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Proactive Opinion-Driven Robot Navigation around Human Movers

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arXiv 2022年

作者： Cathcart, Charlotte Santos, María Park, Shinkyu Leonard, Naomi Ehrich Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08544 United States the Electrical and Computer Engineering program King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

— We propose, analyze, and experimentally verify a new proactive approach for robot social navigation driven by the robot’s "opinion" for which way and by how much to pass human movers crossing its path. The robot forms an opinion over time according to nonlinear dynamics that depend on the robot’s observations of human movers and its level of attention to these social cues. For these dynamics, it is guaranteed that when the robot’s attention is greater than a critical value, deadlock in decision making is broken, and the robot rapidly forms a strong opinion, passing each human mover even if the robot has no bias nor evidence for which way to pass. We enable proactive rapid and reliable social navigation by having the robot grow its attention across the critical value when a human mover approaches. With human-robot experiments we demonstrate the flexibility of our approach and validate our analytical results on deadlock-breaking. We also show that a single design parameter can tune the trade-off between efficiency and reliability in human-robot passing. The new approach has the additional advantage that it does not rely on a predictive model of human behavior. Copyright © 2022, The Authors. All rights reserved.

关键词： Decision making

Periodic phase diagrams in micromagnetics with an eigenvalue solver

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arXiv 2024年

作者： Ai, Fangzhou Lin, Zhuonan Duan, Jiawei Lomakin, Vitaliy Department of Electrical and Computer Engineering University of California La Jolla San DiegoCA92093 United States Center for Memory and Recording Research University of California La Jolla San DiegoCA92093 United States Program in Materials Science and Engineering University of California La Jolla San Diego92093 United States

This work introduces an approach to compute periodic phase diagram of micromagnetic systems by solving a periodic linearized Landau-Lifshitz-Gilbert (LLG) equation using an eigenvalue solver with the Finite Element Method formalism. The linear operator in the eigenvalue problem is defined as a function of the periodic phase shift wave vector. The dispersion diagrams are obtained by solving the eigenvalue problem for complex eigen frequencies and corresponding eigen states for a range of prescribed wave vectors. The presented approach incorporates a calculation of the periodic effective field, including the exchange and magnetostatic field components. The approach is general in that it allows handling 3D problems with any 1D, 2D, and 3D periodicities. The ability to calculated periodic diagrams provides insights into the spin wave propagation and localized resonances in complex micromagnetic structures. © 2024, CC BY-NC-ND.

关键词： Spin waves

Microstructural analysis and electro-optic properties of thick epitaxial BaTiO3 films integrated on silicon (001)

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Physical Review Materials 2022年第9期6卷 095201-095201页

作者： Marc Reynaud Zuoming Dong Hyoju Park Wente Li Agham B. Posadas Jamie H. Warner Daniel Wasserman Alexander A. Demkov Department of Physics University of Texas at Austin Austin Texas 78712 USA Department of Electrical and Computer Engineering University of Texas at Austin Austin Texas 78758 USA Walker Department of Mechanical Engineering University of Texas at Austin Austin Texas 78712 USA Materials Science and Engineering Program and Texas Materials Institute The University of Texas at Austin Texas 78712 USA

Recent advances in epitaxial oxide deposition have enabled the fabrication of thick films of ferroelectric perovskite BaTiO3 capable of providing a robust electro-optic response via the Pockels effect in silicon photonic devices. We report a microstructure analysis of such films integrated on Si(001) by molecular beam epitaxy, showing how the crystallographic and polarization orientation change as a function of thickness. The measured electro-optic properties of the film correlate well with the microstructural analysis and demonstrate the potential of Si-integrated BaTiO3 for silicon photonics. An effective Pockels coefficient of up to 268 pm/V has been demonstrated in 110-nm-thick films in transmission measurements and 352 pm/V in waveguide measurements.

关键词： Ferroelectricity Photonics Epitaxy

Implantable Biosensor for Continuous Serotonin Detection in Freely Moving Crayfish 22

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Implantable Biosensor for Continuous Serotonin Detection in ...

