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2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

作者： Da Costa Rocha, Jesse De Souza, Marcela Alves Cardoso, Evelin Helena Silva Vijaykumar, Nandamudi De Araujo, Jasmine Priscyla Leite Frances, Renato Lisboa Graduate Program in Electrical Engineering Belém Para Brazil Information and Communication Technology Center Marabá Para Brazil Department of Computer Science Capitão Poço Para Brazil Coordination of Applied Research and Technological Development São Paulo Brazil

ISBN: (纸本)9798350302523

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics. © 2023 IEEE.

关键词： Students

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Strong nonlinear optical processes with extraordinary polarization anisotropy in inversionsymmetry broken two-dimensional PdPSe

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Light(science & Applications) 2024年第8期13卷 1524-1533页

作者： Song Zhu Ruihuan Duan Xiaodong Xu Fangyuan Sun Wenduo Chen Fakun Wang Siyuan Li Ming Ye Xin Zhou Jinluo Cheng Yao Wu Houkun Liang Junichiro Kono Xingji Li Zheng Liu Qi Jie Wang School of Electrical and Electronic Engineering Nanyang Technological University639798 SingaporeSingapore School of Material Science and Engineering Nanyang Technological University639798 SingaporeSingapore CINTRA CNRS/NTU/THALES UMI 3288Research Techno PlazaNanyang Technological University637371 SingaporeSingapore School of Materials Science and Engineering Harbin Institute of Technology150001 HarbinChina Department of Chemistry National University of Singapore117543 SingaporeSingapore GPL Photonics Lab State Key Laboratory of Applied OpticsChangchun Institute of OpticsFine Mechanics and PhysicsChinese Academy of Sciences130033 ChangchunChina School of Electronics and Information Engineering Sichuan University610064 ChengduSichuanChina School of Physical and Mathematical Sciences Nanyang Technological University637371 SingaporeSingapore Departments of Electrical and Computer Engineering Physics and Astronomyand Materials Science and NanoEngineeringRice UniversityHoustonTXUSA

Nonlinear optical activities,especially second harmonic generation(SHG),are key phenomena in inversion-symmetrybroken two-dimensional(2D)transition metal dichalcogenides(TMDCs).On the other hand,anisotropic nonlinear optical processes are important for unique applications in nano-nonlinear photonic devices with polarization functions,having become one of focused research topics in the field of nonlinear ***,the strong nonlinearity and strong optical anisotropy do not exist simultaneously in common 2D ***,we demonstrate strong secondorder and third-order susceptibilities of 64 pm/V and 6.2×10^(-19)m^(2)/V^(2),respectively,in the even-layer PdPSe,which has not been discovered in other common TMDCs(e.g.,MoS2).Strikingly,it also simultaneously exhibited strong SHG anisotropy with an anisotropic ratio of~45,which is the largest reported among all 2D materials to date,to the best of our *** addition,the SHG anisotropy ratio can be harnessed from 0.12 to 45(375 times)by varying the excitation wavelength due to the dispersion ofχ^(2)*** an illustrative example,we further demonstrate polarized SHG imaging for potential applications in crystal orientation identification and polarization-dependent spatial *** findings in 2D PdPSe are promising for nonlinear nanophotonic and optoelectronic applications.

关键词： materials anisotropy nonlinear

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Improving DL-Learner on a Malware Detection Use Case 36

Improving DL-Learner on a Malware Detection Use Case

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36th International Workshop on Description Logics, DL 2023

作者： Bisták, Tomáš Švec, Peter Kluka, Ján Šimko, Alexander Balogh, Štefan Homola, Martin Department of Applied Informatics Faculty of Mathematics Physics and Informatics Comenius University Mlynská dolina Bratislava842 48 Slovakia Institute of Computer Science and Mathematics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Ilkovicova 3 Bratislava812 19 Slovakia

Automation of malware characterization has become increasingly important for early malware detection over the past decades. Since it is crucial to be able to perform malware detection transparently, explainable machine-learning methods may be considered particularly suitable for this application. In our previous work, we thus employed algorithms for learning description-logics concept expressions to obtain structured characterizations of malicious software. The results of our initial experiments, however, lead us to several inconsistencies in the behaviour of the studied algorithms included in DL-Learner, a widely adopted framework for concept learning. Hence, in this work, we make a couple of corrections to DL-Learner, along with a few further enhancements, and repeat the experiments to empirically assess the effects of our changes. The outcomes show that the modified algorithms can mark an improvement in terms of the predictability of their behaviour as well as evaluation metrics. © 2023 CEUR-WS. All rights reserved.

