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International Journal of Information and Communication Technology 2024年第2期24卷 145-155页

作者： Wang, Kaiku Huang, Congkuan Yang, Yang Department of Computer Science and Technology Beijing University of Aeronautics and Astronautics Beijing100191 China Department of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China

Aiming at the problem of low precision and large cleaning error in multi-link similar data mining, a multi-link similar data mining cleaning method based on Bayesian algorithm is proposed in this paper. On the basis of extracting multi-link data, the data is preprocessed and the similarity between the data is calculated. The data with high similarity is input into the Bayesian network, and the data cleaning process is completed according to the maximum likelihood value of the data. Experimental results show that the mining accuracy of the proposed method for similar data can reach 98.51%, and the cleaning error is about 1.22%, indicating that the proposed method can more effectively complete the mining and cleaning of similar data in multi-links. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Directed graphs

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A Deep Neural Network Approach for Fault Detection in Industrial Motors: Enhancing Reliability and Efficiency in Industry 4.0 21

A Deep Neural Network Approach for Fault Detection in Indust...

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21st IEEE International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2024

作者： Ali, Hassan Ahyen, Mostafa Yaqub, Raziq Badawi, Ahmed Shifa, Noora Khandakar, Amith University of Doha for Science and Technology Department of Electrical Engineering Doha Qatar Alabama A and M University Department of Electrical Engineering and Computer Science Huntsville United States Qatar University Department of Electrical Engineering Doha Qatar

ISBN: (纸本)9798350378078

In the era of Industry 4.0, the integration of sophisticated monitoring and control technologies is essential for the reliability and efficiency of industrial equipment. This paper presents a deep neural network (DNN)-based approach for fault detection and classification in industrial motors. The approach identifies common motor faults, including bent shaft, loose vibration, loosely mounted components, electrical faults, and bearing vibration. The proposed DNN model demonstrated robust performance, achieving an overall training accuracy of 83.49% ± 0.43% and a test accuracy of 81.91 % ± 0.82%. The model also achieved a mean precision of 82.05% ± 0.77%, mean recall of 81.91 % ± 0.82%, and mean F1-Score of81.86%± 0.78%. The 95% confidence intervals for accuracy, precision, recall, and F1-Score were (80.77%, 83.04%), (80.98%, 83.11 %), (80.77%, 83.04%), and (80.78%,82.95%), respectively. These results demonstrate the DNN model's ability to precisely classify various motor faults with minimal variability, as evidenced by its narrow confidence intervals and low standard deviations. The model's reliability and efficacy for real-world applications in proactive maintenance and fault detection are confirmed by the consistent performance that is observed across cross-validation folds. © 2024 IEEE.

关键词： Predictive maintenance

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Visually-Aware Context Modeling for News Image Captioning

Visually-Aware Context Modeling for News Image Captioning

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2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024

作者： Qu, Tingyu Tuytelaars, Tinne Moens, Marie-Francine Department of Computer Science KU Leuven Belgium Department of Electrical Engineering KU Leuven Belgium

ISBN: (纸本)9798891761148

News Image Captioning aims to create captions from news articles and images, emphasizing the connection between textual context and visual elements. Recognizing the significance of human faces in news images and the face-name co-occurrence pattern in existing datasets, we propose a face-naming module for learning better name embeddings. Apart from names, which can be directly linked to an image area (faces), news image captions mostly contain context information that can only be found in the article. We design a retrieval strategy using CLIP to retrieve sentences that are semantically close to the image, mimicking human thought process of linking articles to images. Furthermore, to tackle the problem of the imbalanced proportion of article context and image context in captions, we introduce a simple yet effective method Contrasting with Language Model backbone (CoLaM) to the training pipeline. We conduct extensive experiments to demonstrate the efficacy of our framework. We outperform the previous state-of-the-art (without external data) by 7.97/5.80 CIDEr scores on GoodNews/NYTimes800k. ©2024 Association for Computational Linguistics.

