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arXiv 2025年

作者： Yang, Lingxiao Dong, Xuewen Wan, Zhiguo Lu, Di Zhang, Yushu Shen, Yulong School of Computer Science and Technology Xidian University Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education Shaanxi Key Laboratory of Blockchain and Secure Computing Xi’an710071 China Zhejiang Lab Zhejiang Hangzhou311121 China School of Computer Science and Technology Xidian University Shaanxi Key Laboratory of Network and System Security Xi’an710071 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing210016 China

As the foundation of the Web3 trust system, blockchain technology faces increasing demands for scalability. Sharding emerges as a promising solution, but it struggles to handle highly concurrent cross-shard transactions (CSTxs), primarily due to simultaneous ledger operations on the same account. Hyperledger Fabric, a permissioned blockchain, employs multi-version concurrency control for parallel processing. Existing solutions use channels and intermediaries to achieve cross-sharding in Hyperledger Fabric. However, the conflict problem caused by highly concurrent CSTxs has not been adequately resolved. To fill this gap, we propose HiCoCS, a high concurrency cross-shard scheme for permissioned blockchains. HiCoCS creates a unique virtual sub-broker for each CSTx by introducing a composite key structure, enabling conflict-free concurrent transaction processing while reducing resource overhead. The challenge lies in managing large numbers of composite keys and mitigating intermediary privacy risks. HiCoCS utilizes virtual sub-brokers to receive and process CSTxs concurrently while maintaining a transaction pool. Batch processing is employed to merge multiple CSTxs in the pool, improving efficiency. We explore composite key reuse to reduce the number of virtual sub-brokers and lower system overhead. Privacy preservation is enhanced using homomorphic encryption. Evaluations show that HiCoCS improves cross-shard transaction throughput by 3.5-20.2 times compared to the baselines. Copyright © 2025, The Authors. All rights reserved.

关键词： Concurrency control

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Spatial Extent-Aware Multimodal Fusion Method for Measuring Urban Socioeconomic Status

Spatial Extent-Aware Multimodal Fusion Method for Measuring ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Fang Fang Jiahui Zhang Shengwen Li Daoyuan Zheng Linyun Zeng Bo Wan School of Computer Science China University of Geosciences Wuhan China National Engineering Research Center of Geographic Information System China University of Geosciences Wuhan China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural Resources Shenzhen China

The automatic measurement of socioeconomic status (SES), such as household income, provides fundamental data for policymakers and business applications. Although several urban data sources were employed in previous studies, the spatial extent of the measured objects was ignored, which left room for further improvement in the accuracy of measuring SES. This study develops a multimodal semantic segmentation framework to fuse the spatial extent of ground objects, remote sensing, and near-sensing images for predicting SES levels. The framework first constructs ground feature layer (GFL) tiles by projecting ground-level features from sparse ground images. Then, the ground feature tiles aggregate regional ground-level features with the help of the spatial extents of ranges. Lastly, an improved deep semantic segmentation network is employed to fuse GFL and remote sensing images to predict SES levels. Experimental results on the London dataset show that the proposed method outperforms SOTA models and is robust. The framework provides a rewarding exploration in fusing image data and spatial vector data for image-based intelligent applications and can be applied to a series of socioeconomic applications.

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaoke Zhu Danyang Li Xiaopan Chen Fumin Qi Fan Zhang Xiao-Yuan Jing School of Computer and Information Engineering Henan University Kaifeng China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng China Department of System Operation National Supercomuting Center in Shenzhen Shenzhen China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China School of Computer Science Wuhan University Wuhan China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Facial image based kinship verification aims to decide whether there exists kinship between the given facial images. In practice, the cross-generation differences will cause adverse effects on kinship verification, which limits the performance. Therefore, how to mine the implied similarity from facial images with large cross-generation divergence is an important problem in kinship verification, which has not yet been well studied. In view of this, we propose a Similarity Mining via Implicit matching pattern LEarning (SMILE) approach for kinship verification. Specifically, SMILE mainly consists of two modules, including a Semi-coupled Multi-pattern Similarity Learning (SMSL) module and a Cross-Generation Feature Normalization (CGFN) module. The SMSL module is designed to learn multiple semi-coupled matching patterns for mining the implicit facial similarity information from different perspectives. The CGFN module aims to reduce the divergence between facial images of parent and child. Extensive experiments demonstrate that the proposed approach outperforms the existing state-of-the-art methods.

