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Low-Frequency Nonresonant Rectification in Spin Diodes

Physical Review Applied 2020年第2期14卷 024043-024043页

作者： R. Tomasello B. Fang P. Artemchuk M. Carpentieri L. Fasano A. Giordano O.V. Prokopenko Z.M. Zeng G. Finocchio Institute of Applied and Computational Mathematics FORTH GR-70013 Heraklion-Crete Greece Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-Bionics CAS Suzhou Jiangsu 215123 People’s Republic of China Faculty of Radiophysics Electronics and Computer Systems Taras Shevchenko National University of Kyiv Kyiv 01601 Ukraine Department of Physics Oakland University Rochester Michigan 48309 USA Department of Electrical and Information Engineering Politecnico of Bari via Orabona 4 70125 Bari Italy Italian Space Agency (ASI) Rome Italy Department of Mathematical and Computer Sciences Physical Sciences and Earth Sciences University of Messina I-98166 Messina Italy

Spin diodes are usually resonant in nature (GHz frequency) and tunable by magnetic field and bias current with performances, in terms of sensitivity and minimum detectable power, overcoming the semiconductor counterpart, i.e., Schottky diodes. Recently, spin diodes characterized by a low-frequency detection (MHz frequency) have been proposed. Here, we show a strategy to design low-frequency detectors based on magnetic tunnel junctions with the interfacial perpendicular anisotropy of the same order of the demagnetizing field out-of-plane component. Micromagnetic calculations show that, to reach this detection regime, a threshold input power has to be overcome and the phase shift between the oscillation magnetoresistive signal and the input radiofrequency current plays a key role in determining the value of the rectification voltage.

关键词： Spintronics Magnetic tunnel junctions Ferromagnetic resonance Micromagnetic modeling

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The Inverse Gamma Distribution: A New Shadowing Model 8

The Inverse Gamma Distribution: A New Shadowing Model

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8th Asia-Pacific Conference on Antennas and Propagation, APCAP 2019

作者： Yoo, Seong Ki Cotton, Simon L. Zhang, Lei Sofotasios, Paschalis C. Queen's University Centre for Wireless Innovation Ecit Institute BelfastBT3 9DT United Kingdom Khalifa University Center for Cyber-Physical Systems Department of Electrical Engineering and Computer Science Abu Dhabi127788 United Arab Emirates

ISBN: (纸本)9781665400541

In this paper, we provide empirical evidence that the inverse gamma distribution is an excellent alternative for the lognormal and gamma distributions which are often used to model shadowing. To illustrate this, we have used field measurements obtained for wearable communication channels. The goodness-of-fit is compared with two other distributions, namely lognormal and gamma. It has been found that the inverse gamma distribution is chosen as the best model in two out of three cases considered in this study. © 2019 IEEE.

关键词： Probability distributions

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A study on frequency adjustment mechanism for wind turbine generation systems

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Journal of International Council on electrical engineering 2019年第1期9卷 113-122页

作者： Yawata, Ryo Tanaka, Shunya Takano, Hirotaka Taoka, Hisao Yasuhara, Takashi Yan Qingyuan Aoki, Mutsumi Department of Electrical and Electronics Engineering Graduate School of Engineering University of Fukui Fukui-shi Japan Department of Electrical Electronic and Computer Engineering Faculty of Engineering Gifu University Gifu City Japan Department of Electrical and Electronics Engineering Faculty of Engineering University of Fukui Fukui-shi Japan Department of Systems Science and Informatics Graduate School of Information science and Technology Hokkaido University Sapporo Japan Department of Electrical and Mechanical Engineering Nagoya Institute of Technology Nagoya Japan

ABSTRACTFormulae display:?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to *** turbine generation systems (WTs) normally do not have mechanisms to control their output, so that the growth in WT penetration has brought difficulty in the frequency control operation of power grids. This paper presents a frequency adjustment mechanism for the WTs consisting of the following controllers: an active power controller, a governor controller, a pseudo synchronization controller and a pitch angle controller. The governor and the synchronization controllers calculate a correction value to make variability of the WT output in response to its share of power generation. Besides, the pitch angle controller is customized from a viewpoint of relaxing restraint in the frequency adjustment mechanism. By these controllers, the proposed mechanism supplies the frequency adjustability to the power grid in consideration of the actual WT output while effectively suppressing the rapid change of rotor angular speed. Through numerical simulations and discussions on their results, validity of the authors’ proposal is verified.

