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arXiv 2021年

作者： Burnum-Johnson, Kristin E. Conrads, Thomas P. Drake, Richard R. Herr, Amy E. Iyengar, Ravi Kelly, Ryan T. Lundberg, Emma MacCoss, Michael J. Naba, Alexandra Nolan, Garry P. Pevzner, Pavel A. Rodland, Karin D. Sechi, Salvatore Slavov, Nikolai Spraggins, Jeffrey M. van Eyk, Jennifer E. Vidal, Marc Vogel, Christine Walt, David R. Kelleher, Neil L. The Environmental Molecular Sciences Laboratory Pacific Northwest National Laboratory RichlandWA United States Inova Women's Service Line Inova Health System Falls ChurchVA United States Cell and Molecular Pharmacology and Experimental Therapeutics Medical University of South Carolina CharlestonSC United States Department of Bioengineering University of California BerkeleyCA United States Department of Pharmacology and Systems Therapeutics Icahn School of Medicine at Mount Sinai New YorkNY United States Department of Chemistry and Biochemistry Brigham Young University ProvoUT United States Science for Life Laboratory KTH Royal Institute of Technology Stockholm Sweden Department of Genome Sciences University of Washington SeattleWA United States Department of Physiology and Biophysics University of Illinois at Chicago ChicagoIL United States Dept of Pathology Stanford University StanfordCA United States Department of Computer Science and Engineering University of California at San Diego San DiegoCA United States Biological Sciences Division Pacific Northwest National Laboratory RichlandWA United States National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health BethesdaMD United States Department of Bioengineering Northeastern University BostonMA United States Department of Chemistry Vanderbilt University NashvilleTN United States Advanced Clinical Biosystems Institute The Department of Biomedical Sciences Cedars-Sinai Medical Center Los AngelesCA United States Department of Genetics Harvard University CambridgeMA United States New York University Center for Genomics and Systems Biology New York University New YorkNY United States Department of Pathology Harvard Medical School Brigham and Women's Hospital Wyss Institute at Harvard University BostonMA United States Department of Chemistry Northwestern University EvanstonIL United States

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide provocative projections for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we offer potential futures for a next generation of disruptive approaches to define, quantify and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade. © 2021, CC0.

关键词： Proteins

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Data Correlation-Aware Resource Management in Wireless Virtual Reality (VR): An Echo State Transfer Learning Approach

arXiv

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arXiv 2019年

作者： Chen, Mingzhe Saad, Walid Yin, Changchuan Debbah, Mérouane Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA United States Mathematical and Algorithmic Sciences Lab Huawei France R and D Paris

Providing seamless connectivity for wireless virtual reality (VR) users has emerged as a key challenge for future cloud-enabled cellular networks. In this paper, the problem of wireless VR resource management is investigated for a wireless VR network in which VR contents are sent by a cloud to cellular small base stations (SBSs). The SBSs will collect tracking data from the VR users, over the uplink, in order to generate the VR content and transmit it to the end-users using downlink cellular links. For this model, the data requested or transmitted by the users can exhibit correlation, since the VR users may engage in the same immersive virtual environment with different locations and orientations. As such, the proposed resource management framework can factor in such spatial data correlation, so as to better manage uplink and downlink traffic. This potential spatial data correlation can be factored into the resource allocation problem to reduce the traffic load in both uplink and downlink. In the downlink, the cloud can transmit 360 contents or specific visible contents (e.g., user field of view) that are extracted from the original 360 contents to the users according to the users' data correlation so as to reduce the backhaul traffic load. In the uplink, each SBS can associate with the users that have similar tracking information so as to reduce the tracking data size. This data correlation-Aware resource management problem is formulated as an optimization problem whose goal is to maximize the users' successful transmission probability, defined as the probability that the content transmission delay of each user satisfies an instantaneous VR delay target. To solve this problem, a machine learning algorithm that uses echo state networks (ESNs) with transfer learning is introduced. By smartly transferring information on the SBS's utility, the proposed transfer-based ESN algorithm can quickly cope with changes in the wireless networking environment due to users' conten

关键词： Virtual reality

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Implications of Sea Breezes on Air Quality Monitoring in a Coastal Urban Environment: Evidence From High Resolution Modeling of NO2and O3

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Journal of Geophysical Research: Atmospheres 2023年第11期128卷 e2022JD037860-e2022JD037860页

