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IEEE Internet of Things Journal 2024年第15期11卷 25925-25938页

作者： Kaliski, Rafael Han, Yue-Hua National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung804 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei115 Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei106 Taiwan

Vehicle to Everything (V2X) is a core 5G technology. V2X and its enabler, Device-to-Device (D2D), are essential for the Internet of Things (IoT) and the Internet of Vehicles (IoV). V2X enables vehicles to communicate with other vehicles (V2V), networks (V2N), and infrastructure (V2I). While V2X enables ubiquitous vehicular connectivity, the impact of bursty data on the network's overall Quality of Service (QoS), such as when a vehicle accident occurs, is often ignored. In this work, we study both 4G and 5G V2X utilizing Evolved Universal Terrestrial Radio Access New Radio (E-UTRA-NR) and propose the use of socially aware 5G NR dual connectivity (en-DC) for traffic differentiation. We also propose localized QoS, wherein high-priority QoS flows traverse 5G road side units (RSUs) and normal-priority QoS flows traverse 4G base station (BS). We formulate a max-min fair QoS-aware nonorthogonal multiple access (NOMA) resource allocation scheme, QoS reclassify. QoS reclassify enables localized QoS and traffic steering to mitigate bursty network traffic's impact on the network's overall QoS. We then solve QoS reclassify via integer linear programming (ILP) and derive its approximation. We demonstrate that both optimal and approximation QoS reclassify resource allocation schemes in our socially aware QoS management methodology outperform socially unaware legacy 4G V2X algorithms (no localized QoS support, no traffic steering) and socially aware 5G V2X (no localized QoS support, yet utilizes traffic steering). Our proposed QoS reclassify scheme's QoS flow end-to-end latency requires only approx 15% of the time legacy 4G V2X requires. © 2014 IEEE.

关键词： Quality of service

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Automated object recognition in high-resolution optical remote sensing imagery

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National science Review 2023年第6期10卷 38-41页

作者： Yazhou Yao Tao Chen Hanbo Bi Xinhao Cai Gensheng Pei Guoye Yang Zhiyuan Yan Xian Sun Xing Xu Hai Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology (NIST) Aerospace Information Research Institute Chinese Academy of Sciences Department of Computer Science and Technology Tsinghua University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the *** provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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Improvement of Spiking Neural network with Bit Plane Coding 16

Improvement of Spiking Neural Network with Bit Plane Coding

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16th IEEE International Conference on Computational Intelligence and Communication networks, CICN 2024

作者： Luu, Nhan T. Luu, Duong T. Nam, Pham Ngoc Thang, Truong Cong The University of Aizu Department of Computer Science and Engineering Aizuwakamatsu Japan Can Tho University Information and Network Management Center Can Tho Viet Nam College of Engineering and Computer Science VinUniversity Hanoi Viet Nam

ISBN: (纸本)9798331505264

Spiking neural networks (SNNs) have gained sig-nificant attention as a promising framework in computational neuroscience and artificial intelligence, offering benefits such as low energy consumption and minimal memory requirements. Despite these advantages, their practical deployment is hindered by several challenges, particularly in performance optimization. This paper introduces a novel methodology to enhance the performance of SNNs in image processing by leveraging a bit-plane-based coding scheme. The proposed approach is specifically designed to improve the accuracy of SNNs without increasing their model size. Comprehensive experimental evaluations demonstrate the efficacy of this coding strategy across multiple datasets. To the best of our knowledge, this work is the first to explore the application of bit-plane representation in the context of SNNs. © 2024 IEEE.

关键词： network coding

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The Design of Portrait Photography Guiding System Using VGG16 Model 14th

The Design of Portrait Photography Guiding System Using VGG1...

