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A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

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Computers, Materials & Continua 2024年第8期80卷 2099-2119页

作者： Tajmal Hussain Jungpyo Hong Jongwon Seok department of Information and communication engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational *** technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing *** this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing ***,features are extracted by the VGG19 convolutional ***,after processing through the GAP layer,the extracted features are fed to the SVM classifier for *** this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the *** outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS ***,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.

关键词： Smart manufacturing steel defect detection deep learning CNN

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CAGCN:Centrality-Aware Graph Convolution Network for Anomaly Detection in Industrial Control Systems

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Journal of Computer Science & Technology 2024年第4期39卷 967-983页

作者： Jun Yang Yi-Qiang Sheng Jin-Lin Wang Hong Ni National Network New Media engineering Research Center Institute of AcousticsChinese Academy of SciencesBeijing 100190China School of electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100049China

In industrial control systems,the utilization of deep learning based methods achieves improvements for anomaly ***,most current methods ignore the association of inner components in industrial control *** industrial control systems,an anomaly component may affect the neighboring components;therefore,the connective relationship can help us to detect anomalies *** this paper,we propose a centrality-aware graph convolution network(CAGCN)for anomaly detection in industrial control *** the traditional graph convolution network(GCN)model,we utilize the concept of centrality to enhance the ability of graph convolution networks to deal with the inner relationship in industrial control *** experiments show that compared with GCN,our CAGCN has a better ability to utilize this relationship between components in industrial control *** performances of the model are evaluated on the Secure Water Treatment(SWaT)dataset and the Water Distribution(WADI)dataset,the two most common industrial control systems datasets in the field of industrial anomaly *** experimental results show that our CAGCN achieves better results on precision,recall,and F1 score than the state-of-the-art methods.

关键词： graph convolution network(GCN) data mining network centrality anomaly detection industrial control system

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Performance Improvement of Multiband Triangular Microstrip Patch Antenna Using Frequency Selective Surface

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Journal of Shanghai Jiaotong university(Science) 2024年第2期29卷 316-321页

作者： MAHENDRAN Krishnakumar GAYATHRI Rajaraman department of electronics and communication engineering Annamalai UniversityChidambaram 608002India

Today's antennas have to operate in multiple resonant frequencies to satisfy the need of recent advances in communication *** paper presents split ring resonator based triangular multiband antenna whose antenna performance is enhanced with the help of frequency selective surfaces(FSSs).The antenna has multiple resonances at S,C,and X *** array of 4×3 crisscross-shaped unit cells are arranged to form the FSS *** antenna is fed with a microstrip line feeding *** proposed antenna operates at 3.5 GHz,4.1 GHz,5.5GHz,9.4GHz,and 9.8 GHz with a better return loss and *** and measured results yield a good match.

关键词： triangular microstrip antenna split ring resonator frequency selective surface(FSS) metamaterial

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Few-shot incremental radar target recognition framework based on scattering-topology properties

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Chinese Journal of Aeronautics 2024年第8期37卷 246-260页

作者： Chenxuan LI Weigang ZHU Bakun ZHU Yonggang LI Graduate School Space Engineering UniversityBeijing 101400China department of electronic and Optical engineering Space Engineering UniversityBeijing 101400China

The continuous emergence of new targets in open scenarios leads to a substantial decrease in the performance of Inverse Synthetic Aperture Radar(ISAR)recognition ***,data scarcity further exacerbates the challenge of identifying new classes of ISAR *** this paper,a few-shot incremental target recognition framework based on Scattering-Topology Properties(STPIL)is ***,STPIL extracts scattering-topology properties of ISAR targets as recognition ***,the pseudo-incremental training strategy effectively alleviates the algorithm’s forgetting of old knowledge,and improves compatibility with new ***,a feature embedding network,with few parameters,is designed based on the graph neural *** embedding network is highly adaptable to changes in data ***,STPIL fully considers the joint distribution and marginal distribution in scattering features,and uses the Brownian distance metric module to make the scattering-topology features more *** results on both the simulation dataset and the public measured data indicate that STPIL can effectively balance new classes with old classes,and has superior performance to other advanced methods in the incremental recognition of targets.