关键词： Pattern matching Similarity learning

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Blockchain-Based Identity Authentication Oriented to Multi-Cluster UAV Networking

arXiv

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arXiv 2023年

作者： Dong, Zesong Tong, Wei Zhang, Zhiwei Li, Jian Yang, Weidong Shen, Yulong The Hangzhou Institute of Technology Xidian University Hangzhou China The School of Computer Science and Technology Xidian University Xi’an China The Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education Xi’an China Shaanxi Key Laboratory of Network and System Security Xi’an China

Unmanned Aerial Vehicle (UAV) networking is increasingly used in field environments such as power inspection, agricultural plant protection, and emergency rescue. To guarantee UAV networking security, UAV identity authentication attracts wide attention, especially in the field environment without perfect infrastructure. Some blockchain-based UAV identity authentication solutions are proposed to establish decentralized and trusted authentication systems without relying on infrastructure. However, these solutions do not support disconnected UAV reconnection or even disband a cluster directly after its head UAV disconnection, which compromises cluster robustness and task result integrity. In this paper, we propose a blockchain-based identity authentication solution oriented to multi-cluster UAV networking with a UAV disconnection mechanism and a task result backup mechanism. Specifically, we build a blockchain maintained by head UAVs of all clusters, managing identity information to guarantee the security of decentralized identity management. The UAV disconnection mechanism permits a verified distributed UAV reconnection to ensure the robustness of the UAV cluster, and on this basis, the task result backup mechanism ensures the integrity of the task results stored in a cluster even any UAV disconnection. Finally, extensive experimental results prove the superiority of our solutions in terms of robustness, integrity, delay, and energy consumption. Copyright © 2023, The Authors. All rights reserved.

关键词： Blockchain

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Blockchain-Based Identity Authentication Oriented to Multi-Cluster UAV Networking

Blockchain-Based Identity Authentication Oriented to Multi-C...

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IEEE International Conference on Blockchain (Blockchain)

作者： Zesong Dong Wei Tong Zhiwei Zhang Jian Li Weidong Yang Yulong Shen Hangzhou Institute of Technology Xidian University Hangzhou China Shaanxi Key Laboratory of Network and System Security Xi’an China Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education Xi’an China School of Computer Science and Technology Xidian University Xi’an China

Unmanned Aerial Vehicle (UAV) networking is increasingly used in field environments such as power inspection, agricultural plant protection, and emergency rescue. To guarantee UAV networking security, UAV identity authentication attracts wide attention, especially in the field environment without perfect infrastructure. Some blockchain-based UAV identity authentication solutions are proposed to establish decentralized and trusted authentication systems without relying on infrastructure. However, these solutions do not support disconnected UAV reconnection or even disband a cluster directly after its head UAV disconnection, which compromises cluster robustness and task result integrity. In this paper, we propose a blockchain based identity authentication solution oriented to multi-cluster UAV networking with a UAV disconnection mechanism and a task result backup mechanism. Specifically, we build a blockchain maintained by head UAVs of all clusters, managing identity information to guarantee the security of decentralized identity management. The UAV disconnection mechanism permits a verified distributed UAV reconnection to ensure the robustness of the UAV cluster, and on this basis, the task result backup mechanism ensures the integrity of the task results stored in a cluster even any UAV disconnection. Finally, extensive experimental results prove the superiority of our solutions in terms of robustness, integrity, delay, and energy consumption.

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Methodology,progress and challenges of geoscience knowledge graph in International Big Science Program of Deep-Time Digital Earth

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Journal of Geographical Sciences 2025年第5期35卷 1132-1156页

作者： ZHU Yunqiang WANG Qiang WANG Shu SUN Kai WANG Xinbing LV Hairong HU Xiumian ZHANG Jie WANG Bin QIU Qinjun YANG Jie ZHOU Chenghu State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China University of Chinese Academy of Sciences Beijing 100049China School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Tsinghua UniversityBeijing 100084China State Key Laboratory for Mineral Deposits Research School of Earth Sciences and EngineeringNanjing UniversityNanjing 210023China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China Command Center of Natural Resources Comprehensive Survey China Geological SurveyBeijing 100055China School of Computer Science China University of GeosciencesWuhan 430074China

Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary *** advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in *** the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big *** DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience *** its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.

关键词： deep-time Earth geoscience knowledge graph Deep-time Digital Earth International Big Science Program

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Provably Secure Authenticated Key-Management Mechanism for e-Healthcare Environment

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IEEE Internet of Things Journal 2025年

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Ghaffar, Zahid Xie, Yong Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan Qinghai Institute of Technology School of Computer and Information Science China Qinghai Provincial Laboratory for Intelligent Computing and Application China Key Laboratory of Computing Power Network and Information Security Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security China Shandong Fundamental Research Center for Computer Science Jinan250353 China

The Internet of Things (IoT) is rapidly permeating all aspects of human life, involving a network of devices that share sensitive data. A notable application is the e-healthcare systems, which employ connected sensors, medical servers, and wearable devices. However, the public nature of communication in e-healthcare systems poses challenges such as security, privacy, and authentication of participating entities. Recently, many authentication protocols have been introduced to address these challenges. However, most of these protocols remain vulnerable to various security attacks, including device or medical server impersonation, denial of service, physical or cloning, and de-synchronization attacks. Therefore, we introduce an authenticated key-management protocol utilizing hash functions and Cipher-Block Chaining-Advanced Encryption Standard encryption (CBC-AES) encryption. The proposed protocol also employs the Physical Unclonable Function (PUF), which makes it more robust and efficient in resisting physical or cloning attacks. Additionally, the proposed scheme resists various security threats, including impersonation, session key leakage, ephemeral secret leakage, and de-synchronization attacks. We analyze the scheme’s security and reliability through formal and informal analysis. The informal analysis demonstrates that the scheme encompasses crucial security features, while the formal analysis substantiates. Moreover, performance analysis of the proposed protocol with various competing results indicates that our protocol achieves an average reduction in communication and computation overheads by 36.03.% and 41.79%, respectively. © 2014 IEEE.

