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Magnon gap tuning in lithium-doped MnTe

physical Review B 2024年第21期109卷 214434-214434页

作者： George Yumnam Duncan H. Moseley Joseph A. M. Paddison Christiana Z. Suggs Emma Zappala David S. Parker Garrett E. Granroth Gerald D. Morris Md Mobarak Hossain Polash Daryoosh Vashaee Michael A. McGuire Huaizhou Zhao Michael E. Manley Benjamin A. Frandsen Raphaël P. Hermann Materials Science and Technology Division Department of Physics and Astronomy Neutron Scattering Division Centre for Molecular and Materials Science Department of Electrical and Computer Engineering Beijing National Laboratory for Condensed Matter Physics

Manganese telluride (MnTe) is a prospective platform for ultrafast carrier dynamics, spin-based thermoelectrics, and magnon-drag transport due to its unique electronic and magnetic properties. We use inelastic neutron scattering to study both pure and lithium-doped MnTe, focusing on the influence of doping in opening a magnon gap. We use neutron powder diffraction to determine critical exponents for the phase transition in both pure and Li-doped MnTe and complement this information with muon spin rotation/relaxation. The opening of the magnon gap and spin reorientation in Li-doped MnTe is mainly due to increased magnetic anisotropy along the [001] axis, a feature not present in pure MnTe.

关键词： Antiferromagnetism Exchange interaction First-principles calculations Magnetic anisotropy Magnons Density functional theory Inelastic neutron scattering Linear spin wave theory Muon spin relaxation & rotation Neutron diffraction

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Enhancing Power Quality through Harmonic Reduction: A Triple-Memristor Hopfield Neural Network Approach 8

Enhancing Power Quality through Harmonic Reduction: A Triple...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Varaprasad, K.S.B. Sukhi, Y. Subramaniyan, Shanmugapriya Dhandapani, Ramya Rajendiran, M. Kaliappan, S. Visakha Institute of Engineering & Technology Department of Electrical and Electronics Engineering Andhra Pradesh Visakhapatnam530027 India R.M.K. Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Tiruvallur601206 India Srm Institute of Science & Technology Department of Electrical and Electronics Engineering Tamil Nadu Kattankulathur603203 India Sri Eshwar College of Engineering Coimbatore Department of Computer Science and Business Systems Tamil Nadu Coimbatore641202 India Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai600123 India Lovely Professional University Division of Research and Development Delhi Jalandhar144411 India

ISBN: (纸本)9798350376425

Harmonic distortion in power systems is a significant concern that impacts the efficiency, reliability, and safety of electrical networks. Implementing effective harmonic distortion mitigation solutions, such as filters or advanced control systems, can be expensive and may necessitate substantial changes to existing infrastructure. This paper proposes a Triple-Memristor Hopfield Neural Network (TMHNN) as a novel method for mitigating harmonic distortion in power systems. The main objective of the proposed approach is to improve the quality of power by mitigating the harmonics. The TMHNN is used to predict the actual harmonic current injected by specific harmonic sources within a power system. The results demonstrate the significant advantages of the proposed TMHNN method over existing techniques such as Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Recurrent Neural Network (RNN). TMHNN achieves the highest efficiency at 96.3%, lowest error rate at 4.16% and minimizing total harmonic distortion (THD), with the lowest value of 3.74%. These results highlight TMHNN's superior performance in terms of efficiency, harmonic distortion reduction, and accuracy. © 2024 IEEE.

关键词： Harmonic distortion

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A Super-Resolution Electromagnetic Inversion Scheme for Brain Stroke Detection

A Super-Resolution Electromagnetic Inversion Scheme for Brai...

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European Conference on Antennas and Propagation, EuCAP

作者： Lingqi Gao Hakan Bagci Electrical and Computer Engineering (ECE) Program Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

A super-resolution electromagnetic inversion scheme is proposed for brain stroke detection. The scheme operates in two stages: (i) A quantitative Gauss-Newton method with Tikhonov regularization and frequency-hopping is employed to get a low-resolution inversion result. (ii) A U-Net-based super-resolution method is used to significantly enhance the spatial resolution of the inversion result from (i), The proposed scheme is demonstrated through several numerical examples, highlighting its effectiveness in accurately reconstructing the brain's permittivity and conductivity profiles, thereby contributing to advancements in stroke diagnosis.

