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MCDS: An Effective Multi-UAV Collaborative Decision-Making System in Mobile Edge Computing Networks

IEEE Internet of Things Journal 2025年

作者： Xiong, Naixue Zhong, Weiyu Chen, Yuxiang He, Dacheng Li, Yuhui Chen, Linshu Liang, Wei Sanya Research Institute of Hunan University of Science and Technology School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology China Sanya Research Institute of Hunan University of Science and Technology Hunan University School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology School of Information Science and Engineering China The Hong Kong Polytechnic University Department of Computing Hong Kong

Mobile Edge Computing (MEC) pushes computing resources from the network center to the network edge to provide efficient and reliable computing services. However, due to the mobility and diversity of mobile users (MUs), edge servers (ESs) are likely to be overloaded, which leads to a rapid decline in the quality of service provided by the MEC system. This paper introduces unmanned aerial vehicles (UAVs) to solve the problem of ES overload. This paper presents an effective Multi-UAV Collaborative Decision-Making System (MCDS) tailored to optimize task offloading and resource allocation in MEC networks. The proposed system seeks to reduce task computing delays and energy consumption while guaranteeing timely task completion and compliance with resource constraints. We design a distributed two-stage optimization algorithm to jointly optimize the task offloading decision and resource allocation of the collaborative computing system (UAVs, ESs, and MUs). To address the flight cooperation problem of multi-UAVs, we also proposed a task-aware scheduling algorithm for multi-UAVs. In addition, we conducted a large number of simulation experiments. Experimental results show that our two-stage optimization scheme is lower than other benchmark algorithms in terms of task completion delay, energy consumption and total cost of objective function. Specifically, compared with seven baseline algorithms under three different system setting scenarios, our algorithm reduces the total cost by an average of 38.79%, the energy consumption by an average of 40.70%, and the delay by an average of 15.67%. © 2014 IEEE.

关键词： Drones

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Improving Maritime Data: A Machine Learning-based Model for Missing Vessel Trajectories Reconstruction

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IEEE Transactions on Vehicular technology 2025年

作者： Chen, Jin Liang, Maohan Peng, Chang Zhang, Jixin Huo, Shengxu Sanya Institute Hunan University of Science and Technology China Department of Civil and Environmental Engineering National University of Singapore Singapore Singapore College of Computer Science and Electronic Engineering Hunan University China School of Computer Science Hubei University of Technology China

Advancements in maritime satellite technology have significantly impacted the maritime industry, enhancing both communication and safety at sea. These technological improvements have enabled Automatic Identification Systems (AIS) to transmit data through robust maritime communication networks. However, despite these advancements, AIS data often contain significant missing data due to limitations in both devices and network coverage. To overcome these limitations, this research presents an innovative approach for reconstructing missing points. In this paper, we first extracted the geometric shape and motion characteristics of vessels and constructed a decision tree using an adaptive sparse constraint mechanism to classify four types of vessel trajectories. Then, the vessel classification findings serve as input and the vessel acceleration features are constructed using the heading and velocity features of the trajectories at both ends. Finally, We employ a bidirectional Gate Recurrent Unit (GRU) network to simultaneously train on historical trajectory data. The method progressively shortens the reconstructed trajectory, thereby enhancing the accuracy of the reconstruction. In this paper, comparative experiments are conducted with several algorithms across various dimensions, including algorithm performance, trajectory types, and navigation scenarios. It is indicated by the experimental results that the algorithm discussed in this study outperforms baselines. Significant methodological advancements in vessel trajectory reconstruction are represented by this study, which also shows promising potential for application in intelligent maritime transportation systems. © 1967-2012 IEEE All rights reserved.

关键词： Waterway transportation

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MEASURING COMPUTATIONAL THINKING - DEVELOPING A SHORT PERFORMANCE TEST FOR HIGHER EDUCATION 21

MEASURING COMPUTATIONAL THINKING - DEVELOPING A SHORT PERFOR...

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21st International Conference on Cognition and Exploratory Learning in the Digital Age, CELDA 2024

作者： Guggemos, Josef Rietsche, Roman Aier, Stephan Strecker, Jannis Mayer, Simon Department of Vocational Education and Training University of Education Schwäbisch Gmünd Germany Institute for Digital Technology Management Bern University of Applied Sciences Switzerland School of Computer Science University of St.Gallen Switzerland

