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IACR Transactions on Cryptographic Hardware and Embedded Systems 2023年第2期2023卷 270-285页

作者： Ding, Yuanchao Guo, Hua Guan, Yewei Song, Hutao Zhang, Xiyong Liu, Jianwei School of Cyber Science and Technology Beihang University Beijing China State Key Laboratory of Cryptology P.O. Box Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing China Beijing Institute of Satellite Information Engineering Beijing China

Modular exponentiation and scalar multiplication are important operations in most public-key cryptosystems, and their efficient computation is essential to cryptosystems. The shortest addition chain is one of the most important mathematical concepts to realize the optimization of computation. However, finding a shortest addition chain of length r is generally regarded as an NP-hard problem, whose time complexity is comparable to O(r!). This paper proposes some novel methods to generate short addition chains. We firstly present a Simplified Power-tree method by deeply deleting the power-tree whose time complexity is reduced to O(r2). In this paper, a Cross Window method and its variant are introduced by improving the Window method. The Cross Window method uses the cross correlation to deal with the windows and its pre-computation is optimized by a new Addition Sequence Algorithm. The theoretical analysis is conducted to show the correctness and effectiveness. Meanwhile, our experiments show that the new methods can obtain shorter addition chains compared to the existing methods. The Cross Window method with the Addition Sequence algorithm can attain 44.74% and 9.51% reduction of the addition chain length, in the best case, compared to the Binary method and the Window method respectively. © 2023, Ruhr-University of Bochum. All rights reserved.

关键词： Optimization

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ICCG:low-cost and efficient consistency with adaptive synchronization for metadata replication

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Frontiers of Computer Science 2025年第1期19卷 53-70页

作者： Chenhao ZHANG Liang WANG Jing SHANG Zhiwen XIAO Limin XIAO Meng HAN Bing WEI Runnan SHEN Jinquan WANG State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China School of Cyberspace Security Hainan UniversityHaikou 570228China China Mobile Information Technology Center Beijing 100033China

The rapid growth in the storage scale of wide-area distributed file systems (DFS) calls for fast and scalable metadata management. Metadata replication is the widely used technique for improving the performance and scalability of metadata management. Because of the POSIX requirement of file systems, many existing metadata management techniques utilize a costly design for the sake of metadata consistency, leading to unacceptable performance overhead. We propose a new metadata consistency maintenance method (ICCG), which includes an incremental consistency guaranteed directory tree synchronization (ICGDT) and a causal consistency guaranteed replica index synchronization (CCGRI), to ensure system performance without sacrificing metadata consistency. ICGDT uses a flexible consistency scheme based on the state of files and directories maintained through the conflict state tree to provide an incremental consistency for metadata, which satisfies both metadata consistency and performance requirements. CCGRI ensures low latency and consistent access to data by establishing a causal consistency for replica indexes through multi-version extent trees and logical time. Experimental results demonstrate the effectiveness of our methods. Compared with the strong consistency policies widely used in modern DFSes, our methods significantly improve the system performance. For example, in file creation, ICCG can improve the performance of directory tree operations by at least 36.4 times.

关键词： metadata management metadata replication consistency directory tree replica index

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Light field depth estimation:A comprehensive survey from principles to future

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High-Confidence Computing 2024年第1期4卷 92-107页

作者： Tun Wang Hao Sheng Rongshan Chen Da Yang Zhenglong Cui Sizhe Wang Ruixuan Cong Mingyuan Zhao State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Zhongfa Aviation Institute Beihang UniversityHangzhou 311115China Faculty of Applied Sciences Macao Polytechnic UniversityMacao 999078China State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Light Field(LF)depth estimation is an important research direction in the area of computer vision and computational photography,which aims to infer the depth information of different objects in threedimensional scenes by capturing LF *** this new era of significance,this article introduces a survey of the key concepts,methods,novel applications,and future trends in this *** summarize the LF depth estimation methods,which are usually based on the interaction of radiance from rays in all directions of the LF data,such as epipolar-plane,multi-view geometry,focal stack,and deep *** analyze the many challenges facing each of these approaches,including complex algorithms,large amounts of computation,and speed *** addition,this survey summarizes most of the currently available methods,conducts some comparative experiments,discusses the results,and investigates the novel directions in LF depth estimation.