关键词： Neuroimaging Location awareness Superresolution Europe Conductivity Classification algorithms Electromagnetics Permittivity Spatial resolution Image reconstruction

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Optimization of Microwave Resonant Cavity Flowmeter Design for High Temperature Fluid Sensing Applications

Optimization of Microwave Resonant Cavity Flowmeter Design f...

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Fang, Tianyang Saniie, Jafar Bakhtiari, Sasan Heifetz, Alexander Illinois Institute of Technology Ecasp Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States Nuclear Science and Engineering Division Argonne National Laboratory LemontIL United States

ISBN: (纸本)9781665493765

This paper investigates optimization of parameters to enhance performance of a microwave resonant cavity transducer for high temperature fluid flow sensing in advanced reactors. The cylindrical microwave cavity flowmeter is a novel sensor that measures fluid flow velocity through deflection of the cavity wall due to dynamic fluid pressure. This sensor is designed to operate in harsh environments of a nuclear reactor because sensor material is resilient to high temperatures, ionizing radiation, and corrosion. Parameters that determine performance characteristics of the transducer include dimensions of the microwave cavity, cavity electromagnetic excitation method, and cavity material. We investigate transducer design through computer simulations, with the objective of maximizing cavity Q-factor. © 2023 IEEE.

关键词： Microwave resonators

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Software-Defined Ultrasonic Communication System using PPM-EMAT with High Transmission Rate

Software-Defined Ultrasonic Communication System using PPM-E...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Huang, Xin Saniie, Jafar Bakhtiari, Sasan Heifetz, Alexander Illinois Institute of Technology Ecasp Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States Argonne National Laboratory Nuclear Science and Engineering Division LemontIL United States

ISBN: (纸本)9798350346459

A novel approach to ultrasonic communication systems introduces a software-defined system that utilizes Periodic-permanent-magnet electromagnetic acoustic transducers (PPM-EMATs) as transmitters and receivers. Traditional systems had limitations in adaptability and flexibility. The software-defined system provides enhanced versatility, adaptability, and portability, allowing customization for diverse applications. The use of PPM-EMATs is explored for optimizing energy transfer through metal plate channels, generating shear horizontal waves. Experimental tests validate the efficiency of PPM-EMATs, showing successful communication at a 10-kbps bitrate using ASK modulation with a high signal-to-noise ratio (SNR). The research highlights the potential of PPM-EMAT technology in high-speed software-defined ultrasonic communication systems. © 2023 IEEE.

关键词： Signal to noise ratio

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A Standardized Vibro-tactile Sensory Feedback System For Upper-limb Prostheses 46

A Standardized Vibro-tactile Sensory Feedback System For Upp...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Besharatzad, Niloufar Thurston, Tegan Sylwester, Sean Mathews, V John Oregon State University School of Electrical Engineering and Computer Science CorvallisOR97331 United States The Children's Hospital of Philadelphia Division of Human Genetics and Metabolism PhiladelphiaPA19104 United States

ISBN: (纸本)9798350371499

This work describes the design and evaluation of a vibro-tactile sensory feedback system with standardized stimuli for force perception. Five vibration intensities corresponding to five force levels were identified by a calibration experiment on six intact-arm subjects. Eight of ten intact-arm participants and the trans-radial amputee subject learned to distinguish the force levels within one hour of force recognition training. Augmenting visual feedback with vibro-tactile feedback in a force replication task did not significantly affect performance. Participants' force replication performance did not significantly degrade one hour after training. Participants performed significantly worse when using only vibro-tactile feedback after a single training session. However, the amputee subject after four daily training sessions achieved a 93.3% success rate in the force recognition task and 73.3% in the force replication task with only vibro-tactile feedback, approaching their performance with visual feedback. These results suggest that it is possible to train prosthesis users to evoke and control force levels almost as well with vibro-tactile feedback as with visual feedback. This technology could play a key role in reducing prosthesis abandonment and enhancing the quality of life of upper-limb amputees. © 2024 IEEE.