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14th International Conference on Frontier Computing, FC 2024

作者： Chiu, Chuan-Feng Huang, Chun-Hong Tseng, Hsiang-Chieh Wu, Pei-Jung Lin, Wei-Sheng Peng, Hsiang-Min Department of Information Management Minghsin University of Science and Technology Hsinchu Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan City Taiwan

ISBN: (纸本)9789819623945

Because of the population of photography camera, human being could have photography equipment to take a picture became an easy task. However, to have a good photography is not an easy task. The basic of a good photo is the composition of the photography. A better photography composition could lead better visual effect. So, in this paper we intent to design a photography guiding system framework for users to have good photos especially for portrait photography. In our work, we design a system framework using VGG16 model based on Rule of Thirds and luminance distribution to guide user to select better photography composition. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Photographic equipment

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Real-Time On-Site Ground-Motion Prediction Using ResNet

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Seismological Research Letters 2025年第3期96卷 1834-1845页

作者： Yang, Tzu-Yi Chen, Da-Yi Chin, Tai-Lin Mobile Computing and Networking Lab Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Seismological Center of Central Weather Administration Taipei Taiwan

On-site warnings can decrease the range of late alert zone during earthquakes. This study develops a deep learning model to predict whether the maximum peak ground acceleration at a station exceeds 25 Gal based on the waveform of the initial P-wave. A ResNet architecture model is developed to address the degradation problem in multilayered models, thereby enhancing performance. The model exhibits high performance for a test dataset, achieving F1-scores higher than 90% over various time windows, and outperforms the traditional progressive displacement value (Pdv) method and newer convolutional neural network (CNN) methods. Ground motion of two actual earthquakes are applied to test the model and validate its prediction capabilities, and the results indicate that the proposed model has higher accuracy and speed than Pdv and CNN methods. In addition, the model is integrated with the Earthworm earthquake early warning system for real-time waveform analysis and prediction, extending the model’s applicability beyond experimental stages to online systems. The proposed method is also tested using data from earthquakes that occurred in March 2023. © Seismological Society of America.

关键词： Convolutional neural networks

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Towards intelligent and trustworthy task assignments for 5G-enabled industrial communication systems

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Digital Communications and networks 2025年第1期11卷 246-255页

作者： Mingfeng Huang Anfeng Liu Neal N.Xiong Athanasios V.Vasilakos School of Computer and Communication Engineering Changsha University of Science&TechnologyChangsha410114China School of Electronic Information Central South UniversityChangsha410083China Department of Computer Science and Mathematics Sul Ross State UniversityAlpineTX 79830USA College of Mathematics and Computer Science Fuzhou UniversityFuzhou350116China Center for AI Research University of AgderGrimstad 999026Norway

With the unprecedented prevalence of Industrial Internet of Things(IIoT)and 5G technology,various applications supported by industrial communication systems have generated exponentially increased processing tasks,which makes task assignment inefficient due to insufficient *** this paper,an Intelligent and Trustworthy task assignment method based on Trust and Social relations(ITTS)is proposed for scenarios with many tasks and few ***,ITTS first makes initial assignments based on trust and social influences,thereby transforming the complex large-scale industrial task assignment of the platform into the small-scale task assignment for each ***,an intelligent Q-decision mechanism based on workers'social relation is proposed,which adopts the first-exploration-then-utilization principle to allocate *** when a worker cannot cope with the assigned tasks,it initiates dynamic worker recruitment,thus effectively solving the worker shortage problem as well as the cold start *** importantly,we consider trust and security issues,and evaluate the trust and social circles of workers by accumulating task feedback,to provide the platform a reference for worker recruitment,thereby creating a high-quality worker ***,extensive simulations demonstrate ITTS outperforms two benchmark methods by increasing task completion rates by 56.49%-61.53%and profit by 42.34%-47.19%.

