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Design and implementation of a noise temperature measurement system for the Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX)

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arXiv 2021年

作者： Kuhn, Emily R. Saliwanchik, Benjamin R.B. Harris, Maile Aich, Moumita Bandura, Kevin Chang, Tzu-Ching Cynthia Chiang, H. Crichton, Devin Ewall-Wice, Aaron Gumba, Austin A. Gupta, N. Kesebonye, Kabelo Calvin Kneib, Jean-Paul Kunz, Martin Moodley, Kavilan Newburgh, Laura B. Nistane, Viraj Naidoo, Warren Ölçek, Deniz Peterson, Jeffrey B. Refregier, Alexandre Sievers, Jonathan L. Ungerer, Corrie Sadr, Alireza Vafaei van Dyk, Jacques Weltman, Amanda Wulf, Dallas Department of Physics Yale University New HavenCT United States Department of Physics Brookhaven National Laboratory UptonNY United States School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Westville Campus Durban4041 South Africa Department of Computer Science and Electrical Engineering Center for Gravitational Waves and Cosmology West Virginia University MorgantownWV United States Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States Department of Physics McGill University MontréalQC Canada Institute for Particle Physics and Astrophysics ETH Zürich Zürich Switzerland Department of Astronomy and Physics UC BerkeleyCA United States Inter-University Centre for Astronomy and Astrophysics Post Bag 4 Ganeshkhind Pune411 007 India Observatoire de Sauverny Versoix1290 Switzerland Département de Physique Théorique Center for Astroparticle Physics University of Geneva Durban4041 South Africa Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban4041 South Africa Department of Physics Carnegie Mellon University PittsburghPA United States School of Chemistry and Physics University of KwaZulu-Natal Durban South Africa Ltd Pretoria South Africa Pronex Engineering Management Consultants CC Pretoria South Africa Department of Mathematics and Applied Mathematics University of Cape Town South Africa

This paper describes the design, implementation, and verification of a test-bed for determining the noise temperature of radio antennas operating between 400-800 MHz. The requirements for this test-bed were driven by the HIRAX experiment, which uses antennas with embedded amplification, making system noise characterization difficult in the laboratory. The test-bed consists of two large cylindrical cavities, each containing radio-frequency (RF) absorber held at different temperatures (300 K and 77 K), allowing a measurement of system noise temperature through the well-known ‘Y-factor’ method. The apparatus has been constructed at Yale, and over the course of the past year has undergone detailed verification measurements. To date, three preliminary noise temperature measurement sets have been conducted using the system, putting us on track to make the first noise temperature measurements of the HIRAX feed and perform the first analysis of feed repeatability. © 2021, CC BY.

关键词： Temperature measurement

A closed form for Jacobian reconstruction from timeseries and its application as an early warning signal in network dynamics

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arXiv 2019年

作者： Barter, Edmund Brechtel, Andreas Drossel, Barbara Gross, Thilo University of Bristol Department of Engineering Mathematics Merchant Venturers Building Woodland Road BristolBS8 1UB United Kingdom TU Darmstadt Fachbereich Physik Hochschulstrasse 12 Darmstadt64289 Germany UC Davis Department of Computer Science 1 Shields Av Davis Ca95616 United States

The Jacobian matrix of a dynamical system describes its response to perturbations. Conversely one can estimate the Jacobian matrix by carefully monitoring how the system responds to environmental noise. Here we present a closed form analytical solution for the calculation of a system's Jacobian from a timeseries. Being able to access a system's Jacobian enables us to perform a broad range of mathematical analyses by which deeper insights into the system can be gained. Here we consider in particular the computation of the leading Jacobian eigenvalue as an early warning signal for critical transition. To illustrate this approach we apply it to ecological meta-foodweb models, which are strongly nonlinear dynamical multi-layer networks. Our analysis shows that accurate results can be obtained, although the data demand of the method is still high. Copyright © 2019, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

General feature selection technique supporting sex-debiasing in chronic illness algorithms validated using wearable device data