关键词： Doubly-fed induction generators (DFIGs) governor controller power grid frequency pitch angle controller synchronization controller wind turbine generation systems (WTs)

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Inverse design of figure eight fiber laser by artificial neural network

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Optical Fiber Technology 2025年 94卷

作者： Mahdi Kasmi Abdullah S. Karar Ahmad Atieh Kaboko Jean-Jacques Monga Ehsan Adibnia Hafedh Mahmoud Zayani Mohamed Salhi Alexander Perepelov Faouzi Bahloul University of Carthage SERCOM Laboratory Tunisia Polytechnic School EPT B.P. 743 2078 Tunisia Optiwave Systems Inc 7 Capella Court Suite 900 Ottawa K2E 8A7 Ontario Canada Department of Electronics Carleton University 1125 Colonel By Drive Ottawa K1S 5B6 Ontario Canada University of Johannesburg Electrical and Electronic Engineering Science Department Auckland Park 2006 South Africa Faculty of Electrical and Computer Engineering University of Sistan and Baluchestan (USB) P.O. Box *** Zahedan Iran Department of Electrical Engineering College of Engineering Northern Border University Arar Saudi Arabia Univ Angers LPHIA SFR MATRIX F-49000 Angers France Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 Building 1 Moscow 121205 Russia University of Tunis El Manar National Engineering School of Tunis B.P. 37 1002 Tunisia

Fiber lasers have become indispensable tools in modern photonics, offering unparalleled efficiency, stability, and versatility. Among them, the figure-eight fiber laser (F8FL) has gained prominence for its ability to generate ultra-short pulses with high peak power, making it highly suitable for applications in ultrafast spectroscopy, nonlinear microscopy, and optical frequency comb generation. However, designing and optimizing F8FLs remains a significant challenge due to the intricate interplay of nonlinear effects, dispersion management, and gain dynamics. Traditional design approaches rely on numerical simulations and iterative experimental tuning, which are computationally expensive and often yield suboptimal results. To address these challenges, we introduce a machine learning-based inverse design framework for optimizing F8FL parameters. Using a dataset generated from numerical simulations, an artificial neural network (ANN) is trained to establish a direct mapping between pulse characteristics and the key amplifier parameters, including small-signal gain and saturation energy. This approach enables rapid and accurate prediction of laser settings required to achieve a target pulse profile, significantly reducing the computational burden compared to conventional numerical methods. Our results demonstrate that the trained ANN model achieves excellent agreement with numerical simulations, effectively predicting the optimal parameters for producing high-energy rectangular pulses in the dissipative soliton resonance (DSR) regime. To validate the effectiveness of the predicted parameters, the ANN outputs were independently verified using OptiSystem simulations, confirming strong agreement with the desired pulse profiles. This study highlights the potential of machine learning in photonics, paving the way for the development of self-optimizing, adaptive laser systems with enhanced precision and efficiency. The proposed methodology can be extended to other nonlinear o

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Brain implantation of soft bioelectronics via embryonic development