关键词： Industrial Internet of Things Insufficient workers Trust evaluation Social relation Task assignment

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On Construction of Precise Positioning System via IEEE 802.11ax

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IEEE Internet of Things Journal 2023年第14期10卷 12951-12960页

作者： Tsung, Chen-Kun Yang, Chao-Tung Liu, Jung-Chun Hsiung, Chun Chang, Shih-Kuang Hsu, Ming-Shang National Chin-Yi University of Technology Department of Computer Science and Information Engineering Taichung41170 Taiwan Tunghai University Department of Computer Science and Research Center for Smart Sustainable Circular Economy Taichung407224 Taiwan Tunghai University Department of Computer Science Taichung40704 Taiwan Krystal Technology Company Ltd. Network Department Taichung42756 Taiwan

Wireless network stability is critical for organizations. Most companies rely on a solid Internet connection for at least part of their day-to-day activities. It is essential to show the fast and high capacity of Wi-Fi. Wireless network management also significantly supplies the user with quality service and helps the system administrator manage and track the network infrastructure. The user must be able to stay connected. The Wi-Fi connection engine was applied in this article using the analysis and locations engine (ALE). ALE provides the information, including MAC address, location, floor information, and the building where the device belongs. From this data, we presented the Web visualization of the Wi-Fi network monitoring system on the map using Cesium. Except for the common information about Wi-Fi users, this work presents the vertical position visualization in the buildings to provide more details about user usage. This work analyzes the user experience of using the proposed system, and latency is the appropriate metric to measure the user experience. The experiment results show that the optimized number of cluster partitions is four, and the latency is less than 1.3 s for 4-MB data. Therefore, the system provides a visualization platform with acceptable system response, and Internet managers would consider the proposed system as the management tool. © 2014 IEEE.

关键词： Engines

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Inverse Scattering of Two-dimensional Circular Cylindrical Conductors by Convolutional Neural network 4

Inverse Scattering of Two-dimensional Circular Cylindrical C...

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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Chen, Po-Hsiang Hsu, Hsiu-Hui Chiu, Chien-Ching Chien, Wei Yu, Kai-Xu Tamkang University Department of Electrical and Computer Engineering New Taipei City Taiwan Lunghwa University of Science and Technology Department of Computer Information and Network Engineering Taoyuan City Taiwan

ISBN: (纸本)9798350360721

We used a Convolutional Neural network (CNN) to reconstruct the electromagnetic imaging of a perfect conductor in half-space through the traverse magnetic wave. Since the conventional iterative algorithm is time-consuming, we developed a real-time electromagnetic imaging technique to apply to the CNN to reconstruct the half-space conducting cylinders. The sizes and positions of the cylinders were calculated through the Direct Sampling Method (DSM) in the scattered field. The original ground truth was fed to CNN for training to predict accurate sizes and positions of the shape. The accurate size and position of the shape for the perfect conductor were reconstructed. © 2024 IEEE.

关键词： Convolution

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A Data Consistency Insurance Method for Smart Contract

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computers, Materials & Continua 2023年第9期76卷 3783-3795页

作者： Jing Deng Xiaofei Xing Guoqiang Deng Ning Hu Shen Su Le Wang Md Zakirul Alam Bhuiyan School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou510006China Information Network Engineering and Reasearch Center South China University of TechnologyGuangzhou510640China Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China Department of Computer and Information Sciences Fordham UniversityNew York10458USA

As one of the major threats to the current DeFi(Decentralized Finance)ecosystem,reentrant attack induces data inconsistency of the victim smart contract,enabling attackers to steal on-chain assets from DeFi projects,which could terribly do harm to the confidence of the blockchain ***,protecting DeFi projects from the reentrant attack is very difficult,since generating a call loop within the highly automatic DeFi ecosystem could be very *** researchers mainly focus on the detection of the reentrant vulnerabilities in the code testing,and no method could promise the non-existent of reentrant *** this paper,we introduce the database lock mechanism to isolate the correlated smart contract states from other operations in the same contract,so that we can prevent the attackers from abusing the inconsistent smart contract *** to the existing resolutions of front-running,code audit,andmodifier,our method guarantees protection resultswith better *** we further evaluate our method on a number of de facto reentrant attacks observed from *** results prove that our method could efficiently prevent the reentrant attack with less running cost.

关键词： Blockchain smart contract data consistency reentrancy attack

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