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Sensor Switching-Based Automatic Misalignment Detection and Correction System for Wireless Power Transfer

IEEE Open Journal of Vehicular Technology

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IEEE Open Journal of Vehicular Technology 2025年 6卷 1380-1398页

作者： Dahhan, Ali Younis Al Mukhopadhyay, Shayok Hassan, Mohamed S. Osman, Ahmed H. American University of Sharjah Department of Electrical Engineering P.O. Box 26666 Sharjah United Arab Emirates Electrical & Computer Engineering and Computer Science Department West HavenCT06516 United States

Misalignment between the transmitting and receiving coils is an inevitable problem for electric vehicle (EV) wireless power transfer (WPT) systems. Regardless of the WPT system being static or dynamic, coil misalignment reduces the efficiency of the charging system. This paper, focuses on using a combination of computer vision and one of two different misalignment sensors to detect, and further correct lateral misalignment between the EV receiving (Rx) coil and the segmented transmitting (Tx) coils in a charging lane. The vision-based component uses a camera for lane detection and is primarily responsible for detecting larger deviations and making coarse compensations by estimating the lateral shift of the EV, relative to the center of the charging lane. The sensor-based approach relies on Hall effect sensors or detection coils to detect the misalignment in a smaller range, and perform finer corrections. A one-dimensional (1D) actuator moves the receiving coil to correct the coil misalignment, independent of vehicle movements. The vision-based approach showed a wide detection range for misalignment spanning [−15,15] cm, with a correction accuracy of ≈ ±2 cm. This is juxtaposed with the sensor-based approach which operates on a misalignment range of [−3,3] cm, but outperforms the vision-based approach with a correction accuracy of less than ±1 mm. The proposed sensor switching-based approach combines the advantages of the above individual techniques. An experimental setup is developed and tests are performed to evaluate the proposed approach while transferring 108 W of power wirelessly © 2020 IEEE.

关键词： Coils Switches Hall effect Wireless power transfer Inductance Estimation Electric vehicles Costs Batteries Anxiety disorders

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Transaction transmission model for blockchain channels based on non-cooperative games

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science China(Information sciences) 2023年第1期66卷 97-114页

作者： Peiyun ZHANG Chenxi LI Mengchu ZHOU Wenjun HUANG Abdullah ABUSORRAH Omaimah O.BAMASAG Engineering Research Center of Digital Forensics of Ministry of Education School of Computer and SoftwareNanjing University of Information Science and Technology School of Computer and Information Anhui Normal University Department of Electrical and Computer Engineering New Jersey Institute of Technology Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Faculty of Engineering and K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University Department of Computer Science Faculty of Computing and Information Technology Center of Excellence in Smart Environment Research King Abdulaziz University

In blockchain networks, transactions can be transmitted through channels. The existing transmission methods depend on their routing information. If a node randomly chooses a channel to transmit a transaction, the transmission may be aborted due to insufficient funds(also called balance) or a low transmission rate. To increase the success rate and reduce transmission delay across all transactions, this work proposes a transaction transmission model for blockchain channels based on non-cooperative game *** balance, channel states, and transmission probability are fully considered. This work then presents an optimized channel transaction transmission algorithm. First, channel balances are analyzed and suitable channels are selected if their balance is sufficient. Second, a Nash equilibrium point is found by using an iterative sub-gradient method and its related channels are then used to transmit transactions. The proposed method is compared with two state-of-the-art approaches: Silent Whispers and Speedy Murmurs. Experimental results show that the proposed method improves transmission success rate, reduces transmission delay,and effectively decreases transmission overhead in comparison with its two competitive peers.

关键词： Blockchain channel transaction transmission channel balance channel state channel transmission probability non-cooperative game

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Blockchain-Enhanced Security for LEO Satellite Firmware Updates in Beyond-5G NTN Networks 29

Blockchain-Enhanced Security for LEO Satellite Firmware Upda...