关键词： Malware

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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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Two-Dimensional Magnetic Exciton Polariton with Strongly Coupled Atomic and Photonic Anisotropies

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Physical Review Letters 2024年第26期133卷 266901-266901页

作者： Qiuyang Li Xin Xie Adam Alfrey Christiano W. Beach Nicholas McLellan Yang Lu Jiaqi Hu Wenhao Liu Nikhil Dhale Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Applied Physics Program University of Michigan Ann Arbor Michigan 48109 USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor Michigan 48109 USA Department of Physics The University of Texas at Dallas Richardson Texas 75080 USA

Anisotropy is a fundamental property of both material and photonic systems. The interplay between material and photonic anisotropies, however, has hardly been explored due to the vastly different length scales. Here we demonstrate exciton polaritons in a 2D antiferromagnet, CrSBr, coupled with an anisotropic photonic crystal cavity, where the spin, atomic, and photonic anisotropies are strongly correlated. Atomic anisotropy led to exceptionally strong coupling between anisotropic exciton and optical modes, which are stable against excitation densities a few orders of magnitude higher than polaritons in isotropic materials. The resulting polaritons feature anisotropic polarizations determined by the interplay of not only the anisotropies but also the dissipations and coupling of both exciton and photon modes, tunable by tens of degrees via many parameters. The work provides insights of excitons in CrSBr and demonstrates a prototype where atomic- and photonic-scale orders strongly couple, giving rise to unconventional properties in quantum materials and photonic devices.

关键词： Atoms

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On the Characterization of Quantum Flip Stars with Quantum Network Tomography

arXiv

引用

arXiv 2023年

作者： de Andrade, Matheus Guedes Navas, Jake Montaño, Inès Towsley, Don Manning College of Information and Computer Science University of Massachusetts Amherst United States Department of Applied Physics and Materials Science Northern Arizona University United States

The experimental realization of quantum information systems will be difficult due to how sensitive quantum information is to noise. Overcoming this sensitivity is central to designing quantum networks capable of transmitting quantum information reliably over large distances. Moreover, the ability to characterize communication noise in quantum networks is crucial in developing network protocols capable of overcoming the effects of noise in quantum networks. In this context, quantum network tomography refers to the characterization of channel noise in a quantum network through end-to-end measurements. In this work, we propose network tomography protocols for quantum star networks formed by quantum channels characterized by a single, non-trivial Pauli operator. Our results further the end-to-end characterization of quantum bit-flip star networks by introducing tomography protocols where state distribution and measurements are designed separately. We build upon previously proposed quantum network tomography protocols, as well as provide novel methods for the unique characterization of bit-flip probabilities in stars. We introduce a theoretical benchmark based on the Quantum Fisher information matrix to compare the efficiency of quantum network protocols. We apply our techniques to the protocols proposed, and provide an initial analysis on the potential benefits of entanglement for Quantum Network Tomography. Furthermore, we simulate the proposed protocols using NetSquid to assess the convergence properties of the estimators obtained for particular parameter regimes. Our findings show that the efficiency of protocols depend on parameter values and motivate the search for adaptive quantum network tomography protocols. Copyright © 2023, The Authors. All rights reserved.

关键词： Efficiency

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Amplified Cooling of Light via Emergent Onsager Irreversible Thermodynamics

Amplified Cooling of Light via Emergent Onsager Irreversible...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Xiong, Zhongfei Wu, Fan O. Liu, Yang Jiang, Jian-Hua Christodoulides, Demetrios N. Chen, Yuntian School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Ming Hsieh Department of Electrical and Computer School of Physical Science and Technology Soochow University Suzhou215006 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China Department of Electrical Engineering University of Southern California Los AngelesCA90089 United States Wuhan National Laboratory of Optoelectronics Huazhong University of Science and Technology Wuhan430074 China

While conventional cooling schemes solely depend on temperature differences, here we demonstrate that in photonics configurations, amplified cooling can be achieved by judiciously manipulating Onsager coefficients thr... 详细信息

ISBN: (纸本)9781957171395

关键词： Photonics

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GRB 220408B:A Three-episode Burst from a Precessing Jet

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Research in Astronomy and Astrophysics 2023年第11期23卷 214-224页