ISBN: (纸本)9789898704610

Technological advancements, particularly in artificial intelligence, significantly transform our society and work practices. Computational thinking (CT) has emerged as a crucial 21st-century skill, enabling individuals to solve problems more effectively through an automation-oriented perspective and fundamental concepts of computer science. To ensure the effective integration of CT into educational curricula, it is crucial to develop efficient assessment frameworks that allow teachers to measure and promote student CT proficiency. Therefore, our aim is to develop a short test to measure CT among undergraduate students. To this end, we consider two performance tests: the Computational Thinking test (CTt) and the Algorithmic Thinking Test for Adults (ATTA). We use items from both instruments to compile a short test. Based on a sample of 290 second-year non-computer science undergraduate students, we provide evidence on the quality of our test. Besides classical test theory, we apply item response theory, namely Rasch modeling, and confirmatory factor analysis. Our test shows favorable properties, e.g., Cronbach's alpha > .75, and may be suitable for the efficient assessment of CT across higher education programs. © 2024 Proceedings of the 21st International Conference on Cognition and Exploratory Learning in the Digital Age, CELDA 2024. All rights reserved.

关键词： Students

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Modular chaotification model with FPGA implementation

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science China(Technological sciences) 2021年第7期64卷 1472-1484页

作者： HUA Zhong Yun ZHOU BingHang ZHANG YinXing ZHOU YiCong School of Computer Science and Technology Harbin Institute of TechnologyShenzhenShenzhen518055China College of Electrical and Information Engineering Hunan UniversityChangsha410082China Department of Computer and Information Science University of MacaoMacao999078China

Chaotic systems are an effective tool for various applications, including information security and internet of things. Many chaotic systems may have the weaknesses of incomplete output distributions, discontinuous chaotic regions, and simple chaotic *** may result in many negative influences in practical applications utilizing chaos. To deal with these issues, this study introduces a modular chaotification model(MCM) to increase the dynamic properties of current one-dimensional(1 D) chaotic maps. To exhibit the effect of the MCM, three 1 D chaotic maps are improved using the MCM as examples. Studies of the resulting properties show the robust and complex dynamics of these improved chaotic maps. Moreover, we implement these improved chaotic maps of MCM in a field-programmable gate array hardware platform and apply them to the application of PRNG. Performance analyses verify that these chaotic maps improved by the MCM have more complicated chaotic behaviors and wider chaotic ranges than the existing and several new chaotic maps.

关键词： nonlinear system chaotic system field-programmable gate array(FPGA) pseudorandom number generator(PRNG) hardware implementation

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Recent innovations in laser additive manufacturing of titanium alloys

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International Journal of Extreme Manufacturing 2024年第3期6卷 2-37页

作者： Jinlong Su Fulin Jiang Jie Teng Lequn Chen Ming Yan Guillermo Requena Lai-Chang Zhang Y Morris Wang Ilya V Okulov Hongmei Zhu Chaolin Tan College of Materials Science and Engineering Hunan UniversityChangsha 410082People’s Republic of China Singapore Institute of Manufacturing Technology(SIM Tech) Agency for ScienceTechnology and Research(A∗STAR)5 Cleantech LoopSingapore 636732Singapore Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055People’s Republic of China Institute of Materials Research German Aerospace Center(DLR)Linder Höhe51147 CologneGermany Centre for Advanced Materials and Manufacturing Edith Cowan University270 Joondalup DriveJoondalupPerthWestern Australia 6027Australia Department of Materials Science and Engineering University of CaliforniaLos AngelesCA 900095United States of America Leibniz Institute for Materials Engineering-IWT Badgasteiner Str.328359 BremenGermany Faculty of Production Engineering University of BremenBadgasteiner Str.128359 BremenGermany Key Laboratory of Hunan Province of Equipment Safety Service Technology under Extreme Environment University of South ChinaHengyangPeople’s Republic of China RWTH Aachen University Metallic Structures and Materials Systems for Aerospace EngineeringD-52062 AachenGermany

Titanium(Ti)alloys are widely used in high-tech fields like aerospace and biomedical *** additive manufacturing(LAM),as an innovative technology,is the key driver for the development of Ti *** the significant advancements in LAM of Ti alloys,there remain challenges that need further research and development *** recap the potential of LAM high-performance Ti alloy,this article systematically reviews LAM Ti alloys with up-to-date information on process,materials,and *** feasible solutions to advance LAM Ti alloys are reviewed,including intelligent process parameters optimization,LAM process innovation with auxiliary fields and novel Ti alloys customization for *** auxiliary energy fields(***,acoustic,mechanical deformation and magnetic fields)can affect the melt pool dynamics and solidification behaviour during LAM of Ti alloys,altering microstructures and mechanical *** kinds of novel Ti alloys customized for LAM,like peritecticα-Ti,eutectoid(α+β)-Ti,hybrid(α+β)-Ti,isomorphousβ-Ti and eutecticβ-Ti alloys are reviewed in ***,machine learning in accelerating the LAM process optimization and new materials development is also *** review summarizes the material properties and performance envelops and benchmarks the research achievements in LAM of Ti *** addition,the perspectives and further trends in LAM of Ti alloys are also highlighted.

