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Spectral period doubling and encoding of dissipative optical solitons via gain control

PhotoniX 2024年第1期5卷 290-305页

作者： Kangwen Yang Yi Zhou Yuqing Ling Kevin K.Tsia Heping Zeng Kenneth K.Y.Wong Shanghai Key Laboratory of Modern Optical System and Engineering Research Center of Optical Instrument and SystemMinistry of EducationSchool of Optical Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Advanced Biomedical Instrumentation Centre Hong Kong Science ParkHong KongChina State Key Laboratory of Precision Spectroscopy East China Normal UniversityShanghai 200062China

Period-doubling bifurcation,as an intermediate state between order and chaos,is ubiquitous in all disciplines of nonlinear ***,previous experimental observations of period doubling in ultrafast fiber lasers are mainly restricted to self-sustained steady state,controllable manipulation and dynamic switching between period doubling and other intriguing dynamical states are still largely ***,we propose to expand the vision of dissipative soliton periodic doubling,which we illustrate experimentally by reporting original spontaneous,collisional,and controllable spectral period doubling in a polarization-maintaining ultrafast fiber ***,the spontaneous period doubling can be observed in both single-and *** mechanism of the switchable state and periodic doubling was revealed by numerical ***,state transformation of individual solitons can be resolved during the collision of triple solitons involving stationary,oscillating,and period ***,controllable deterministic switching between period doubling and other dynamical states,as well as exemplifying the application of period-doubling-based digital encoding,is achieved under programmable pump *** results open a new window for unveiling complex Hopf bifurcation in dissipative systems and bring useful insights into nonlinear science and applications.

关键词： Period doubling Mode locking Ultrafast fiber lasers

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Coexistence of Distributed Sensing and Ultra-simple Coherent RoF based Front-haul for Radio Access Network

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Journal of Lightwave technology 2025年第12期43卷 5669-5675页

作者： Liu, Maoqi Wang, Jingchuan Liu, Chen Yu, Changyuan Lu, Chao Huazhong University of Science and Technology National Engineering Laboratory for Next Generation Internet Access System School of Optical and Electronic Information Wuhan430074 China The Hong Kong Polytechnic University Photonics Research Institute Department of Electrical and Electronic Engineering Hong Kong

The radio access network requires high-speed transmission and multifunctionality to support the increasing demand for advanced communication services. Radio-over-fiber (RoF) technology fulfills these requirements by enabling the delivery of millimeter-wave (MMW) band wireless signals via optical fiber front-haul. This paper presents an ultra-simple RoF system that achieves the coexistence of distributed sensing and telecommunication. A commercially available coherent modulator achieves signal modulation and remote up-conversion by the beat between the residual carrier and the modulated radio signal. The linear-frequency modulated carrier enables distributed sensing while simultaneously serving as the beat tone of RoF communication, showcasing the potential for integrated sensing and communication (ISAC) applications in next-generation radio access networks. We demonstrate the sensing and transmission performance over a 10-km fiber link and a 1-m wireless MMW channel. The system achieves a distributed sensing detection sensitivity of 28 pΕ/√ Hz and supports 1.6 GBaud 16QAM radio transmission in the Ka-band of 28 GHz. © 1983-2012 IEEE.

关键词： Radio access networks

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Incorporating Lasso Regression to Physics-Informed Neural Network for Inverse PDE Problem

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Computer Modeling in engineering & Sciences 2024年第10期141卷 385-399页

作者： Meng Ma Liu Fu Xu Guo Zhi Zhai National Key Lab of Aerospace Power System and Plasma Technology Xi’an Jiaotong UniversityXi’an710049China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an710049China Department of Electrical and Computer Engineering University of Massachusetts LowellLowellMA 01854USA

Partial Differential Equation(PDE)is among the most fundamental tools employed to model dynamic *** PDE modeling methods are typically derived from established knowledge and known phenomena,which are time-consuming and ***,discovering governing PDEs from collected actual data via Physics Informed Neural Networks(PINNs)provides a more efficient way to analyze fresh dynamic systems and establish *** study proposes Sequentially Threshold Least Squares-Lasso(STLasso),a module constructed by incorporating Lasso regression into the Sequentially Threshold Least Squares(STLS)algorithm,which can complete sparse regression of PDE coefficients with the constraints of l0 *** further introduces PINN-STLasso,a physics informed neural network combined with Lasso sparse regression,able to find underlying PDEs from data with reduced data requirements and better *** addition,this research conducts experiments on canonical inverse PDE problems and compares the results to several recent *** results demonstrated that the proposed PINN-STLasso outperforms other methods,achieving lower error rates even with less data.

关键词： Physics-informed neural network inverse partial differential equation Lasso regression scientific machine learning

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Light-Weight Low-Cost Drive Control Modules Design and Mass Production Research in SAR Satellites 4

Light-Weight Low-Cost Drive Control Modules Design and Mass ...

