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arXiv 2024年

作者： Runck, Bryan C. Schulz, Bobby Bishop, Jeff Carlson, Nathan Chantigian, Bryan Deters, Gary Erdmann, Jesse Ewing, Patrick M. Felzan, Michael Fu, Xiao Greyling, Jan Hogan, Christopher J. Hollman, Andrew Joglekar, Ali Junker, Kris Kantar, Michael Kaunda, Lumbani Krishna, Mohana Lynch, Benjamin Marchetto, Peter Marsolek, Megan McKay, Troy Morris, Brad Niaghi, Ali Rashid Pamulaparthy, Keerthi Pardey, Philip Piotrowski, Ann Poudyal, Christina Prather, Tom Raghavan, Barath Reiter, Maggie Rosen, Lucas Salazar, Benjamin Scobbie, Andrew Sharma, Vasudha Silverstein, Kevin A.T. Singh, Gurparteet Strock, Jeff Subedi, Samikshya Tang, Evan Turturillo, Gianna Watkins, Eric Webster, Blake Wilgenbusch, James GEMS Informatics Center University of Minnesota Twin Cities United States Department of Geography Environment and Society University of Minnesota Twin Cities United States Minnesota Supercomputing Institute University of Minnesota United States Department of Electrical Engineering University of Minnesota Twin Cities United States Department of Applied Economics University of Minnesota Twin Cities United States Department of Horticultural Science University of Minnesota Twin Cities United States Department of Computer Science University of Southern California United States Sensing Inc. Conservify Graphspan LLC USDA-ARS Food Systems Research Unit BurlingtonVT05405 United States Amazon United States Department of Soil Water and Climate University of Minnesota Twin Cities United States Department of Computer Science and Engineering University of Minnesota Twin Cities United States Departmnet of Agricultural Education Communication and Marketing University of Minnesota Twin Cities United States Benson Hill United States Southwest Research and Outreach Center University of Minnesota Twin Cities United States Code Weavers Department of Mechanical Engineering University of Minnesota Twin Cities United States University of Hawaii at Manoa HonoluluHI United States Minnesota Agricultural Experiment Station University of Minnesota Twin Cities United States Sunday Stellenbosch AgroInformatics Initiative Stellenbosch University South Africa Ameriprise Financial Services LLC Optum University of Minnesota Twin Cities United States

With the increasing emphasis on machine learning and artificial intelligence to drive knowledge discovery in the agricultural sciences, spatial internet of things (IoT) technologies have become increasingly important for collecting real-time, high resolution data for these models. However, managing large fleets of devices while maintaining high data quality remains an ongoing challenge as scientists iterate from prototype to mature end-to-end applications. Here, we provide a set of case studies using the framework of technology readiness levels for an open source spatial IoT system. The spatial IoT systems underwent 3 major and 14 minor system versions, had over 2,727 devices manufactured both in academic and commercial contexts, and are either in active or planned deployment across four continents. Our results show the evolution of a generalizable, open source spatial IoT system designed for agricultural scientists, and provide a model for academic researchers to overcome the challenges that exist in going from one-off prototypes to thousands of internet-connected devices. © 2024, CC BY-NC-ND.

关键词： Internet of things

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Revisiting Power Systems Time-domain Simulation Methods and Models

arXiv

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arXiv 2023年

作者： Lara, Jose Daniel Henriquez-Auba, Rodrigo Ramasubramanian, Deepak Dhople, Sairaj Callaway, Duncan S. Sanders, Seth Energy and Resources Group University of California Berkeley United States Department of Electrical Engineering and Computer Sciences University of California Berkeley United States National Renewable Energy Laboratory GoldenCO United States Electric Power Research Institute KnoxvilleTN United States Department of Electrical Engineering University of Minnesota United States

The changing nature of power systems dynamics is challenging present practices related to modeling and study of system-level dynamic behavior. While developing new techniques and models to handle the new modeling requirements, it is also critical to review some of the terminology used to describe existing simulation approaches and the embedded assumptions. This paper provides a first-principles review of the simplifications and transformations commonly used in the formulation of time-domain simulation models. It introduces a taxonomy and classification of time-domain simulation models depending on their frequency bandwidth, network representation, and software availability. Furthermore, it focuses on the fundamental aspects of averaging techniques, and model reduction approaches that result in modeling choices, and discusses the associated challenges and opportunities of applying these methods in systems with large shares of Inverter Based Resources (IBRs). The paper concludes with an illustrative simulation that compares the trajectories of an IBR-dominated system. Copyright © 2023, The Authors. All rights reserved.

