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Leveraging Augmented Reality,Semantic-Segmentation,and VANETs for Enhanced Driver’s Safety Assistance

Computers, Materials & Continua 2024年第1期78卷 1443-1460页

作者： Sitara Afzal Imran Ullah Khan Irfan Mehmood Jong Weon Lee Mixed Reality and Interaction Lab Department of SoftwareSejong UniversitySeoul05006Korea Faculty of Engineering and Digital Technologies School of Computer ScienceAI and ElectronicsUniversity of BradfordBradfordUK

Overtaking is a crucial maneuver in road transportation that requires a clear view of the road ***,limited visibility of ahead vehicles can often make it challenging for drivers to assess the safety of overtaking maneuvers,leading to accidents and *** this paper,we consider atrous convolution,a powerful tool for explicitly adjusting the field-of-view of a filter as well as controlling the resolution of feature responses generated by Deep Convolutional Neural Networks in the context of semantic image *** article explores the potential of seeing-through vehicles as a solution to enhance overtaking ***-through vehicles leverage advanced technologies such as cameras,sensors,and displays to provide drivers with a real-time view of the vehicle ahead,including the areas hidden from their direct line of *** address the problems of safe passing and occlusion by huge vehicles,we designed a see-through vehicle system in this study,we employed a windshield display in the back car together with cameras in both *** server within the back car was used to segment the car,and the segmented portion of the car displayed the video from the front *** see-through system improves the driver’s field of vision and helps him change lanes,cross a large car that is blocking their view,and safely overtake other *** network was trained and tested on the Cityscape dataset using semantic *** transparent technique will instruct the driver on the concealed traffic situation that the front vehicle has *** our findings,we have achieved 97.1% *** article also discusses the challenges and opportunities of implementing see-through vehicles in real-world scenarios,including technical,regulatory,and user acceptance factors.

关键词： Overtaking safety augmented reality VANET V2. deep learning

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Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1022-1038页

作者： Xiao Xue Deyu Zhou Xiangning Yu Gang Wang Juanjuan Li Xia Xie Lizhen Cui Fei-Yue Wang the school of Computer software College of Intelligence and ComputingTianjin UniversityTianjin 300350China the school of software and the Joint SDUNTU Centre for Artificial Intelligence Research(C-FAIR) Shandong UniversityJinan 250101China the Information school Xi’an University of Financial and EconomicsXi’an 710100China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Hainan University Haikou 570228China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 1001901China

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system *** address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2.Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating ***,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

关键词： Agent-based modeling computational experiments cyber-physical-social systems(CPSS) generative deduction generative experiments meta model

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LMR-CBT: learning modality-fused representations with CB-Transformer for multimodal emotion recognition from unaligned multimodal sequences

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Frontiers of Computer Science 2024年第4期18卷 39-47页

作者： Ziwang FU Feng LIU Qing XU Xiangling FU Jiayin QI school of Computer Science(National Pilot software Engineering school) Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Trustworthy Distributed Computing and Service(BUPT) Beijing 100876China Shanghai International school of Chief Technology Officer East China Normal UniversityShanghai 200062China school of Computer Science and Technology East China Normal UniversityShanghai 200062China school of Cyberspace Security Guangzhou UniversityGuangdong 510006China

Learning modality-fused representations and processing unaligned multimodal sequences are meaningful and challenging in multimodal emotion *** approaches use directional pairwise attention or a message hub to fuse language,visual,and audio ***,these fusion methods are often quadratic in complexity with respect to the modal sequence length,bring redundant information and are not *** this paper,we propose an efficient neural network to learn modality-fused representations with CB-Transformer(LMR-CBT)for multimodal emotion recognition from unaligned multi-modal ***,we first perform feature extraction for the three modalities respectively to obtain the local structure of the ***,we design an innovative asymmetric transformer with cross-modal blocks(CB-Transformer)that enables complementary learning of different modalities,mainly divided into local temporal learning,cross-modal feature fusion and global self-attention *** addition,we splice the fused features with the original features to classify the emotions of the ***,we conduct word-aligned and unaligned experiments on three challenging datasets,IEMOCAP,CMU-MOSI,and *** experimental results show the superiority and efficiency of our proposed method in both *** with the mainstream methods,our approach reaches the state-of-the-art with a minimum number of parameters.

