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Effect of individual atmospheric parameters on beam spreading of higher-order Gaussian beam

optical and Quantum Electronics 2024年第12期56卷 1-18页

作者： kumar, Mukesh Khandelwal, Arpit Azeemuddin, Syed Center for VLSI and Embedded System Technologies International Institute of Information Technology Hyderabad India Department of Electrical Engineering Indian Institute of Technology Jodhpur India Department of Electrical and Computer Engineering Behrend College Penn State University EriePA United States

The beam spreading is essential for evaluating the higher-order Gaussian beam when it propagates through atmospheric turbulence. In this paper, we investigate the impact of individual atmospheric parameters such as jitter, turbulence, wind speed, and thermal blooming on beam spreading of Hermite Gaussian (HG), and Laguerre Gaussian (LG) beams. We also examine spot size variations due to beam quality on various HG and LG modes. It is seen that the impact of spreading caused by beam quality and turbulence is higher than that of jitter, wind speed, and thermal blooming. As the mode order increases, the effect of turbulence strength increases, leading to more spread for HG and LG beams. Spreading due to diffraction and beam quality on higher mode LG beam is higher than the HG beam in different modes. Beam spreading due to thermal blooming for the lower mode is higher compared to the higher mode for LG and HG beams. The sensitivity of higher mode LG beams to turbulence distortions is greater than HG beams as they experience more significant fractional increases in their spot size due to turbulence. The combined beam spread for the Laguerre Gaussian beam is larger than the Hermite Gaussian beam. This paper aims to understand better individual beam spreading in the atmosphere and its impact on the overall performance of higher-order laser propagation to develop optimized laser systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Gaussian beams

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Investigation of operation and degradation mechanisms in ZnTeSe blue quantum-dot light-emitting diodes by identifying recombination zone

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Nano Research 2024年第7期17卷 6527-6533页

作者： Oul Cho Sujin Park Hogeun Chang Jiwhan Kim Jaekwon Kim Sungwoo Kim Taehyung Kim Jeonghun Kwak Department of Electrical and Computer Engineering Inter-university Semiconductor Research Centerand Soft Foundry InstituteSeoul National UniversitySeoul 08826Republic of Korea Material Research Center Samsung Advanced Institute of TechnologySuwonGyeonggi-do 16419Republic of Korea

ZnTeSe quantum dots(QDs),recognized as promising eco-friendly blue electroluminescent emitters,remain under-explored in light-emitting diode(LED)***,to elucidate the operation and degradation mechanisms of ZnTeSe blue QD-LEDs,stacked ZnTeSe QD layers with discernable luminescence are designed by varying Te doping concentrations,and the recombination zones(RZs)of the blue QD-LEDs are *** RZs are identified near the hole-transport layer(HTL),confirmed by angular-dependent electroluminescence measurements and optical *** addition,in order to investigate carrier dynamics in the process of recombination,the transient electroluminescence(tr-EL)signals of the dichromatic QD-LEDs are *** a result,it is inferred that the RZ initially formed near the electron-transport layer(ETL)due to the high injection barriers of ***,due to the fast electron mobility,the RZ shifts toward the HTL as the operating current *** the device lifetime tests,the RZ remains stationary while the photoluminescence(PL)corresponding to the RZ undergoes a substantial decrease,indicating that the degradation is accelerated by the concentrated *** this study contributes to a deeper understanding of the operational mechanisms of ZnTeSe blue QD-LEDs.

关键词： quantum dots light-emitting diodes degradation recombination zones carrier dynamics

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Generalized hybrid LiFi-WiFi UniPHY learning framework towards intelligent UAV-based indoor networks

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International Journal of Intelligent Networks 2024年第1期5卷 255-266页

作者： Ahmad, Rizwana Anwar, Dil Nashin Bany Salameh, Haythem Elgala, Hany Ayyash, Moussa Almajali, Sufyan El-Khazali, Reyad Electronic and Electrical Engineering Department University of Cambridge United Kingdom Electrical and Computer Engineering Department University at Albany-State University of New York United States Artificial Intelligence Research Center Al Ain University Al Ain United Arab Emirates Telecommunications Engineering Department Yarmouk University Irbid Jordan Department of Computing Information and Technology Chicago State University ChicagoIL United States Department of Computer Science Princess Sumaya University for Technology Amman Jordan Electrical Engineering and Computer Science Department Khalifa University Abu Dhabi United Arab Emirates

