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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Li, Jiangkun Deng, Weiwen Wang, Ying Wang, Jian Ding, Juan School of Transportation Science and Engineering Beihang University Beijing China College of Computer Science and Technology Jilin Univerisity Changchun China PanoSim Technology Company Limited Jiaxing China

Complex traffic scenarios at uncontrolled intersections are crucial for the test validation of autonomous driving systems. The core of the test scenario construction lies in the accurate modeling of the complex interaction behaviors between vehicles in dynamic traffic. Data-driven models are difficult to support long-term simulation due to the existence of cumulative errors. In addition, existing mechanistic models usually assume rational driver behavior and focus mainly on improving efficiency and safety, thus simplifying vehicle interactions. To overcome the limitations of existing studies, we construct a complex traffic interaction model based on social force theory. This model captures the intricate interactions among vehicles at uncontrolled intersections by introducing the concepts of driving and repulsive forces. In particular, we propose a novel concept of segmented conflicting repulsion, an approach that can accurately model high-risk scrambling interactions between vehicles at intersections. Validation of the model using real data sets demonstrates its ability to accurately reproduce complex interaction behaviors at real-world intersections. Further, simulation analysis and application results reveal that our model-generated scenarios significantly outperform those created by SUMO in terms of complexity, thereby effectively enhancing the safety assessment of the autonomous driving system, Apollo. IEEE

关键词： Safety testing

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A Quadratic Step-Up DC-DC Converter Based on Switched Capacitor and Coupled Inductor 7

A Quadratic Step-Up DC-DC Converter Based on Switched Capaci...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Hao, Shicheng Fu, Yu Li, Shouxiang Ren, Zepei School of Automation Beijing Institute of Technology Beijing China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao China

ISBN: (纸本)9798350359558

This paper proposes a cascaded high gain DC-DC converter based on the switched capacitor and coupled inductor with merits of high voltage-boost capability, low voltage stress and only one active switch. The combination of the coupled inductor and switched capacitor cell not only improves the voltage gain, but also decreases voltage stress on semiconductor devices. The quadratic structure makes the converter to have a wide voltage-gain range. Theoretical analysis of steady-state operation, voltage-gain derivation and component stress is conducted, and an experimental prototype was built to verify the theoretical analysis and feasibility of the converter. © 2024 IEEE.

关键词： Semiconductor devices

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Design of 5G Multi-Frequency Antenna Based on Multi-Objective Sequential Domain Patching

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Progress In Electromagnetics Research C 2024年 145卷 53-61页

作者： Zhu, Wenjian Chen, Jiayi Hu, Panshi Song, Zhi Xue, Yanbing School of Automation and Electrical Engineering Dalian Jiaotong University China School of Computer and Communication Engineering Dalian Jiaotong University Applied Basic Research Project of Liaoning Science and Technology Department Dalian116028 China

This paper introduces a 5G multi-frequency antenna design method based on multi-objective sequential domain patching. By etching helical metamaterials on radiation patches and loading asymmetric electric-inductive-capacitive metamaterials on the transmission line side, the antenna structure is designed and optimized using electromagnetic simulation software, HFSS, and MATLAB. The resulting multi-frequency antenna operates across multiple frequency bands: n1, n41, 3.5G, and 4.9G. To ensure antenna performance and radiation efficiency, the antenna multi-frequency bands are precisely controlled. The experimental results show that the error between each operating frequency band and target frequency bands of the antenna is within 7.2%. Compared with conventional antenna design methods, the use of metamaterials and intelligent algorithms to optimize the structural parameters and loading positions of metamaterials can improve antenna performance while shortening the design cycle. Overall, this research offers novel insights into the design of 5G high-performance antennas. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Metamaterials

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Toward Optimal Broadcast Mode in Offline Finding Network

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IEEE Transactions on Mobile Computing 2025年第7期24卷 6550-6565页

作者： Li, Tong Ding, Yukuan Liang, Jiaxin Zheng, Kai Zhang, Xu Pan, Tian Wang, Dan Xu, Ke Renmin University DEKE Lab and Information School Beijing100872 China Delft Netherlands 2012 Labs Shenzhen Huawei518129 China Nanjing University School of Electronic Science and Engineering Nanjing210023 China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong Tsinghua University Department of Computer Science and Technology Beijing100084 China

This paper proposes ElastiCast, a novel Bluetooth Low Energy (BLE) broadcast mode that reduces the neighbor discovery latency in offline finding networks (OFNs). ElastiCast adapts the broadcast mode of the lost devices to the scan modes of the finder devices, considering their diversity. We start with an overview of OFNs, followed by a detailed analysis of the issues and challenges of existing solutions, which motivates the design of ElastiCast. Then we provide Blender, a simulator that models the neighbor discovery behavior of different broadcasters and scanners. By adopting Blender, ElastiCast can be implemented with three components: Local Optima Estimation, Common Interest Extraction, and Interval Multiplexing, in which we capture the key features of BLE neighbor discovery and globally optimize the broadcast mode interacting with diverse scan modes. Experimental evaluation results and commercial product deployment experience demonstrate that ElastiCast is effective in achieving stable and bounded neighbor discovery latency within the power budget. © 2002-2012 IEEE.

