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Influence of different anodised nanoporous structures on the anti-icing and electrical properties of transmission Al lines

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High Voltage 2025年第1期10卷 167-177页

作者： Xu Dai Yuan Yuan Jie Xiao Chenghao Jiang Xujiang Hua Huiying Xiang Tao Zhu Guoyong Liu Jiang Zhou Ruijin Liao State Key Laboratory of Power Transmission Equipment&System Security and New Technology Chongqing UniversityChongqingChina College of Materials Science and Engineering Chongqing UniversityChongqingChina Dongfang Electric Machinery Co. LtdDeyangChina

Ice accumulation of overhead transmission lines can lead to serious damage to power *** nanostructured Al conductors are proposed to replace the de-icing or ice-melting equipment for economic advantages,good anti-icing properties and robust electrical *** under different direct current densities is adopted to fabricate two nanostructures on Al conductors,including the reticular and honeycomb-like nanoporous *** to pure Al conductors,the anodised surface of honeycomb-like nanoporous structures exhibits lower ice adhesion(3.82 kPa)and ice *** conductor steel reinforced treated in the proposed method has also been validated to exhibit a significant anti-glaze icing ***-tionally,corona performance and line loss are experimentally measured and calculated to prove good electrical *** 0.27 A Al strand shows the highest corona inception voltage(27.86 kV)and the lowest AC resistance(4.65Ω/km),which is attributed to the good dielectric property and heat ***,the proposed anti-icing transmission conductors show profound application potential for power systems.

关键词： electrical structures properties

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A Post-Quantum Cross-Domain Authentication Scheme Based on Multi-Chain Architecture

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Computers, Materials & Continua 2024年第2期78卷 2813-2827页

作者： Yi-Bo Cao Xiu-Bo Chen Yun-Feng He Lu-Xi Liu Yin-Mei Che Xiao Wang Ke Xiao Gang Xu Si-Yi Chen Information Security Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Information Center of China North Industries Group Corporation Beijing100089China School of Information Science and Technology North China University of TechnologyBeijing100144China

Due to the rapid advancements in network technology,blockchain is being employed for distributed data *** the Internet of Things(IoT)scenario,different participants manage multiple blockchains located in different trust domains,which has resulted in the extensive development of cross-domain authentication ***,the emergence of many attackers equipped with quantum computers has the potential to launch quantum computing attacks against cross-domain authentication schemes based on traditional cryptography,posing a significant security *** response to the aforementioned challenges,our paper demonstrates a post-quantum cross-domain identity authentication scheme to negotiate the session key used in the cross-chain asset exchange ***,our paper designs the hiding and recovery process of user identity index based on lattice cryptography and introduces the identity-based signature from lattice to construct a post-quantum cross-domain authentication ***,our paper utilizes the hashed time-locked contract to achieves the cross-chain asset exchange of blockchain nodes in different trust ***,the security analysis reduces the security of the identity index and signature to Learning With Errors(LWE)and Short Integer Solution(SIS)assumption,respectively,indicating that our scheme has post-quantum *** but not least,through comparison analysis,we display that our scheme is efficient compared with the cross-domain authentication scheme based on traditional cryptography.

关键词： Cross-domain identity authentication lattice-based cryptography blockchain hashed time-locked contract

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Clock Bias Gross Error Detection Method Based on WS-MAD

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Gyroscopy and Navigation 2024年第1期15卷 68-82页

作者： Jia Su Gao, Mengjia Yi, Qingwu Wang, Binbin Ma, Zhiwei College of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang China State Key Laboratory of Satellite Navigation System and Equipment Technology Shijiazhuang China Henan University of Economics and Law Zhengzhou China

Abstract: This paper proposes a clock bias gross error detection method, which combines weighted support vector data description (SVDD) with modified median absolute deviation (MAD) to address the limitations of the traditional MAD method. The method uses the local reachable density as the weighting factor of SVDD, which fully considers the local characteristics of each data. By constructing the minimum hypersphere in the high-dimensional feature space, the one-dimensional data are transformed into the distance from the vector point to the center of the hypersphere in the high-dimensional space. This transformation increases the discrepancy between normal data and gross errors. The modified MAD method probes the distance from the current epoch vector point to the center of the hypersphere for gross errors, and thus determines whether the current clock bias is a gross error. The precision clock bias data of BDS-3 with different sampling intervals provided by GFZ were used for simulation experiments. By comparing the results of the MAD method and the WS-MAD method, it is found that the WS-MAD method can detect the small gross errors in the smooth clock bias frequency data and more gross errors in the clock bias data with trend term floating. The fitting and prediction analyses on satellites with different orbits and clock types show that the WS-MAD method improves the fitting and prediction accuracy of MEO and IGSO satellites better than that of GEO satellites. For the same MEO satellites, the enhancement effect of hydrogen clocks is better than that of rubidium clocks. © Pleiades Publishing, Ltd. 2024.