Advancements in unmanned aerial vehicle (UAV) technology, along with indoor hybrid LiFi-WiFi networks (HLWN), promise the development of cost-effective, energy-efficient, adaptable, reliable, rapid, and on-demand HLWN-capable indoor flying networks (IFNs). To achieve this, a unified physical layer (UniPHY) capable of simultaneous control communication, data transfer, and sensing is crucial. However, traditional block-based decoders, designed independently for LiFi and WiFi, perform poorly in complex and hybrid LiFi-WiFi-enabled UniPHY systems. In this study, we propose an end-to-end learning framework based on convolutional neural networks (CNNs) for UniPHY, which can be trained to serve hybrid LiFi-WiFi transmissions to improve error performance and simplify UAV hardware. In this work, the performance of the proposed framework is assessed and compared with that of the conventional independent block-based communication system. Furthermore, a comprehensive summary of optimal hyper-parameters for efficient training of our learning framework has been provided. It is shown that, with optimal hyper-parameters, the proposed CNN-based framework outperforms the conventional block-based approach by providing a signal-to-noise ratio gain of approximately 7 dB for the LiFi channel and 23 dB for the WiFi channel. In addition, we evaluate the complexity and training convergence for loss and accuracy. © 2024 The Authors

关键词： Data transfer

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Fast and Accurate Interrogation of Vernier Effect-based optical Fiber Sensors Enabled by Machine Learning

Fast and Accurate Interrogation of Vernier Effect-based Opti...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Zhu, Chen Huang, Jie Research Center for Optical Fiber Sensing Zhejiang Laboratory Hangzhou311100 China Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

The possibility of employing a light source with a small wavelength bandwidth (35 nm) and a coarsely resolved spectrometer (~166 pm) for the interrogation of a Vernier effect-based high-sensitivity optical fiber senso... 详细信息

ISBN: (纸本)9781957171395

关键词： optical fibers

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Perfomance comparison of Machine Learning (ML) based fault detection scheme for a compensated transmission line

Perfomance comparison of Machine Learning (ML) based fault d...

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2024 IEEE PES/IAS PowerAfrica, PowerAfrica 2024

作者： Mazibuko, N. Akindeji, K.T. Moloi, K. University of Technology Smartgrid Research Center Durban Department of Electrical Power Engineering Department of Electronics and Computer Engineering Durban South Africa

ISBN: (纸本)9798350389388

Compensated transmission lines are employed in power system networks to increase energy transmission capacity, improve system stability, decrease transmission losses, and provide more flexibility in power management. However, the effectiveness of protection relays in detecting, classifying, and locating faults in such networks is significantly impacted. This is due to changes in impedance within the fault loop caused by devices used in compensated networks, which alters the apparent impedance seen by the relay. This study introduces three different fault detection and classification schemes for compensated transmission lines. Initially, an IEEE 9-bus system with series compensation at line 4-6 is utilized for data collection. Feature extraction using Principal Component Analysis (PCA) is then conducted, followed by the implementation of fine k-nearest neighbors (KNN), Medium Nuero network (MNN), and SQVM classifiers. A comprehensive performance analysis is carried out, revealing that SQVM achieves the highest overall accuracy of 99.3%, while the fine tree outperforms SQVM in single-line fault detection. © 2024 IEEE.

关键词： Power transmission lines

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Fast and Accurate Interrogation of Vernier Effect-based optical Fiber Sensors Enabled by Machine Learning

Fast and Accurate Interrogation of Vernier Effect-based Opti...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Spectrometers

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SEOE:an option graph based semantically embedding method for prenatal depression detection

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Frontiers of computer Science 2024年第6期18卷 245-258页

作者： Xiaosong HAN Mengchen CAO Dong XU Xiaoyue FENG Yanchun LIANG Xiaoduo LANG Renchu GUAN College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun 130012China Department of Electrical Engineering and Computer Science and Christopher S.Bond Life Sciences Center University of MissouriColumbiaMO 65211USA Department of Computer Science and Technology Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationZhuhai College of Science and TechnologyZhuhai 519041China Jilin Provincial Institute of Population Science and Technology Changchun 130000China