作者： Bo Wang Jeffrey A. Geddes Taylor J. Adams Elena S. Lind Brian C. McDonald Jian He Colin Harkins Dan Li Gabriele G. Pfister Department of Earth and Environment Boston University MA Boston USA B. Wang Contribution: Conceptualization Methodology Formal analysis Investigation Resources Writing - original draft Writing - review & editing Visualization Contribution: Conceptualization Methodology Formal analysis Investigation Resources Data curation Writing - review & editing Supervision Project administration Funding acquisition Contribution: Resources Writing - review & editing Department of Electrical and Computer Engineering Virginia Tech VA Blacksburg USA Now at NASA Goddard Space Flight Center Greenbelt MD USA Chemical Sciences Laboratory NOAA Earth System Research Laboratories CO Boulder USA Cooperative Institute for Research in Environmental Sciences University of Colorado CO Boulder USA Contribution: Methodology Resources Writing - review & editing Atmospheric Chemistry Observations and Modeling Laboratory NCAR CO Boulder USA Contribution: Conceptualization Resources Writing - review & editing

Coastal urban environments face unique challenges associated with air quality-meteorology interactions. In this study, high resolution chemical transport modeling over the Greater Boston area was performed to improve our understanding of sea breezes impacts on the spatiotemporal variability of primary and secondary pollutants. We perform WRF-Chem simulations at 3 km resolution over June 22 to 10 July 2019 (a period that included 10 sea breeze occurrences), and use Pandora tropospheric NO 2 column, surface air quality monitoring, and vertical meteorological aircraft profiles for evaluation. The model generally reproduces observed spatiotemporal variability of air pollution during sea breezes well. Tropospheric columns of NO 2 predicted by the model and observed by the Pandora instrument show that sea breezes are associated with rapid increases and steep gradients in tropospheric NO 2 and confirm accumulation of local primary emissions. Spatial heterogeneity in tropospheric NO 2 is strongly governed by inland penetration lengths of the sea breeze front. Process diagnostics show that three sea-breeze days where O 3 observations recorded hourly concentrations >70 ppb have both efficient net chemical O 3 production in the boundary layer (>10 ppb/hr) and rapid O 3 convergence in the near-surface convergence zone (>20 ppb/hr). During sea breezes, interactions between photochemistry, the convergence zone inland penetration, and urban NO x titration effects, contribute to strong heterogeneity and high O 3 inland that is not captured by the current monitoring network. We discuss monitoring needs and model applications for the sea breeze scenarios, with broad implications for air quality monitoring in coastal urban environments. High resolution WRF-Chem modeling reproduces observed spatiotemporal variability of NO 2 and O 3 during sea breezes in the Greater Boston area Model results suggest high O 3 pollution and NO 2 column spatial variability associated with sea breezes is n

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Artificial impostors for location privacy preservation

arXiv

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arXiv 2018年

作者： Wang, Cheng Xie, Zhiyang Department of Computer Science and Engineering Tongji University Key Laboratory of Embedded System and Service Computing Ministry of Education China

The progress of location-based services has led to severe concerns about location privacy leakage. However, existing methods are still incompetent for effective and efficient location privacy preservation (LPP). They are often vulnerable under the identification attack with side information, or hard to be implemented due to the high computational complexity. In this paper, we pursue the high protection efficacy and low computational complexity simultaneously. We propose a scalable LPP method based on the paradigm of counterfeiting locations. To make fake locations extremely plausible, we forge them by synthesizing artificial impostors (AIs). The so-called AIs refer to the synthesized traces that have similar semantic features to the actual traces and do not contain any target location. We devise two dedicated techniques: the sampling-based synthesis method and population-level semantic model. They respectively play the significant roles in two critical steps of synthesizing AIs. We conduct the experiments on real datasets in two cities (Shanghai of China and Asturias of Spain) to validate the high efficacy and scalability of the proposed method. In these two datasets, the experimental results show that our method achieves the preservation efficacy of 97:68% and 96:24%, and the time spent for building generators is only 230:47 and 215:92 seconds, respectively. This study would give the research community new insights into improving the practicality of the state-of-the-art LPP paradigm via counterfeiting locations. Copyright © 2018, The Authors. All rights reserved.

关键词： Location

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Vision-based Semantic Mapping and Localization for Autonomous Indoor Parking

Vision-based Semantic Mapping and Localization for Autonomou...

引用

2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Huang, Yewei Zhao, Junqiao He, Xudong Zhang, Shaoming Feng, Tiantian Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China School of Surveying and Geo-Informatics Tongji University Shanghai China

ISBN: (纸本)9781538644522

In this paper, we proposed a novel and practical solution for the real-time indoor localization of autonomous driving in parking lots. High-level landmarks, the parking slots, are extracted and enriched with labels to avoid the aliasing of low-level visual features. We then proposed a robust method for detecting incorrect data associations between parking slots and further extended the optimization framework by dynamically eliminating suboptimal data associations. Visual fiducial markers are introduced to improve the overall precision. As a result, a semantic map of the parking lot can be established fully automatically and robustly. We experimented the performance of real-time localization based on the map using our autonomous driving platform TiEV, and the average accuracy of 0.3m track tracing can be achieved at a speed of 10kph. © 2018 IEEE.