关键词： modality-fused representations cross-model blocks multimodal emotion recognition unaligned multimodal sequences computational affection

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Flexible wide-range multidimensional force sensors inspired by bones embedded in muscle

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Microsystems & Nanoengineering 2024年第3期10卷 49-61页

作者： Jie Zhang Xiaojuan Hou Shuo Qian Jiabing Huo Mengjiao Yuan Zhigang Duan Xiaoguang Song HuiWu Shuzheng Shi Wenping Geng Jiliang Mu Jian He Xiujian Chou Science and Technology on Electronic Test and Measurement Laboratory North University of ChinaTaiyuan 030051China school of software North University of ChinaTaiyuan 030051China school of Mechanical Engineering Hebei University of ArchitectureZhangjiakou 075000China HBIS Group Co.Ltd. Shijiazhuang 050023China

Flexible sensors have been widely studied for use in motion monitoring,human‒machine interactions(HMIs),personalized medicine,and soft intelligent ***,their practical application is limited by their low output performance,narrow measuring range,and unidirectional force ***,to achieve flexibility and high performance simultaneously,we developed a flexible wide-range multidimensional force sensor(FWMFS)similar to bones embedded in muscle *** adjustable magnetic field endows the FWMFS with multidimensional perception for detecting forces in different *** multilayer stacked coils significantly improved the output from theμV to the mV level while ensuring FWMFS *** optimized FWMFS exhibited a high voltage sensitivity of 0.2.7 mV/N(0.5–8.4 N)and 0.047 mV/N(8.4–60 N)in response to normal forces ranging from 0.5 N to 60 N and could detect lateral forces ranging from 0.2.1.1 N and voltage sensitivities of 1.039 mV/N(0.2.0.5 N)and 0.194 mV/N(0.5–1.1 N).In terms of normal force measurements,the FWMFS can monitor finger pressure and sliding trajectories in response to finger taps,as well as measure plantar pressure for assessing human *** plantar pressure signals of five human movements collected by the FWMFS were analyzed using the k-nearest neighbors classification algorithm,which achieved a recognition accuracy of 92..Additionally,an artificial intelligence biometric authentication system is being developed that classifies and recognizes user *** on the lateral force measurement ability of the FWMFS,the direction of ball movement can be distinguished,and communication systems such as Morse Code can be *** research has significant potential in intelligent sensing and personalized spatial recognition.

关键词： password Morse force

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Generalized splitting-ring number theoretic transform

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Frontiers of Computer Science 2024年第4期18卷 205-207页

作者： Zhichuang LIANG Yunlei ZHAO Zhenfeng ZHANG school of Computer Science Fudan UniversityShanghai 200433China State Key Laboratory of Cryptology Beijing 100036China Institute of software Chinese Academy of SciencesBeijing 100190China

1 Introduction Lattice-based cryptography is one of the most promising routine of post-quantum cryptography(PQC).The fundamental and time-consuming operation in lattice-based schemes is the polynomial multiplication i... 详细信息

关键词： ring splitting polynomial

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Generalized Embedding Machines for Recommender Systems

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Machine Intelligence Research 2024年第3期21卷 571-584页

作者： Enneng Yang Xin Xin Li Shen Yudong Luo Guibing Guo software College Northeastern UniversityShenyang110000China school of Computer Science and Technology Shandong UniversityQingdao266000China JD Explore Academy JD Explore AcademyBeijing100000China

Factorization machine (FM) is an effective model for feature-based recommendation that utilizes inner products to capture second-order feature interactions. However, one of the major drawbacks of FM is that it cannot capture complex high-order interaction signals. A common solution is to change the interaction function, such as stacking deep neural networks on the top level of FM. In this work, we propose an alternative approach to model high-order interaction signals at the embedding level, namely generalized embedding machine (GEM). The embedding used in GEM encodes not only the information from the feature itself but also the information from other correlated features. Under such a situation, the embedding becomes high-order. Then we can incorporate GEM with FM and even its advanced variants to perform feature interactions. More specifically, in this paper, we utilize graph convolution networks (GCN) to generate high-order embeddings. We integrate GEM with several FM-based models and conduct extensive experiments on two real-world datasets. The results demonstrate significant improvement of GEM over the corresponding baselines.