Prenatal depression,which can affect pregnant women’s physical and psychological health and cause postpartum depression,is increasing ***,it is essential to detect prenatal depression early and conduct an attribution *** studies have used questionnaires to screen for prenatal depression,but the existing methods lack *** diagnose the early signs of prenatal depression and identify the key factors that may lead to prenatal depression from questionnaires,we present the semantically enhanced option embedding(SEOE)model to represent questionnaire *** can quantitatively determine the relationship and patterns between options and *** first quantifies options and resorts them,gathering options with little difference,since Word2Vec is highly dependent on *** resort task is transformed into an optimization problem involving the traveling salesman ***,all questionnaire samples are used to train the options’vector using ***,an LSTM and GRU fused model incorporating the cycle learning rate is constructed to detect whether a pregnant woman is suffering from *** verify the model,we compare it with other deep learning and traditional machine learning *** experiment results show that our proposed model can accurately identify pregnant women with depression and reach an F1 score of *** most relevant factors of depression found by SEOE are also verified in the *** addition,our model is of low computational complexity and strong generalization,which can be widely applied to other questionnaire analyses of psychiatric disorders.

关键词： questionnaire analyses text classification graph representation learning traveling salesman problem prenatal depression

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24.9-GHz-bandwidth VCSEL enables 170-Gbit/s OFDM, GFDM, and DMT transmissions

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Photonics Research 2024年第2期12卷 377-390页

作者： Wu, Wei-Li Cheng, Chih-Hsien Matsumoto, Atsushi Akahane, Kouichi Yang, Yun-Cheng Su, Borching Wu, Chao-Hsin Feng, Milton Lin, Gong-Ru Graduate Institute of Photonics and Optoelectronics Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan Optical Access Technology Laboratory Photonic ICT Research Center Network Research Institute National Institute of Information and Communications Technology Koganei184-8795 Japan Graduate Institute of Electrical Engineering Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan Graduate Institute of Communication Engineering Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan Department of Electrical and Computer Engineering Microelectronics and Nanotechnology Laboratory University of Illinois at Urbana–Champaign ChampaignIL61801 United States NTU-Tektronix Joint Research Center National Taiwan University Tektronix Inc. Taipei10617 Taiwan

The direct modulation and fiber transmission performances of a bi-layer-oxide-confined 850-nm vertical cavity surface emitting laser (VCSEL) containing an emission aperture size of 3.5 μm with versatile novel complex data formats are compared. With delivering quadrature amplitude modulation-orthogonal frequency-division multiplexing (QAM-OFDM), generalized frequency-division multiplexing (GFDM), and discrete multi-tone (DMT) data streams, the highest data rate allowable for encoding the 3.5-μm-aperture VCSEL is demonstrated under back-to-back (BtB) and 100-m OM5-multi-mode fiber (OM5-MMF) transmissions. The newly designed 3.5-μm-aperture VCSEL contains InGaAs/AlGaAs multiple quantum wells and bi-layer-oxide-confined aperture to enhance its differential gain, reduce its thermal resistance, and improve its parasitic resistance for providing broader encoding bandwidth. Optimizing the VCSEL bias at 9 mA (11Ith) makes the lasing with three to four transverse modes suffer from a low modal dispersion effect, which also provides its 3-dB bandwidth as wide as 24.9 GHz and suppresses its RIN level to −138.0 dBc∕Hz for broadband OFDM/GFDM/DMT data encoding. By using the pre-distortion technique on the OFDM to compensate the SNR degradation, the OFDM modified with a pre-leveling slope of 0.5 dB/GHz can provide 160 Gbit/s for BtB and 140 Gbit/s for 100-m OM5-MMF transmissions. By dividing the N OFDM subcarriers into K equally-sized GFDM subcarriers and M equally-sized GFDM subsymbols, the QAM-GFDM with K = 2 can effectively enhance the out-of-band suppression to 35.9 dB and reduce the peak-to-average-power ratio to 9.7 dB, which can support 168 Gbit/s under BtB and 144 Gbit/s in 100-m OM5-MMF transmissions. To achieve the maximal spectral-usage efficiency, the DMT with the adaptive bit-loading algorithm is employed to improve the data rate up to 172 Gbit/s for BtB and 146 Gbit/s for 100-m OM5-MMF conditions. These advanced pre-leveled 16-QAM OFDM, GFDM, and DMT formats carried b