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npj Women's Health

npj Women's Health 2024年第1期2卷 1-11页

作者： Jamison H. Burks Patrick Kasl Benjamin L. Smarr Lauryn Keeler Bruce Severine Soltani Varun Viswanath Wendy Hartogensis Frederick M. Hecht Ashley E. Mason Stephan Dilchert Subhasis Dasgupta Ilkay Altintas Amarnath Gupta Shu Chien-Gene Lay Department of Bioengineering University of California San Diego San Diego CA USA Halıcıoğlu Data Science Institute University of California San Diego San Diego CA USA UC San Diego Health Department of Biomedical Informatics University of California San Diego San Diego CA USA Bioinformatics and Systems Biology University of California San Diego San Diego CA USA Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA Osher Center for Integrative Health University of California San Francisco San Francisco CA USA Department of Management Zicklin School of Business Baruch College The City University of New York New York NY USA San Diego Supercomputer Center University of California San Diego San Diego CA USA

In tasks involving human health condition data, feature selection is heavily affected by data types, the complexity of the condition manifestation, and the variability in physiological presentation. One type of variability often overlooked or oversimplified is the effect of biological sex. As females have been chronically underrepresented in clinical research, we know less about how conditions manifest in females. Innovations in wearable technology have enabled individuals to generate high temporal resolution data for extended periods of time. With millions of days of data now available, additional feature selection pipelines should be developed to systematically identify sex-dependent variability in data, along with the effects of how many per-person data are included in analysis. Here we present a set of statistical approaches as a technique for identifying sex-dependent physiological and behavioral manifestations of complex diseases starting from longitudinal data, which are evaluated on diabetes, hypertension, and their comorbidity.

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Learning visual servoing with deep features and fitted Q-iteration 5

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Learning visual servoing with deep features and fitted Q-ite...

5th International Conference on Learning Representations, ICLR 2017

作者： Lee, Alex X. Levine, Sergey Abbeel, Pieter UC Berkeley Department of Electrical Engineering and Computer Sciences United States OpenAI United States International Computer Science Institute

Visual servoing involves choosing actions that move a robot in response to observations from a camera, in order to reach a goal configuration in the world. Standard visual servoing approaches typically rely on manually designed features and analytical dynamics models, which limits their generalization capability and often requires extensive application-specific feature and model engineering. In this work, we study how learned visual features, learned predictive dynamics models, and reinforcement learning can be combined to learn visual servoing mechanisms. We focus on target following, with the goal of designing algorithms that can learn a visual servo using low amounts of data of the target in question, to enable quick adaptation to new targets. Our approach is based on servoing the camera in the space of learned visual features, rather than image pixels or manually-designed keypoints. We demonstrate that standard deep features, in our case taken from a model trained for object classification, can be used together with a bilinear predictive model to learn an effective visual servo that is robust to visual variation, changes in viewing angle and appearance, and occlusions. A key component of our approach is to use a sample-efficient fitted Q-iteration algorithm to learn which features are best suited for the task at hand. We show that we can learn an effective visual servo on a complex synthetic car following benchmark using just 20 training trajectory samples for reinforcement learning. We demonstrate substantial improvement over a conventional approach based on image pixels or hand-designed keypoints, and we show an improvement in sample-efficiency of more than two orders of magnitude over standard model-free deep reinforcement learning algorithms. Videos are available at http://***/visual_servoing. © ICLR 2019 - Conference Track Proceedings. All rights reserved.

关键词： Reinforcement learning

Author Correction: General feature selection technique supporting sex-debiasing in chronic illness algorithms validated using wearable device data

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npj Women's Health

npj Women's Health 2024年第1期2卷 1页

TVM: An automated end-to-end optimizing compiler for deep learning

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arXiv 2018年

作者： Chen, Tianqi Moreau, Thierry Jiang, Ziheng Zheng, Lianmin Yan, Eddie Cowan, Meghan Shen, Haichen Wang, Leyuan Hu, Yuwei Ceze, Luis Guestrin, Carlos Krishnamurthy, Arvind Paul G. Allen School of Computer Science & Engineering University of Washington AWS Shanghai Jiao Tong University UC Davis Cornell