关键词： Feature interactions high-order interaction factorization machine(FM) recommender system graph neural network(GNN)

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Multi-user reinforcement learning based task migration in mobile edge computing

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Frontiers of Computer Science 2024年第4期18卷 161-173页

作者： Yuya CUI Degan ZHANG Jie ZHANG Ting ZHANG Lixiang CAO Lu CHEN Tianjin Key Lab of Intelligent Computing and Novel software Technology Tianjin University of TechnologyTianjin 300384China school of Internet of Things Engineering Jiangsu Vocational College of Information TechnologyWuxi 214153China school of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China school of Sports Economics and Management Tianjin University of SportTianjin 301617China

Mobile Edge Computing(MEC)is a promising *** service migration is a key technology in *** order to maintain the continuity of services in a dynamic environment,mobile users need to migrate tasks between multiple servers in real *** to the uncertainty of movement,frequent migration will increase delays and costs and non-migration will lead to service ***,it is very challenging to design an optimal migration *** this paper,we investigate the multi-user task migration problem in a dynamic environment and minimizes the average service delay while meeting the migration *** order to optimize the service delay and migration cost,we propose an adaptive weight deep deterministic policy gradient(AWDDPG)*** distributed execution and centralized training are adopted to solve the high-dimensional *** show that the proposed algorithm can greatly reduce the migration cost and service delay compared with the other related algorithms.

关键词： mobile edge computing mobility service migration deep reinforcement learning deep deterministic policy gradient

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Caching Strategies in NDN Based Wireless Ad Hoc Network:A Survey

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Computers, Materials & Continua 2024年第7期80卷 61-103页

作者： Ahmed Khalid Rana Asif Rehman Byung-Seo Kim Department of Computer Science FAST School of ComputingNational University of Computer and Emerging SciencesLahore54000Pakistan Department of software and Communications Engineering Hongik UniversitySejong City30016Republic of Korea

Wireless Ad Hoc Networks consist of devices that are wirelessly *** Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc *** is used in wireless ad hoc *** is based on Transmission Control Protocol(TCP)/Internet Protocol(IP)network where clients and servers interact with each other with the help of IP in a pre-defined *** fetches data from a fixed *** redundancy,mobility,and location dependency are the main issues of the IP network *** these factors result in poor performance of wireless ad hoc *** main disadvantage of IP is that,it does not provide in-network ***,there is a need to move towards a new network that overcomes these *** Data Network(NDN)is a network that overcomes these *** is a project of Information-centric Network(ICN).NDN provides in-network caching which helps in fast response to user *** NDN in wireless ad hoc network provides many benefits such as caching,mobility,scalability,security,and *** considering the certainty,in this survey paper,we present a comprehensive survey on Caching Strategies in NDN-based Wireless *** cachingmechanism-based results are also *** the last,we also shed light on the challenges and future directions of this promising field to provide a clear understanding of what caching-related problems exist in NDN-based wireless ad hoc networks.

关键词： Content centric network Internet of Things mobile ad hoc network named data network vehicular ad hoc 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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A program logic for obstruction-freedom

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Frontiers of Computer Science 2024年第06期18卷 1-16页

作者： LI Zhao-Hui FENG Xin-Yu school of Computer Science and Technology University of Science and Technology of China Department of Computer Science and Technology Nanjing University State Key Laboratory for Novel software Technology Nanjing University

Though obstruction-free progress property is weaker than other non-blocking properties including lock-freedom and wait-freedom, it has advantages that have led to the use of obstruction-free implementations for software transactional memory (STM) and in anonymous and fault-tolerant distributed computing. However, existing work can only verify obstruction-freedom of specific data structures (e.g., STM and list-based algorithms).In this paper, to fill this gap, we propose a program logic that can formally verify obstruction-freedom of practical implementations, as well as verify linearizability, a safety property, at the same time. We also propose informal principles to extend a logic for verifying linearizability to verifying obstruction-freedom. With this approach, the existing proof for linearizability can be reused directly to construct the proof for both linearizability and ***, we have successfully applied our logic to verifying a practical obstruction-free double-ended queue implementation in the first classic paper that has proposed the definition of obstruction-freedom.

关键词： verification program logic progress properties obstruction-freedom concurrent objects

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