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arXiv 2018年

作者： Zhong, Guoqiang Gao, Wei Liu, Yongbin Yang, Youzhao Department of Computer Science and Technology Ocean University of China Qingdao266100 China Fudan Univesity Department of Electrical and Computer Engineering College of Computer and Information Science Northeastern University BostonMA02115 United States

In recent years, research on image generation methods has been developing fast. The auto-encoding variational Bayes method (VAEs) was proposed in 2013, which uses variational inference to learn a latent space from the image database and then generates images using the decoder. The generative adversarial networks (GANs) came out as a promising framework, which uses adversarial training to improve the generative ability of the generator. However, the generated pictures by GANs are generally blurry. The deep convolutional generative adversarial networks (DCGANs) were then proposed to leverage the quality of generated images. Since the input noise vectors are randomly sampled from a Gaussian distribution, the generator has to map from a whole normal distribution to the images. This makes DCGANs unable to reflect the inherent structure of the training data. In this paper, we propose a novel deep model, called generative adversarial networks with decoder-encoder output noise (DE-GANs), which takes advantage of both the adversarial training and the variational Bayesain inference to improve the performance of image generation. DE-GANs use a pre-trained decoder-encoder architecture to map the random Gaussian noise vectors to informative ones and pass them to the generator of the adversarial networks. Since the decoder-encoder architecture is trained by the same images as the generators, the output vectors could carry the intrinsic distribution information of the original images. Moreover, the loss function of DE-GANs is different from GANs and DCGANs. A hidden-space loss function is added to the adversarial loss function to enhance the robustness of the model. Extensive empirical results show that DE-GANs can accelerate the convergence of the adversarial training process and improve the quality of the generated images. Copyright © 2018, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Inverse Design Methods: Inverse Design Strategies for 3D Surfaces Formed by Mechanically Guided Assembly (Adv. Mater. 14/2020)

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Advanced Materials 2020年第14期32卷

作者： Zhichao Fan Yiyuan Yang Fan Zhang Zheng Xu Hangbo Zhao Taoyi Wang Honglie Song Yonggang Huang John A. Rogers Yihui Zhang Applied Mechanics Laboratory Department of Engineering Mechanics Center for Flexible Electronics Technology Tsinghua University Beijing 100084 P. R. China Departments of Mechanical Engineering Northwestern University Evanston IL 60208 USA The State Key Laboratory for Manufacturing and Systems Engineering School of Mechanical Engineering Xi'an Jiaotong University Xi'an 710049 P. R. China Center for Bio‐Integrated Electronics Northwestern University Evanston IL 60208 USA Department of Physics Tsinghua University Beijing 100084 P. R. China Departments of Civil and Environmental Engineering Mechanical Engineering and Materials Science and Engineering Center for Bio‐Integrated Electronics Northwestern University Evanston IL 60208 USA Department of Materials Science and Engineering Biomedical Engineering Neurological Surgery Chemistry Mechanical Engineering Electrical Engineering and Computer Science Simpson Querrey Institute and Feinberg Medical School Center for Bio‐Integrated Electronics Northwestern University Evanston IL 60208 USA

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Achieving a quantum smart workforce

arXiv

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arXiv 2020年

作者： Aiello, Clarice D. Awschalom, D.D. Bernien, Hannes Brower-Thomas, Tina Brown, Kenneth R. Brun, Todd A. Caram, Justin R. Chitambar, Eric Di Felice, Rosa Fox, Michael F.J. Haas, Stephan Holleitner, Alexander W. Hudson, Eric R. Hunt, Jeffrey H. Joynt, Robert Koziol, Scott Lewandowski, H.J. McClure, Douglas T. Palsberg, Jens Passante, Gina Pudenz, Kristen L. Richardson, Christopher J.K. Rosenberg, Jessica L. Ross, R.S. Saffman, Mark Singh, M. Steuerman, David W. Stark, Chad Thijssen, Jos Vamivakas, A. Nick Whitfield, James D. Zwickl, Benjamin M. Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA90095 United States Pritzker School of Molecular Engineering University of Chicago ChicagoIL60637 United States Department of Physics University of Chicago ChicagoIL60637 United States Center for Molecular Engineering and Materials Science Division Argonne National Laboratory LemontIL60439 United States Howard University Graduate School WashingtonDC20059 United States Center for Integrated Quantum Materials Howard University PI WashingtonDC20059 United States Departments of Electrical and Computer Engineering Chemistry and Physics Duke University DurhamNC27708 United States Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States UCLA Department of Chemistry and Biochemistry Center for Quantum Science and Engineering University of California – Los Angeles Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of Illinois Urbana-ChampaignIL61801 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States JILA National Institute of Standards and Technology University of Colorado BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States Garching85748 Germany UCLA Center for Quantum Science and Engineering University of California – Los Angeles Los AngelesCA90095 United States Boeing Company El SegundoCA90245 United States Department of Physics University of Wisconsin-Madison MadisonWI53706 United States Department of Electrical and Computer Engineering Baylor University WacoTX76798 United States Department of Physics University of Colorado BoulderCO80309 United States IBM T.J. Watson Research Center Yorktown HeightsNY