关键词： Light field Depth estimation Deep learning Sub-aperture image Epipolar-plane image

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Cross-Chain Privacy-Preserving for BIoMT With Designated Verifier Proxy Signature

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IEEE Internet of Things Journal 2025年第12期12卷 20042-20055页

作者： Li, Chaoyang Jiang, Bohao Dong, Mianxiong Chen, Yuling Huang, Min Xin, Xiangjun Ota, Kaoru Zhengzhou University of Light Industry College of Software Engineering Zhengzhou450001 China Muroran Institution of Technology Muroran050-8585 Japan Guizhou University State Key Laboratory of Public Big Data Guizhou Guiyang550025 China

Blockchain-enabled Internet of Medical Things (BIoMT) has received extensive attention and in-depth research to solve the centralized, data island problems with the rapid developments of blockchain-related technologies. However, many different chains with different data structures, consensus protocols, and cryptographic algorithms are constructed, which brings a new »data island» problem. Meanwhile, the cryptographic algorithms used in most current BIoMT systems are weak against quantum attacks. In this paper, a cross-chain privacy-preserving (CCPP) model and a designated verifier proxy signature (DVPS) scheme have been proposed. This CCPP model is equipped with the relay chain technology and DVPS to achieve secure cross-chain medical data-sharing among different BIoMT systems. The DVPS scheme is constructed with lattice theory, which can achieve signer proxy, designated user verification, and anti-quantum attack. Then, the security proof shows that the proposed DVPS can capture the security properties of correctness, unforgeability, the signer's anonymity, and non-transferability. The performance evaluations show that the cross-chain transactions are efficient and stable with the transaction number increasing, and the proposed DVPS is efficient about the key size, time consumption, and energy consumption. This work can also improve the privacy security of system users and medical data in BIoMT systems and promote the value play of medical data. © 2014 IEEE.

关键词： Lattice theory

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A Virtual Hand Based Manipulation Learning Framework for Dexterous Hand 14

A Virtual Hand Based Manipulation Learning Framework for Dex...

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14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023

作者： Zhou, Luyue Hu, Yumeng Lin, Mengxiang State Key Laboratory of Software Development Environment China Beihang University School of Mechanical Engineering and Automation China

ISBN: (纸本)9798350324228

Dexterous hand programming is considered to be generally difficult suffering from high degree of freedom. Vision-based manipulation learning provides an efficient way to support automatic programming by human demonstration. However, complex visual perception is tightly coupled with the kinematics structure of dexterous hand in existing solutions, which makes it hard to migrate the developed algorithm from one kind of dexterous hand to another due to their kinematic difference. To address the issue, we introduce an intermediary called virtual hand and a new paradigm of motion mapping, serving as the link between human hand and dexterous hand. The virtual hand is generated in real time by hand pose estimation to track the motion of human hand. Then the joint configurations of dexterous hand and robotic arm can be calculated using geometry and optimization method based on the motion mapping paradigm we proposed. The method we introduced decouples the visual perception and kinematics calculation, which brings flexibility and low cost. The results of our preliminary experiments show the effectiveness of our method. © 2023 IEEE.