关键词： Sensory feedback

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Hidden Markov Models:Inverse Filtering,Belief Estimation and Privacy Protection

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Journal of Systems science & Complexity 2021年第5期34卷 1801-1820页

作者： LOURENCO Ines MATTILA Robert ROJAS Cristian R. HU Xiaoming WAHLBERG Bo Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of TechnologyStockholmSweden Division of Optimizations and Systems Theory School of Engineering SciencesKTH Royal Institute of TechnologyStockholmSweden

A hidden Markov model(HMM)comprises a state with Markovian dynamics that can only be observed via noisy *** paper considers three problems connected to HMMs,namely,inverse filtering,belief estimation from actions,and privacy enforcement in such a ***,the authors discuss how HMM parameters and sensor measurements can be reconstructed from posterior distributions of an HMM ***,the authors consider a rational decision-maker that forms a private belief(posterior distribution)on the state of the world by filtering private *** authors show how to estimate such posterior distributions from observed optimal actions taken by the *** the setting of adversarial systems,the authors finally show how the decision-maker can protect its private belief by confusing the adversary using slightly sub-optimal *** range from financial portfolio investments to life science decision systems.

关键词： Belief estimation counter-adversarial systems hidden Markov models inverse decision making inverse filtering

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Effect of Signal Conditioning and Evoked-Potential Based Representation on Stability and Distinctiveness of EEG Brain Signatures

Effect of Signal Conditioning and Evoked-Potential Based Rep...

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International Symposium on Digital Forensic and Security (ISDFS)

作者： Muhammed Esad Oztemel Ömer Muhammet Soysal Division of Electrical and Computer Engineering Louisiana State University Southeastern Louisiana University Computer Science

ISBN: (数字)9798350330366

ISBN: (纸本)9798350330373

Biometric patterns have been used for authentication purposes for more than decades. Although traditional biometric measurements including fingerprints, facial recognition, and sound recognition are often used for authentication purposes, there is ongoing concern about the risks associated with their repeatability and susceptibility to theft. The utilization of electroencephalography (EEG) has promising potential thanks to the distinctive patterns extracted from brain signals. The main goal of this study is to explore the effectiveness of signal conditioning and evoked potentials on uniqueness and permanence of individuals' EEG signals for authentication purpose. We utilized the Laplacian of Gaussian as a signal conditioning operator. In addition, three signifying functions were explored in obtaining evoked potential time-domain representation from an individual EEG signal. Different stimuli protocols were employed for comparison. A time-series and a statistical technique were utilized for uniqueness and permanence analysis.

关键词： Electric potential Protocols Laplace equations Authentication Fingerprint recognition Electroencephalography Stability analysis

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Perovskite Nanocrystal Based Plastic Optical Fiber Amplifier via Two-Photon Excitation

Perovskite Nanocrystal Based Plastic Optical Fiber Amplifier...

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IEEE Photonics Conference (IPC)

作者： Yue Wang Chun Hong Kang Partha Maity Tien Khee Ng Omar F. Mohammed Boon S. Ooi Photonics Laboratory Electrical and Computer Engineering Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Advanced Membranes and Porous Materials Center Division of Physical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

A plastic optical fiber amplifier coated with CsPbBr3 nanocrystals and pumped by an 800-nm Ti:Sapphire laser exhibited two-photon-excited amplified spontaneous emission with a 7.4-mJ/cm 2 threshold and >10-dB opti... 详细信息

ISBN: (数字)9798350361957

ISBN: (纸本)9798350361964

关键词： Optical fiber amplifiers Plastic optical fiber Nanocrystals Stimulated emission Optical pumping Ultrafast optics Optical amplifiers Gain Pump lasers Fiber lasers

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Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss 41

Deeper or Wider: A Perspective from Optimal Generalization E...

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41st International Conference on Machine Learning, ICML 2024

作者： Yang, Yahong He, Juncai Department of Mathematics The Pennsylvania State University University Park State CollegePA16802 United States Computer Electrical and Mathematical Science and Engineering Division The King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

Constructing the architecture of a neural network is a challenging pursuit for the machine learning community, and the dilemma of whether to go deeper or wider remains a persistent question. This paper explores a comparison between deeper neural networks (DeNNs) with a flexible number of layers and wider neural networks (WeNNs) with limited hidden layers, focusing on their optimal generalization error in Sobolev losses. Analytical investigations reveal that the architecture of a neural network can be significantly influenced by various factors, including the number of sample points, parameters within the neural networks, and the regularity of the loss function. Specifically, a higher number of parameters tends to favor WeNNs, while an increased number of sample points and greater regularity in the loss function lean towards the adoption of DeNNs. We ultimately apply this theory to address partial differential equations using deep Ritz and physics-informed neural network (PINN) methods, guiding the design of neural networks. Copyright 2024 by the author(s)

关键词： Partial differential equations

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