关键词： additive manufacturing titanium alloys auxiliary field machine learning aerospace materials lightweight materials novel alloys

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Assessing Cascading Effects of Cyber-Attacks in Interconnected Critical Infrastructures 32nd

Assessing Cascading Effects of Cyber-Attacks in Interconnect...

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32nd European safety and Reliability Conference, ESREL 2022

作者： Chockalingam, Sabarathinam Maathuis, Clara Department of Risk Safety and Security Institute for Energy Technology Norway Open University of the Netherlands Department of Computer Science Netherlands

ISBN: (纸本)9789811851834

Critical Infrastructures (CIs) represent the backbone of modern societies. It is essential to ensure a smooth and reliable functioning of vital services, and processes that societies rely on. CIs are either based on or are soon to be embedding (modern) digital technologies. The level of interconnectedness and interdependencies of such systems continue to increase. These developments make them directly exposed to different types of cyber-attacks like ransomware and Distributed Denial of Service (DDoS). Cyber-attacks on such infrastructures would not only impact the overall functioning of such infrastructures, well-being of people and a nation’s economy, but also cause cascading effects. There is a lack of framework to assess cascading effects that propagate in both independent and interdependent CIs regarding the operational level of components. To tackle this gap, this research aims to answer the following research question: "How can we assess the cascading effects in terms of operational level corresponding to different components in both independent and interdependent Critical Infrastructures taking into account component dependencies, vulnerabilities, and existing measures?", by means of building a Bayesian Network-based framework following a Design science Research methodological approach. © 2022 ESREL2022 Organizers. Published by Research Publishing, Singapore.

关键词： Cyber attacks

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Pushing the Boundaries of Molecular Property Prediction for Drug Discovery with Multitask Learning BERT Enhanced by SMILES Enumeration

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Research 2023年第3期2022卷 157-170页

作者： Xiao-Chen Zhang Cheng-Kun Wu Jia-Cai Yi Xiang-Xiang Zeng Can-Qun Yang Ai-Ping Lu Ting-Jun Hou Dong-Sheng Cao Xiangya School of Pharmaceutical Sciences Central South UniversityChangsha 410013Hunan P.R.China Shangqiu Normal University School of Information TechnologyShangqiu 476000HenanP.R.China College of Computer National University of Defense TechnologyChangsha 410005HunanP.R.China Department of Computer Science Hunan UniversityChangsha 410082.HunanP.R.China institute for Advancing Translational Medicine in Bone and Joint Diseases School of Chinese MedicineHong Kong Baptist UniversityHong Kong SAR 999077P.R.China Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University.College of Pharmaceutical Sciences Zhejiang UniversityHangzhou 310058ZhejiangP.R.China

Accurate prediction of pharmacological properties of small molecules is becoming increasingly important in drug *** feature-engineering approaches heavily rely on handcrafted descriptors and/or fingerprints,which need extensive human expert *** the rapid progress of artificial intelligence technology,data-driven deep learning methods have shown unparalleled advantages over feature-engineering-based ***,existing deep learning methods usually suffer from the scarcity of labeled data and the inability to share information between different tasks when applied to predicting molecular properties,thus resulting in poor generalization ***,we proposed a novel multitask learning BERT(Bidirectional Encoder Representations from Transformer)framework,named MTL-BERT,which leverages large-scale pre-training,multitask learning,and SMILES(simplified molecular input line entry specification)enumeration to alleviate the data scarcity ***-BERT first exploits a large amount of unlabeled data through self-supervised pretraining to mine the rich contextual information in SMILES strings and then fine-tunes the pretrained model for multiple downstream tasks simultaneously by leveraging their shared ***,SMILES enumeration is used as a data enhancement strategy during the pretraining,fine-tuning,and test phases to substantially increase data diversity and help to learn the key relevant patterns from complex SMILES *** experimental results showed that the pretrained MTL-BERT model with few additional fine-tuning can achieve much better performance than the state-of-the-art methods on most of the 60 practical molecular ***,the MTL-BERT model leverages attention mechanisms to focus on SMILES character features essential to target properties for model interpretability.