关键词： Time domain analysis

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A 16-Channel Low-Power Neural Connectivity Extraction and Phase-Locked Deep Brain Stimulation SoC

arXiv

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arXiv 2022年

作者： Shin, Uisub Ding, Cong Woods, Virginia Widge, Alik S. Shoaran, Mahsa The Institute of Electrical and Micro Engineering Epfl Geneva1202 Switzerland The School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States The Institute of Electrical and Micro Engineering Center for Neuroprosthetics Epfl Geneva1202 Switzerland The Department of Psychiatry and Behavioral Sciences University of Minnesota MinneapolisMN55455 United States

Growing evidence suggests that phase-locked deep brain stimulation (DBS) can effectively regulate abnormal brain connectivity in neurological and psychiatric disorders. This letter therefore presents a low-power SoC with both neural connectivity extraction and phase-locked DBS capabilities. A 16-channel low-noise analog front-end (AFE) records local field potentials (LFPs) from multiple brain regions with precise gain matching. A novel low-complexity phase estimator and neural connectivity processor subsequently enable energy-efficient, yet accurate measurement of the instantaneous phase and crossregional synchrony measures. Through flexible combination of neural biomarkers such as phase synchrony and spectral energy, a four-channel charge-balanced neurostimulator is triggered to treat various pathological brain conditions. Fabricated in 65nm CMOS, the SoC occupies a silicon area of 2.24mm2and consumes 60μW, achieving over 60% power saving in neural connectivity extraction compared to the state-of-the-art. Extensive in-vivo measurements demonstrate multi-channel LFP recording, realtime extraction of phase and neural connectivity measures, and phase-locked stimulation in rats. Copyright © 2022, The Authors. All rights reserved.

关键词： Extraction

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A Survey of Recent Advances in Optimization Methods for Wireless Communications

arXiv

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arXiv 2024年

作者： Liu, Ya-Feng Chang, Tsung-Hui Hong, Mingyi Wu, Zheyu So, Anthony Man-Cho Jorswieck, Eduard A. Yu, Wei The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen China Shenzhen Research Institute of Big Data China The Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States The Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong The Institute for Communication Technology Technische Universitat Braunschweig Germany The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3G4 Canada

Mathematical optimization is now widely regarded as an indispensable modeling and solution tool for the design of wireless communications systems. While optimization has played a significant role in the revolutionary progress in wireless communication and networking technologies from 1G to 5G and onto the future 6G, the innovations in wireless technologies have also substantially transformed the nature of the underlying mathematical optimization problems upon which the system designs are based and have sparked significant innovations in the development of methodologies to understand, to analyze, and to solve those problems. In this paper, we provide a comprehensive survey of recent advances in mathematical optimization theory and algorithms for wireless communication system design. We begin by illustrating common features of mathematical optimization problems arising in wireless communication system design. We discuss various scenarios and use cases and their associated mathematical structures from an optimization perspective. We then provide an overview of recently developed optimization techniques in areas ranging from nonconvex optimization, global optimization, and integer programming, to distributed optimization and learning-based optimization. The key to successful solution of mathematical optimization problems is in carefully choosing or developing suitable algorithms (or neural network architectures) that can exploit the underlying problem structure. We conclude the paper by identifying several open research challenges and outlining future research directions. Copyright © 2024, The Authors. All rights reserved.

