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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Zhang, Yichi Zhao, Haoqi Wu, Tianwei Gao, Zihe Ge, Li Feng, Liang Department of Materials Science and Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Physics and Astronomy College of Staten Island CUNY Staten IslandNY10314 United States The Graduate Center CUNY New YorkNY10016 United States

ISBN: (纸本)9781957171395

High-dimensional quantum key distribution (HD-QKD) promises to enhance information capacity and noise-resilience. Here we report an integrated spin-orbit microlaser enabled HD-QKD through decoy-state BB84 protocol, demonstrating robust and compact real-time secret key generation strategy. CLEO 2024 © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Quantum cryptography

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Automated Diagnosis of Heart-Lung Diseases in Chest X-ray Images 5

Automated Diagnosis of Heart-Lung Diseases in Chest X-ray Im...

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5th International Conference on engineering Technology and its Applications, IICETA 2022

作者： Alslatie, Mohammad Alquran, Hiam Mustafa, Wan Azani Abu-Qasmieh, Isam Alqudah, Ali Mohammad Alkhayyat, Ahmed The Institute of Biomedical Technology King Hussein Medical Center Royal Jordanian Medical Service Amman Jordan Yarmouk University Biomedical Systems and Medical Informatics Engineering Irbid Jordan Arau Faculty of Electrical Engineering Technology Perlis Malaysia University of Manitoba Biomedical Engineering Program Department of Electrical and Computer Engineering Canada The Islamic University Faculty of Engineering Najaf Iraq

ISBN: (纸本)9781665472159

The state of the art of artificial intelligence (AI) for various medical imaging applications leads to enhanced accuracy, analysis, visualization, and interpretation of chest Xray (CXR) images for diagnosis. Many diseases are diagnosed based on CXR images. In this paper, two types of abnormalities are diagnosed based on AI techniques. The two classes are atelectasis and cardiomegaly. The acquired images are segmented to localize the chest region and then enhanced using gray-level transformation methods. The enhanced images are passed to two pretrained convolutional neural networks (CNNs): shuffle and mobile net. The transfer learning approach is utilized in this stage. The automated features are extracted from the last fully connected layer. Each CNN deserves to have the two most representative features for the two classes. These four features are passed to support the vector machine classifier. The training accuracy reached 100% and the test accuracy was 96.7%. The proposed method can be extended to be a milestone in the classification of all heart-lung diseases that can be diagnosed using chest X-ray images. © 2022 IEEE.

关键词： Convolutional neural networks

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Fully rubbery synaptic transistors made out of all-organic materials for elastic neurological electronic skin

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Nano Research 2022年第2期15卷 758-764页

作者： Hyunseok Shim Seonmin Jang Jae Gyu Jang Zhoulyu Rao Jong-ln Hong Kyoseung Sim Cunjiang Yu Materials Science and Engineering Program University of HoustonHoustonTX 77204 USA Department of Chemistry Seoul National UniversitySeoul 08826Republic of Korea Department of Chemistry Ulsan National Institute of Science and Technology(UNIST)Ulsan 44919Republic of Korea Department of Mechanical Engineering University of HoustonHoustonTX 77204 USA Department of Biomedical Engineering University of HoustonHoustonTX 77204USA Department of Electrical and Computer Engineering University of HoustonHoustonTX 77204 USA Texas Center for Superconductivity University of HoustonHoustonTX 77204USA

Neurologic function implemented soft organic electronic skin holds promise for wide range of applications,such as skin prosthetics,neurorobot,bioelectronics,human-robotic interaction(HRI),***,we report the development of a fully rubbery synaptic transistor which consists of all-organic materials,which shows unique synaptic characteristics existing in biological *** synaptic characteristics retained even under mechanical stretch by 30%.We further developed a neurological electronic skin in a fully rubbery format based on two mechanoreceptors(for synaptic potentiation or depression)of pressure-sensitive rubber and an all-organic synaptic *** converting tactile signals into Morse Code,potentiation and depression of excitatory postsynaptic current(EPSC)signals allow the neurological electronic skin on a human forearm to communicate with a robotic *** collective studies on the materials,devices,and their characteristics revealed the fundamental aspects and applicability of the all-organic synaptic transistor and the neurological electronic skin.

关键词： synaptic transistor stretchable electronic skin all-organic

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Worst-Case Integrity Attacks and Resilient State Estimation With Partially Secured Measurements

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IEEE Transactions on Control of Network systems 2025年

作者： Zhou, Jing Shang, Jun Chen, Tongwen University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Tongji University Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China

This paper examines the problem of optimal deception attacks against state estimation with partially secured measurements, where smart sensors transmit innovation sequences to the remote end for information fusion. Due to resource limitations or defensive countermeasures, the adversary can only modify data packets transmitted through unreliable channels. Meanwhile, the attack should be synthesized with sophistication to deceive an anomaly detector. To investigate the vulnerabilities of such estimation systems without feedback links and enhance security performance, the optimal attack policy is derived by formulating and explicitly solving a convex optimization problem, with the goal of maximizing the sum of estimation errors. Subsequently, a novel attack detection and resilient state estimation algorithm is proposed to ensure an acceptable level of estimation accuracy. The theoretical performance metrics, including false alarm rates for the proposed detector, are provided. Finally, the effectiveness of the results is confirmed through numerical examples. © 2014 IEEE.