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29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Worku, Yonatan M. Tshakwanda, Petro M. Tsegaye, Henok B. Christodoulou, Christos Devetsikiotis, Michael Sacchi, Claudio University of New Mexico Department of Electrical and Computer Engineering United States University of Trento Department of Information Engineering and Computer Science Italy

ISBN: (纸本)9798350377644

The integration of terrestrial and Non-Terrestrial Networks (NTNs) represents a significant advancement in communication technology in the framework of the ongoing beyond-5G standardization process. This integration offers broader coverage, especially in remote and underserved areas, and improved reliability through diversified network paths. Additionally, it paves the way for new services and applications that benefit from ubiquitous connectivity. To achieve enhanced Quality of Service (QoS) and Service Level Agreements (SLAs), the end-to-end network should be open and visible to service providers and users. However, such a clear-mode approach introduces various security threats, making the network susceptible to unauthorized access and service disruption. To address these challenges, a blockchain-based satellite firmware update strategy across terrestrial 5G core and access networks is proposed. This study explores the tradeoff between throughput and QoS in the 5G NTN network when blockchain is implemented. Our experimental setup involved a network of Low Earth Orbit (LEO) satellites integrated with a 5G core, deploying a blockchain-based authentication mechanisms to secure satellite communications. The results show a tangible improvement in authentication efficiency, despite a throughput degradation of around 10 % and a latency increase of 17 % from the baseline values obtained without blockchain security. This tradeoff highlights the cost of enhanced security counter-measures in terms of network performance. Nonetheless, the security benefits, measured through successful authentication attempts, fully justify blockchain integration in scenarios where security is paramount. The proposed approach promises to secure communications in '5G and beyond' NTN hybrid environments by ensuring integrity and confidentiality to the traffic flows. © 2024 IEEE.

关键词： 5G mobile communication systems

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An Innovative Approach Using TKN-Cryptology for Identifying the Replay Assault

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computers, Materials & Continua 2024年第1期78卷 589-616页

作者： Syeda Wajiha Zahra Muhammad Nadeem Ali Arshad Saman Riaz Muhammad Abu Bakr Ashit Kumar Dutta Zaid Alzaid Badr Almutairi Sultan Almotairi Department of Computer Science Alhamd Islamic UniversityIslamabad44000Pakistan Department of Computer Science and Technology University of Science and Technology BeijingBeijing100083China Department of Computer Science National University of TechnologyIslamabad44000Pakistan Department of Electrical Engineering National University of TechnologyIslamabad44000Pakistan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Science Faculty of Computer and Information SystemsIslamic University of MadinahMedinah42351Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia

Various organizations store data online rather than on physical *** the number of user’s data stored in cloud servers increases,the attack rate to access data from cloud servers also *** researchers worked on different algorithms to protect cloud data from replay *** of the papers used a technique that simultaneously detects a full-message and partial-message replay *** study presents the development of a TKN(Text,Key and Name)cryptographic algorithm aimed at protecting data from replay *** program employs distinct ways to encrypt plain text[P],a user-defined Key[K],and a Secret Code[N].The novelty of the TKN cryptographic algorithm is that the bit value of each text is linked to another value with the help of the proposed algorithm,and the length of the cipher text obtained is twice the length of the original *** the scenario that an attacker executes a replay attack on the cloud server,engages in cryptanalysis,or manipulates any data,it will result in automated modification of all associated values inside the *** mechanism has the benefit of enhancing the detectability of replay ***,the attacker cannot access data not included in any of the papers,regardless of how effective the attack strategy *** the end of paper,the proposed algorithm’s novelty will be compared with different algorithms,and it will be discussed how far the proposed algorithm is better than all other algorithms.