22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Han, Jinjing Ho, Tawen Stine, Justin M. Straker, Michael A. Herberholz, Jens Ghodssi, Reza University Of Maryland Department Of Electrical And Computer Engineering College ParkMD United States University Of Maryland Institute For System Research College ParkMD United States University Of Maryland Robert E. Fischell Institute For Biomedical Devices College ParkMD United States University Of Maryland Department Of Psychology College ParkMD United States University Of Maryland Program In Neuroscience And Cognitive Science College ParkMD United States University Of Maryland Fischell Department Of Bioengineering College ParkMD United States

ISBN: (纸本)9784886864352

This work presents, for the first time, an implantable biosensor for continuous in vivo serotonin (5-HT) monitoring in freely moving crayfish. 5-HT is an important neurotransmitter that regulates animal behaviors. Conventional methods for detecting 5-HT do not provide real-time information. Our approach facilitates continuous electrochemical monitoring of 5-HT levels without impeding animal natural behavior. The sensing system shows a linear range of 0.4 - 1.2 μΜ with a sensitivity of 0.07 μA/μΜ for 5-HT detection. With a 3D-printed package, the sensor can be easily attached to crayfish dorsal carapace allowing electrodes implantation into crayfish heart to monitor neurohormonal dynamics of 5-HT. The implantable biosensor system displayed a significant increase in oxidation currents after 5-HT injections. The device successfully demonstrates the application for in vivo detection of 5-HT in the hemolymph (i.e., blood) of freely behaving crayfish underwater. © 2023 IEEJ.

关键词： Biosensing Electrochemical Device Electrochemistry Implantable Electrode In Vivo Sensing

Domain Adaptation via Rebalanced Sub-domain Alignment

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arXiv 2023年

作者： Liu, Yiling Dong, Juncheng Jiang, Ziyang Aloui, Ahmed Li, Keyu Klein, Hunter Tarokh, Vahid Carlson, David Program in Computational Biology and Bioinformatics Duke University School of Medicine DurhamNC United States Department of Electrical and Computer Engineering Duke University DurhamNC United States Department of Civil and Environmental Engineering Duke University DurhamNC United States Department of Biostatistics and Bioinformatics Duke University DurhamNC United States

Unsupervised domain adaptation (UDA) is a technique used to transfer knowledge from a labeled source domain to a different but related unlabeled target domain. While many UDA methods have shown success in the past, they often assume that the source and target domains must have identical class label distributions, which can limit their effectiveness in real-world scenarios. To address this limitation, we propose a novel generalization bound that reweights source classification error by aligning source and target sub-domains. We prove that our proposed generalization bound is at least as strong as existing bounds under realistic assumptions, and we empirically show that it is much stronger on real-world data. We then propose an algorithm to minimize this novel generalization bound. We demonstrate by numerical experiments that this approach improves performance in shifted class distribution scenarios compared to state-of-the-art methods. © 2023, CC BY.

关键词： Numerical methods

engineering dimensionality of collective dipole-dipole interactions using a nanophotonic environment

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Engineering dimensionality of collective dipole-dipole inter...

Conference on Lasers and Electro-Optics (CLEO)

作者： Ashwin K. Boddeti Yi Wang Xitlali Juarez Alexandra Boltasseva Hadiseh Alaeian Teri W. Odom Zubin Jacob Elmore Family School of Electrical and Computer Engineering and Birck Nanotechnology Center Purdue University West Lafayette Indiana USA Graduate Program in Applied Physics Northwestern University Evanston IL USA Department of Materials Science and Engineering Northwestern University Evanston Illinois USA Department of Chemistry and Department of Materials Science and Engineering Northwestern University Evanston Illinois USA

We experimentally demonstrate reduced dimensionality in a interacting ensemble of emitters. The well-known stretched exponential decay dynamics, I(t)/I 0 = exp(−γ D t)exp(−αt β ) with β = 0.5 in 3D geometries, is... 详细信息

ISBN: (纸本)9781957171258

关键词： Energy transfer Fluorescence Molecules Spontaneous emission Titanium dioxide

Deep Learning Approach to Modeling and Exploring Random Sources of Gate-All-Around Silicon Nanosheet MOSFETs

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Deep Learning Approach to Modeling and Exploring Random Sour...