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Nature 2025年 2025 Jun 11页

作者： Hao Sheng Ren Liu Qiang Li Zuwan Lin Yichun He Thomas S Blum Hao Zhao Xin Tang Wenbo Wang Lishuai Jin Zheliang Wang Emma Hsiao Paul Le Floch Hao Shen Ariel J Lee Rachael Alice Jonas-Closs James Briggs Siyi Liu Daniel Solomon Xiao Wang Jessica L Whited Nanshu Lu Jia Liu John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA USA. Department of Chemistry and Chemical Biology Harvard University Cambridge MA USA. Department of Materials Science and Engineering University of Pennsylvania Philadelphia PA USA. Department of Aerospace Engineering and Engineering Mechanics The University of Texas at Austin Austin TX USA. Axoft Inc. Cambridge MA USA. Electrical Engineering and Computer Science MIT Cambridge MA USA. Department of Systems Biology Harvard Medical School Boston MA USA. Broad Institute of MIT and Harvard Cambridge MA USA. Department of Chemistry MIT Cambridge MA USA. Department of Stem Cell and Regenerative Biology Harvard University Cambridge MA USA. John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA USA. jia_liu@seas.harvard.edu.

Developing bioelectronics capable of stably tracking brain-wide, single-cell, millisecond-resolved neural activity in the developing brain is critical for advancing neuroscience and understanding neurodevelopmental disorders. During development, the three-dimensional structure of the vertebrate brain arises from a two-dimensional neural plate. These large morphological changes have previously posed a challenge for implantable bioelectronics to reliably track neural activity throughout brain development. Here we introduce a tissue-level-soft, submicrometre-thick mesh microelectrode array that integrates into the embryonic neural plate by leveraging the tissue's natural two-dimensional-to-three-dimensional reconfiguration. As organogenesis progresses, the mesh deforms, stretches and distributes throughout the brain, seamlessly integrating with neural tissue. Immunostaining, gene expression analysis and behavioural testing confirm no adverse effects on brain development or function. This embedded electrode array enables long-term, stable mapping of how single-neuron activity and population dynamics emerge and evolve during brain development. In axolotl models, it not only records neural electrical activity during regeneration but also modulates the process through electrical stimulation.

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Smith-Purcell radiation from time grating

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Newton 2025年第2期1卷

作者： Juan-Feng Zhu Ayan Nussupbekov Yudi Fan Wenjie Zhou Zicheng Song Xuchen Wang Zi-Wen Zhang Chao-Hai Du Xianlong Wei Ping Bai Ching Eng Png Cheng-Wei Qiu Lin Wu Science Mathematics and Technology Singapore University of Technology and Design 8 Somapah Road Singapore 487372 Singapore Institute of High Performance Computing Agency for Science Technology and Research (A∗STAR) 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 Singapore Center for Composite Materials and Structures School of Astronautics Harbin Institute of Technology Harbin China Institute of Nanotechnology Karlsruhe Institute of Technology Karlsruhe Germany Optical Communication Systems and Networks School of Electronics Peking University Beijing China Key Laboratory for the Physics and Chemistry of Nanodevices School of Electronics Peking University Beijing China

Smith-Purcell radiation (SPR) arises when an electron moves above a spatial grating, where fixed momentum compensation constrains the emission wavelength. In contrast, temporal SPR ( t -SPR) utilizes a time grating to leverage temporal periodicity for energy compensation, enabling more flexible radiation control. We introduce a generalized dispersion equation for t -SPR that predicts the interplay between radiation frequency, direction, electron velocity, modulation period, and harmonic orders. t -SPR offers several advantages over conventional SPR: robustness ( t -SPR maintains stable emission intensity without rapid decay as the electron moves away from the time grating), versatility ( t -SPR enables precise control via temporal modulation of period, amplitude, and waveform), and amplified emission (temporal modulation introduces additional energy channels, boosting emission). These features make t -SPR highly promising for advanced applications in on-chip light sources and electron accelerators.

关键词： Smith-Purcell radiation time grating photonic time crystal free-electron radiation

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Structural Decomposition and its Use in Qualitative Model-based Diagnosis of Complex systems : Plenary Talk

Structural Decomposition and its Use in Qualitative Model-ba...