关键词： Optimal detection

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PID-type Terminal Sliding Mode Control for Permanent Magnet Synchronous Generator-based Enhanced Wind Energy Conversion systems

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CSEE Journal of Power and Energy systems 2022年第4期8卷 993-1003页

作者： Mojtaba Nasiri Saleh Mobayen Ali Arzani the Solar Energy Applications Group Trinity College DublinDublin 2D02 PN40Ireland Department of Electrical Engineering University of ZanjanZanjanIran the Future Technology Research Center National Yunlin University of Science and TechnologyDouliuYunlin County 64002TaiwanChina the Center for Energy Systems Research(CESR) Tennessee Technological UniversityCookevilleTN 38505USA

The provision of wind farm(WF)grid codes(GCs)has become imperative for sustained grid operations,especially for WFs with permanent-magnet synchronous generator(PMSG)wind energy conversion *** techniques have been developed for executing GC requirements in the event of grid *** the methods,an intriguing strategy is to enhance the performance of back-to-back(BTB)converter *** this research,the PID-type terminal sliding mode control(PID-TSMC)scheme is implemented for both machine-side and grid-side converter-modified controllers of BTB-converter,to reinforce the nonlinear relationship among the state-variable and the control *** application of this control scheme decreases the response time and improves the robustness of the BTB-converter controllers regarding uncertainty of parameters and external *** grid-side converter tracks the maximum power point,contributing to the rapid decrease of generator active power output during *** frees up converter capacity for injecting GC-compliant reactive current into the ***,the machine-side converter regulates DC-link voltage,in which its variations during external disturbances decrease substantially with the *** discussions on the simulations contemplate on the robustness and efficiency of the implemented PID-TSMC strategy in comparison to other BTB-converter control strategies.

关键词： Back-to-back converter grid code PMSG-based wind turbine terminal sliding mode control

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Improved Metaheuristics with Machine Learning Enabled Medical Decision Support System

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Computers, Materials & Continua 2022年第11期73卷 2423-2439页

作者： Sara A.Althubiti JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Romany F.Mansour Fayadh Alenezi Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Research Center-CIENS Escuela Naval de Suboficiales A.R.C.“Barranquilla”BarranquillaColombia Electronics and Telecommunications Engineering Program Universidad Autónoma del CaribeBarranquilla080001Colombia Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080001Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga 72511Egypt Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia

Smart healthcare has become a hot research topic due to the contemporary developments of Internet of Things(IoT),sensor technologies,cloud computing,and ***,the latest advances of Artificial Intelligence(AI)tools find helpful for decision-making in innovative healthcare to diagnose several *** Cancer(OC)is a kind of cancer that affects women’s ovaries,and it is tedious to identify OC at the primary stages with a high mortality *** OC data produced by the Internet of Medical Things(IoMT)devices can be utilized to differentiate *** this aspect,this paper introduces a new quantum black widow optimization with a machine learningenabled decision support system(QBWO-MLDSS)for smart *** primary intention of the QBWO-MLDSS technique is to detect and categorize the OC rapidly and ***,the QBWO-MLDSS model involves a Z-score normalization approach to pre-process the *** addition,the QBWO-MLDSS technique derives a QBWO algorithm as a feature selection to derive optimum feature ***,symbiotic organisms search(SOS)with extreme learning machine(ELM)model is applied as a classifier for the detection and classification of ELM model,thereby improving the overall classification *** design of QBWO and SOS for OC detection and classification in the smart healthcare environment shows the study’s *** experimental result analysis of the QBWO-MLDSS model is conducted using a benchmark dataset,and the comparative results reported the enhanced outcomes of the QBWO-MLDSS model over the recent approaches.

