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Energy Harvesting in the Wake of An Inverted C-Shaped Bluff Body

China Ocean engineering 2024年第1期38卷 68-80页

作者： WANG Jun-lei LI Shen-fang Md.Mahbub ALAM ZHU Hong-jun HU Guo-biao school of Mechanical and Power engineering Zhengzhou UniversityZhengzhou 450000China Center for Turbulence Control Harbin Institute of Technology(Shenzhen)Shenzhen 518055China State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Southwest Petroleum UniversityChengdu 610500China internet of things Thrust The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 511400China

This paper proposes a novel wake-induced vibration(WIV)-based energy harvesting system consisting of two bluff *** inverted C-shaped bluff body is stationary installed at the upstream position to generate an interference wake street,and a cylinder bluff body equipped with a transducer is elastically suspended at the downstream position to harness WIV *** hydrodynamics and energy harvesting(EH)performance of the proposed system are investigated via experimental *** reduced velocity(U*)ranging from 2 to 14(the corresponding Reynolds number ranging from 15100 to 106200)is considered in the present *** is found that the wake generated by the inverted C-shaped bluff body significantly affects the EH *** the opening angle(α)of the C-shaped bluff body increases the vibration amplitude of the downstream cylinder,thereby increasing the harvested *** the spacing(L)between two bluff bodies is two times the cylinder diameter(D),the wake-induced vibration(WIV)mode is observed,while the combined WIV and wake galloping(WG)mode occurs whenαis 150°,and L equals 3D or *** average drag coefficient becomes negative when L is 2D,3D,or *** carefully configuring a C-shaped bluff body,the wake generated by it can bring an augmenting effect on the vibration of the downstream EH *** example,the RMS power output of the proposed EH system reaches a maximum of 0.31 W at U*=8 and L=4D,which is 300%greater than that of its traditional ***,after a number of case stud-ies,it is identified that the proposed EH system can achieve the best performance whenαis 150°and L=2D.

关键词： wake-induced vibration vortex-induced vibration galloping energy harvesting bluff body

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A Blockchain-Based Efficient Cross-Domain Authentication Scheme for internet of Vehicles

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Computers, Materials & Continua 2024年第7期80卷 567-585页

作者： Feng Zhao Hongtao Ding Chunhai Li Zhaoyu Su Guoling Liang Changsong Yang Guangxi engineering Research Center of Industrial internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China school of information and Communication Guilin University of Electronic TechnologyGuilin541004China school of Computer Science and information Security Guilin University of Electronic TechnologyGuilin541004China

The internet of Vehicles(IoV)is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the ***,due to the open and variable nature of its network topology,vehicles frequently engage in cross-domain *** such processes,directly uploading sensitive information to roadside units for interaction may expose it to malicious tampering or interception by attackers,thus compromising the security of the cross-domain authentication ***,IoV imposes high real-time requirements,and existing cross-domain authentication schemes for IoV often encounter efficiency *** mitigate these challenges,we propose CAIoV,a blockchain-based efficient cross-domain authentication scheme for *** scheme comprehensively integrates technologies such as zero-knowledge proofs,smart contracts,and Merkle hash tree *** divides the cross-domain process into anonymous cross-domain authentication and safe cross-domain authentication phases to ensure efficiency while maintaining a balance between efficiency and ***,we evaluate the performance of *** results demonstrate that our proposed scheme reduces computational overhead by approximately 20%,communication overhead by around 10%,and storage overhead by nearly 30%.

关键词： Blockchain cross-domain authentication internet of vehicle zero-knowledge proof

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A Study on Idea Adoption Prediction Model Based on SMOTE-AdaBoost:Taking Salesforce Platform as an Example

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Journal of Systems Science and information 2024年第4期12卷 476-490页

作者： Yunjiang XI Futao HUANG Lu HUANG Xiao LIAO Juan YU school of Business Administration South China University of TechnologyGuangzhou 510641China school of internet Finance and information engineering Guangdong University of FinanceGuangzhou 510521China school of Economics and Management Fuzhou UniversityFuzhou 350108China

In the context of information overload,companies often struggle to effectively identify valuable ideas on their open innovation *** this article,we propose an idea adoption strategy based on machine *** used data from a well-known open innovation platform,Salesforce,and extracted characteristic variables using the information Adoption *** classification models were then constructed based on AdaBoost,Random Forest,SVM and Logistic Regression *** to significant differences in the number of positive and negative samples in the OIP,we used the SMOTE method to address the problem of data *** results of the study showed that the ensemble learning models were more accurate in identifying valuable ideas than the individual machine learning *** comparing the two ensemble learning models,AdaBoost outperformed Random Forest in predicting both positive and negative class *** SMOTE-AdaBoost model achieved a recall of 0.93,a precision of 0.92 and an impressive AUC of 0.98 in identifying adopted ideas,which could well identify valuable ideas and has implications for improving the efficiency and quality of idea adoption in *** shortcoming of this work is that it only investigated a single *** the future,we will consider extending this method to different platforms and multiple classification problems.

