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arXiv 2019年

作者： Hu, Jinsong Wu, Yongpeng Chen, Riqing Shu, Feng Wang, Jiangzhou School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Shanghai Jiao Tong University Shanghai China Faculty of Computer Science and Information Engineering Fujian Agriculture and Forestry University Fuzhou China School of Engineering and Digital Arts University of Kent CanterburyCT2 7NT United Kingdom

In this work, an detection strategy based on multiple antennas with beam sweeping is developed to detect UAV's potential transmission in wireless networks. Specifically, suspicious angle range where the UAV may present is divided into different sectors to potentially increase detection accuracy by using beamforming gain. We then develop the optimal detector and derive its detection error probability in a closed-form expression. We also utilize the Pinsker's inequality and Kullback-Leibler divergence to yield low-complex approximation for the detection error probability, based on which we obtain some significant insights on the detection performance. Our examination shows that there exists an optimal number of sectors that can minimize the detection error probability in some scenarios (e.g., when the number of measurements is limited). Intuitively, this can be explained by the fact that there exists an optimal accuracy of the telescope used to find an object in the sky within limited time period. Copyright © 2019, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Coordinate: A Spreadsheet-Programmable Augmented Reality Framework for Immersive Map-Based Visualizations

Coordinate: A Spreadsheet-Programmable Augmented Reality Fra...

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IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Aashiq Shaikh Linda Nguyen Alireza Bahremand Hannah Bartolomea Frank Liu Van Nguyen Derrick Anderson Robert LiKamWa School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA School of Arts Media and Engineering Arizona State University Tempe AZ USA School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ USA Department of Psychology Arizona State University Tempe AZ USA School of Public Affairs Arizona State University Tempe AZ USA

ISBN: (数字)9781728156040

ISBN: (纸本)9781728156057

Augmented reality devices are opening up a new design space for immersive visualizations. 3D spatial content can be overlaid onto existing physical visualizations for new insights into the data. We present Coordinate, a collaborative analysis tool for augmented reality visualizations of map-based data designed for mobile devices. Coordinate leverages a spreadsheet-programmable web interface paired with a contemporary augmented reality infrastructure for an easy-to-use tool that can provide spatial information to multiple users. It also offers an immersive visualization experience that seeks to enrich presentations for business, educational, and scientific discussions.

关键词： Conferences Artificial intelligence Virtual reality 6G mobile communication Integrated circuits

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Smart Virtual Care Centers in the Context of Performance and Privacy

Smart Virtual Care Centers in the Context of Performance and...

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International Conference on Telecommunications (ConTEL)

作者： Denis Gračanin R. Benjamin Knapp Thomas L. Martin Sarah Parker Dept. of Computer Science Virginia Tech Blacksburg VA USA Inst. for Creativity Arts and Technology Virginia Tech Blacksburg VA USA Dept. of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Virginia Tech Carilion Research Inst. Virginia Tech Blacksburg VA USA

US and Europe have been experiencing an unprecedented increase in the number of older adults. Increased life expectancy and increasingly aging population present challenges in terms of costs associated with elderly healthcare and wellbeing, as well as decreasing availability of health personnel. Similar trends are occurring in the rest of the world. There is a strong push to promote remote telehealth monitoring centers or virtual care centers (VCCs) as a way to address health care needs, especially for the aging population. technology advances, such as Internet of Things and Smart Built Environments, support proliferation of smart and secure telehealth care that can be implemented at all levels. Remote patient monitoring, combined with personalized interventions and coaching, serves as the foundation for VCCs. However, there are trade-offs with regard to privacy and changes in the living environment and the overall scalability. We need to explore how technology can be utilized to provide health services while protecting and preserving privacy of all stakeholders. A distributed VCC (DVCC), created from individual VCCs and crossing regional and national borders, can provide effective, continuous service with ability to adjust to unforeseen events and emergencies. We discuss a meta-model-based approach to protect patients' data while improving the efficiency of the care center personnel, which will allow remote care centers to more easily scale as need to provide round-the-clock monitoring.

关键词： Privacy Personnel Stress Data privacy Monitoring Medical services Biomedical monitoring

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Adaptive Fault-Tolerant Control of A Two-car High-speed Train Model with Inter-car Flexible Link and Traction Actuator Failures*

Adaptive Fault-Tolerant Control of A Two-car High-speed Trai...

