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Semantic Consistency and Correctness Verification of Digital Traffic Rules

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Engineering 2024年第2期33卷 47-62页

作者： Lei Wan Changjun Wang Daxin Luo Hang Liu Sha Ma Weichao Hu Policy Standardand Patent DepartmentIntelligent Automotive Solution BUHuawei Technologies Co.Ltd.Beijing 100094China Research institute for Road Safety of the ministry of public security Beijing 100062China

The consensus of the automotive industry and traffic management authorities is that autonomous vehicles must follow the same traffic laws as human *** formal or digital methods,natural language traffic rules can be translated into machine language and used by autonomous *** this paper,a translation flow is *** the translation,a deeper examination is required,because the semantics of natural languages are rich and complex,and frequently contain hidden *** issue of how to ensure that digital rules are accurate and consistent with the original intent of the traffic rules they represent is both significant and *** response,we propose a method of formal verification that combines equivalence verification with model *** and reassuring digital traffic rules can be obtained by utilizing the proposed traffic rule digitization flow and verification *** addition,we offer a number of simulation applications that employ digital traffic rules to assess vehicle *** experimental findings indicate that our digital rules utilizing metric temporal logic(MTL)can be easily incorporated into simulation platforms and autonomous driving systems(ADS).

关键词： Autonomous driving Traffic rules Digitization Formalization Verification

Predict the evolution of mechanical property of Al-Li alloys in a marine environment

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Defence Technology（防务技术） 2024年第1期31卷 557-566页

作者： Wei Li Lin Xiang Guang Wu Hongli Si Jinyan Chen Yiming Jin Yan Su Jianquan Tao Chunyang Huang State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing100036China Chongqing Innovation Center Beijing Institute of TechnologyChongqing400044China First Research institute of the ministry of public security for PR China Beijing100036China Southwest Technology and Engineering Research institute Chongqing400039China

The ocean is one of the essential fields of national defense in the future,and more and more attention is paid to the lightweight research of Marine equipment and *** study it is to develop a Machine learning(ML)-based prediction method to study the evolution of the mechanical properties of Al-Li alloys in the marine *** obtained the mechanical properties of Al-Li alloy samples under uniaxial tensile deformation at different exposure times through Marine exposure *** obtained the strain evolution by digital image correlation(DIC).The strain field images are voxelized using 2D-Convolutional Neural Networks(CNN)autoencoders as input data for Long Short-Term Memory(LSTM)neural ***,the output data of LSTM neural networks combined with corrosion features were input into the Back Propagation(BP)neural network to predict the mechanical properties of Al-Li *** main conclusions are as follows:*** variation law of mechanical properties of2297-T8 in the Marine atmosphere is *** the increase in outdoor exposure test time,the tensile elastic model of 2297-T8 changes slowly,within 10%,and the tensile yield stress changes significantly,with a maximum attenuation of 23.6%.*** prediction model can predict the strain evolution and mechanical response simultaneously with an error of less than 5%.*** study shows that a CNN/LSTM system based on machine learning can be built to capture the corrosion characteristics of Marine exposure *** results show that the relationship between corrosion characteristics and mechanical response can be predicted without considering the microstructure evolution of metal materials.

关键词： Marine environment Al-Li alloy Machine learning Corrosion

Source Camera Identification Algorithm Based on Multi-Scale Feature Fusion

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Computers, Materials & Continua 2024年第8期80卷 3047-3065页

作者： Jianfeng Lu Caijin Li Xiangye Huang Chen Cui Mahmoud Emam School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Shangyu institute of Science and Engineering Hangzhou Dianzi UniversityShaoxing312300China Key Laboratory of public security Information Application Based on Big-Data Architecture Ministry of Public SecurityZhejiang Police CollegeHangzhou310000China Faculty of Artificial Intelligence Menoufia UniversityShebin El-Koom32511Egypt

The widespread availability of digital multimedia data has led to a new challenge in digital *** source camera identification algorithms usually rely on various traces in the capturing ***,these traces have become increasingly difficult to extract due to wide availability of various image processing *** Neural Networks(CNN)-based algorithms have demonstrated good discriminative capabilities for different brands and even different models of camera ***,their performances is not ideal in case of distinguishing between individual devices of the same model,because cameras of the same model typically use the same optical lens,image sensor,and image processing algorithms,that result in minimal overall *** this paper,we propose a camera forensics algorithm based on multi-scale feature fusion to address these *** proposed algorithm extracts different local features from feature maps of different scales and then fuses them to obtain a comprehensive feature *** representation is then fed into a subsequent camera fingerprint classification *** upon the Swin-T network,we utilize Transformer Blocks and Graph Convolutional Network(GCN)modules to fuse multi-scale features from different stages of the backbone ***,we conduct experiments on established datasets to demonstrate the feasibility and effectiveness of the proposed approach.