关键词： Beamforming

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Fast spin precession and strong perpendicular magnetic anisotropy in ferrimagnetic Mn4N thin films improved by Pd buffer layer

arXiv

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arXiv 2025年

作者： Zhang, Yao Kim, Yun Murmu, Peter P. Huang, Dingbin Lyu, Deyuan Wang, Jian-Ping Wang, Xiaojia Granville, Simon Robinson Research Institute Victoria University of Wellington P.O. Box 33436 Petone5046 New Zealand MacDiarmid Institute for Advanced Materials and Nanotechnology P.O. Box 600 Wellington6140 New Zealand Department of Mechanical Engineering University of Minnesota MinneapolisMN55455 United States National Isotope Centre GNS Science PO Box 30368 Lower Hutt5010 New Zealand Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States

Ferrimagnets take the advantages of both ferromagnets and antiferromagnets making them promise for spintronic applications. Here we prepared ferrimagnetic Mn4N thin films with high Curie temperature and investigated the crystalline structure and magnetic properties affected by the Pd buffer layer. We demonstrated that both crystalline quality and perpendicular magnetic anisotropy (PMA) of Mn4N thin films are enhanced significantly due to the relaxation of tensile stress induced by the Pd buffer layer. We also demonstrated a fast spin precession at room temperature, almost 100 GHz, in Mn4N thin films. With the characteristics of high thermal stability, enhanced PMA by buffer layer and fast spin precession, Mn4N thin film is a promising material for spintronic applications. © 2025, CC0.

关键词： Ferrimagnetism

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Observation of the unidirectional magnetoresistance in antiferromagnetic insulator Fe2O3/Pt bilayers

arXiv

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arXiv 2022年

作者： Fan, Yihong Zhang, Pengxiang Han, Jiahao Lv, Yang Liu, Luqiao Wang, Jian-Ping Department of Electrical and Computer Engineering University of Minnesota 200 Union St. SE MinneapolisMN55455 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 77 Massachusetts Ave. Room 38-401 CambridgeMA02139 United States

Unidirectional magnetoresistance (UMR) has been observed in a variety of stacks with ferromagnetic/spin Hall material bilayer structures. In this work, we reported UMR in antiferromagnetic insulator Fe2O3/Pt structure. The UMR has a negative value, which is related to interfacial Rashba coupling and band splitting. Thickness-dependent measurement reveals a potential competition between UMR and the unidirectional spin Hall magnetoresistance (USMR). This work revealed the existence of UMR in antiferromagnetic insulators/heavy metal bilayers and broadens the way for the application of antiferromagnet-based spintronic devices. © 2022, CC BY.

关键词： Magnetoresistance

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Gigantic tunneling magnetoresistance in magnetic Weyl semimetal tunnel junctions

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Physical Review B 2021年第4期104卷 L041401-L041401页

作者： D. J. P. de Sousa C. O. Ascencio P. M. Haney J. P. Wang Tony Low Department of Electrical and Computer Engineering University of Minnesota Minneapolis Minnesota 55455 USA School of Physics and Astronomy University of Minnesota Minneapolis Minnesota 55455 USA Physical Measurement Laboratory National Institute of Standards and Technology Gaithersburg Maryland 20899-6202 USA

We investigate the tunneling magnetoresistance in magnetic tunnel junctions (MTJs) comprised of Weyl semimetal contacts. We show that chirality-magnetization locking leads to a gigantic tunneling magnetoresistance ratio, an effect that does not rely on spin filtering by the tunnel barrier. Our results indicate that the conductance in the antiparallel configuration is more sensitive to magnetization fluctations than in MTJs with normal ferromagnets, and predicts a TMR as large as 104 % when realistic magnetization fluctuations are accounted for. In addition, we show that the Fermi arc states give rise to a non-monotonic dependence of conductance on the misalignment angle between the magnetizations of the two contacts.

关键词： Spin current Spintronics Weyl semimetal

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Cell-by-Cell Line-of-Sight Probability Models Based on Real-World Base Station Deployment

Cell-by-Cell Line-of-Sight Probability Models Based on Real-...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Bassel Abou Ali Modad Xin Yu Hae Jin Song Yao-Yi Chiang Andreas F. Molisch Dept. of Electrical and Computer Engineering University of Southern California Los Angeles USA Spatial Sciences Institute University of Southern California Los Angeles USA Dept. of Computer Science and Engineering University of Minnesota Twin Cities Minneapolis USA

ISBN: (纸本)9781665435413

Knowing the wireless channel characteristics, particularly the existence of a line-of-sight (LOS) connection from the user equipment (UE) to the base station (BS), is key in wireless system development and deployments. The LOS becomes even more important in high frequency systems such as fifth generation (5G) mm-wave and terahertz (THz) systems where the difference in channel characteristics varies greatly from LOS to non-LOS (NLOS) situations. While existing LOS models such as the 3GPP model and others in the literature are valuable, they lack cell-by-cell specificity and/or do not generalize well to different environments. In this paper, we aim to close these gaps and propose generalized models derived from extensive real-world analysis in diverse environments. We also study the performance of our models in system-level simulations in terms of signal-to-interference-ratio (SIR) and coverage.