关键词： open innovation platform AdaBoost information adoption ensemble learning

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Key Technologies and Prospects for Electric Vehicles Within Emerging Power Systems: Insights from Five Aspects

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 439-447页

作者： Yalun Li Minggao Ouyang C.C.Chan Xueliang Sun Yonghua Song Wei Cai Yilin Xie Yuqiong Mao Department of Electrical engineering and School of Vehicle and MobilityTsinghua UniversityBeijing 100084China school of Vehicle and Mobility Tsinghua UniversityBeijing 100084China Department of Electrical and Electronic engineering The University of Hong KongHong Kong 999077China Department of Mechanical and Materials engineering University of Western OntarioLondonON N6A 3K7Canada State Key Laboratory of internet of things for Smart City University of MacaoTaipaMacao 999078China Department of Electrical engineering Tsinghua UniversityBeijing 100084China school of Electrical and Electronic engineering Harbin University of Science and TechnologyHarbin 150080China

The energy revolution requires coordination in energy consumption, supply, storage and institutional *** energy generation technologies, along with their associated costs, are already fully equipped for large-scale ***, energy storage remains a bottleneck, and solutions areneeded through the use of electric vehicles, which traditionallyplay the role of energy consumption in power systems. Toclarify the key technologies and institutions that support EVsas terminals for energy use, storage, and feedback, the CSEEJPES forum assembled renowned experts and scholars in relevantfields to deliver keynote reports and engage in discussions ontopics such as vehicle–grid integration technology, advancedsolid-state battery technology, high-performance electric motortechnology, and institutional innovation in the industry *** experts also provided prospects for energy storage andutilization technologies capable of decarbonizing new powersystems.

关键词： Electric vehicles engineering philosophy highpower density motor new power system solid state batteries vehicle grid integration.

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An Enhanced Clustering-Based(k, t)-Anonymity Algorithm for Graphs

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Chinese Journal of Electronics 2024年

作者： Yuanyuan WANG Xing ZHANG Zhiguang CHU Wei SHI Xiang LI school of Electronics and information engineering Liaoning University of Technology Key Laboratory of Security for Network and Data in Industrial internet of Liaoning Province Faculty of information Technology Beijing University of Technology

As people become increasingly reliant on the internet, securely storing and publishing private data has become an important issue. In real life, the release of graph data can lead to privacy breaches, which is a highly challenging problem. Although current research has addressed the issue of identity disclosure, there are still two challenges: First, the privacy protection for large-scale datasets is not yet comprehensive; Second, it is difficult to simultaneously protect the privacy of nodes, edges, and attributes in social networks. To address these issues, this paper proposes a(k, t)-graph anonymity algorithm based on enhanced clustering. The algorithm uses k-means++ clustering for k-anonymity and t-closeness to improve k-anonymity. We evaluated the privacy and efficiency of this method on two datasets and achieved good results. This research is of great significance for addressing the problem of privacy breaches that may arise from the publication of graph data.

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Dynamic Hypergraph Modeling and Robustness Analysis for SIoT

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Computer Modeling in engineering & Sciences 2024年第9期140卷 3017-3034页

作者： Yue Wan Nan Jiang Ziyu Liu school of information engineering East China Jiaotong UniversityNanchang330013China

The Social internet of things(SIoT)integrates the internet of things(IoT)and social networks,taking into account the social attributes of objects and diversifying the relationship between humans and objects,which overcomes the limitations of the IoT’s focus on associations between *** Intelligence(AI)technology is rapidly *** is critical to build trustworthy and transparent systems,especially with system security issues coming to the *** paper emphasizes the social attributes of objects and uses hypergraphs to model the diverse entities and relationships in SIoT,aiming to build an SIoT hypergraph generation model to explore the complex interactions between entities in the context of intelligent *** hypergraph generation models impose too many constraints and fail to capture more details of real *** contrast,this paper proposes a hypergraph generation model that evolves dynamically over time,where only the number of nodes is *** combines node wandering with a forest fire model and uses two different methods to control the size of the *** new nodes are added,the model can promptly reflect changes in entities and relationships within *** results exhibit that our model can effectively replicate the topological structure of real-world *** also evaluate the vulnerability of the hypergraph under different attack strategies,which provides theoretical support for building a more robust intelligent SIoT hypergraph model and lays the foundation for building safer and more reliable systems in the future.

关键词： Large-scale artificial intelligence Social internet of things hypernetwork robustness analysis

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Blockchain-Enabled Federated Learning for Privacy-Preserving Non-IID Data Sharing in Industrial internet

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Computers, Materials & Continua 2024年第8期80卷 1967-1983页

作者： Qiuyan Wang Haibing Dong Yongfei Huang Zenglei Liu Yundong Gou school of Electrical and information engineering Hunan Institute of TechnologyHengyang421002China

Sharing data while protecting privacy in the industrial internet is a significant *** machine learning methods require a combination of all data for training;however,this approach can be limited by data availability and privacy *** learning(FL)has gained considerable attention because it allows for decentralized training on multiple local ***,the training data collected by data providers are often non-independent and identically distributed(non-IID),resulting in poor FL *** paper proposes a privacy-preserving approach for sharing non-IID data in the industrial internet using an FL approach based on blockchain *** overcome the problem of non-IID data leading to poor training accuracy,we propose dynamically updating the local model based on the divergence of the global and local *** approach can significantly improve the accuracy of FL training when there is relatively large *** addition,we design a dynamic gradient clipping algorithm to alleviate the influence of noise on the model accuracy to reduce potential privacy leakage caused by sharing model ***,we evaluate the performance of the proposed scheme using commonly used open-source image *** simulation results demonstrate that our method can significantly enhance the accuracy while protecting privacy and maintaining efficiency,thereby providing a new solution to data-sharing and privacy-protection challenges in the industrial internet.