关键词： Source camera identification camera forensics convolutional neural network feature fusion transformer block graph convolutional network

An End-To-End Hyperbolic Deep Graph Convolutional Neural Network Framework

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 537-563页

作者： Yuchen Zhou Hongtao Huo Zhiwen Hou Lingbin Bu Yifan Wang Jingyi Mao Xiaojun Lv Fanliang Bu School of Information Network security People’s Public Security University of ChinaBeijing100038China institute of Computing Technology China Academy of Railway Sciences Corporation LimitedBeijing100081China

Graph Convolutional Neural Networks(GCNs)have been widely used in various fields due to their powerful capabilities in processing graph-structured ***,GCNs encounter significant challenges when applied to scale-free graphs with power-law distributions,resulting in substantial ***,most of the existing GCN models are shallow structures,which restricts their ability to capture dependencies among distant nodes and more refined high-order node features in scale-free graphs with hierarchical *** more broadly and precisely apply GCNs to real-world graphs exhibiting scale-free or hierarchical structures and utilize multi-level aggregation of GCNs for capturing high-level information in local representations,we propose the Hyperbolic Deep Graph Convolutional Neural Network(HDGCNN),an end-to-end deep graph representation learning framework that can map scale-free graphs from Euclidean space to hyperbolic *** HDGCNN,we define the fundamental operations of deep graph convolutional neural networks in hyperbolic ***,we introduce a hyperbolic feature transformation method based on identity mapping and a dense connection scheme based on a novel non-local message passing *** addition,we present a neighborhood aggregation method that combines initial structural featureswith hyperbolic attention *** the above methods,HDGCNN effectively leverages both the structural features and node features of graph data,enabling enhanced exploration of non-local structural features and more refined node features in scale-free or hierarchical *** results demonstrate that HDGCNN achieves remarkable performance improvements over state-ofthe-art GCNs in node classification and link prediction tasks,even when utilizing low-dimensional embedding ***,when compared to shallow hyperbolic graph convolutional neural network models,HDGCNN exhibits notable advantages and performance enhanceme

关键词： Graph neural networks hyperbolic graph convolutional neural networks deep graph convolutional neural networks message passing framework

Neurotoxicity of tetramethylammonium ion on larval and juvenile zebrafish:Effects on neurobehaviors and multiple biomarkers

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Journal of Environmental Sciences 2024年第9期143卷 138-147页

作者： Ruixin Zhang Rui Wang Jiajun Chang GDaniel Sheng Daqiang Yin Key Laboratory of Yangtze River Water Environment Ministry of EducationCollege of Environmental Science and EngineeringTongji UniversityShanghai 200092China Shanghai institute of Pollution Control and Ecological security Shanghai 200092China

Tetramethylammonium hydroxide(TMAH)is an important compound that utilized and released by the rapidly expanding semiconductor industry,which could hardly be removed by the conventional wastewater treatment *** a cholinergic agonist,the tetramethylammonium ion(TMA^(+))has been reported to induce toxicity to muscular and respiratory systems of mammals and human,however the toxicity on aquatic biota remains poorly *** investigated the neurotoxic effects of TMA^(+)exposure on zebrafish,based on neurobehavior tests and a series of *** inhibitions on the swimming distance of zebrafish larvae were observed when the exposure level exceeded 50 mg/L,and significant alterations on swimming path angles(straight and deflective movements)occurred even at 10 mg/*** tested neurobehavioral endpoints of zebrafish larvae were significantly positively correlated with reactive oxygen species(ROS)and malondialdehyde(MDA),significantly negatively related with the activities of antioxidant enzymes,but not significantly correlated with the level of acetylcholinesterase(AChE).Such relationship indicates that the observed neurotoxic effects on swimming behavior of zebrafish larvae is mainly driven by oxidative stress,rather than the alterations of *** the highest exposure concentration(200 mg/L),TMA^(+)evoked more severe toxicity on zebrafish juveniles,showing significantly stronger elevation on the MDA activity,and greater inhibitions on the activities of antioxidant enzymes and ACh E,suggesting juveniles were more susceptible to TMA^(+)exposure than larval zebrafish.

关键词： Tetramethylammonium Zebrafish Oxidative stress Acetylcholinesterase Neurobehavior

SAT-Based Automatic Searching for Differential and Linear Trails: Applying to CRAX

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Chinese Journal of Electronics 2024年第1期33卷 72-79页

作者： Yiyi HAN Caibing WANG Zhongfeng NIU Lei HU State Key Laboratory of Information security Institute of Information Engineering Chinese Academy of Sciences School of Cyber security University of Chinese Academy of Sciences

Boolean satisfiability problem(SAT) is now widely applied in differential cryptanalysis and linear cryptanalysis for various cipher *** generated many excellent results for some ciphers,for example,*** this research,we study the differential and linear propagations through the operations of addition,rotation and XOR(ARX),and construct the SAT *** apply the models to CRAX to search differential trails and linear trails *** this sense,our contnbution can be broadly divided into two *** give the bounds for differential and linear cryptanalysis of Alzette both up to 12 steps,by which we present a 3-round differential attack and a 3-round linear attack for *** construct a 4-round key-recovery attack for CRAX with time complexity289times of 4-round encryption and data complexity 225.