关键词： Autonomous vehicles

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A Deep Learning Framework for Optimization of MISO Downlink Beamforming

arXiv

引用

arXiv 2019年

作者： Xia, Wenchao Zheng, Gan Zhu, Yongxu Zhang, Jun Wang, Jiangzhou Petropulu, Athina P. IEEE Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing210003 China Wolfson School of Mechanical Electrical and Manufacturing Engineering Loughborough University LeicestershireLE11 3TU United Kingdom School of Engineering and Digital Arts University of Kent KentCT2 7NT United Kingdom Department of Electrical & Computer Engineering Rutgers State University of New Jersey PiscatawayNJ08854

Beamforming is an effective means to improve the quality of the received signals in multiuser multiple-input-single-output (MISO) systems. This paper studies fast optimal downlink beamforming strategies by leveraging the powerful deep learning techniques. Traditionally, finding the optimal beamforming solution relies on iterative algorithms which leads to high computational delay and is thus not suitable for real-time implementation. In this paper, we propose a deep learning framework for the optimization of downlink beamforming. In particular, the solution is obtained based on convolutional neural networks and exploitation of expert knowledge, such as the uplink-downlink duality and the structure of known optimal solutions. Using this framework, we construct three beamforming neural networks (BNNs) for three typical optimization problems, i.e., the signal-to-interference-plus-noise ratio (SINR) balancing problem, the power minimization problem and the sum rate maximization problem. The BNNs for the former two problems adopt the supervised learning approach, while the BNN for the sum rate maximization problem employs a hybrid method of supervised and unsupervised learning to improve the performance beyond the state of the art. Simulation results show that with much reduced computational complexity, the BNNs can achieve near-optimal solutions to the SINR balancing and power minimization problems, and outperform the existing algorithms that maximize the sum rate. In summary, this work paves the way for fast realization of the optimal beamforming in multiuser MISO systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Beamforming

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Exploration of intercell wireless millimeter-wave communication in the landscape of intelligent metasurfaces

arXiv

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arXiv 2019年

作者： Tasolamprou, Anna C. Pitilakis, Alexandros Abadal, Sergi Tsilipakos, Odysseas Timoneda, Xavier Taghvaee, Hamidreza Mirmoosa, Mohammad Sajjad Liu, Fu Liaskos, Christos Tsioliaridou, Ageliki Kantartzis, Nikolaos V. Manessis, Dionysios Georgiou, Julius Cabellos-Aparicio, Albert Alarcón, Eduard Pitsillides, Andreas Akyildiz, Ian Tretyakov, Sergei A. Economou, Eleftherios N. Kafesaki, Maria Soukoulis, Costas M. Foundation for Research and Technology Hellas Heraklion Crete71110 Greece Electrical and Computer Engineering Aristotle University of Thessaloniki Department Thessaloniki54124 Greece Universitat Politècnica de Catalunya Barcelona Spain Department of Electronics and Nanoengineering Aalto University P.O. Box 15500 AaltoFI-00076 Finland System Integration and Interconnection Technologies Fraunhofer IZM Berlin Germany Department of Electrical and Computer Engineering University of Cyprus Cyprus Department of Computer Science University of Cyprus Cyprus Georgia Institute of Technology School of Electrical and Computer Engineering United States Department of Physics University of Crete Heraklion Crete70013 Greece Department of Materials Science and Technology University of Crete Heraklion Crete70013 Greece Ames Laboratory Department of Physics and Astronomy Iowa State University AmesIA50011 United States

Software-defined metasurfaces are electromagnetically ultra-thin, artificial components that can provide engineered and externally controllable functionalities. The control over these functionalities is enabled by the metasurface tunability, which is implemented by embedded electronic circuits that modify locally the surface resistance and reactance. Integrating controllers within the metasurface cells, able to intercommunicate and adaptively reconfigure it, thus imparting a desired electromagnetic operation, opens the path towards the creation of an artificially intelligent (AI) fabric where each unit cell can have its own sensing, programmable computing, and actuation facilities. In this work we take a crucial step towards bringing the AI metasurface technology to emerging applications, in particular exploring the wireless mm-wave intercell communication capabilities in a software-defined HyperSurface designed for operation is the microwave regime. We examine three different wireless communication channels within the landscape of the reflective metasurface: Firstly, in the layer where the control electronics of the HyperSurface lie, secondly inside a dedicated layer enclosed between two metallic plates, and, thirdly, inside the metasurface itself. For each case we examine the physical implementation of the mm-wave transponder nodes, we quantify communication channel metrics, and we identify complexity vs. performance trade-offs. Copyright © 2019, The Authors. All rights reserved.