关键词： Bluetooth

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Congestion Control Using In-Network Telemetry for Lossless Datacenters

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computers, Materials & Continua 2023年第4期75卷 1195-1212页

作者： Jin Wang Dongzhi Yuan Wangqing Luo Shuying Rao R.Simon Sherratt Jinbin Hu School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410004China School of Systems Engineering The University of ReadingReadingRG66AYUK

In the Ethernet lossless Data Center Networks (DCNs) deployedwith Priority-based Flow Control (PFC), the head-of-line blocking problemis still difficult to prevent due to PFC triggering under burst trafficscenarios even with the existing congestion control solutions. To addressthe head-of-line blocking problem of PFC, we propose a new congestioncontrol mechanism. The key point of Congestion Control Using In-NetworkTelemetry for Lossless Datacenters (ICC) is to use In-Network Telemetry(INT) technology to obtain comprehensive congestion information, which isthen fed back to the sender to adjust the sending rate timely and *** is possible to control congestion in time, converge to the target rate quickly,and maintain a near-zero queue length at the switch when using ICC. Weconducted Network Simulator-3 (NS-3) simulation experiments to test theICC’s performance. When compared to Congestion Control for Large-ScaleRDMA Deployments (DCQCN), TIMELY: RTT-based Congestion Controlfor the Datacenter (TIMELY), and Re-architecting Congestion Managementin Lossless Ethernet (PCN), ICC effectively reduces PFC pause messages andFlow Completion Time (FCT) by 47%, 56%, 34%, and 15.3×, 14.8×, and11.2×, respectively.

关键词： Data center lossless networks congestion control head of line blocking in-network telemetry

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Deep-EERA:DRL-Based Energy-Efficient Resource Allocation in UAV-Empowered Beyond 5G Networks

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Tsinghua science and technology 2025年第1期30卷 418-432页

作者： Shabeer Ahmad Jinling Zhang Ali Nauman Adil Khan Khizar Abbas Babar Hayat School of Electronic Engineering Beijing University of Posts and TelecommunicationBeijing 1000876China Department of Information and Communication Engineering Yeungnam UniversityGyeongsan 38541Republic of Korea School of Information Engineering Xi’an Eurasia UniversityXi’an 710065China Department of Computer Science Hanyang UniversitySeoul 04763Republic of Korea

The rise of innovative applications,like online gaming,smart healthcare,and Internet of Things(IoT)services,has increased demand for high data rates and seamless connectivity,posing challenges for Beyond 5G(B5G)*** is a need for cost-effective solutions to enhance spectral efficiency in densely populated areas,ensuring higher data rates and uninterrupted connectivity while minimizing *** Aerial Vehicles(UAVs)as Aerial Base Stations(ABSs)offer a promising and cost-effective solution to boost network capacity,especially during emergencies and high-data-rate ***,integrating UAVs into the B5G networks presents new challenges,including resource scarcity,energy efficiency,resource allocation,optimal power transmission control,and maximizing overall *** paper presents a UAV-assisted B5G communication system where UAVs act as ABSs,and introduces the Deep Reinforcement Learning(DRL)based Energy Efficient Resource Allocation(Deep-EERA)*** efficient DRL-based Deep Deterministic Policy Gradient(DDPG)mechanism is introduced for optimal resource allocation with the twin goals of energy efficiency and average throughput *** proposed Deep-EERA method learns optimal policies to conserve energy and enhance throughput within the dynamic and complex UAV-empowered B5G *** extensive simulations,we validate the performance of the proposed approach,demonstrating that it outperforms other baseline methods in energy efficiency and throughput maximization.

关键词： Deep Reinforcement Learning(DRL) Unmanned Aerial Vehicles(UAVs) resource allocation energy efficiency 5G and beyond network

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When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system

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Green Energy and Intelligent Transportation 2024年第3期3卷 24-41页

作者： Malak Abid Ali Khan Hongbin Ma Arshad Farhad Asad Mujeeb Imran Khan Mirani Muhammad Hamza National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Computer Science Namal UniversityPakistan Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