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4th China International SAR Symposium, CISS 2023

作者： Liu, Pengfei Ma, Xiaoyan Wang, Jun Qian, Weixin Feng, Zhengkang Aerospace System Engineering Shanghai Department of Electrical Control Shanghai China Shanghai Aerospace Electronic Technology Institute Department of Radar System Shanghai China

ISBN: (纸本)9798350307955

In order to adapt to the development trend of light-weight and low-cost SAR (Synthetic Aperture Radar) satellites, products of drive control modules, especially drive control modules of SAR antenna deployment mechanism and solar array, are required to be light-weight and low-cost. At the level of product design, the mechanical structure of light-weight drive control module and low-cost hardware circuit design are given. The design scheme mainly involves the electromechanical integration interface of the drive control module and the drive mechanism, and the protection and reinforcement of the industrial components of the hardware circuit. At the level of product production, firstly, the product is designed according to modularization. Secondly, a series of standard systems from production to test are established. Finally, automatic production lines and automatic testing equipment are used for mass production and testing of products. The above design and production optimization measures reduce the weight and cost of drive control module products. The light-weight and low-cost drive control modules is conducive to carrying more payloads on SAR satellites and networking between satellites. © 2023 IEEE.

关键词： Synthetic aperture radar

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Transformer Internal and Inrush Current Fault Detection Using Machine Learning

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Intelligent Automation & Soft Computing 2023年第4期36卷 153-168页

作者： R.Vidhya P.Vanaja Ranjan N.R.Shanker Department of Electronics and Communication Engineering Loyola-ICAM College of Engineering and TechnologyChennai600034India Embedded System Technologies Department of Electrical and Electronics EngineeringCollege of EngineeringGuindyChennai 600025India Department of Computer Science and Engineering Aalim Muhammed Salegh College of EngineeringChennai 600055India

Preventive maintenance in the transformer is performed through a dif-ferential relay protection system,and it protects the transformer from internal and external ***,the Current Transformer(CT)in the differential protec-tion system mal-operates during inrush *** saturates due to magnetizing inrush currents and causes false tripping of the differential ***,iden-tiﬁcation of tripping in protection relay either due to inrush current or internal faults needs to be *** the above problem,continuous monitoring of transformer breather and CT terminals with thermal camera helps detect the trip-ping in relay due to inrush or internal *** transformer’s internal fault leads to high breathing process in the transformer breather,never for inrush *** inrush currents,CT temperature is *** monitoring of breather and CT of the transformer through thermal imaging and radiometric pix-els detect the causes of CT saturation and differentiates *** wavelet threshold image analytics(HWT-IA)based radiometric pixels analysis of the transformer breather and CT after de-noising provides an accurate result of about 95%for identiﬁcation of the false tripping of differential protection system of transformer.

关键词： Wavelet threshold inrush transformer breather current transformer thermal image

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A New Technique of Soluble NPK Nutrient Detection system Using Deep Learning-Based Recurrent Neural Networks (RNN) 12

A New Technique of Soluble NPK Nutrient Detection System Usi...

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12th International electrical engineering Congress, iEECON 2024

作者： Tipwong, Wallop Sirikham, Adisorn Konpang, Jessada Kirdpipat, Putthiphong Chongjarearn, Yutana Preutisrunyanont, Oradee Rajamangala University Of Technology Krungthep Department Of Electrical And Telecommunication Engineering Bangkok Thailand Thammasat School Of Engineering Thammasat University Faculty Of Engineering Department Of Electrical And Computer Engineering Pathum Thani Thailand Dhurakij Pundit University Department Of Robotic Engineering And Automation System Bangkok Thailand

ISBN: (纸本)9798350383591

Modern agriculture relies heavily on effective process monitoring, control, and remote data collection, making accurate and cost-effective sensors crucial for innovation. This research focuses on the development of a spectroscopy-based device for real-time and remote monitoring of nutrient levels in hydroponic systems. The device utilizes IoT architecture, incorporating principles of light absorbance to quantify concentrations of essential nutrients during crop growth. Three deep learning techniques, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) were adopted for data analysis. Results demonstrate that tailored implementation of deep learning can significantly enhance the performance of sensor network system (SNS). Specifically, the RNN format achieved an impressive 98% model accuracy during both training and testing phases. The technological advancements in addressing contract variation and photometric levels contribute to increased accuracy as more sensors become available. The findings serve as a comprehensive guide for collecting extensive agricultural data, encompassing environmental factors throughout the entire cultivation period, using state-of-the-art remote control sensor equipment. This work provides a practical, efficient, and cost-effective solution for precise nutrient control and continuous data monitoring in agricultural production. © 2024 IEEE.

关键词： Cost effectiveness

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Fast Balancing Data-Driven Equalization Strategies of Series-Parallel Switched Capacitor Active Balancing Architecture 3

Fast Balancing Data-Driven Equalization Strategies of Series...