关键词： Millimeter waves

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Common Limitations of Image Processing Metrics: A Picture Story

arXiv

引用

arXiv 2021年

作者： Reinke, Annika Tizabi, Minu D. Sudre, Carole H. Eisenmann, Matthias Rädsch, Tim Baumgartner, Michael Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Bankhead, Peter Benis, Arriel Blaschko, Matthew Buettner, Florian Cardoso, M. Jorge Chen, Jianxu Cheplygina, Veronika Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Engelhardt, Sandy Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hamprecht, Fred Hashimoto, Daniel A. Heckmann-Nötzel, Doreen Hirsch, Peter Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kavur, A. Emre Kenngott, Hannes Kleesiek, Jens Kleppe, Andreas Koehler, Sven Kofler, Florian Kopp-Schneider, Annette Kooi, Thijs Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moher, David Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Noyan, M. Alican Petersen, Jens Polat, Gorkem Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Rieke, Nicola Riegler, Michael A. Rivaz, Hassan Saez-Rodriguez, Julio Sánchez, Clara I. Schroeter, Julien Saha, Anindo Selver, M. Alper Sharan, Lalith Shetty, Shravya Smeden, Maarten V.A.N. Stieltjes, Bram Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben V.A.N. Varoquaux, Gaël Wiesenfarth, Manuel Yaniv, Ziv R. Jäger, Paul Maier-Hein, Lena Division of Intelligent Medical Systems and HI Helmholtz Imaging Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Intelligent Medical Systems Heidelberg Germany NCT Heidelberg DKFZ University Medical Center Heidelberg Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Division of Medical Image Computing Heidelberg Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Institute of Genetics and Cancer University of Edinburgh Edinburgh United Kingdom Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 - box 2441 Leuven3001 Belgium Frankfurt/Mainz DKFZ UCT Frankfurt-Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany Frankfurt Cancer Insititute Germany Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for St

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide. © 2021, CC BY.

关键词： Medical imaging

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Insulation Simulation Analysis of Press-Pack IGBT

Insulation Simulation Analysis of Press-Pack IGBT

引用

China International Electrical and Energy Conference (CIEEC)

作者： Yuzhe Liu Chaoqun Jiao Zhibin Zhao Chengzong Pang Yuanliang Fan School of Electrical Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China Department of Electrical Engineering and Computer Science Wichita State University Wichita USA Fujian Provincial Enterprise Key Laboratory of High Reliable Electric Power Distribution Technology State Grid Fujian Electric Power Research Institute Fuzhou China

ISBN: (数字)9781728116754

ISBN: (纸本)9781728116761

In high voltage applications such as power grid and rail transportation, IGBT devices generally operate under very harsh conditions, which places high demands on device reliability. In this paper, the electric field distribution of silicon chip termination area and press-pack IGBT package structure under high voltage reverse bias experimental conditions is simulated by Fem software. The results indicate the potential electrical insulation failure areas in the package model and the corresponding optimization measures are proposed. To some extent, the problem of breakdown discharge of IGBT devices during operation is alleviated.

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PISTA-SENSE-ResNet for Parallel MRI Reconstruction

arXiv

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arXiv 2019年

作者： Lu, Tieyuan Zhang, Xinlin Huang, Yihui Yang, Yonggui Guo, Gang Bao, Lijun Huang, Feng Guo, Di Qu, Xiaobo Xiamen University Xiamen China Department of Radiology The Second Affiliated Hospital of Xiamen Medical College Xiamen China Neusoft Medical System Shanghai China Fujian Provincial University Key Laboratory of Internet of Things Application Technology School of Computer and Information Engineering Xiamen University of Technology Xiamen China

Magnetic resonance imaging has been widely applied in clinical diagnosis, however, is limited by its long data acquisition time. Although imaging can be accelerated by sparse sampling and parallel imaging, achieving promising reconstruction images with a fast reconstruction speed remains a challenge. Recently, deep learning approaches have attracted a lot of attention for its encouraging reconstruction results but without a proper interpretability. In this letter, to enable high-quality image reconstruction for the parallel magnetic resonance imaging, we design the network structure from the perspective of sparse iterative reconstruction and enhance it with the residual structure. The experimental results of a public knee dataset show that compared with the optimization-based method and the latest deep learning parallel imaging methods, the proposed network has less error in reconstruction and is more stable under different acceleration factors. Copyright © 2019, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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