关键词： Ciphers Encryption Complexity theory Time complexity

Hierarchical Task Planning for Power Line Flow Regulation

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 29-40页

作者： Chenxi Wang Youtian Du Yanhao Huang Yuanlin Chang Zihao Guo the ministry of Education Key Lab for Intelligent Networks and Network security Xi'an Jiaotong UniversityXi'an 713599China the State Key Laboratory of Power Grid Safety and Energy Conservation China Electric Power Research InstituteBeijing 100192China

The complexity and uncertainty in power systems cause great challenges to controlling power *** a popular data-driven technique,deep reinforcement learning(DRL)attracts attention in the control of power ***,DRL has some inherent drawbacks in terms of data efficiency and *** paper presents a novel hierarchical task planning(HTP)approach,bridging planning and DRL,to the task of power line flow ***,we introduce a threelevel task hierarchy to model the task and model the sequence of task units on each level as a task planning-Markov decision processes(TP-MDPs).Second,we model the task as a sequential decision-making problem and introduce a higher planner and a lower planner in HTP to handle different levels of task *** addition,we introduce a two-layer knowledge graph that can update dynamically during the planning procedure to assist *** results conducted on the IEEE 118-bus and IEEE 300-bus systems demonstrate our HTP approach outperforms proximal policy optimization,a state-of-the-art deep reinforcement learning(DRL)approach,improving efficiency by 26.16%and 6.86%on both systems.

关键词： Knowledge graph power line flow regulation reinforcement learning task planning

Time-domain dynamic constitutive model suitable for mucky soil site seismic response

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Earthquake Engineering and Engineering Vibration 2024年第1期23卷 1-13页

作者： Dong Qing Chen Su Jin Liguo Zhou Zhenghua Li Xiaojun Architectural Engineering institute Huaiyin Institute of TechnologyHuai’an 223600China Key Laboratory of Urban security and Disaster Engineering of ministry of Education Beijing University of TechnologyBeijing 100020China institute of Geophysics China Earthquake AdministrationBeijing 100089China College of Transportation Science and Engineering Nanjing Tech UniversityNanjing 211816China

Soil nonlinear behavior displays noticeable effects on the site seismic *** study proposes a new functional expression of the skeleton curve to replace the hyperbolic skeleton *** integrating shear modulus and combining the dynamic skeleton curve and the damping degradation coefficient,the constitutive equation of the logarithmic dynamic skeleton can be obtained,which considers the damping effect in a soil dynamics *** on the finite difference method and the multi-transmitting boundary condition,a 1D site seismic response analysis program called Soilresp1D has been developed herein and used to analyze the time-domain seismic response in three types of *** the same time,this study also provides numerical simulation results based on the hyperbolic constitutive model and the equivalent linear *** results verify the rationality of the new soil dynamic constitutive *** can analyze the mucky soil site nonlinear seismic response,reflecting the deformation characteristics and damping effect of the silty *** hysteresis loop area is more extensive,and the residual strain is evident.

关键词： seismic response time-domain dynamic constitutive model logarithmic dynamic skeleton dampening effect mucky soil

Angle-resolved photoemission study of NbGeSb with non-symmorphic symmetry

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Chinese Physics B 2024年第2期33卷 464-470页

作者：马欢谭宁吴徐传李满王义炎路洪艳夏天龙王善才 Department of Physics Key Laboratory of Quantum State Construction and Manipulation(Ministry of Education)Renmin University of ChinaBeijing 100872China Beijing Key Laboratory of Opto-Electronic Functional Materials&Micro-Nano Devices Renmin University of ChinaBeijing 100872China School of Information Network security People’s Public Security University of ChinaBeijing 100038China institute of Physical Science and Information Technology Anhui UniversityHefei 230601China School of Physics and Physical Engineering Qufu Normal UniversityQufu 273165China

We investigate the electronic structure of NbGeSb with non-symmorphic *** employ angle-resolved photoemission spectroscopy(ARPES)to observe and identify the bulk and surface states over the Brillouin *** utilizing high-energy photons,we identify the bulk Fermi surface and bulk nodal line along the direction X–R,while the Fermi surface of the surface state is observed by using low-energy *** observe the splitting of surface bands away from the high-symmetry point *** density functional theory calculations on bulk and 1 to 5-layer slab models,as well as spin textures of NbGeSb,verify that the band splitting could be attributed to the Rashba-like spin–orbit coupling caused by space-inversion-symmetry breaking at the *** splitted surface bands cross with each other,forming two-dimensional Weyl-like crossings that are protected by mirror *** findings provide insights into the two-dimensional topological and symmetry-protected band inversion of surface states.

关键词： non-symmorphic symmetry nodal line splitting of surface bands angle-resolved photoemission spectroscopy