关键词： Vector spaces

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Near Optimal Probabilistic Constructions of Frameproof Codes

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IEEE Transactions on information Theory 2025年第6期71卷 4137-4144页

作者： Liu, Miao Ma, Zengjiao Shangguan, Chong Shandong University Research Center for Mathematics and Interdisciplinary Sciences Qingdao266237 China Shandong University State Key Laboratory of Cryptography and Digital Economy Security Key Laboratory of Cryptologic Technology and Information Security of Ministry of Education School of Cyber Science and Technology Shandong Qingdao266237 China Ministry of Education Frontiers Science Center for Nonlinear Expectations Qingdao266237 China

Frameproof codes are a class of secure codes that were originally introduced in the pioneering work of Boneh and Shaw in the context of digital fingerprinting. They can be used to enhance the security and credibility of digital contents. Let Mc,l(q) denote the largest cardinality of a q-ary c-frameproof code with length l. Based on an intriguing observation that relates Mc,l(q) to the renowned Erdős Matching Conjecture in extremal set theory, in 2003, Blackburn posed an open problem on the precise value of the limit (Formula presented). By combining several ideas from the probabilistic method, we present a lower bound for Mc,l(q), which, together with an upper bound of Blackburn, completely determines Rc,l for all fixed c, l, and resolves the above open problem in the full generality. We also present an improved upper bound for Mc,l(q). © 1963-2012 IEEE.

关键词： Optimal systems

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A merged machine learning model for seasonal climate prediction in China

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science China Earth sciences 2025年第5期68卷 1469-1484页

作者： Danwei QIAN Yanyan HUANG Huijun WANG State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Nansen-Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences

Improving the current level of skill in seasonal climate prediction is urgent for achieving sustainable socioeconomic development, and this is especially true in China where meteorological disasters are experienced frequently. In this study, based upon big climate data and traditional statistical prediction experiences, a merged machine learning model(Y-model) was developed to address this, as well as to further explore unknown potential predictors. In Y-model, empirical orthogonal function analysis was firstly applied to reduce the data dimensionality of the target predictand(temperature and precipitation in the four seasons over China). Image recognition techniques were used to automatically identify possible predictors from the big climate data. These predictors, associated with significant circulation anomalies, were recombined into a large ensemble according to different threshold settings for five factors determining the statistical forecast skill. Facebook Prophet was chosen to conduct the independent hindcasts for each season's climate at a lead time of two months. During 2011–2022, the seasonal climate in China was skillfully predicted by Y-model, with an averaged pattern correlation coefficient skill of 0.60 for temperature and 0.24 for precipitation, outperforming CFSv2. Potential predictor analysis for recent extreme events suggested that prior signals from the Indian Ocean and the stratosphere were important for determining the super Mei-yu in 2020, while the prior sea surface temperature over the western Pacific and the soil temperature over West Asia may have contributed to the extreme high temperatures in 2022. Our study provides new insights for seasonal climate prediction in China.

关键词： Machine learning Seasonal climate prediction China’s climate Image recognition techniques Large ensemble

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Cryptanalysis of Full-Round Magpie Block Cipher

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Chinese Journal of Electronics 2023年第2期32卷 217-224页

作者： YANG Yunxiao SUN Bing LIU Guoqiang College of Liberal Arts and Sciences National University of Defense Technology State Key Laboratory of Cryptology Hunan Engineering Research Center of Commercial Cryptography Theory and Technology Innovation State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Science

Magpie is a lightweight block cipher proposed by Li et al. in Acta Electronica Sinica volumn 45,issue 10. It adopts an substitution-permutation network（SPN） structure with a block size of 64 bits and the key size of 96 bits, respectively. To achieve the consistency of the encryption and decryption, which is both hardware and software friendly, 16 bits of the key are used as control signals to select S-boxes and another 16 bits of the key are used to determine the order of the operations. As the designers claimed, the security might be improved as different keys generate different ciphers. This paper analyzes the security of Magpie, studies the difference propagation of Magpie, and finally finds that the cipher has a set of 280weak keys which makes the full-round encryption weak, and corrects the lower bound of the number of active S-boxes to 10 instead of 25 proposed by the designers. In the weak key model, the security of the cipher is reduced by the claimed 280to only 4×216.

关键词： Ciphers Force Aerospace electronics Software Hardware Encryption security

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Discriminative feature encoding for intrinsic image decomposition

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Computational Visual Media 2023年第3期9卷 597-618页

作者： Zongji Wang Yunfei Liu Feng Lu Key Laboratory of Network Information System Technology(NIST) Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100190China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Peng Cheng Laboratory Shenzhen 518000China

Intrinsic image decomposition is an important and long-standing computer vision *** an input image,recovering the physical scene properties is *** physically motivated priors have been used to restrict the solution space of the optimization problem for intrinsic image *** work takes advantage of deep learning,and shows that it can solve this challenging computer vision problem with high *** focus lies in the feature encoding phase to extract discriminative features for different intrinsic layers from an input *** achieve this goal,we explore the distinctive characteristics of different intrinsic components in the high-dimensional feature embedding *** define feature distribution divergence to efficiently separate the feature vectors of different intrinsic *** feature distributions are also constrained to fit the real ones through a feature distribution *** addition,a data refinement approach is provided to remove data inconsistency from the Sintel dataset,making it more suitable for intrinsic image *** method is also extended to intrinsic video decomposition based on pixel-wise correspondences between adjacent *** results indicate that our proposed network structure can outperform the existing state-of-the-art.

