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9th International Conference on Big Data and information Analytics, BigDIA 2023

作者： Li, Zhanzhe Li, Kai Liu, Lihua Wang, Mao Liu, Qingbao National University of Defense Technology Laboratory for Big Data and Decision Changsha China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Changsha China

ISBN: (纸本)9798350330076

The maintenance big data management of aviation equipment has always been a major issue in equipment maintenance reform. Especially, the analysis of maintenance errors based on aviation equipment maintenance database is particularly important. This paper proposes an association analysis method based on Apriori algorithm for date mining of a certain aviation equipment maintenance monthly report. Firstly, the BI-LSTM-CRF neural network is used for feature entity recognition. Then, the Apriori algorithm is used for association rule analysis to mine potential laws between multidimensional data, and radar charts are drawn to customize comprehensive evaluation indicators for overall visual analysis of different aviation equipment. Finally, a case demonstration is presented at the end. The proposed method aims to mine the hidden value information in unstructured text materials for key data such as equipment fault location, fault type, and impact degree. © 2023 IEEE.

关键词： Data mining

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A Transfer Learning Based Approach for COVID-19 Detection Using Inception-v4 Model

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Intelligent Automation & Soft Computing 2023年第2期35卷 1721-1736页

作者： Ali Alqahtani Shumaila Akram Muhammad Ramzan Fouzia Nawaz Hikmat Ullah Khan Essa Alhashlan Samar MAlqhtani Areeba Waris Zain Ali College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia Department of Computer Science and Information Technology University of SargodhaSargodha40100Pakistan School of Systems and Technology University of Management and TechnologyLahore54782Pakistan Department of Computer Science COMSATS University IslamabadWah CampusIslamabad47040Pakistan Department of Medical Imaging King Khaled HospitalNajran61441Saudi Arabia Electrical&Electronics Engineering Department Universiti TeknologiPetronas31750Malaysia Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan

Coronavirus(COVID-19 or SARS-CoV-2)is a novel viral infection that started in December 2019 and has erupted rapidly in more than 150 *** rapid spread of COVID-19 has caused a global health emergency and resulted in governments imposing lock-downs to stop its *** is a signiﬁ-cant increase in the number of patients infected,resulting in a lack of test resources and kits in most *** overcome this panicked state of affairs,researchers are looking forward to some effective solutions to overcome this situa-tion:one of the most common and effective methods is to examine the X-radiation(X-rays)and computed tomography(CT)images for detection of ***-ever,this method burdens the radiologist to examine each ***,to reduce the burden on the radiologist,an effective,robust and reliable detection system has been developed,which may assist the radiologist and medical specia-list in effective detecting of *** proposed a deep learning approach that uses readily available chest radio-graphs(chest X-rays)to diagnose COVID-19 *** proposed approach applied transfer learning to the Deep Convolutional Neural Network(DCNN)model,Inception-v4,for the automatic detection of COVID-19 infection from chest X-rays *** dataset used in this study contains 1504 chest X-ray images,504 images of COVID-19 infection,and 1000 normal images obtained from publicly available medical *** results showed that the proposed approach detected COVID-19 infection with an overall accuracy of 99.63%.

关键词： COVID-19 transfer learning deep learning artiﬁcial intelligence chest X-rays machine learning

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Restoration of Simple Lens Captured Images based on Deep Multi-Scale Network 9

Restoration of Simple Lens Captured Images based on Deep Mul...

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9th International Conference on Big Data and information Analytics, BigDIA 2023

作者： Li, Weili Ren, Jiaqi Yin, Xiaoqing Dong, Yibo Wang, Yonghui National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Changsha China National University of Defense Technology College of Advanced Interdisciplinary Studies Changsha China

ISBN: (纸本)9798350330076

Inspired by computational imaging technology, simple lens can be combined with the image restoration algorithm to achieve satisfactoy imaging quality. Therefore, the conventional complex lens can be replaced with simple lens to reduce the cost and weight. However, images captured by simple-lens cameras suffer from spatial varying blur. An image restoration algorithm is proposed based on a deep multi-scale network for simple lens imaging systems. Image feature are processed and analyzed at multiple resolution levels to improve the learning ability of the network. The experimental and results prove that the image restoration algorithm we proposed can achieve promising restoration results. © 2023 IEEE.

关键词： Image reconstruction

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Nonconvex Noise-Tolerant Neural Model for Repetitive Motion of Omnidirectional Mobile Manipulators

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1766-1768页

作者： Zhongbo Sun Shijun Tang Jiliang Zhang Junzhi Yu the Department of Control Engineering Changchun University of TechnologyChangchun 130012China IEEE College of Information Science and Engineering Northeastern UniversityShenyang 110819China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered t... 详细信息

关键词： directional programming hardware

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Velocity Estimation of an Underwater Vehicle Using Doppler Shift of Positioning Signals

Velocity Estimation of an Underwater Vehicle Using Doppler S...