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3rd IEEE International Conference on Sustainable Energy and Future Electric Transportation, SeFet 2023

作者： Sahoo, Jyotirmaya Ramesh, P. Patra, Amit Mukhopadhyay, Siddhartha Indian Institute of Technology Kharagpur Battery Management and Integrated System Lab Department of Electrical Engineering India

ISBN: (纸本)9798350319972

The cycle life and health of a lithium-ion battery pack are impacted due to the cell imbalance, thereby constraining the optimum performance of the application. The charge equalization circuit (CEC) is an integrated unit of the battery management system responsible for equalizing the imbalanced cells. The switched capacitor (SC) CECs are a cost-effective active charge equalization solution that offers high power density and control simplicity compared to other CECs. The series-parallel switch capacitor (SPSC) topology is developed to improve voltage balancing by allowing parallel charge transfer operations among series cells. Due to the conventional switching algorithm, the equalization operation in SPSC necessitates the participation of each series cell until the balanced state is achieved. The energy loss resulting from the equalization process is increased as a result of the operation of multiple switches. This paper proposes three equalization algorithms for SRSP topology that have successfully achieved independent balancing control of each cell and optimized utilization of each switched capacitor to minimize operational loss. For validation, simulation and modeling are carried out in the PLECS environment using 14 series cells, where a 9% improvement in equalization time is recorded using proposed switching operation during equalization. © 2023 IEEE.

关键词： Lithium-ion batteries

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Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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Computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara Rehman Muhammad Farrukh Qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

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Cost-Effective Electroluminescence Imaging for Solar PV Inspection Using a Modified Consumer Camera

Cost-Effective Electroluminescence Imaging for Solar PV Insp...

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2023 IEEE International Conference on electrical, Computer and Energy Technologies, ICECET 2023

作者： Kaligambe, Abraham Nakagawa, Kota Fujita, Goro Graduate School of Engineering and Science Shibaura Institute of Technology Power System Laboratory Tokyo Japan Shibaura Institute of Technology Power System Laboratory Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798350327816

As the adoption of renewable energy surges, the global proliferation of solar photovoltaic (PV) systems intensifies. However, PV panels remain vulnerable to defects during transportation, installation, and harsh weather exposures, compromising their longevity and efficiency. Traditional visual and I-V curve tests, frequently employed for PV system maintenance, often fall short due to their restricted defective detection capacity, and extended inspection durations. While infrared (IR) and electroluminescence (EL) imaging methods excel in efficiency, their accompanying equipment is prohibitively expensive. Addressing this gap, the paper introduces a novel, cost-effective EL imaging solution using a modified consumer camera. The findings highlight the efficacy of EL imaging in detecting an array of solar cell defects, underscored by the affordability of the setup. The accessible and cost-friendly nature of the EL methodology offers a promising inspection alternative for small to medium-sized PV systems, marking a significant stride in PV inspection innovations. © 2023 IEEE.

关键词： electroluminescence imaging inspection photovoltaic solar defects

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A Multi-Bit ECRAM-Based Analog Neuromorphic system With High-Precision Current Readout Achieving 97.3% Inference Accuracy

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IEEE Transactions on Biomedical circuits and systems 2025年第3期19卷 590-604页

作者： Um, Minseong Kang, Minil Eom, Kyeongho Kwak, Hyunjeong Noh, Kyungmi Lee, Jimin Son, Jeonghoon Kwon, Jiseok Kim, Seyoung Lee, Hyung-Min Korea University School of Electrical Engineering Seoul02841 Korea Republic of Korea University Department of Semiconductor System Engineering Seoul02841 Korea Republic of Pohang University of Science and Technology Department of Materials Science and Engineering Pohang37673 Korea Republic of The Catholic University of Korea School of Information Communications and Electronic Engineering Bucheon14662 Korea Republic of

This article proposes an analog neuromorphic system that enhances symmetry, linearity, and endurance by using a high-precision current readout circuit for multi-bit nonvolatile electro-chemical random-access memory (ECRAM). For on-chip training and inference, the system uses activation modules and matrix processing units to manage analog update/read paths and perform precise output sensing with feedback-based current scaling on the ECRAM array. The 250nm CMOS neuromorphic chip was tested with a 32 × 32 ECRAM synaptic array, achieving linear and symmetric updates and accurate read operations. The proposed circuit system updates the 32 × 32 ECRAM across 100 levels, maintaining consistent synaptic weights, and operates with an output error rate of up to 2.59% per column. It consumes 5.9 mW of power excluding the ECRAM array and achieves 97.3% inference accuracy on the MNIST dataset, close to the software-confirmed 97.78%, with only the final layer (64 × 10) mapped to the ECRAM. © 2007-2012 IEEE.

关键词： CMOS integrated circuits

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