关键词： intrinsic image decomposition deep learning feature distribution data refinement

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Effect of the grain boundary character distribution on the sulfur corrosion behaviour and mechanisms of copper windings under different high temperatures

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High Voltage 2024年第3期9卷 566-580页

作者： Xu Dai Yuan Yuan Jiang Zhou Guoyong Liu Tao Zhu Huiying Xiang Qi Yu Xue Gao Ruijin Liao State Key Laboratory of Power Transmission Equipment&System Security and New Technology Chongqing UniversityChongqingChina College of Materials Science and Engineering Chongqing UniversityChongqingChina Dongfang Electric Machinery Co. LtdDeyangChina

As a typical failure phenomenon in transformers,sulfur corrosion has garnered significant attention in the field of high-voltage *** boundary character distribution(GBCD)copper windings have been introduced to enhance sulfur corrosion resistance by slowing down intergranular *** this study,the sulfur corrosion behaviour and mechanisms of the GBCD copper windings under various temperatures were experi-mentally and theoretically *** show that GBCD can enhance the corrosion resistance of copper in liquid *** the increase in temperatures,the insulating properties of oil and papers in traditional copper windings experience notable degradation,while GBCD copper windings show more stable insulating *** addition,modelling of grain boundary energy indicates that the grain boundary structure of GBCD copper windings has a lower average interface energy of 0.170 eV/Å***-culations of reaction thermodynamics show that GBCD copper windings possess a higher failure temperature(135.2℃)and inhibition degree(activation energy)of the sulfur corrosion(32,557.62 J/mol),revealing the stability and enhanced sulfur corrosion resis-tance at elevated temperatures.

关键词： corrosion grain copper

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Heuristic Search with Cut Point Based Strategy for Critical Node Problem

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Journal of Computer science & technology 2024年第6期39卷 1328-1340页

作者： Zhi-Han Chen Shao-Wei Cai Jian Gao Shi-Ke Ge Chan-Juan Liu Jin-Kun Lin School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 101408China Key Laboratory of System Software(Chinese Academy of Sciences)and State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China College of Information Science and Technology Northeast Normal UniversityChangchun 130024China School of Computer Science and Technology Dalian University of TechnologyDalian 116024China SeedMath Technology Limited Beijing 100086China

The critical node problem(CNP)aims to deal with critical node identification in a graph,which has extensive applications in many *** CNP is a challenging task due to its computational complexity,and it attracts much attention from both academia and *** this paper,we propose a population-based heuristic search algorithm called CPHS(Cut Point Based Heuristic Search)to solve CNP,which integrates two main *** first one is a cut point based greedy strategy in the local search,and the second one involves the functions used to update the solution pool of the ***,a mutation strategy is applied to solutions with probability based on the overall average similarity to maintain the diversity of the solution *** are performed on a synthetic benchmark,a real-world benchmark,and a large-scale network benchmark to evaluate our *** with state-of-the-art algorithms,our algorithm has better performance in terms of both solution quality and run time on all the three benchmarks.

关键词： local search cut point heuristic search critical node problem

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Fine-Grained Source Code Vulnerability Detection via Graph Neural Networks 35

Fine-Grained Source Code Vulnerability Detection via Graph N...

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35th International Conference on Software Engineering and Knowledge Engineering, SEKE 2023

作者： Wang, Jingjing Huang, Minhuan Nie, Yuanpin Kuang, Xiaohui Li, Xiang Zhong, Wenjing National Key Laboratory of Science and Technology Information System Security Beijing China Xidian University Xi’an China

Although the number of exploitable vulnerabilities in software continues to increase, the speed of bug fixes and software updates have not increased accordingly. It is therefore crucial to analyze the source code and identify vulnerabilities in the early phase of software development. However, vulnerability location in most of the current machine learning-based methods tends to concentrate at the function level. It undoubtedly imposes a burden on further manual code audits when faced with large-scale source code projects. In this paper, a fine-grained source code vulnerability detection model based on Graph Neural Networks (GNNs) is proposed with the aim of locating vulnerabilities at the function level and line level. Our empirical evaluation on different C/C++ datasets demonstrated that our proposed model outperforms the state-of-the-art methods and achieves significant improvements even when faced with more complex, real-project source code. © 2023 Knowledge systems Institute Graduate School. All rights reserved.

关键词： Graph neural networks

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