关键词： Federated learning data sharing non-IID data differential privacy blockchain

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Gas sensor array based on carbon-based thin-film transistor for selective detection of indoor harmful gases

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Rare Metals 2024年第9期43卷 4401-4411页

作者： Can Liu Yu Sun Jia-Yi Guo Xiu-Lei Li Lu Tao Jin-Yong Hu Jue-Xian Cao Ping-Hua Tang Yong Zhang school of Electrical and information engineering Hunan Institute of EngineeringXiangtan 411104China Physics and Optoelectronics&Hunan Institute of Advanced Sensing and information Technology Xiangtan UniversityXiangtan 411105China

The identification of indoor harmful gases is imperative due to their significant threats to human health and *** achieve accurate identification,an effective strategy of constructing a sensor array combined with the pattern recognition algorithm is ***-based thin-film transistors are selected as the sensor array unit,with semiconductor carbon nanotubes(CNTs)within the TFT channels modified with different metals(Au,Cu and Ti)for selective responses to NH3,H2S and HCHO,*** accurate gas species identification,an identification mode that combines linear discriminant analysis algorithms and logistic regression classifier is *** test results demonstrate that by preprocessing the sensor array’s sensing data with the LDA algorithm and subsequently employing the LR classifier for identification,a 100%recognition rate can be achieved for three target gases(NH3,H2S and HCHO).This work provides significant guidance for future applications of chip-level gas sensors in the realms of the internet of things and Artificial Intelligence.

关键词： Carbon-based thin-film transistors Gas sensor arrays Semiconductor carbon nanotubes Multi-gas detection Linear discriminant analysis

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Multi-layer network embedding on scc-based network with motif

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Digital Communications and Networks 2024年第3期10卷 546-556页

作者： Lu Sun Xiaona Li Mingyue Zhang Liangtian Wan Yun Lin Xianpeng Wang Gang Xu Department of Communication engineering Institute of Information Science TechnologyDalian Maritime UniversityDalian116026China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province DUT School of Software Technology&DUT-RU International School of Information Science and EngineeringDalian University of TechnologyDalian 116620China College of information and Communication engineering Harbin Engineering UniversityHarbin 150001China school of information and Communication engineering Hainan UniversityHaikou 570228China State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new *** is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based *** previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node ***,the content of semantic information is quite *** graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of ***,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology *** Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node *** verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

关键词： Semantic communication and computing Multi-layer network Graph neural network Motif

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A novel medical image data protection scheme for smart healthcare system

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 821-836页

作者： Mujeeb Ur Rehman Arslan Shafique Muhammad Shahbaz Khan Maha Driss Wadii Boulila Yazeed Yasin Ghadi Suresh Babu Changalasetty Majed Alhaisoni Jawad Ahmad school of Computer Science and Informatics Cyber Technology InstituteDe Montfort UniversityLeicesterUK Department of Biomedical engineering University of GlasgowGlasgowUK school of Computing Engineering and the Built EnvironmentEdinburgh Napier UniversityEdinburghUK Robotics and internet‐of‐things Laboratory Prince Sultan UniversityRiyadhSaudi Arabia Department of Computer Science Al Ain UniversityAl AinUnited Arab Emirates Department of Computer engineering College of Computer Science King Khalid UniversityAbhaSaudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The internet of Multimedia things(IoMT)refers to a network of interconnected multimedia devices that communicate with each other over the ***,smart healthcare has emerged as a significant application of the IoMT,particularly in the context of knowledge‐based learning *** healthcare systems leverage knowledge‐based learning to become more context‐aware,adaptable,and auditable while maintain-ing the ability to learn from historical *** smart healthcare systems,devices capture images,such as X‐rays,Magnetic Resonance *** security and integrity of these images are crucial for the databases used in knowledge‐based learning systems to foster structured decision‐making and enhance the learning abilities of ***,in knowledge‐driven systems,the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel,leading to data trans-mission *** address the security and latency concerns,this paper presents a lightweight medical image encryption scheme utilising bit‐plane decomposition and chaos *** results of the experiment yield entropy,energy,and correlation values of 7.999,0.0156,and 0.0001,*** validates the effectiveness of the encryption system proposed in this paper,which offers high‐quality encryption,a large key space,key sensitivity,and resistance to statistical attacks.

关键词： data analysis medical image processing security

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