关键词： simplified generalization tuning

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Tailoring cobalt-free La_(0.5)Sr_(0.5)FeO_(3-δ)cathode with a nonmetal cation-doping strategy for high-performance proton-conducting solid oxide fuel cells

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SusMat 2022年第5期2卷 607-616页

作者： Yanru Yin Hailu Dai Shoufu Yu Lei Bi Enrico Traversa School of Resource Environment and Safety Engineering University of South ChinaHengyangHunanChina School of Materials Science and Engineering Yancheng Institute of TechnologyYanchengJiangsuChina School of Materials and Energy University of Electronic Science and Technology of ChinaChengduSichuanChina Department of Chemical Science and Technology University of Rome Tor VergataRomeItaly

A nonmetal doping strategy was exploited for the conventional La_(0.5)Sr_(0.5)FeO_(3-δ)(LSF)cathode,allowing high performance for proton-conducting solid oxide fuel cells(H-SOFCs).Unlike previous studies focusing on the utilization of metal oxides as dopants,phosphorus,which is a nonmetal element,was used as the cation dopant for LSF by partially replacing Fe ions to form the new La_(0.5)Sr_(0.5)Fe_(0.9)P_(0.1)O_(3-δ)(LSFP)*** H-SOFC using the LSFP cathode showed a two-fold peak power density as compared to that using the LSF *** experimental studies and first-principle calculations were used to unveil the mechanisms for the high performance of the LSFP cells.

关键词： cathode high performance nonmetal doping proton conductor solid oxide fuel cell

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High-Precision Intelligent Dynamic Scheduling Algorithm and Application During Service of Wind Turbine Group 18th

High-Precision Intelligent Dynamic Scheduling Algorithm and ...

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18th Annual Conference of China Electrotechnical Society, ACCES 2023

作者： Zhao, Qiaohong Zhou, Zhou Song, Xiaoping Zhang, Jingjing Zhou, Wuxi Liu, Qiao Liu, Jie Zhan, Jun Hebei Vocational College of Rail Transportation Shijiazhuang050000 China Hunan Institute of Engineering Xiangtan411104 China Harbin Electric Corporation Wind Power Co. Ltd Xiangtan411102 China College of Computer Science National University of Defense Technology Changsha410000 China

ISBN: (纸本)9789819714193

The problem of low control accuracy is common in the new energy power system, especially with the increase of the installed capacity of wind turbines and the increase in the number of controlled wind turbines, the higher requirements for the whole field control strategy, the more obvious the problem of low control accuracy. In response to the above problems,, after analyzing the two fundamental reasons for the large control error of wind turbine group, Firstly, this paper optimizes the closed-loop control of the entire wind farm by using the improved PID (Proportion Integration Differentiation) controller, and eliminates the error caused by line loss. Secondly, aiming at the problem of large error caused by obvious oscillation in the small power section in the wind turbine group control process, the sliding step theory is proposed, and in the process of small power section control, the wind turbines with the least amount of intelligent allocation participates in the control, thereby reducing the oscillation and error, and finally, the actual open-loop and closed-loop control data of multiple wind turbine group are analyzed. The actual field results show that after using the algorithm in this paper, the whole field control accuracy of the wind turbine group can reach within 1%, which effectively solves the problem of low control accuracy of the whole field of the large-capacity wind turbine group, The frequency stability of wind farm grid connection has been improved step-by-step. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Controllers

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Revisiting the topology of urban road networks with graph embeddings

Revisiting the topology of urban road networks with graph em...

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2024 China Automation Congress, CAC 2024

作者： Liu, Kang Wang, Feng He, Bing Wang, Wei Wu, Guohua Jiang, Jincheng Yuan, Diping Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Intelligent Science & Technology Academy Limited Limited of CASIC Beijing China School of Computer Science Chengdu University of Information Technology Chengdu China Department of Mechanical Engineering City University of Hong Kong Hong Kong Shenzhen Technology University Shenzhen China School of Safety Engineering China University of Mining and Technology Xuzhou China

ISBN: (纸本)9798350368604

Representing and depicting topological structures of road networks is beneficial for route planning, traffic management and network optimization. Even though road segments are basic management units in practice, the topological structures of road-segment based networks have not been well characterized due to the homogeneity of their network metrics (e.g., degree). Therefore, this study introduced graph-embedding technique and investigated its potential for characterizing topological structures of road-segment based networks. A popular graph-embedding model called Node2Vec is applied to learn embeddings of road segments from the networks. On this basis, we firstly explored the relationship between road-segment embeddings and centrality metrics by testing if the latter can be predicted by the former. Second, we investigated the clustering results of the road-segment embeddings and tested if the clustered road segments are modularized in topology. Experiments based on road networks of six Chinese cities proved that road-segment embeddings can not only well represent various centrality metrics (e.g., degree, closeness, and PageRank), but also detect community structures that road segments with similar embeddings tend to be densely connected with each other. Those findings revealed the characteristics of road embeddings and proved their potential for representing road-segment based network structures, thus we can better apply them to more related downstream tasks such as transport network optimization and traffic prediction. © 2024 IEEE.

关键词： Graph embeddings

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