LoRa technology contributes to green energy by enabling efficient,long-range communication for the Internet of Things(IoT).This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa,where the network performance is affected by the density of gateways(GWs)and end devices(EDs),as well as environmental *** mitigate interference,data throughput losses,and high-power consumption,the proposed spreading factor(SF)and hybrid(data rate|SF)models dynamically adjust the transmission *** orchestration of concurrent data modifications within the network server(NS)is crucial for uninterrupted communication between GWs and EDs,especially in monitoring electric vehicle(EV)stations to reduce traffic congestion and *** K-means and density-based spatial clustering of applications with noise(DBSCAN)algorithms optimizes ED allocation,averts data congestion,and improves the signal-tointerference noise ratio(SINR).These methods ensure seamless information reception by meticulously allocated EDs across various GW *** estimate the free-space losses(FSL),a log-distance path loss model(log-PL)is *** various bandwidths(BWs),bidirectional communications,and duty cycles(DCs)helps to prevent saturation,thus prolonging the operational lifespan of *** findings reveal a notable packet rejection rate(PRR)of 0%for the DBSCAN(hybrid model).In contrast,the K-means exhibits a PRR ranging from 5%(hybrid model)to 35.29%(SF model)for the ten GWs ***,the network saturation is reduced to 10.185%and 9.503%,respectively,highlighting an improvement in the average efficiency of slotted ALOHA(91.1%)and pure ALOHA(90.7%).These enhancements increase the lifespan of EDs to 15,465.27 days.

关键词： DBSCAN Green transportation Hybrid model Intelligent transportation K-means

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Visual Measurement of Foam Thickness in Flotation Process Based on Depth Stereo Matching

Visual Measurement of Foam Thickness in Flotation Process Ba...

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2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Zheng, Xiuguang Li, Xiaorui Yuan, Zhaolin Ban, Xiaojuan School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350378658

In the process of copper flotation, the traditional detection method has some defects in accurately detecting the depth of foam layer in the flotation cell, especially for the identification of foam information of highly reflective and attenuation materials in the flotation foam system. We aim to introduce a new synthetic dataset, specifically for the flotation foam system, and pay special attention to the foam information of high reflection and high attenuation materials, so as to promote it to the actual flotation foam system and improve the accuracy of liquid level detection. We combine the newly synthesized dataset with binocular ranging methods and propose a soft strategy method for depth estimation of flotation cell thickness using binocular stereo matching based on IoT technology. The experimental results show that our method has achieved remarkable results in the flotation foam system, can accurately measure the depth of the flotation cell, and provides reliable technical support for the control and optimization of the flotation process. Therefore, this binocular stereo matching depth estimation method based on IoT technology provides an effective way to solve the limitations of traditional flotation depth detection methods. It not only effectively monitors the current efficiency of the flotation cell but also automatically identifies instances of flotation cell froth overflowing, offering automated inspection and diagnostics. © 2024 IEEE.

关键词： Stereocenters

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D-scheduler:A scheduler in time-triggered distributed system through decoupling dependencies between tasks and messages

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science China(Technological sciences) 2024年第1期67卷 183-196页

作者： YANG TingTing ZHANG YuQi YUE FengLai WUNIRI QiQiGe TONG Chao School of Computer Science&Engineering Beihang UniversityBeijing 100191China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China National Innovation Center of Intelligent and Connected Vehicles Beijing 100176China

Time-triggered architecture,as a mainstream design of the distributed real-time system,has been successfully applied in the aerospace,automotive and mechanical ***,time-triggered scheduling is a challenging NP-hard *** are few studies that could quickly solve the scheduling problem of large distributed time-triggered *** solve this problem,a communication affinity parameter is defined in this paper to describe the degree of bias of the shaper task towards sending or receiving *** on this,an innovative task-message decoupling model named D-scheduler is built to reduce the computation complexity of the scheduling problem in large-scale ***,we provide mathematical proof that our model is a convex optimization that is easy to solve with existing computational *** experiments substantiate the efficacy of the *** dramatically reduces the scheduling complexity of large-scale real-time systems with a small loss of solving space compared to the federal scheduler.

关键词： time-triggered architecture time-triggered scheduling communication affinity parameter task-message decoupling model

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Predicting software vulnerability based on software metrics: a deep learning approach

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Iran Journal of computer science 2024年第4期7卷 801-812页

作者： Agbenyegah, Francis Kwadzo Asante, Micheal Chen, Jinfu Akpaku, Ernest Department of Computer Science Kwame Nkrumah University of Science and Technology Kumasi Ghana School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China Department of Information Technology Faculty of Computing and Information Systems Ghana Communication Technology University Accra Ghana

The security of IT systems is the topmost priority of software developers. Software vulnerabilities undermine the security of computer systems. Lately, there have been a lot of reported issues of software vulnerabilities recorded in individuals and corporate systems. Software metrics-based techniques have been used and found to be effective due to low false positives and false negatives. However, there are software metrics that have not been investigated and could have an impact on the performance of the predictive model. In this study, we developed an ensemble deep learning algorithm made of LSTM, CNN, and MLP models with the non-investigated metrics as a feature to learn the latent representation of code metrics to predict anomalies in source code effectively. We trained the proposed model on the SySeVR datasets and compared the model's performance against five deep learning algorithms and four state-of-the-art SVPs. The proposed model performs better than the other deep learning with a classification accuracy of 96.17%, and a precision of 97.72%. The model's classification accuracy is 4.98% higher than that of the five deep learning models and 1.71% lower in precision than the state-of-the-art SVP. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Deep learning Machine learning Software metrics Software security Software vulnerabilities

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