关键词： Wireless communication Base stations Line-of-sight propagation Probability Data models Power system reliability 3GPP

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Joint Attention-Guided Feature Fusion Network for Saliency Detection of Surface Defects

arXiv

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arXiv 2024年

作者： Jiang, Xiaoheng Yan, Feng Lu, Yang Wang, Ke Guo, Shuai Zhang, Tianzhu Pang, Yanwei Niu, Jianwei Xu, Mingliang The School of Computer and Artificial Intelligence Zhengzhou University Engineering Research Center of Intelligent Swarm Systems Ministry of Education National Supercomputing Center in Zhengzhou Zhengzhou450001 China The School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China The School of Information Science and Technology University of Science and Technology of China Hefei230026 China The School of Electrical Automation and Information Engineering Tianjin University Tianjin300072 China The State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Hangzhou Innovation Institute of Beihang University Hangzhou310051 China

Surface defect inspection plays an important role in the process of industrial manufacture and production. Though Convolutional Neural Network (CNN) based defect inspection methods have made huge leaps, they still confront a lot of challenges such as defect scale variation, complex background, low contrast, and so on. To address these issues, we propose a joint attention-guided feature fusion network (JAFFNet) for saliency detection of surface defects based on the encoder-decoder network. JAFFNet mainly incorporates a joint attention-guided feature fusion (JAFF) module into decoding stages to adaptively fuse low-level and high-level features. The JAFF module learns to emphasize defect features and suppress background noise during feature fusion, which is beneficial for detecting low-contrast defects. In addition, JAFFNet introduces a dense receptive field (DRF) module following the encoder to capture features with rich context information, which helps detect defects of different scales. The JAFF module mainly utilizes a learned joint channel-spatial attention map provided by high-level semantic features to guide feature fusion. The attention map makes the model pay more attention to defect features. The DRF module utilizes a sequence of multi-receptive-field (MRF) units with each taking as inputs all the preceding MRF feature maps and the original input. The obtained DRF features capture rich context information with a large range of receptive fields. Extensive experiments conducted on SD-saliency-900, Magnetic tile, and DAGM 2007 indicate that our method achieves promising performance in comparison with other state-of-the-art methods. Meanwhile, our method reaches a real-time defect detection speed of 66 FPS. Copyright © 2024, The Authors. All rights reserved.

关键词： Feature extraction

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Control when confidence is costly

arXiv

引用

arXiv 2024年

作者： Castillo, Itzel Olivos Schrater, Paul Pitkow, Xaq Department of Computer Science Rice University HoustonTX77005 United States Departments of Computer Science and Psychology University of Minnesota MinneapolisMN55455 United States Departments of Electrical and Computer Engineering and Computer Science Rice University HoustonTX77005 United States Neuroscience Institute Department of Machine Learning Carnegie Mellon University PittsburghPA15213 United States Department of Neuroscience Baylor College of Medicine HoustonTX77030 United States

We develop a version of stochastic control that accounts for computational costs of inference. Past studies identified efficient coding without control, or efficient control that neglects the cost of synthesizing information. Here we combine these concepts into a framework where agents rationally approximate inference for efficient control. Specifically, we study Linear Quadratic Gaussian (LQG) control with an added internal cost on the relative precision of the posterior probability over the world state. This creates a trade-off: an agent can obtain more utility overall by sacrificing some task performance, if doing so saves enough bits during inference. We discover that the rational strategy that solves the joint inference and control problem goes through phase transitions depending on the task demands, switching from a costly but optimal inference to a family of suboptimal inferences related by rotation transformations, each misestimate the stability of the world. In all cases, the agent moves more to think less. This work provides a foundation for a new type of rational computations that could be used by both brains and machines for efficient but computationally constrained control. © 2024, CC BY.

关键词： Stochastic systems

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