关键词： Kinematics

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Efficient and Lossless Integrity-preserving Training Scheme for High-dimensional Logistic Regression over Vertical Data

Efficient and Lossless Integrity-preserving Training Scheme ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Xu, Wei Zhu, Hui Liu, Ruikang Zheng, Yandong Wang, Fengwei Feng, Dengguo Xidian University School of Cyber Engineering Xi'an710126 China Institute of Software State Key Laboratory of Computer Science Beijing100190 China

ISBN: (纸本)9798350351255

Logistic regression is a widely used and efficient machine learning algorithm for data analysis. However, data is often distributed among different participants, and building high-quality models often involves data interaction, which might easily lead to sensitive information leakage. While some schemes have been proposed to address the data security issue through privacy-preserving technologies such as multi-party computation, homomorphic encryption, and trusted execution environment (TEE), they still suffer from some limitations in terms of security, efficiency, and model integrity and are not suitable for the secure outsourcing training. Therefore, in this paper, we propose an efficient and lossless integrity-preserving training for high-dimensional logistic regression over vertically partitioned data. First, we utilize a block strategy to encrypt the data in batches and outsource them to a cloud with TEE to achieve the non-interactive training. Considering TEE's limited memory, we employ random sampling technology to achieve mini-batch training within TEE, which ensures the data security. We find that the cloud might launch the active attacks to drop the model accuracy, such as lazy attack and replacement attack. To prevent the attacks, we introduce an integrity protection mechanism to verify data integrity and reduce verification frequency using a mixed-probability checking method, including fixed and random probability checking. Detailed analysis has confirmed that our scheme is secure and integrity-preserving. Extensive experiments have demonstrated that our scheme can achieve lossless, non-interactive, and efficient model training. © 2024 IEEE.

关键词： Information leakage

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Development of a Soft Hand and Wrist Rehabilitation Robot Utilizing Lattice Structure Actuators

Development of a Soft Hand and Wrist Rehabilitation Robot Ut...

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2024 International Convention on Rehabilitation engineering and Assistive Technology and World Rehabilitation Robot Convention, i-CREATE and WRRC 2024

作者： Lai, Jianwei Song, Aiguo Zhang, Wenbin Lu, Ye Wang, Jiajin Li, Ye School of Instrument Science and Engineering Southeast University State Key Laboratory of Digital Medical Engineering Jiangsu Key Laboratory of Remote Measurement and Control Nanjing210096 China College of Computer Science and Software Engineering Hohai University Nanjing210024 China

ISBN: (纸本)9798350355123

Soft robots offer promising solutions for rehabilitation due to their inherent attributes such as suppleness, lightweight construction, and safety features. However, prevalent soft actuators face limitations in output force and bending angle, impeding their effective application in rehabilitation. This paper proposes a novel design approach employing a two-layer lattice structure actuator, comprising flexion, guiding, and extension layers. This innovative design facilitates supple and efficient bi-directional rehabilitation training for fingers and wrists. Experimental results demonstrate the efficacy of the proposed dual-layer lattice structure actuator. At an air pressure of 150 kPa, it achieves an end force of 14.88 N, marking a remarkable 906% increase compared to its single-layer counterpart. Additionally, the dual-layer structure exhibits a minimum bending radius of 2.77 cm under 60 kPa, representing a 38.5% reduction relative to the single-layer actuator. Leveraging these actuators, a hand and wrist rehabilitation robot was developed and subjected to a clinical trial involving two healthy subjects. The trial outcomes reveal significant improvements in finger grasping ability and wrist range of motion with the assistance of the rehabilitation robot. These results underscore the practical usability and effectiveness of the soft hand and wrist rehabilitation robot, thereby holding promise for enhancing patient rehabilitation outcomes. © 2024 IEEE.

关键词： Patient rehabilitation

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Tailored energy absorption for a novel auxetic honeycomb structure under large deformation

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Science China(Physics,Mechanics & Astronomy) 2024年第5期67卷 63-80页

作者： Xiuhui Hou Bin Wang Zichen Deng School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi'an 710129China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical UniversityXi'an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China