作者： Zijian Zhang Yi-Han Iris Yin Chenyu Wang Xiangyu Ivy Wang Jun Yang Yan-Zhi Meng Zi-Ke Liu Guo-Yin Chen Xiaoping Fu Huaizhong Gao Sihao Li Yihui Liu Xiangyun Long Yong-Chang Ma Xiaofan Pan Yuanze Sun Wei Wu Zirui Yang Zhizhen Ye Xiaoyu Yu Shuheng Zhao Xutao Zheng Tao Zhou Qing-Wen Tang Qiurong Yan Rong Zhou Zhonghai Wang Hua Feng Ming Zeng Bin-Bin Zhang School of Astronomy and Space Science Nanjing UniversityNanjing 210093China School of Physics Nanjing UniversityNanjing 210093China Department of Astronomy Tsinghua UniversityBeijing 100084China Key Laboratory of Modern Astronomy and Astrophysics Nanjing UniversityMinistry of EducationNanjing 210093China School of Information Engineering Nanchang UniversityNanchang 330031China Department of Engineering Physics Tsinghua UniversityBeijing 100084China Department of Health Physics China Institute for Radiation ProtectionTaiyuan 300000China Key Laboratory of Radiation Physics and Technology of Ministry of Education College of Physics of Sichuan UniversityChengdu 610065China School of Artificial Intelligence Nanjing UniversityNanjing 210093China Key Laboratory of Particle and Radiation Imaging Tsinghua UniversityMinistry of EducationBeijing 100084China Department of Computer Science and Technology Nanjing UniversityNanjing 210093China School of Chemistry and Chemical Engineering Nanjing UniversityNanjing 210093China College of Engineering and Applied Sciences Nanjing UniversityNanjing 210093China Department of Physics School of Physics and Materials ScienceNanchang UniversityNanchang 330031China Purple Mountain Observatory Chinese Academy of SciencesNanjing 210023China

Jet precession has previously been proposed to explain the apparently repeating features in the light curves of a few gamma-ray bursts(GRBs).In this paper,we further apply the precession model to a bright GRB 220408B by examining both its temporal and spectral consistency with the predictions of the *** one of the recently confirmed GRBs observed by our GRID CubeSat mission,GRB 220408B is noteworthy as it exhibits three apparently similar emission ***,the similarities are reinforced by their strong temporal correlations and similar features in terms of spectral evolution and spectral *** analysis demonstrates that these features can be well explained by the modulated emission of a Fast-Rise-Exponential-Decay(FRED)shape light curve intrinsically produced by a precessing jet with a precession period of 18.4_(-0.2)~(+0.2)s,a nutation period of11.1_(-0.2)~(+0.2)s and viewed *** study provides a straightforward explanation for the complex yet similar multiepisode GRB light curves.

关键词： gamma-rays:general (stars:)gamma-ray burst:individual(GRB 220408B) stars:jets

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High-resolution and High-Contrast Imaging of Defects in a Crystal

High-resolution and High-Contrast Imaging of Defects in a Cr...

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CLEO: science and Innovations, S and I 2022

作者： Moon, Jong Sung Lee, Haneul Lee, Jin Hee Jeon, Woong Bae Lee, Dowon Lee, Junghyun Paik, Seoyoung Han, Sang-Wook Reuter, Rolf Denisenko, Andrej Wrachtrup, Jörg Lee, Sang-Yun Kim, Je-Hyung Center for Quantum Information Korea Institute of Science and Technology Seoul02792 Korea Republic of Department of Electrical and Computer Engineering Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States University of Stuttgart Stuttgart70569 Germany Department of Physics and Photon Science Gwangju Institute of Science and Technology Gwangju61005 Korea Republic of

ISBN: (纸本)9781557528209

Optically active color centers in crystals provide important building blocks for quantum applications. However, conventional confocal fluorescence microscopy of high-refractive-index crystals suffers from limited photon collection efficiency and spatial resolution. Here, we demonstrate high-resolution, high-contrast imaging of defects in diamonds using microsphere-assisted confocal microscopy. A microsphere provides an excellent optical interface for point defects with a magnified virtual image that increases the spatial resolution up to λ/5, as well as the optical signal-to-noise ratio by four times. © Optica Publishing Group 2022, © 2022 The Author(s)

关键词： Microspheres

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Detection and Recognition of Vehicle Components Using Image Processing and Deep Learning Techniques 4

Detection and Recognition of Vehicle Components Using Image ...

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4th Research, Invention, and Innovation Congress: Innovative Electricals and Electronics, RI2C 2023

作者： Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Boonthai, Phumraphi Chumuang, Narumol Department of Information Technology Management King Mongkut's University of Technology North Bangkok Bangkok Thailand Applied Computer Science Program King Mongkut’s University of Technology Thonburi Bangkok Thailand Media Technology Program King Mongkut’s University of Technology Thonburi Bangkok Thailand Department Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand

ISBN: (纸本)9798350330618

This research study presents an algorithmic approach for the detection and identification of key components on license plates, including numerical digits, province codes, vehicle colors, and vehicle makes and types. The methodology integrates image processing techniques and deep learning methodologies to achieve comprehensive image analysis. The algorithm incorporates image preprocessing techniques to optimize the input images, followed by a deep neural network trained on a large annotated dataset. The algorithm utilizes image segmentation and character recognition techniques to detect and classify numerical digits on license plates. Similarly, it employs segmentation and classification processes for identifying province codes, vehicle colors, makes, and types. Extensive training ensures the algorithm's accuracy and robustness under varying conditions. The proposed algorithm demonstrates the potential for accurate license plate component detection and identification, with applications in law enforcement and traffic monitoring systems. . ©2023 IEEE.

关键词： License plates (automobile)

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