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Asian Control Conference

作者： Zehui Mao Gang Tao Bin Jiang Xing-Gang Yan Yali Xue Ministry of Industry and Information Technology and Jiangsu Key Laboratory of Internet of Things and Control Technologies (NUAA) Key Laboratory of Navigation Control and Health Management Technologies of Advanced Aircraft (NUAA) Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA School of Engineering and Digital Arts University of Kent Canterbury United Kingdom

ISBN: (纸本)9781728102634

This paper studies the adaptive fault-tolerant tracking control problem for the high-speed trains with intercar flexible link and traction actuator failures. This study is focused on a benchmark model which, as a main dynamic unit of the CRH (China Railway High-speed) train, is a two-car dynamic system with a flexible link between two cars, for which the input acts on the second car and the output is the speed of the first car. This model is under parameter uncertainties and subject to uncertain actuator failures. For such an underactuated system, to ensure the first car tracking a desired speed trajectory, a coordinate transformation method is employed to decompose the system model into a control dynamics subsystem and a zero dynamics subsystem. Stability analysis is conducted to show that such a zero dynamic system is Lyapunov stable and is partially input-to-state stable. An adaptive fault-tolerant controller is developed which is able to ensure the closed-loop system signal boundedness and desired speed tracking, in the presence of the actuator failures and unknown system parameters. Simulation results from a realistic train dynamic model are presented to verify the effectiveness of the adaptive controller.

关键词： Automobiles Actuators Fault tolerance Fault tolerant systems Adaptation models Aerodynamics Adaptive systems

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Telecommunication-wavelength lasing in er-doped gan multiple quantum wells at room temperature

Telecommunication-wavelength lasing in er-doped gan multiple...

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Advanced Solid State Lasers, ASSL 2018

作者： Ho, V.X. Al Tahtamouni, T.M. Wang, Y. Jiang, H.X. Lin, J.Y. Zavada, J.M. Vinh, N.Q. Department of Physics Center for Soft Matter and Biological Physics Virginia Tech BlacksburgVA24061 United States Materials Science and Technology Program College of Arts and Sciences Qatar University Doha2713 Qatar Department of Electrical and Computer Engineering Texas Tech University LubbockTX79409 United States Department of Electrical and Computer Engineering New York University BrooklynNY11201 United States

We report the realization of room-temperature, stimulated-emission in Er-doped-GaN multiple-quantum-wells at the 1.5-µm. Structures were grown by MOCVD and lasing was confirmed by threshold-behaviors of emission-... 详细信息

ISBN: (纸本)9781943580484

关键词： Semiconductor quantum wells

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Transfer properties of touch elicited waves: Effect of posture and contact conditions 7

Transfer properties of touch elicited waves: Effect of postu...

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7th IEEE World Haptics Conference, WHC 2017

作者： Schafer, Harald Wells, Zachary Shao, Yitian Visell, Yon Department of Electrical and Computer Engineering Media Arts and Technology Program California NanoSystems Institute University of California Santa BarbaraCA93106 United States

ISBN: (纸本)9781509014255

During haptic interaction with touched objects, contact with the skin elicits mechanical signals that propagate rapidly to distances removed from the location of contact. Prior research has shown that these touch elicited mechanical signals travel predominantly as waves, and during manual touch, reach distances spanning the entire hand. While the structure in these signals is well preserved across distance, it is unknown how the propagation of these signals from the contact locus to other areas of the hand or finger depend on posture or contact conditions. To address this, we measured empirical transfer functions from a contacting plate that stimulated the fingertip to other sites on the finger, and analyzed the dependence of the corresponding frequency domain transfer functions on location, posture, and contact forces. The results suggest that the frequency and spatial dependence of these transfer functions varied consistently, and encoded contact conditions and relative contact location. Greatest variation was observed in the low or high frequency ranges of vibrotactile sensation, and at large distances from the contact surface. In contrast, mechanical information in the frequency range from 100 to 200 Hz was well preserved at large distances, and across conditions, indicating that tactile information in this frequency range is transmitted to other finger locations in a manner that is relatively invariant to the conditions and location of touch contact. The results may refine current understanding of the biomechanics of cutaneous wave propagation in the hand, may hold implications for understanding information content in touch-related cutaneous waves, and could hold inform the design of tactile displays worn on the skin. © 2017 IEEE.