关键词： Replay attack malware message attack file encryption cryptology data security

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Effectiveness of Almost Sub Frame Approach as Inter Cell Interference Management in LTE-A Macro - Pico Scenario 9

Effectiveness of Almost Sub Frame Approach as Inter Cell Int...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Jember, Kehali A. Abose, Tadele A. Kassahun, Ermias Madhav, T. Venu Adama Science And Technology University Department Electronics And Communication Engineering Adama Ethiopia Mettu University Department Electrical And Computer Engineering Ethiopia Gondar University Department Electrical And Computer Engineering Gondar Ethiopia

ISBN: (纸本)9798350394474

Heterogeneous networks are promising solutions for enhancing network performance of LTE-A mobile networks by deploying small cells within the area of the serving macro cells. The goal of deploying such networks is to offload data from the congested macro cells towards the small cells. However, cross tier interference is a serious issue, which is introduced due to the transmitted power difference between Macro cell node and small cell node. Hence, cell age users are mainly affected by high power interference originated from Macro node. The paper develops enhanced inter-cell interference coordination using Almost Blank Sub-Frame (ABS) to improve user throughput. This can be achieved by stopping data transmission on in certain sub frame of macro cell while Pico users are scheduled at the same frame. computer simulation results depict that the performance of Pico cell users is highly degraded, especially for cell edge users. The ABS technique improves cell edge user throughput of Pico cell by 95% and center cell user throughput by 75.25%. © 2024 IEEE.

关键词： Heterogeneous networks

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Two-Dimensional Golay Complementary Array Sets with Arbitrary Lengths for Omnidirectional MIMO Transmission

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IEEE Transactions on Communications 2024年第2期72卷 1135-1145页

作者： Zhao, You-Qi Pai, Cheng-Yu Huang, Zhen-Ming Liu, Zilong Chen, Chao-Yu National Cheng Kung University Department of Engineering Science Tainan701 Taiwan National Cheng Kung University Department of Engineering Science and the Institute of Computer and Communication Engineering Tainan701 Taiwan University of Essex School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom National Cheng Kung University Department of Electrical Engineering and the Institute of Computer and Communication Engineering Tainan701 Taiwan

This paper presents a coding approach for achieving omnidirectional transmission of certain common signals in massive multi-input multi-output (MIMO) networks such that the received power at any direction in a cell remains constant for any given distance. Specifically, two-dimensional (2D) Golay complementary array set (GCAS) can be used to design the massive MIMO precoding matrix so as to achieve omnidirectional transmission due to its complementary autocorrelation property. In this paper, novel constructions of new 2D GCASs with arbitrary array lengths are proposed. Our key idea is to carefully truncate the columns of certain larger arrays generated by 2D generalized Boolean functions. Finally, the power radiation patterns and numerical results are provided to verify the omnidirectional property of the GCAS-based precoding. The error performances of the proposed precoding scheme are presented to validate its superiority over the existing alternatives. © 1972-2012 IEEE.

关键词： Peak to average power ratio

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Direct Edge-To-Edge Local-Learning-Assisted Model-Based Transfer Learning

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IEEE Internet of Things Journal 2024年第11期11卷 20223-20235页

作者： Huang, Zih-Syuan Lu, Ching-Hu Hwang, I-Shyan Hsinchu308 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Yuan-Ze University Department of Computer Science and Engineering Taoyuan320 Taiwan

With the gradual advancement of technology in the production of consumer goods, the Internet of Things (IoT) systems have experienced rapid development, resulting in a massive amount of data that can be processed using deep neural networks. However, annotating the data and training the models require significant manpower, time, and computational resources. Transfer learning can address this problem. Traditional systems rely on centralized servers for transfer learning. Although several studies have proposed distributed systems for direct edge-To-edge (e2e) instance-based and feature-based transfer learning, they neglect model-based transfer learning (MTL) within the same domain. This leads to lower learning efficiency, lower privacy protection, and higher transmission costs. Therefore, our study proposes direct e2e local-learning-Assisted MTL for a direct e2e many-To-many MTL scenario. The method can transfer model structures and weights between distributed devices without relying on powerful centralized servers. The effectiveness of the proposed approach is demonstrated by applying it to various scenarios. © 2014 IEEE.

关键词： Feature extraction

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