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High Contrast Metastructures XIV 2025

作者： Tang, Haoning Lou, Beicheng Du, Fan Gao, Guangqi Zhang, Mingjie Ni, Xueqi Yacoby, Amir Cao, Yuan Fan, Shanhui Mazur, Eric School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Applied Physics Ginzton Laboratory Stanford University StanfordCA94305 United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States

Our MEMS-based twistoptics device enables precise control of interlayer gaps and twist angles in photonic crystals, offering high-accuracy, multidimensional light manipulation. This finding holds potential for applica... 详细信息

ISBN: (纸本)9781510685048

关键词： Nanophotonics

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INTELLIGENT DATA-DRIVEN METHODS FOR ENHANCING DISTRIBUTED EXCITATION CONTROL IN electrical GRID

INTELLIGENT DATA-DRIVEN METHODS FOR ENHANCING DISTRIBUTED EX...

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2025 International Conference on Energy, Power, Environment, Control and Computing, ICEPECC 2025

作者： Qamar, Hafiz Ghulam Murtza Imran, Muhammad Ahmad, Fareed Riaz, Ayesha Ashraf, Adil Yousaf, Muhammad Zain Khan, Imran School of Electrical Engineering Yanshan University Qinhuangdao066004 China Department of Electrical Electronics and Computer Systems University of Sargodha Pakistan Center for Renewable Energy and Microgrids Huanjiang Laboratory Zhejiang University Zhejiang Zhuji311816 China

ISBN: (纸本)9781837243235

This paper proposes a decentralized excitation control method based on synchronized estimation using asynchronous measurements from voltage/current transformers (VT/CT), addressing the challenges of decentralized excitation control caused by asynchronous updates. Due to the high cost and limited use of Phasor Measurement Units (PMUs), synchronized generator output measurements are often not feasible. The proposed method establishes a framework for decentralized excitation control that aligns with synchronized estimation in multi-machine power systems. It develops an estimation model for synchronized acquisition of excitation control feedback inputs, even under asynchronous sampling conditions. Simulation results using IEEE standard test systems demonstrate that synchronized estimated values offer a more accurate representation of the system’s status compared to asynchronous measurements, with better compatibility with the network structure. The findings show that decentralized excitation control based on synchronized estimation significantly enhances power system stability compared to traditional control methods that rely on asynchronous feedback. © The Institution of engineering & Technology 2025.

关键词： Electric power system control

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An Efficient Scheme for Interference Mitigation in 6G-IoT Wireless Networks

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computers, Materials & Continua 2021年第12期69卷 3889-3902页

作者： Fahd N.Al-Wesabi Imran Khan Nadhem Nemri Mohammed A.Al-Hagery Huda G.Iskander Quang Ngoc Nguyen Babar Shah Ki-Il Kim Department of Computer Science King Khalid UniversityMuhayel AseerKSA Department of Electrical Engineering University of Engineering and TechnologyPeshawarPakistan Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Communications and Computer Engineering Faculty of Science and EngineeringWaseda UniversityShinjuku-kuTokyo169-0051Japan College of Technological Innovation Zayed UniversityAbu DhabiUAE Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Korea

The Internet of Things(IoT)is the fourth technological revolution in the global information industry after computers,the Internet,and mobile communication *** combines radio-frequency identification devices,infrared sensors,global positioning systems,and various other *** sensing equipment is connected via the Internet,thus forming a vast *** these physical devices are connected to the Internet,the user terminal can be extended and expanded to exchange information,communicate with anything,and carry out identification,positioning,tracking,monitoring,and triggering of corresponding events on each device in the *** real life,the IoT has a wide range of applications,covering many fields,such as smart homes,smart logistics,fine agriculture and animal husbandry,national defense,and *** of the most significant factors in wireless channels is interference,which degrades the system *** the existing QR decomposition-based signal detection method is an emerging topic because of its low complexity,it does not solve the problem of poor detection ***,this study proposes a maximumlikelihood-based QR decomposition *** main idea is to estimate the initial level of detection using the maximum likelihood principle,and then the other layer is detected using a reliable *** optimal candidate is selected from the feedback by deploying the candidate points in an unreliable *** results show that the proposed algorithm effectively reduces the interference and propagation error compared with the algorithms reported in the literature.

关键词： 6G networks internet of things resource allocation optimization

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Cross-Modality Image Transformation Using Generative Adversarial Network 24th

Cross-Modality Image Transformation Using Generative Adversa...

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24th Conference on Man-Machine-Environment System engineering, MMESE 2024

作者： Liu, Haoting Yu, Shiqi Hou, Qingwen Chen, Shuai Guo, Kuiyuan Wang, Xu Li, Qing Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China CATARC Technology Co. Ltd. Shenzhen518118 China

ISBN: (纸本)9789819771387

A cross-modality image transformation method using the Generative Adversarial Network (GAN) is proposed in this paper. First, the preprocessing methods are performed to the original image data. The computational steps include adjusting image size and suppressing image noises. Second, a kind of GAN is constructed. Both the generator network and discriminator network are created. Third, the GAN is trained and the back propagation optimization is performed continuously. Finally, the trained GAN can be used for data enhancement. To test the effects of computational steps above, the image transformation from the visible light image to other noise-contaminated image is performed. Lots of experiments have illustrated the correctness of our method. © Beijing KeCui Man-Machine-Environment System engineering Technology Research Academy 2024.