关键词： Location

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Anonymization of labeled TOF-MRA images for brain vessel segmentation using generative adversarial networks

arXiv

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arXiv 2020年

作者： Kossen, Tabea Subramaniam, Pooja Madai, Vince I. Hennemuth, Anja Hildebrand, Kristian Hilbert, Adam Sobesky, Jan Livne, Michelle Galinovic, Ivana Khalil, Ahmed A. Fiebach, Jochen B. Frey, Dietmar CLAIM - Charité Lab for AI in Medicine Charité Universitätsmedizin Berlin Germany Department of Computer Engineering and Microelectronics Computer Vision & Remote Sensing Technical University Berlin Berlin Germany Department of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany School of Computing and Digital Technology Faculty of Computing Engineering and the Built Environment Birmingham City University Birmingham United Kingdom Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine Charité Universitätsmedizin Berlin Berlin Germany Fraunhofer MEVIS Bremen Germany Department VI Computer Science and Media Beuth University of Applied Sciences Berlin Germany Johanna-Etienne-Hospital Neuss Germany Centre for Stroke Research Berlin Charité Universitätsmedizin Berlin Berlin Germany Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany Mind Brain Body Institute Berlin School of Mind and Brain Humboldt University Berlin Berlin Germany Berlin Institute of Health Berlin Germany

Anonymization and data sharing are crucial for privacy protection and acquisition of large datasets for robust medical image analysis. This represents a major challenge, especially for brain imaging research. Here, the unique structure of brain images allows for potential re-identification and thus requires anonymization beyond conventional methods. Generative adversarial networks (GANs) have the potential to provide anonymous images while maintaining their predictive properties. Analyzing brain vessel segmentation as a use case, we trained 3 GAN architectures on time-of-flight (TOF) magnetic resonance angiography (MRA) patches of patients with cerebrovascular disease for image-label pair generation: 1) Deep convolutional GAN, 2) Wasserstein-GAN with gradient penalty (WGAN-GP) and 3) WGAN-GP with spectral normalization (WGAN-GP-SN). First, the synthesized image-labels from each GAN architecture were used to train a U-net for vessel segmentation. The U-nets were then tested on real patient data. In total, 66 patients were used for this analysis. In a second step, we simulated the application of our synthetic patches in a transfer learning approach using a second, independent dataset. Here, for an increasing number of up to 15 patients we evaluated vessel segmentation model performance on real data with and without pre-training on generated patches. Finally, performance for all models was assessed by the Dice Similarity Coefficient (DSC) and the 95th percentile of the Hausdorff Distance (95HD). Comparing the 3 GAN architectures, the U-net model trained on synthetic data generated by the WGAN-GP-SN showed the highest performance to predict brain vessels (DSC/95HD 0.82/28.97) benchmarked by the U-net trained on real data (0.89/26.61). The transfer learning approach showed superior performance for the same GAN architecture compared to no pre-training, especially for one labeled patient only (DSC/95HD 0.91/25.68 compared to DSC/95HD 0.85/27.36). In a brain imaging segment

关键词： Image segmentation

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Author Correction: Disrupting cellular memory to overcome drug resistance

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Nature communications 2024年第1期15卷 4264页

作者： Guillaume Harmange Raúl A Reyes Hueros Dylan L Schaff Benjamin Emert Michael Saint-Antoine Laura C Kim Zijian Niu Shivani Nellore Mitchell E Fane Gretchen M Alicea Ashani T Weeraratna M Celeste Simon Abhyudai Singh Sydney M Shaffer Cellular and Molecular Biology Graduate Group Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Biochemistry and Molecular Biophysics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Bioengineering School of Engineering and Applied Sciences University of Pennsylvania Philadelphia PA USA. Division of Biology and Biological Engineering California Institute of Technology Pasadena CA 91125 USA. Department of Electrical and Computer Engineering University of Delaware Newark DE 19716 USA. Abramson Family Cancer Research Institute Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Chemistry College of the Arts and Sciences University of Pennsylvania Philadelphia PA USA. Department of Physics College of the Arts and Sciences University of Pennsylvania Philadelphia PA USA. Department of Biology College of the Arts and Sciences University of Pennsylvania Philadelphia PA USA. The Wharton School University of Pennsylvania Philadelphia PA USA. Cancer Signaling and Microenvironment Research Program Fox Chase Cancer Center Philadelphia PA USA. Department of Biochemistry and Molecular Biology Johns Hopkins School of Public Health Baltimore MD USA. Sidney Kimmel Cancer Center Johns Hopkins School of Medicine Baltimore MD USA. Department of Cell and Developmental Biology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Bioengineering School of Engineering and Applied Sciences University of Pennsylvania Philadelphia PA USA. sydshaffer@***. Department of Pathology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. sydshaffer@***.