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2025 IEEE Underwater technology, UT 2025

作者： Tsuchiya, Atsushi Ebihara, Tadashi Wakatsuki, Naoto Yoshihara, Tohru University of Tsukuba Graduate School of Science and Technology Tsukuba Japan University of Tsukuba Institute of Systems and Information Engineering Tsukuba Japan Aomi Construction Co. Ltd. Technology Development Department Tokyo Japan

ISBN: (纸本)9798331534189

This paper proposes a method for estimating the moving velocity of underwater vehicles by utilizing the Doppler shift in positioning signals employed for time-of-arrival (ToA) acoustic positioning. The Doppler shift generated in the received signal was measured by resampling, and the moving velocity in global coordinates was estimated by finding the least-squares solution using the Doppler shift generated in the direct wave and the position measured by ToA positioning. Field experiments conducted in a real marine environment demonstrated the feasibility and effectiveness of the proposed velocity estimation method. © 2025 IEEE.

关键词： Underwater acoustics

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Distributed data-driven consensus control of multi-agent systems under switched uncertainties

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Control Theory and technology 2023年第3期21卷 478-487页

作者： Wenjie Liu Yifei Li Gang Wang Jian Sun Jie Chen National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

Cooperative control of multi-agent systems(MASs),particularly consensus control,has gained significant attention in the last two decades,thanks to the rapid and sustained development of distributed and networked *** this paper,we present some new results focused on consensus control of a set of unknown linear MASs(whose system matrices are unknown)under unknown switched uncertainties,with an emphasis on distributed data-driven *** proposed controller is end-to-end,designed by solving two data-based semi-definite programs(SDPs),which adjust to the changes of the uncertainty *** approach achieves asymptotic consensus of the MAS provided that the switching is slow enough and the uncertainty is *** illustrate the effectiveness of our proposed method through a numerical example.

关键词： Data-driven control Multi-agent systems Consensus-Switched uncertainties

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Digital Twin-Driven Intrusion Detection for IoT and Cyber-Physical System

Digital Twin-Driven Intrusion Detection for IoT and Cyber-Ph...

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2024 International Conference on Intelligent Algorithms for Computational Intelligence systems, IACIS 2024

作者： Ramamoorthy, Saravanan Kandaneri Sindhu, L. Valarmathi, K. Gobinath, C. Umaeswari, P. College of Non-Medicine University: Texila American University Guyana Sona College of Technology Department of Information Technology Salem India S. A. Engineering College Department of Information Technology Chennai India Reva University School of Computing and Information Technology Bengaluru India R.M.K. Engineering College Department of Computer Science and Business Systems Kavaraipettai India

ISBN: (纸本)9798350360660

From smart homes to industrial automation, the efficiency and connectivity of many applications have been greatly improved by the fast expansion of the Internet of Things (IoT) and Cyber-Physical systems (CPS). Sophisticated cyberattacks are becoming more common in this networked ecosystem, thus strong security measures are needed. In order to protect CPS and IoT settings, this study presents a new intrusion detection method that makes use of Digital Twin technology. To build an adaptable and dynamic Intrusion Detection System (IDS), our suggested architecture combines Digital Twins with state-of-the-art machine learning methods. In order to accurately detect and categorize any threats, the IDS constantly learns from data in both the past and the present. When tested on benchmark datasets and in real-world Internet of Things (IoT) settings, the framework outperforms conventional intrusion detection system (IDS) solutions in terms of detection accuracy and false alarm rate reduction. To protect IoT and CPS infrastructures from ever-changing cyber threats, this scalable and resilient security solution is offered by this IDS that is powered by digital twins. We present ICNN-FCID, an Integrated Convolutional Neural Network for Fog Computing Environment, a hybrid deep learning intrusion detection model for fog computing environments. © 2024 IEEE.

关键词： Network intrusion

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Unraveling the skatole biodegradation process in an enrichment consortium using integrated omics and culture-dependent strategies

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Journal of Environmental sciences 2023年第5期127卷 688-699页

作者： Qiao Ma Nan Meng Jiancheng Su Yujie Li Jiazheng Gu Yidi Wang Jingwei Wang Yuanyuan Qu Zelong Zhao Yeqing Sun Institute of Environmental Systems Biology College of Environmental Science and EngineeringDalian Maritime UniversityDalian 116026China Liaoning Key Lab of Germplasm Improvement and Fine Seed Breeding of Marine Aquatic Animals Liaoning Ocean and Fisheries Science Research InstituteDalian 116023China Key Laboratory of Industrial Ecology and Environmental Engineering(Ministry of Education) School of Environmental Science and TechnologyDalian University of TechnologyDalian 116024China