关键词： Generative adversarial networks

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A Compact 28 GHz Millimeter Wave Antenna for Future Wireless Communication

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computers, Materials & Continua 2022年第7期72卷 301-314页

作者： Shahid Khan Adil Bashir Haider Ali Abdul Rauf Mohamed Marey Hala Mostafa Ikram Syed LCOMS ASECUniversity de LorraineMetz57070France Department of Electrical and Computer Engineering Comsats University IslamabadAbbottabad Campus22060Pakistan Electrical Engineering Department Bahauddin Zakariya UniversityMultan60800Pakistan Department of Electronics Technology University of TechnologyNowshera24100Pakistan Department of Electrical Engineering National University of Sciences and TechnologyH-12Islamabad44000Pakistan Smart Systems Engineering Laboratory College of EngineeringPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Software Engineering Military College of SignalsNational University of Sciences and TechnologyIslamabad44000Pakistan

This article presents a novel modified chuck wagon dinner bell shaped millimeter wave(mm-wave)antenna at 28 *** proposed design has ultra-thin Rogers 5880 substrate with relative permittivity of *** design consists of T shaped resonating elements and two open ended side *** desired 28 GHz frequency response is achieved by careful parametric modeling of the proposed *** maximum achieved single element gain at the desired resonance frequency is 3.45 *** efficiency of the proposed design over the operating band is more than 88%.The impedance bandwidth achieved for−10 dB reference value is nearly 2.9 *** proposed antenna is transformed into four element linear array which increases the gain up to 10.5 *** fabricated prototype is tested for the measured *** is observed that measured results closely match the simulated *** considering its simple structure and focused radiation patterns,the proposed design is well suited for IoT(Internet of Things),mmWave microwave sensing,5G and future RF(Radio Frequency)frontends.

关键词： RF front-ends mmWave partial ground plane 28 GHz IoT 5G antenna

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Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

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computers, Materials & Continua 2022年第3期70卷 5133-5142页

作者： Ibrahim M.Mehedi Rachid Mansouri Ubaid M.Al-Saggaf Ahmed I.M.Iskanderani Maamar Bettayeb Abdulah Jeza Aljohani Thangam Palaniswamy Shaikh Abdul Latif Abdul Latif Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia L2CSP Laboratory Mouloud Mammeri UniversityTizi OuzouAlgeria Electrical&Computer Engineering Department University of SharjahUnited Arab Emirates Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics King Abdulaziz UniversityJeddah21589Saudi Arabia

A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this *** this control scheme,the performance against disturbances,uncertainties,and attenuation is *** active disturbance rejection control(LADRC)is mainly based on an extended state observer(ESO)technology.A fractional integral(FOI)action is combined with the LADRC technique which proposes a hybrid control scheme like *** this FOI action improves the robustness of the standard *** set-point tracking of the proposed FO-LADRC scheme is designed by Bode’s ideal transfer function(BITF)based robust closed-loop concept,an appropriate pole placement *** effectiveness of the proposed FO-LADRC scheme is illustrated through experimental results on the linear flexible joint system(LFJS).The results show the enhancement of the robustness with disturbance ***,a comparative analysis is presented with the results obtained using the integer-order LADRC and FO-LADRC scheme.

关键词： Active disturbance rejection fractional calculus ADRC pole placement linear flexible joint system robust control

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Predicting the friction angle of clays using a multi-layer perceptron neural network enhanced by yeo-johnson transformation and coral reefs optimization

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Journal of Rock Mechanics and Geotechnical engineering 2024年第10期16卷 3982-4003页

作者： Libing Yang Trung Nguyen-Thoi Trung-Tin Tran College of Civil Engineering and Architecture Hunan Institute of Science and TechnologyYueyang414006China Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityViet Nam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh CityViet Nam Department of Information Technology Greenwich VietnamFPT UniversityDa Nang550000Viet Nam

The accurate prediction of the friction angle of clays is crucial for assessing slope stability in engineering *** study addresses the importance of estimating the friction angle and presents the development of four soft computing models:YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and *** of all,the Yeo-Johnson(YJ)transformation technique was used to stabilize the variance of data and make it more suitable for parametric statistical models that assume normality and equal *** technique is expected to improve the accuracy of friction angle prediction *** friction angle prediction models then utilized multi-layer perceptron neural networks(MLPnet)and metaheuristic optimization algorithms to further enhance performance,including flower pollination algorithm(FPA),coral reefs optimization(CRO),ant colony optimization continuous(ACOC),and cuckoo search algorithm(CSA).The prediction models without the YJ technique,***-MLPnet,CRO-MLPnet,ACOC-MLPnet,and CSA-MLPnet,were then compared to those with the YJ technique,***-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and *** these,the YJ-CRO-MLPnet model demonstrated superior reliability,achieving an accuracy of up to 83%in predicting the friction angle of clay in practical engineering *** improvement is significant,as it represents an increase from 1.3%to approximately 20%compared to the models that did not utilize the YJ transformation technique.