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Gravity Spy: Lessons Learned and a Path Forward

arXiv

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arXiv 2023年

作者： Zevin, Michael Jackson, Corey B. Doctor, Zoheyr Wu, Yunan Østerlund, Carsten Johnson, L. Clifton Berry, Christopher P.L. Crowston, Kevin Coughlin, Scott B. Kalogera, Vicky Banagiri, Sharan Davis, Derek Glanzer, Jane Hao, Renzhi Katsaggelos, Aggelos K. Patane, Oli Sanchez, Jennifer Smith, Joshua Soni, Siddharth Trouille, Laura Walker, Marissa Aerith, Irina Domainko, Wilfried Baranowski, Victor-Georges Niklasch, Gerhard Téglás, Barbara Zooniverse The Adler Planetarium 1300 South DuSable Lake Shore Drive ChicagoIL60605 United States Kavli Institute for Cosmological Physics The University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Enrico Fermi Institute The University of Chicago 933 East 56th Street ChicagoIL60637 United States Information School University of Wisconsin–Madison 600 N Park Street MadisonWI53706 United States Northwestern University 1800 Sherman Ave EvanstonIL60201 United States Department of Electrical and Computer Engineering Northwestern University 2145 Sheridan Road EvanstonIL60208 United States School of Information Studies Syracuse University 343 Hinds Hall SyracuseNY13210 United States SUPA School of Physics and Astronomy University of Glasgow Kelvin Building University Ave Glasgow8QQ G12 United Kingdom Department of Physics and Astronomy Northwestern University 2145 Sheridan Road EvanstonIL60208 United States LIGO Laboratory California Institute of Technology 1200 East California Boulavard PasadenaCA91125 United States Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton RougeLA70803 United States LIGO Hanford Observatory 127124 N Route 10 Hanford WA99354 United States The Nicholas and Lee Begovich Center for Gravitational-Wave Physics and Astronomy California State University Fullerton 800 N. State College Blvd FullertonCA92831 United States LIGO Laboratory Massachusetts Institute of Technology 185 Albany Street CambridgeMA02139 United States Department of Physics Computer Science and Engineering Christopher Newport University One Avenue of the Arts Newport NewsVA23606 United States Cedar Falls IA United States Hermagor Austria Sorbonne Paris Nord University 99 Avenue Jean Baptiste Clément Villetaneuse93430 France ConSol Software GmbH St.-Cajetan-Strasse 43 Munich81669 Germany Budapest Hungary Gravity Spy Moderator

The Gravity Spy project aims to uncover the origins of glitches, transient bursts of noise that hamper analysis of gravitational-wave data. By using both the work of citizen-science volunteers and machine-learning algorithms, the Gravity Spy project enables reliable classification of glitches. Citizen science and machine learning are intrinsically coupled within the Gravity Spy framework, with machine-learning classifications providing a rapid first-pass classification of the dataset and enabling tiered volunteer training, and volunteer-based classifications verifying the machine classifications, bolstering the machine-learning training set and identifying new morphological classes of glitches. These classifications are now routinely used in studies characterizing the performance of the LIGO gravitational-wave detectors. Providing the volunteers with a training framework that teaches them to classify a wide range of glitches, as well as additional tools to aid their investigations of interesting glitches, empowers them to make discoveries of new classes of glitches. This demonstrates that, when giving suitable support, volunteers can go beyond simple classification tasks to identify new features in data at a level comparable to domain experts. The Gravity Spy project is now providing volunteers with more complicated data that includes auxiliary monitors of the detector to identify the root cause of glitches. © 2023, CC BY.

关键词： Machine learning

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Coarse-to-fine annotation enrichment for semantic segmentation learning

arXiv

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arXiv 2018年

作者： Luo, Yadan Wang, Ziwei Huang, Zi Yang, Yang Zhao, Cong School of Information Technology and Electrical Engineering University of Queensland Center for Future Media School of Computer Science and Engineering University of Electronic Science and Technology of China DJI Innovation Inc

Rich high-quality annotated data is critical for semantic segmentation learning, yet acquiring dense and pixel-wise ground-truth is both labor- and time-consuming. Coarse annotations (e.g., scribbles, coarse polygons) offer an economical alternative, with which training phase could hardly generate satisfactory performance unfortunately. In order to generate high-quality annotated data with a low time cost for accurate segmentation, in this paper, we propose a novel annotation enrichment strategy, which expands existing coarse annotations of training data to a finer scale. Extensive experiments on the Cityscapes and PASCAL VOC 2012 benchmarks have shown that the neural networks trained with the enriched annotations from our framework yield a significant improvement over that trained with the original coarse labels. It is highly competitive to the performance obtained by using human annotated dense annotations. The proposed method also outperforms among other state-of-the-art weakly-supervised segmentation methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Semantic Segmentation

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