2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang-Ming Chiao Tung University Parallel and Scientific Computing Laboratory Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Electrical Engineering and Computer Science International Graduate Program Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Communications Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Department of Electrical Engineering and Computer Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Biomedical Engineering Hsinchu300 Taiwan Center for mmWave Smart Radar System and Technologies National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300 Taiwan

ISBN: (纸本)9781665409230

In this paper, for the first time, deep learning (DL) based artificial neural network (ANN) is applied to model the effects of various random variations: work function fluctuation, random dopant fluctuation, and interface trap fluctuation, on gate-all-around silicon nanosheet MOSFETs. The number of fluctuations for each source variation is used as input features and their effects on devices of interest are studied qualitatively and quantitatively. The key figures of merit (FoM) are also extracted accurately from the transfer characteristics, which shows the competency of the ANN model in the domain of device modeling. © 2022 IEEE.

关键词： Nanosheets

Boosting the Performance of Image Restration Models Through Training with Deep-Feature Auxiliary Guidance

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SSRN

SSRN 2024年

作者： Jang, Cheolhun Ji, Deahyun Cho, Nam Ik Interdisciplinary Program in Artificial Intelligence INMC Seoul National University Seoul08826 Korea Republic of Samsung Advanced Institute of Technology Suwon-si Gyenggi-do16678 Korea Republic of Department of Electrical and Computer Engineering INMC Seoul National University Seoul08826 Korea Republic of

Many neural network architectures have been suggested for image restoration models to enhance the accuracy of restored images while keeping the computational time reasonable. However, most previous studies have primarily focused on introducing new network architectures, with relatively less emphasis on efficient training techniques. This paper introduces a novel training strategy that improves the accuracy of image restoration models without increasing inference times by preserving their structures. To achieve this, we add auxiliary guidance at a feature map of each multi-scale level during the training process. All modules added to the model for the application of auxiliary guidance are only used during training time and can be removed at the inference phase, thereby eliminating the need for additional computation. Our proposed training method, named deep-feature auxiliary guidance (DFAG), can be easily applied to existing encoder-decoder architectures. By applying DFAG to train existing image restoration models, we have obtained enhanced performance in real-image denoising, Gaussian denoising, motion deblurring, JPEG artifact reduction, and super-resolution for all tested models. The source code and pre-train models will be released. © 2024, The Authors. All rights reserved.

关键词： Image denoising

Ground state phases of the two-dimension electron gas with a unified variational approach

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arXiv 2024年

作者： Smith, Conor Chen, Yixiao Levy, Ryan Yang, Yubo Morales, Miguel A. Zhang, Shiwei Center for Computational Quantum Physics Flatiron Institute New YorkNY10010 United States Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM87131 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

The two-dimensional electron gas (2DEG) is a fundamental model, which is drawing increasing interest because of recent advances in experimental and theoretical studies of 2D materials. Current understanding of the ground state of the 2DEG relies on quantum Monte Carlo calculations, based on variational comparisons of different ansatze for different phases. We use a single variational ansatz, a general backflow-type wave function using a message-passing neural quantum state architecture, for a unified description across the entire density range. The variational optimization consistently leads to lower ground-state energies than previous best results. Transition into a Wigner crystal (WC) phase occurs automatically at rs = 37±1, a density lower than currently believed. Between the liquid and WC phases, the same ansatz and variational search strongly suggest the existence of intermediate states in a broad range of densities, with enhanced short-range nematic spin correlations. Copyright © 2024, The Authors. All rights reserved.

关键词： Message passing