There is an increasing need to bring machine learning to a wide diversity of hardware devices. Current frameworks rely on vendor-specific operator libraries and optimize for a narrow range of server-class GPUs. Deploying workloads to new platforms – such as mobile phones, embedded devices, and accelerators (e.g., FPGAs, ASICs) – requires significant manual effort. We propose TVM, a compiler that exposes graph-level and operator-level optimizations to provide performance portability to deep learning workloads across diverse hardware back-ends. TVM solves optimization challenges specific to deep learning, such as high-level operator fusion, mapping to arbitrary hardware primitives, and memory latency hiding. It also automates optimization of low-level programs to hardware characteristics by employing a novel, learning-based cost modeling method for rapid exploration of code optimizations. Experimental results show that TVM delivers performance across hardware back-ends that are competitive with state-of-the-art, hand-tuned libraries for low-power CPU, mobile GPU, and server-class GPUs. We also demonstrate TVM’s ability to target new accelerator back-ends, such as the FPGA-based generic deep learning accelerator. The system is open sourced and in production use inside several major companies. Copyright © 2018, The Authors. All rights reserved.

关键词： Libraries

ICGM-FRAX: Iterative Cross Graph Matching for Hip Fracture Risk Assessment using Dual-energy X-ray Absorptiometry Images

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arXiv 2025年

作者： Zhao, Chen Shaik, Anjum Keyak, Joyce H. Lane, Nancy E. Deng, Jeffrey D. Su, Kuan-Jui Sha, Qiuying Shen, Hui Deng, Hong-Wen Zhou, Weihua Department of Computer Science Kennesaw State University 680 Arntson Dr MariettaGA30060 United States Department of Applied Computing Michigan Technological University 1400 Townsend Dr HoughtonMI49931 United States Department of Radiological Sciences Department of Biomedical Engineering Department of Mechanical and Aerospace Engineering University of California IrvineCA92697 United States Department of Internal Medicine Division of Rheumatology UC Davis Health SacramentoCA95817 United States Geisel School of Medicine Dartmouth College HanoverNH03755 United States Division of Biomedical Informatics and Genomics Tulane Center of Biomedical Informatics and Genomics Deming Department of Medicine Tulane University New OrleansLA70112 United States Department of Mathematical Sciences Michigan Technological University HoughtonMI49931 United States Center for Biocomputing and Digital Health Institute of Computing and Cybersystems Health Research Institute Michigan Technological University HoughtonMI49931 United States Department of Applied Computing Michigan Technological University 1400 Townsend Dr HoughtonMI49931 United States

Hip fractures represent a major health concern, particularly among the elderly, often leading decreased mobility and increased mortality. Early and accurate detection of at risk individuals is crucial for effective intervention. In this study, we propose Iterative Cross Graph Matching for Hip Fracture Risk Assessment (ICGM-FRAX), a novel approach for predicting hip fractures using Dual-energy X-ray Absorptiometry (DXA) images. ICGM-FRAX involves iteratively comparing a test (subject) graph with multiple template graphs representing the characteristics of hip fracture subjects to assess the similarity and accurately to predict hip fracture risk. These graphs are obtained as follows. The DXA images are separated into multiple regions of interest (RoIs), such as the femoral head, shaft, and lesser trochanter. Radiomic features are then calculated for each RoI, with the central coordinates used as nodes in a graph. The connectivity between nodes is established according to the Euclidean distance between these coordinates. This process transforms each DXA image into a graph, where each node represents a RoI, and edges derived by the centroids of RoIs capture the spatial relationships between them. If the test graph closely matches a set of template graphs representing subjects with incident hip fractures, it is classified as indicating high hip fracture risk. We evaluated our method using 547 subjects from the UK Biobank dataset, and experimental results show that ICGM-FRAX achieved a sensitivity of 0.9869, demonstrating high accuracy in predicting hip fractures. © 2025, CC BY.