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International Symposium on Intelligent systems and Informatics (SISY)

作者： Katalin M. Hangos A. I. Pózna Systems and Control Laboratory Institute for Computer Science and Control HAS Budapest Hungary Department of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary

ISBN: (数字)9781728121437

ISBN: (纸本)9781728121444

Decomposition offers the potential to reduce the complexity of model-based optimization, prediction, control and diagnosis by accounting for the structure and sparsity of the describing model. Motivated by this fact, a rich and powerful collection of decomposition methods are available for model based diagnosis of large-scale complex dynamic systems, too. At the same time, one usually does not have enough information about a large-scale complex dynamic system to construct its precise enough model, so a kind of qualitative dynamic model is often used for the diagnosis. Two structural decomposition based qualitative diagnostic methods are presented in this lecture, together with their component-driven system decomposition techniques.

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Multiple heads outsmart one: A computational model for distributed decision making 40

Multiple heads outsmart one: A computational model for distr...

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40th Annual Meeting of the Cognitive Science Society: Changing Minds, CogSci 2018

作者： Kapourchali, Masoumeh Heidari Banerjee, Bonny Institute for Intelligent Systems Department of Electrical & Computer Engineering The University of Memphis MemphisTN38152 United States

ISBN: (纸本)9780991196784

Distributed cognition and decision making has been a topic of intense research in the recent years. In this paper, a computational model of distributed decision making using a community of predictive coding agents is developed. The agents are embodied multimodal entities and situated in a shared environment. They have different visibility of the environment due to unique sensory and generative models. We show that communication between agents helps each of them reach a shared decision in a way that cannot be reached by brain processes in a single agent. Using a simulated environment, we show that sensory limitations may lead to incorrect or delayed causal inferences giving rise to conflicts in the mind of a predictive coding agent, and communication helps to resolve such conflicts and overcome the limitations. © 2018 Proceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018. All rights reserved.

关键词： Free energy

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Big data analytics in smart mobility: Modeling and analysis of the Aarhus smart city dataset 1

Big data analytics in smart mobility: Modeling and analysis ...

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1st IEEE International Conference on Industrial Cyber-Physical systems, ICPS 2018

作者： Zenkert, Johannes Dornhofer, Mareike Weber, Christian Ngoukam, Charly Fathi, Madjid University of Siegen Institute of Knowledge Based Systems and Knowledge Management Department of Electrical Engineering and Computer Science Germany

ISBN: (纸本)9781538665312

A smart city is a modern and visionary approach for a city to provide intelligent and smart urban services by using information and communication technologies (ICT). The Internet of Things (IoT), emerging through intelligent networking and sensing technologies, is seen as the data-driven enabler for smart cities with current and future infrastructures. The Open Data Aarhus datasets have been created from sensor data in the city Aarhus in Denmark. This paper presents how big data technologies in the context of smart cities are used to implement a framework with a prototype R Shiny application to analyze road traffic and pollution data to make a step towards smart mobility. The main objective of the approach is the calculation and visualization of the least polluted route from a chosen start to an end point by applying an algorithm utilizing the MapReduce framework running on a Hadoop cluster. © 2018 IEEE.

关键词： MapReduce

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Robot Learning via Human Adversarial Games

Robot Learning via Human Adversarial Games

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2019 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Jiali Duan Qian Wang Lerrel Pinto C.-C. Jay Kuo Stefanos Nikolaidis Department of Electrical and Computer Engineering University of Southern California Los Angeles USA Department of Computer Science University of Southern California Los Angeles USA Robotics Institute Carnegie Mellon University Pittsburgh USA

Much work in robotics has focused on “humanin-the-loop” learning techniques that improve the efficiency of the learning process. However, these algorithms have made the strong assumption of a cooperating human supervisor that assists the robot. In reality, human observers tend to also act in an adversarial manner towards deployed robotic systems. We show that this can in fact improve the robustness of the learned models by proposing a physical framework that leverages perturbations applied by a human adversary, guiding the robot towards more robust models. In a manipulation task, we show that grasping success improves significantly when the robot trains with a human adversary as compared to training in a self-supervised manner.

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