In comparison to conventional hexagonal honeycomb structures,auxetic metamaterials with re-entrant configurations have exhibited superior mechanical properties in terms of energy *** further enhance the energy absorption capacity of these materials,a novel re-entrant honeycomb configuration,named novel auxetic re-entrant honeycomb(NARH),is developed by incorporating“<>”-shaped cell walls into the conventional auxetic re-entrant honeycomb(ARH).Two analytical models for the plateau stress are formulated to consider the plastic deformation of NARH during quasi-static compression and the dynamic impact using the linear momentum ***-static compression tests on 3D printed NARH honeycomb specimens and finite element simulations are performed to verify the effectiveness of the theoretical *** exhibits higher plateau stresses compared with ARH during compression,which can be attributed to the presence of more plastic hinges formed in *** hinges,the embedded parts with inclined cell walls,not only improve stability by forming stable triangles during compression but also enhance the energy absorption capacity.A parametric study is conducted to analyze the effect of impact velocity,thickness,and incline angle of cell walls on *** simulations demonstrate higher sensitivity of the mechanical properties to impact velocity and cell wall *** ribs to the“<>”-shaped cell walls in NARH further reduces the initial peak force during dynamic crushing while maintaining high energy *** research provides valuable guidelines for the design of energy absorption metamaterials.

关键词： absorption walls shaped

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Unsigned Road Incidents Detection Using Improved RESNET From Driver-View Images

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1203-1216页

作者： Li, Changping Wang, Bingshu Zheng, Jiangbin Zhang, Yongjun Chen, C.L. Philip Northwestern Polytechnical University School of Software Xi’an710129 China Shenzhen University Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security Shenzhen518060 China Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China South China University of Technology School of Computer Science and Engineering Guangzhou510641 China

Frequent road incidents cause significant physical harm and economic losses globally. The key to ensuring road safety lies in accurately perceiving surrounding road incidents. However, the highly dynamic nature of traffic introduces significant challenges, particularly in detecting sudden and temporary incidents. In this article, we propose a novel detection framework, multihead attention ResNet with dynamic bottleneck (DB_RESNET_MHA), to identify physical unsigned road incidents. Our approach introduces three key innovations. First, we develop a tailored data augmentation strategy to create images that closely mimic the complex variations found in real-world road environments. Second, we enhance model expressiveness by employing attention mechanisms to nonlinearly integrate convolutional kernels within the residual network. Furthermore, we refine the prediction head by applying spatially distinct attention weights, enabling the model to capture intricate correlations between different features more effectively. To demonstrate the effectiveness of our method, we create a dataset for unsigned road incidents (UnsignRI), comprising a total of 16 323 images that capture 12 distinct types of incidents. It stands out as the most comprehensive dataset in the field, encompassing a wide range of geographical features and incident categories. Experimental results show that DB_RESNET_MHA achieves an average accuracy of 96.2% and a f1-score of 0.955 across various categories of unsigned incidents, surpassing other models. © 2020 IEEE.

关键词： Highway accidents

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In-Plane Dynamic Crushing Behaviors of a Vertex-Based Hierarchical Auxetic Honeycomb

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Acta Mechanica Solida Sinica 2024年第1期37卷 53-62页

作者： Yichen Zan Xiuhui Hou Zichen Deng School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi'an 710072China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical UniversityXi'an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China

Auxetic metamaterials,which exhibit the negative Poisson’s ratio(NPR)effect,have found wide applications in many engineering ***,their high porosity inevitably weakens their bearing capacity and impact *** improve the energy absorption efficiency of auxetic honeycombs,a novel vertex-based hierarchical star-shaped honeycomb(VSH)is designed by replacing each vertex in the classical star-shaped honeycomb(SSH)with a newly added self-similar *** analytical model is built to investigate the Young’s modulus of VSH,which shows good agreement with experimental results and numerical *** in-plane dynamic crushing behaviors of VSH at three different crushing velocities are investigated,and empirical formulas for the densification strain and plateau stress are *** results reveal more stable deformation modes for VSH,attributed to the addition of self-similar star-shaped ***,compared with SSH under the same relative densities,VSH exhibits better specific energy absorption and higher plateau ***,VSH is verified to be a better candidate for energy absorption while maintaining the auxetic *** study is expected to provide a new design strategy for auxetic honeycombs.

关键词： Vertex-based hierarchical star-shaped honeycomb Auxetic honeycomb Energy absorption Plateau stress Negative Poisson's ratio

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