关键词： Natural hazards Slope stability Friction angle Clay Soft computing models Geotechnical engineering

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An efficient data aggregation scheme with local differential privacy in smart grid

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Digital Communications and Networks 2022年第3期8卷 333-342页

作者： Na Gai Kaiping Xue Bin Zhu Jiayu Yang Jianqing Liu Debiao He School of Cyber Science and Technology University of Science and Technology of ChinaHefeiAnhui230027China Department of Electronic Engineering and Information Science University of Science and Technology of ChinaHefeiAnhui230027China Department of Electrical and Computer Engineering University of Alabama in HuntsvilleHuntsvilleAL35899USA Key Laboratory of Aerospace Information Security and Trusted Computing of Ministry of Education School of Cyber Science and EngineeringWuhan UniversityWuhanBeihu430072China

By integrating the traditional power grid with information and communication technology, smart grid achieves dependable, efficient, and flexible grid data processing. The smart meters deployed on the user side of the smart grid collect the users' power usage data on a regular basis and upload it to the control center to complete the smart grid data acquisition. The control center can evaluate the supply and demand of the power grid through aggregated data from users and then dynamically adjust the power supply and price, etc. However, since the grid data collected from users may disclose the user's electricity usage habits and daily activities, privacy concern has become a critical issue in smart grid data aggregation. Most of the existing privacy-preserving data collection schemes for smart grid adopt homomorphic encryption or randomization techniques which are either impractical because of the high computation overhead or unrealistic for requiring a trusted third party.

关键词： Local differential privacy Data aggregation Smart grid Privacy preserving

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Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration

Real-Time Data-Driven Maintenance Logistics: A Public-Privat...

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2024 Commit2Data, C2D 2024

作者： van Jaarsveld, Willem Bliek, Laurens de Weerdt, Mathijs Kapodistria, Stella Pronk, Verus Verleijsdonk, Peter Voorberg, Simon Akçay, Alp da Costa, Paulo Eshuis, Rik Kaymak, Uzay van Houtum, Geert-Jan Verwer, Sicco Zhang, Yingqian Department of Industrial Engineering and Innovation Sciences Eindhoven University of Technology Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Netherlands Department of Mathematics and Computer Science Eindhoven University of Technology Netherlands Philips Research Laboratories Eindhoven Netherlands Department of Information Systems Supply Chain Management and Decision Analysis NEOMA Business School Rouen France Etsy Inc. Dublin Ireland Jheronimus Academy of Data Science Eindhoven University of Technology Netherlands

ISBN: (纸本)9783959773515

The project "Real-time data-driven maintenance logistics" was initiated with the purpose of bringing innovations in data-driven decision making to maintenance logistics, by bringing problem owners in the form of three innovative companies together with researchers at two leading knowledge institutions. This paper reviews innovations in three related areas: How the innovations were inspired by practice, how they materialized, and how the results impact practice. © Willem van Jaarsveld, Alp Akçay, Laurens Bliek, Paulo da Costa, Mathijs de Weerdt, Rik Eshuis, Stella Kapodistria, Uzay Kaymak, Verus Pronk, Geert-Jan van Houtum, Peter Verleijsdonk, Sicco Verwer, Simon Voorberg, and Yingqian Zhang.

关键词： Scheduled maintenance

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Research on Deep Learning Model of Feature Extraction Based on Convolutional Neural Network 2

Research on Deep Learning Model of Feature Extraction Based ...

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2nd IEEE International Conference on Image Processing and computer Applications, ICIPCA 2024

作者： Liu, Houze Li, Iris Liang, Yaxin Sun, Dan Yang, Yining Yang, Haowei New York University Department Computer Science and Engineering New York United States Graduate School of Art & Science New York University New York United States Viterbi School of Engineering University of Southern California Los Angeles United States Washington University Department of Electrical and Systems Engineering St. Louis United States School of Computer Science Carnegie Mellon University Pittsburgh United States University of Houston Cullen College of Engineering Houston United States

ISBN: (纸本)9798350360240

Neural networks with relatively shallow layers and simple structures may have limited ability in accurately identifying pneumonia. In addition, deep neural networks also have a large demand for computing resources, which may cause convolutional neural networks to be unable to be implemented on terminals. Therefore, this paper will carry out the optimal classification of convolutional neural networks. Firstly, according to the characteristics of pneumonia images, AlexNet and InceptionV3 were selected to obtain better image recognition results. Combining the features of medical images, the forward neural network with deeper and more complex structure is learned. Finally, knowledge extraction technology is used to extract the obtained data into the AlexNet model to achieve the purpose of improving computing efficiency and reducing computing costs. The results showed that the prediction accuracy, specificity, and sensitivity of the trained AlexNet model increased by 4.25 percentage points, 7.85 percentage points, and 2.32 percentage points respectively. The graphics processing usage has decreased by 51% compared to the InceptionV3 mode. © 2024 IEEE.

关键词： Convolutional neural networks

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