关键词： Brownian distance metric Graph neural networks Incremental learning Inverse Synthetic Aperture Radar(ISAR) Scattering

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A Review of State-of-the-art Flexible Power Point Tracking Algorithms in Photovoltaic Systems for Grid Support:Classification and Application

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 1-21页

作者： Mina Haghighat Mehdi Niroomand Hossein Dehghani Tafti Christopher D.Townsend Tyrone Fernando the department of Electrical engineering University of IsfahanIsfahanIran the department of Electrical Electronic and Computer EngineeringUniversity of Western AustraliaCrawley WA 6009Australia

To maximize conversion efficiency,photovoltaic(PV)systems generally operate in the maximum power point tracking(MPPT)***,due to the increasing penetra tion level of PV systems,there is a need for more developed control functions in terms of frequency support services and voltage control to maintain the reliability and stability of the power ***,flexible active power control is a manda tory task for grid-connected PV systems to meet part of the grid ***,a significant number of flexible pow er point tracking(FPPT)algorithms have been introduced in the existing *** purpose of such algorithms is to real ize a cost-effective method to provide grid support functional ities while minimizing the reliance on energy storage *** paper provides a comprehensive overview of grid support functionalities that can be obtained with the FPPT control of PV systems such as frequency support and volt-var *** of these grid support functionalities necessitates PV sys tems to operate under one of the three control strategies,which can be provided with FPPT *** three control strate gies are classified as:①constant power generation control(CP GC),②power reserve control(PRC),and③power ramp rate control(PRRC).A detailed discussion on available FPPT algo rithms for each control strategy is also *** paper can serve as a comprehensive review of the state-of-the-art FPPT algorithms that can equip PV systems with various grid support functionalities.

关键词： Maximum power point tracking(MPPT) flexi ble power point tracking(FPPT) power reserve control(PRC) power ramp rate control(PRRC) low voltage ride-through(LVRT) constant power generation(CPG)

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A nano-plasmonic HMIM waveguide based concurrent dual-band BPF using circular ring resonator

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Optoelectronics Letters 2024年第3期20卷 152-156页

作者： Miriyala Sridhar Surendra Kumar Bitra TS N Murthy Koppireddi Padmaraju department of electronics and communication engineering Koneru Lakshmaiah Education FoundationGunturIndia Astra Microwave Products Ltd. HyderabadIndia department of electronics and communication engineering JNTU-GV College of EngineeringVizianagaramIndia department of electronics and communication engineering Jawaharlal Nehru Technological University KakinadaKakinadaIndia

This article analyzes the transmission line characteristics of plasmonic hybrid metal insulator metal(HMIM) wave-guide, circular ring resonator(CRR) based dual-band band-pass filters with two transmission poles in both pass-bands in the optical regime using coupled line feed. The transmission line characteristics of an HMIM waveguide, such as characteristic impedance(Z_(PV)), effective refractive index(n_(eff)) and propagation length(L_(spp)), have been obtained by using full wave simulation.

关键词： waveguide resonator circular

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A peak enhancement of frequency response of waveguide integrated silicon-based germanium avalanche photodetector

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Journal of Semiconductors 2024年第7期45卷 61-68页

作者： Linkai Yi Daoqun Liu Wenzheng Cheng Daimo Li Guoqi Zhou Peng Zhang Bo Tang Bin Li Wenwu Wang Yan Yang Zhihua Li Institute of Microelectronics Chinese Academy of SciencesBeijing 100029China School of electronic Electrical and communication engineering University of Chinese Academy of SciencesBeijing 100049China

Avalanche photodetectors(APDs) featuring an avalanche multiplication region are vital for reaching high sensitivity and responsivity in optical transceivers. Waveguide-coupled Ge-on-Si separate absorption, charge, and multiplication(SACM)APDs are popular due to their straightforward fabrication process, low optical propagation loss, and high detection sensitivity in optical communications. This paper introduces a lateral SACM Ge-on-Si APD on a silicon-on-insulator(SOI) wafer, featuring a 10 μm-long, 0.5 μm-wide Ge layer at 1310 nm on a standard 8-inch silicon photonics platform. The dark current measures approximately 38.6 μA at-21 V, indicating a breakdown voltage greater than-21 V for the device. The APDs exhibit a unitgain responsivity of 0.5 A/W at-10 V. At-15 V, their responsivity reaches 2.98 and 2.91 A/W with input powers of-10 and-25 dBm, respectively. The device's 3-dB bandwidth is 15 GHz with an input power of-15 dBm and a gain is 11.68. Experimental results show a peak in impedance at high bias voltages, attributed to inductor and capacitor(LC) circuit resonance, enhancing frequency response. Furthermore, 20 Gbps eye diagrams at-21 V and-9 dBm input power reveal signal to noise ratio(SNRs) of 5.30. This lateral SACM APD, compatible with the stand complementary metal oxide semiconductor(CMOS) process,shows that utilizing the peaking effect at low optical power increases bandwidth.