3-Methylindole(skatole)is regarded as one of the most offensive compounds in odor *** is feasible for skatole removal but the functional species and genes responsible for skatole degradation remain *** this study,an efficient aerobic skatole-degrading consortium was *** and Pseudomonas were identified as the two major and active populations by integrated metagenomic and metatranscriptomic *** analyses indicated that the skatole downstream degradation wasmainly via the catechol pathway,and upstream degradation was likely catalyzed by the aromatic ring-hydroxylating oxygenase and flavin *** binning and gene analyses indicated that Pseudomonas,Pseudoclavibacter,and Raineyella should cooperate with Rhodococcus for the skatole degradation ***,a pure strain Rhodococcus ***1 was successfully obtained which could utilize skatole as the sole carbon *** genome sequencing showed that strain DMU1 was the predominant population in the *** crude enzyme and RT-qPCR assays indicated that strain DMU1 degraded skatole through the catechol ortho-cleavage ***,our results suggested that synergistic degradation of skatole in the consortium should be performed by diverse bacteria with Rhodococcus as the primary degrader,and the degradation mainly proceeded via the catechol pathway.

关键词： Skatole Biodegradation Bacterial consortium Metagenomics and metatranscriptomics Rhodococcus

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Adaptive Varying Contention Window MAC Protocol Based on Underwater Acoustic Propagation Delay

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IEEE Sensors Journal 2023年第13期23卷 15019-15031页

作者： Guo, Yongan Obaidat, Mohammad S. Guo, Jing Wu, Tin-Yu Tey, Fu Jie Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Ministry of Education College of Telecommunications and Information Engineering Nanjing210003 China The King Abdullah II School of Information Technology University of Jordan Amman11942 Jordan The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Amity University UP Noida201301 India Nanjing University of Posts and Telecommunications College of Telecommunications and Information Engineering Nanjing210003 China National Pingtung University of Science and Technology Department of Management Information Systems Pingtung912301 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106335 Taiwan

Underwater acoustic wave propagation time delay and fluctuations are much greater than radio waves. However, many of the protocols used for underwater acoustic networking and communication are designed according to the principles of terrestrial wireless communication networks, failing to give full consideration to utilizing the underwater acoustic propagation and its time delay variation. For this reason, this article proposes an adaptive varying contention window media access control (AVCW-MAC) protocol based on propagation delay. The protocol uses AVCW random backoff mechanism to differently set up the CW of each node based on the different propagation delays from each underwater sensor node to the cluster head node to improve the channel utilization. In addition, to avoid excessive difference in the CW of each node, the backoff factors K1 and K2 are introduced in the AVCW random backoff mechanism to improve the fairness of nodes' accessing the channel. Simulation results show that for the same amount of sensor nodes, the AVCW-MAC protocol has significantly improved network throughput and decreased average end-to-end latency when compared to legacy CW-MAC protocols. © 2001-2012 IEEE.

关键词： Underwater acoustics

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Zero-DCE++Inspired Object Detection in Less Illuminated Environment Using Improved YOLOv5

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Computers, Materials & Continua 2023年第12期77卷 2751-2769页

作者： Ananthakrishnan Balasundaram Anshuman Mohanty Ayesha Shaik Krishnadoss Pradeep Kedalu Poornachary Vijayakumar Muthu Subash Kavitha Centre for Cyber Physical Systems Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiTamil Nadu600127India School of Information and Data Sciences Nagasaki UniversityNagasaki8528521Japan

Automated object detection has received the most attention over the *** cases ranging from autonomous driving applications to military surveillance systems,require robust detection of objects in different illumination ***-of-the-art object detectors tend to fare well in object detection during daytime ***,their performance is severely hampered in night light conditions due to poor *** address this challenge,the manuscript proposes an improved YOLOv5-based object detection framework for effective detection in unevenly illuminated nighttime ***,the preprocessing strategies involve using the Zero-DCE++approach to enhance lowlight *** is followed by optimizing the existing YOLOv5 architecture by integrating the Convolutional Block Attention Module(CBAM)in the backbone network to boost model learning capability and Depthwise Convolutional module(DWConv)in the neck network for efficient compression of network *** Night Object Detection(NOD)and Exclusively Dark(ExDARK)dataset has been used for this *** proposed framework detects classes like humans,bicycles,and *** demonstrate that the proposed architecture achieved a higher Mean Average Precision(mAP)along with a reduction in model size and total parameters,*** proposed model is lighter by 11.24%in terms of model size and 12.38%in terms of parameters when compared to baseline YOLOv5.

关键词： Object detection deep learning nighttime road scenes YOLOv5 DWConv Zero-DCE++ CBAM

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