关键词： Electronic health record

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Parallel Optimization of Computational Fluid Dynamics application code_saturne Based on Next Generation Sunway Supercomputer

Parallel Optimization of Computational Fluid Dynamics Applic...

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International Symposium on Parallel Architectures, Algorithms and Programming (PAAP)

作者： Anjun Liu Yin Liao Xihao Xu YanYan Chen Hongjun Zhong Jianming Wu Bo Kong Alexander Raikov Meng Guo Jinan Key Laboratory of High Performance Industrial Software Jinan Institute of Supercomputing Technology Jinan China Jinan Supercomputing-Zhejiang Yuansuan Industrial Simulation System Joint Laboratory Zhejiang Yuansuan Technology Co. Ltd Hangzhou China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan ) Qilu University of Technology (Shandong Academy of Sciences) Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

code_saturne is an open-source general large-scale computational fluid dynamics software independently developed by Electricite de France since 1997. Due to its high computing performance, code_saturne has been widely used in the nuclear industry, heavy fuel and biomass combustion, particle tracking and other computational fluid dynamics fields. In this work, we implemented code_saturne on the new generation Sunway supercomputer (SW26010pro) at the first time. By applying the data value-taking technology of double cache, combined with Sunway shared memory technology, we have adapted the data structure and Modular programming of code_saturne conducively to the new generation Sunway supercomputer (SW26010pro) and accelerated the software hotspots the software hotspots by 1–2 times. After optimizing and porting, this software has successfully served in the numerical simulation of the lateral flow of fuel assemblies in the nuclear industry.

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PseudoSC: A Binary Approximation to Stochastic Computing within Latent Operation-Space for Ultra-Lightweight on-Edge DNNs

PseudoSC: A Binary Approximation to Stochastic Computing wit...

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Design Automation Conference

作者： Jihe Wang Zhaoqing Wang Danghui Wang School of Computer Science Northwestern Polytechnical University Xi’an China Engineering Research Center of Embedded System Integration Ministry of Education Northwestern Polytechnical University Xi’an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Northwestern Polytechnical University Xi’an China

Recently, stochastic computing (SC) is increasingly popular in constructing MAC for on-edge DNNs benefiting from its outstanding energy-efficiency, including its adequate precision and gate-level operation. However, current SC-DNN systems always include a lot of costly SNGs/APCs for inevitably switches between binary and stochastic domains, which mortgages incongruous resources to pay the "bill" of the domain-switches and impedes highly-concurrent deployments. In this work, PseudoSC, a binary approximation to low-discrepancy SC, is proposed to totally remove the domain-switch for SNG/APC-free SC-DNNs. Its basic idea is to virtually re-arrange a couple of stochastic operands into a 2-D latent op-space, in which, original Monte Carlo sampling can be partitioned into three sub-ops, i.e., two fixed binary-ops and a fractal recursion. In theory, the recursion forms an isomorphic partition of the sampling repeated in smaller scales until the binary base-case achieved, as a result, a SC-op is well approximated only with binary-ops. Based on above theory, a multi-lane micro-architecture is designed to unroll the recursion within a few cycles and its advantages on hardware saving is verified under popular DNNs. The evaluation shows that the DNN-models with our schemes achieve 98.7% accuracy of the fixed-point implementations, which significantly outperform other SOTA methods. In addition, its reduced structure improves the power efficiency by 3.67 times on average.

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A Multi-objective optimization model for simulation-based acquisition 7

A Multi-objective optimization model for simulation-based ac...

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7th IEEE International Conference on Progress in Informatics and Computing, PIC 2020

作者： Zhang, Xue Xue, Junjie Zhou, Junhua Shi, Guoqiang Yu, Yan Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China Beijing Simulation Center Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9781728170862

Large-scale equipment presents the characteristics of technology-intensive, knowledge-intensive and complex, which brings high investment and high risk to equipment acquisition. This paper analyzes the various components of equipment acquisition to fully apply modeling and simulation technology to each stage of it. On the basis of multi-objective optimization theory, the objective function of the lowest risk and lowest cost of simulation-based acquisition (SBA) is proposed. Then establishing a multi-objective optimization model for simulation-based acquisition according to the corresponding constraints. The nondominated sorting genetic algorithm II (NSGA II) and multi-objective particle swarm optimization (MOPSO) algorithms are used to optimize the model, and the majority voting method is used for integration. The comparison of simulation examples proves that the multi-objective optimization model oriented to SBA designed in this paper can effectively realize the optimization of each objective of SBA under cost constraints. And the feasibility and efficiency of optimization solution are guaranteed. © 2020 IEEE.

关键词： Multiobjective optimization

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