributes. To address these issues, we propose a blockchain-enabled secure, fair and scalable data sharing framework in a zero-trust edge-end environment in this paper. Specifically, we first propose a Merkle forest-based data storage model for the classified storage of loosely coupled data, consequently enhancing the scalability of the model. Then, we design a node behavior-based reputation assessment mechanism to ensure fairness during data sharing. Moreover, a data sharing protocol supervised by smart contract is proposed, working with the aforementioned storage and assessment schemes, to ensure the security of data sharing. Finally, comprehensive security analysis validates the security, fairness and scalability of the proposed framework. Extensive experimental results show that, as transaction volume grows, the time cost of data traversal in the storage model becomes progressively more efficient. Additionally, when the size of the smart contract is increased tenfold, the maximum time cost of the data sharing protocol rises by only 4.98 times. © 1983-2012 IEEE.

关键词： Data integrity

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When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference 24

When Neural Code Completion Models Size up the Situation: At...

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44th ACM/IEEE International Conference on software engineering, ICSE 2024

作者： Sun, Zhensu Du, Xiaoning Song, Fu Wang, Shangwen Li, Li Beihang University Beijing China Monash University Melbourne VIC Australia Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science Beijing China National University of Defense Technology Changsha China Beihang University Beijing Yunnan Key Laboratory of Software Engineering China

ISBN: (纸本)9798400702174

Leveraging recent advancements in large language models, modern neural code completion models have demonstrated the capability to generate highly accurate code suggestions. However, their massive size poses challenges in terms of computational costs and environmental impact, hindering their widespread adoption in practical scenarios. Dynamic inference emerges as a promising solution, as it allocates minimal computation during inference while maintaining the model's performance. In this research, we explore dynamic inference within the context of code completion. Initially, we conducted an empirical investigation on GPT-2, focusing on the inference capabilities of intermediate layers for code completion. We found that 54.4% of tokens can be accurately generated using just the first layer, signifying significant computational savings potential. Moreover, despite using all layers, the model still fails to predict 14.5% of tokens correctly, and the subsequent completions continued from them are rarely considered helpful, with only a 4.2% Acceptance Rate. These findings motivate our exploration of dynamic inference in code completion and inspire us to enhance it with a decision-making mechanism that stops the generation of incorrect code. We thus propose a novel dynamic inference method specifically tailored for code completion models. This method aims not only to produce correct predictions with largely reduced computation but also to prevent incorrect predictions proactively. Our extensive evaluation shows that it can averagely skip 1.7 layers out of 16 layers in the models, leading to an 11.2% speedup with only a marginal 1.1 % reduction in ROUGE- L. © 2024 ACM.

关键词： Forecasting

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A Survey of Topology Optimization Methods Considering Manufacturable Structural Feature Constraints for Additive Manufacturing Structures

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Additive Manufacturing Frontiers 2024年第2期3卷 90-111页

作者： Shutian Liu Quhao Li Jingyu Hu Wenjiong Chen Yongcun Zhang Yunfeng Luo Qi Wang State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian116024China School of Mechanical Engineering Shandong UniversityJinan250061China

Additive manufacturing(AM)has made significant progress in recent years and has been successfully applied in various fields owing to its ability to manufacture complex *** method efficiently expands the design space,allowing for the creation of products with better performance than ever *** the emergence of new manufacturing technologies,new design methods are required to efficiently utilize the expanded design ***,topology optimization methods have attracted the attention of researchers because of their ability to generate new and optimized designs without requiring prior *** combination of AM and topology optimization has proven to be a powerful tool for structural innovation in design and ***,it is important to note that AM does not eliminate all manufacturing restrictions but instead replaces them with a different set of design considerations that designers must consider for the successful implementation of these *** has motivated research on topology optimization methods that incorporate manufacturable constraints for AM *** this paper,we present a survey of the latest studies in this research area,with a particular focus on developments in ***,we discuss the existing research gaps and future development trends.

关键词： Additive manufacturing Topology optimization Manufacturable constraint Structural feature constraint

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Research on key technologies of edge cache in virtual data space across WAN

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Frontiers of Computer Science 2023年第1期17卷 15-34页

作者： Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China

The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and Computer Network Information Center in Chinese Academy of Sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).

关键词： virtual data space system wide area network edge cache redundant data transmission

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Color Image Steganalysis Algorithm Based on Quaternion Convolutional Neural Network 30th

Color Image Steganalysis Algorithm Based on Quaternion Convo...

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30th International Conference on Computational and Experimental engineering and Sciences, ICCES 2024

作者： Xu, Meng Wang, Jinwei State Key Laboratory of Mathematical Engineering and Advanced Computing Henan450001 China Department of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9783031687747

Most of the images on the Internet are color images, and steganalysis of color images is a very critical issue in the field of steganalysis. The current proposed color image steganalysis features mainly rely on manual design, and the steganalysis features do not fully consider the internal connections between the three channels of color images. Most steganalyzers based on deep learning are also designed for grayscale images. In recent years, the continuous introduction of advanced steganography techniques for color images has also brought more severe challenges to the steganography analysis of color images. Quaternions are a tool that can effectively represent color images, and utilizing quaternion transformations can fully exploit the correlation between color image channels. Combining quaternion theory with convolutional neural networks, this paper proposed a color image steganalysis algorithm based on quaternion convolutional neural networks. Firstly, the image is represented by quaternion, and then input into the quaternion convolutional neural network. The convolution kernel in the network is composed of quaternions, and then perform convolution and pooling. The experimental results have demonstrated the significant effectiveness of the proposed network. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Convolutional neural networks

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