关键词： Surface emitting lasers

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AQROM:A quality of service aware routing optimization mechanism based on asynchronous advantage actor-critic in software-defined networks

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Digital Communications and Networks 2024年第5期10卷 1405-1414页

作者： Wei Zhou Xing Jiang Qingsong Luo Bingli Guo Xiang Sun Fengyuan Sun Lingyu Meng School of Information and Communication Guilin University of Electronic TechnologyGuilin541004China The 34th Research Institute of China Electronics Technology Group Corporation Guilin541004China Guangxi Key Laboratory of Optical Network and Optical Information Security Guilin541004China State Key Laboratory of Information Photonics and Optical Communications BeijingUniversity of Posts and TelecommunicationsBeijing100876China Department of Electrical and Computer Engineering University of New MexicoAlbuquerqueNM87131USA

In Software-Defined Networks(SDNs),determining how to efficiently achieve Quality of Service(QoS)-aware routing is challenging but critical for significantly improving the performance of a network,where the metrics of QoS can be defined as,for example,average latency,packet loss ratio,and *** SDN controller can use network statistics and a Deep Reinforcement Learning(DRL)method to resolve this *** this paper,we formulate dynamic routing in an SDN as a Markov decision process and propose a DRL algorithm called the Asynchronous Advantage Actor-Critic QoS-aware Routing Optimization Mechanism(AQROM)to determine routing strategies that balance the traffic loads in the *** can improve the QoS of the network and reduce the training time via dynamic routing strategy updates;that is,the reward function can be dynamically and promptly altered based on the optimization objective regardless of the network topology and traffic *** can be considered as one-step optimization and a black-box routing mechanism in high-dimensional input and output sets for both discrete and continuous states,and actions with respect to the operations in the *** simulations were conducted using OMNeT++and the results demonstrated that AQROM 1)achieved much faster and stable convergence than the Deep Deterministic Policy Gradient(DDPG)and Advantage Actor-Critic(A2C),2)incurred a lower packet loss ratio and latency than Open Shortest Path First(OSPF),DDPG,and A2C,and 3)resulted in higher and more stable throughput than OSPF,DDPG,and A2C.

关键词： Software-defined networks Asynchronous advantage actor-critic QoS-aware routing optimization mechanism

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Robust graph‐based localization for industrial Internet of things in the presence of flipping ambiguities

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1140-1149页

作者： Mian Imtiaz ul Haq Ruhul Amin Khalil Muhannad Almutiry Ahmad Sawalmeh Tanveer Ahmad Nasir Saeed Faculty of Electrical Engineering Swedish College of Engineering and TechnologyWah CanttPakistan Department of Electrical Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawarPakistan Department of Electrical Engineering Remote Sensing UnitNorthern Border UniversityArarSaudi Arabia Data Science and Artificial Intelligence Department‐College of Science and Information Technology Irbid National UniversityIrbadJordan Innovation Education and Research Center for On‐Device AI Software(Bk21) Department of Computer Science and EngineeringChungnam National UniversityDaejeonRepublic of Korea Department of Electrical and Communication Engineering United Arab Emirates University(UAEU)Al AinUnited Arab Emirates

Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various ***,a novel localisation algorithm is proposed for noisy range measurements in IIoT *** position of an unknown machine device in the network is estimated using the relative distances between blind machines(BMs)and anchor machines(AMs).Moreover,a more practical and challenging scenario with the erroneous position of AM is considered,which brings additional uncertainty to the final position ***,the AMs selection algorithm for the localisation of BMs in the IIoT network is *** those AMs will participate in the localisation process,which increases the accuracy of the final location ***,the closed‐form expression of the proposed greedy successive anchorization process is derived,which prevents possible local convergence,reduces computation,and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement *** results are compared with the state‐of‐the‐art and verified through numerous simulations.

关键词： Cramér‐Rao lower bound greedy successive anchorization industrial internet of things localization

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