关键词： Ovarian cancer decision support system smart healthcare IoMT deep learning feature selection

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In situ construction of PtSe_(2)/Ge Schottky junction array with interface passivation for broadband infrared photodetection and imaging

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InfoMat 2024年第4期6卷 37-46页

作者： Xue Li Shuo-En Wu Di Wu Tianxiang Zhao Pei Lin Zhifeng Shi Yongtao Tian Xinjian Li Longhui Zeng Xuechao Yu School of Physics and Microelectronics Key Laboratory of Material Physics Ministry of EducationZhengzhou UniversityZhengzhouHenanthe People's Republic of China Department of Electrical and Computer Engineering University of CaliforniaLa JollaCaliforniaUSA National Research Center for Optical Sensors/Communications Integrated Networks School of Electronic Science and EngineeringSoutheast UniversityNanjingJiangsuthe People's Republic of China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhouJiangsuthe People's Republic of China

Infrared(IR)detection is vital for various military and civilian *** research has highlighted the potential of two-dimensional(2D)topological semimetals in IR detection due to their distinctive advantages,including van der Waals(vdW)stacking,gapless electronic structure,and Van Hove singularities in the electronic density of ***,challenges such as large-scale patterning,poor photoresponsivity,and high dark current of photodetectors based on 2D topological semimetals significantly impede their wider applications in low-energy photon ***,we demonstrate the in situ fabrication of PtSe_(2)/Ge Schottky junction by directly depositing 2D PtSe_(2) films with a vertical layer structure on a Ge substrate with an ultrathin AlOx *** to high quality junction,the photodetector features a broadband response of up to 4.6μm,along with a high specific detectivity of�1012 Jones,and operates with remarkable stability in ambient conditions as ***,the highly integrated device arrays based on PtSe_(2)/AlOx/Ge Schottky junction showcases excellent Mid-IR(MIR)imaging capability at room *** findings highlight the promising prospects of 2D topological semimetals for uncooled IR photodetection and imaging applications.

关键词： broadband photodetection imaging platinum diselenide Schottky junction van der Waals integration

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An Optimal Framework for SDN Based on Deep Neural Network

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Computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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Explainable Application Intent for Zero-Touch Networking: An Incorporation of Hypergraph and Transformer

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IEEE Transactions on Communications 2025年

作者： Wu, Bing Zou, Sai Liwang, Minghui Ni, Wei Wang, Xianbin Guizhou University College of Big Data and Information Engineering China National Key Laboratory of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering China Tongji University Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China Data61 CSIRO Australia Department of Electrical and Computer Engineering Western University Canada

The autonomous interpretation of application intent (APPI) represents the primary step towards achieving closed-loop autonomy in zero-touch networking (ZTN) and also a prerequisite for intent-based networking (IBN). However, understanding APPIs and invoking the corresponding network resources require network professionals with extensive technical expertise to customize network service requests (NSRs), which presents significant challenges for the large-scale deployment of ZTN. This paper investigates an interesting problem of autonomous interpretation of APPIs for ZTN, where a novel mechanism integrating hypergraph and transformer with completeness assurance (HyperTrans-CA) is proposed. In particular, we first involve the Bayesian theory to model APPIs interpretability as maximizing the correct transition probability, where hypergraph is used to describe the complex relationship between application characteristics (e.g., scenario function, and performance) and NSRs, including network devices, virtual network functions (VNFs), and resources. Then, the hypergraph is integrated into the encoder, decoder, and attention mechanisms of Transformer, and a completeness assurance mechanism is designed to improve the prediction accuracy. The convergence of HyperTrans-CA and the corresponding convergence speed of the hypergraph-boosted Transformer in the graph search process are also analyzed. Comprehensive simulations and empirical measurements regarding industrial internet demonstrate that HyperTrans-CA can effectively explain/understand APPIs. Compared to the state-of-the-art Transformer and ChatGPT3.5 models, HyperTrans-CA improves the prediction accuracy of APPIs mapped to VNFs by 23% and 46%, respectively, while raising the prediction accuracy of VNF locations by 8.6 and 17.3 times. © 2025 IEEE.

关键词： Bayesian networks

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A Numerical Method to Analyze Electromagnetic Fields on Semiconductor Nanostructures

A Numerical Method to Analyze Electromagnetic Fields on Semi...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2022

作者： Uulu, Doolos Aibek Chen, Rui Chen, Liang Li, Ping Bagci, Hakan Computer Electrical and Mathematical Science and Engineering Division Electrical and Computer Engineering Program Thuwal23955-6900 Saudi Arabia Shanghai Jiao Tong University Key Lab. of Min. of Educ. of Des. and Electromagnetic Compatibility of High-Speed Electronic Systems Shanghai200240 China

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

A coupled system of volume integral and two-fluid hydrodynamic equations is solved to analyze electromagnetic field interactions with non-local dispersion effects on semiconductor nanostructures. This coupled system, where the hydrodynamic currents and the electric flux are the unknowns, is discretized using Schaubert-Wilton-Glisson basis functions. Numerical results obtained using this solver show the presence of so-called acoustic modes at the frequencies lower than the resonance frequency of localized surface plasmon (LSP) mode. These modes cannot be identified if a Drude-like model or the single-fluid hydrodynamic equation is used to represent the electrical properties of the semiconductors. © 2022 IEEE.

关键词： Electromagnetic fields

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