关键词： photodetectors optical communications responsivity 3-dB bandwidth

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Precise region semantics-assisted GAN for pose-guided person image generation

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 665-678页

作者： Ji Liu Zhenyu Weng Yuesheng Zhu communication and Information Security Lab Shenzhen Graduate SchoolPeking UniversityShenzhenChina School of Electrical and electronic engineering Nanyang Technological UniversitySingaporeSingapore

Generating a realistic person's image from one source pose conditioned on another different target pose is a promising computer vision *** previous mainstream methods mainly focus on exploring the transformation relationship between the keypoint-based source pose and the target pose,but rarely investigate the region-based human semantic *** current methods that adopt the parsing map neither consider the precise local pose-semantic matching issues nor the correspondence between two different *** this study,a Region Semantics-Assisted Generative Adversarial Network(RSA-GAN)is proposed for the pose-guided person image gen-eration *** particular,a regional pose-guided semantic fusion module is first devel-oped to solve the imprecise match issue between the semantic parsing map from a certain source image and the corresponding keypoints in the source *** well align the style of the human in the source image with the target pose,a pose correspondence guided style injection module is designed to learn the correspondence between the source pose and the target *** addition,one gated depth-wise convolutional cross-attention based style integration module is proposed to distribute the well-aligned coarse style information together with the precisely matched pose-guided semantic information to-wards the target *** experimental results indicate that the proposed RSA-GAN achieves a 23%reduction in LPIPS compared to the method without using the seman-tic maps and a 6.9%reduction in FID for the method with semantic maps,respectively,and also shows higher realistic qualitative results.

关键词： deep learning image processing

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CNN-LSTM based incremental attention mechanism enabled phase-space reconstruction for chaotic time series prediction

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Journal of electronic Science and Technology 2024年第2期22卷 77-90页

作者： Xiao-Qian Lu Jun Tian Qiang Liao Zheng-Wu Xu Lu Gan Bidding and Purchasing Center University of Electronic Science and Technology of ChinaChengdu611731China Yibin Research Institute University of Electronic Science and Technology of ChinaYibin644000China School of Information and communication engineering University of Electronic Science and Technology of ChinaChengdu611731China

To improve the prediction accuracy of chaotic time series and reconstruct a more reasonable phase space structure of the prediction network,we propose a convolutional neural network-long short-term memory(CNN-LSTM)prediction model based on the incremental attention ***,a traversal search is conducted through the traversal layer for finite parameters in the phase ***,an incremental attention layer is utilized for parameter judgment based on the dimension weight criteria(DWC).The phase space parameters that best meet DWC are selected and fed into the input ***,the constructed CNN-LSTM network extracts spatio-temporal features and provides the final prediction *** model is verified using Logistic,Lorenz,and sunspot chaotic time series,and the performance is compared from the two dimensions of prediction accuracy and network phase space ***,the CNN-LSTM network based on incremental attention is compared with long short-term memory(LSTM),convolutional neural network(CNN),recurrent neural network(RNN),and support vector regression(SVR)for prediction *** experiment results indicate that the proposed composite network model possesses enhanced capability in extracting temporal features and achieves higher prediction ***,the algorithm to estimate the phase space parameter is compared with the traditional CAO,false nearest neighbor,and C-C,three typical methods for determining the chaotic phase space *** experiments reveal that the phase space parameter estimation algorithm based on the incremental attention mechanism is superior in prediction accuracy compared with the traditional phase space reconstruction method in five networks,including CNN-LSTM,LSTM,CNN,RNN,and SVR.

关键词： Chaotic time series Incremental attention mechanism Phase-space reconstruction

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Image Fusion Based on Bioinspired Rattlesnake Visual Mechanism Under Lighting Environments of Day and Night Two Levels

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Journal of Bionic engineering 2024年第3期21卷 1496-1510页

作者： Yong Wang Hongmin Zou College of communication engineering Jilin UniversityChangchun130012China

This study,grounded in Waxman fusion method,introduces an algorithm for the fusion of visible and infrared images,tailored to a two-level lighting environment,inspired by the mathematical model of the visual receptive field of rattlesnakes and the two-mode cells'*** research presented here is segmented into three *** the first segment,we design a preprocessing module to judge the ambient light intensity and divide the lighting environment into two levels:day and *** second segment proposes two distinct network structures designed specifically for these daytime and nighttime *** the daytime images,where visible light information is predominant,we feed the ON-VIS signal and the IR-enhanced visual signal into the central excitation and surrounding suppression regions of the ON-center receptive field in the B channel,***,for nighttime images where infrared information takes precedence,the ON-IR signal and the Visual-enhanced IR signal are separately input into the central excitation and surrounding suppression regions of the ON-center receptive field in the B *** outcome is a pseudo-color fused *** third segment employs five different no-reference image quality assessment methods to evaluate the quality of thirteen sets of pseudo-color images produced by fusing infrared and visible *** images are then compared with those obtained by six other methods cited in the relevant *** empirical results indicate that this study's outcomes surpass the comparative results in terms of average gradient and spatial *** one or two sets of fused images underperformed in terms of standard deviation and entropy when compared to the control *** sets of fused images did not perform as well as the comparison in the QAB/F *** conclusion,the fused images generated through the proposed method show superior performance in terms of scene detail,visual perception,and image sharpness

关键词： Rattlesnake Visible image Infrared image Daylight Bionic

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