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Pursuit-evasion of an Evader by Multiple Pursuers

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Pursuit-evasion of an Evader by Multiple Pursuers

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Alexander Von Moll David W. Casbeer Eloy Garcia Dejan Milutinović Controls Science Center of Excellence Air Force Research Laboratory WPAFB OH Department of Computer Engineering UC Santa Cruz Santa Cruz CA

In this paper, we extend the well-studied results of the two-pursuer, single-evader differential game to any number of pursuers. The main objective of this investigation is to exploit the benefits of cooperation amongst the pursuers in order to reduce the capture time of the evader. Computational complexity is a chief concern as this problem would need to be solved in an online fashion, e.g., in the case of autonomous unmanned aerial vehicles. A new geometric approach to solving the game is introduced and analyzed, which changes the problem of optimizing over continuous domains to a discrete combinatoric optimization. While past efforts at solving multiple pursuer problems have suffered from the curse of dimensionality, the geometric algorithms put forth here are shown to be scalable. Categorization and removal of redundant pursuers is the primary means by which scalability is achieved. The solution of this problem serves as a stepping stone to more complex problems such as the M-pursuer N-evader differential game.

关键词： Games Optimization Vehicle dynamics Military aircraft Electronic mail Aircraft Aircraft propulsion

OPTIMADE, an API for exchanging materials data

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arXiv 2021年

作者： Andersen, Casper W. Armiento, Rickard Blokhin, Evgeny Conduit, Gareth J. Dwaraknath, Shyam Evans, Matthew L. Fekete, Ádám Gopakumar, Abhijith Gražulis, Saulius Merkys, Andrius Mohamed, Fawzi Oses, Corey Pizzi, Giovanni Rignanese, Gian-Marco Scheidgen, Markus Talirz, Leopold Toher, Cormac Winston, Donald Aversa, Rossella Choudhary, Kamal Colinet, Pauline Curtarolo, Stefano Di Stefano, Davide Draxl, Claudia Er, Suleyman Esters, Marco Fornari, Marco Giantomassi, Matteo Govoni, Marco Hautier, Geoffroy Hegde, Vinay Horton, Matthew K. Huck, Patrick Huhs, Georg Hummelshøj, Jens Kariryaa, Ankit Kozinsky, Boris Kumbhar, Snehal Liu, Mohan Marzari, Nicola Morris, Andrew J. Mostofi, Arash A. Persson, Kristin A. Petretto, Guido Purcell, Thomas Ricci, Francesco Rose, Frisco Scheffler, Matthias Speckhard, Daniel Uhrin, Martin Vaitkus, Antanas Villars, Pierre Waroquiers, David Wolverton, Chris Wu, Michael Yang, Xiaoyu École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Materials Design and Informatics Unit Department of Physics Chemistry and Biology Linköping University Sweden Tilde Materials Informatics Straßmannstraße 25 Berlin10249 Germany Materials Platform for Data Science Sepapaja 6 Tallinn15551 Estonia Theory of Condensed Matter Group Cavendish Laboratory 19 J.J. Thomson Avenue CambridgeCB3 0HE United Kingdom Lawrence Berkeley Labs BerkeleyCA United States Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium Department of Physics King's College London London United Kingdom Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Institute of Biotechnology Life Science Center Vilnius University Saulétekio av. 7 VilniusLT-10257 Lithuania Institute of Computer Science Faculty of Mathematics and Informatics Vilnius University Naugarduko g. 24 VilniusLT-03225 Lithuania Fritz-Haber-Institut der Max-Planck-Gesellschaft Faradayweg 4-6 Berlin14195 Germany Center for Autonomous Materials Design Duke University DurhamNC27708 United States Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Humboldt-Universität zu Berlin Institut für Physik and IRIS Adlershof Berlin12489 Germany École Polytechnique Fédérale de Lausanne Sion1951 Switzerland Trieste34136 Italy Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany Materials Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Ansys 300 Rustat House 62 Clifton Rd CambridgeCB1 7EG United Kingdom De Zaale 20 Eindhoven5612 AJ Netherlands Department of Physics and Science of Advanced Materials Program Central Michigan University Mount PleasantMI48859 United States Argonne National Laboratory LemontIL60439 United States Thayer School of Engineering Dartmouth College HanoverNH03755 United States Los AltosCA940

The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification. © 2021, CC BY.

关键词： Specifications