Interest in building dedicated Quantum Information science and engineering (QISE) education programs has greatly expanded in recent years. These programs are inherently convergent, complex, often resource intensive and likely require collaboration with a broad variety of stakeholders. In order to address this combination of challenges, we have captured ideas from many members in the community. This manuscript not only addresses policy makers and funding agencies (both public and private and from the regional to the international level) but also contains needs identified by industry leaders and discusses the difficulties inherent in creating an inclusive QISE curriculum. We report on the status of eighteen post-secondary education programs in QISE and provide guidance for building new programs. Lastly, we encourage the development of a comprehensive strategic plan for quantum education and workforce development as a means to make the most of the ongoing substantial investments being made in QISE. Copyright © 2020, The Authors. All rights reserved.

关键词： Personnel

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Direction of Slip Detection for Adaptive Grasp Force Control with a Dexterous Robotic Hand

Direction of Slip Detection for Adaptive Grasp Force Control...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Moaed A. Abd Iker J. Gonzalez Thomas C. Colestock Benjamin A. Kent Erik D. Engeberg Department of Ocean & Mechanical Engineering Florida Atlantic University Boca Raton FL USA Department of Computer & Electrical Engineering & Computer Science Florida Atlantic University Boca Raton FL USA Department of Mechanical Engineering University of Akron Akron OH USA

A novel method of tactile communication among human-robot and robot-robot collaborative teams is developed for the purpose of adaptive grasp control of dexterous robotic hands. Neural networks are applied to the problem of classifying the direction objects slide against different tactile fingertip sensors in real-time. This ability to classify the direction that an object slides in a dexterous robotic hand was used for adaptive grasp synergy control to afford context dependent robotic reflexes in response to the direction of grasped object slip. Case studies with robot-robot and human-robot collaborative teams successfully demonstrated the feasibility; when object slip in the direction of gravity (towards the ground) was detected, the dexterous hand increased the grasp force to prevent dropping the object. When a human or robot applied an upward force to cause the grasped object to slip upward, the dexterous hand was programmed to release the object into the hand of the other team member. This method of adaptive grasp control using direction of slip detection can improve the efficiency of human-robot and robot-robot teams.

关键词： Robot sensing systems Real-time systems Surface impedance Training Electrodes

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Cloth manipulation using random-forest-based imitation learning

arXiv

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arXiv 2018年

作者： Jia, Biao Pan, Zherong Hu, Zhe Pan, Jia Manocha, Dinesh Department of Computer Science University of Maryland College Park United States Department of Computer Science University of North Carolina Chapel Hill United States Department of Mechanical Biomedical Engineering City University of Hong Kong Department of Computer Science University of Hong Kong Departments of Computer Science and Electrical & Computer Engineering University of Maryland College Park United States

We present a novel approach for manipulating highDOF deformable objects such as cloth. Our approach uses a random-forest-based controller that maps the observed visual features of the cloth to an optimal control action of the manipulator. The topological structure of this random-forest is determined automatically based on the training data, which consists of visual features and control signals. The training data is constructed online using an imitation learning algorithm. We have evaluated our approach on different cloth manipulation benchmarks such as flattening, folding, and twisting. In all these tasks, we have observed convergent behavior for the random-forest. On convergence, the random-forest-based controller exhibits superior robustness to observation noise compared with other techniques such as convolutional neural networks and nearest neighbor searches. Copyright © 2018, The Authors. All rights reserved.

关键词： Controllers

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The Development of Raspi-Met System with Raspberry Pi3 for Meteorological Monitoring in Remote Areas

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IOP Conference Series: Earth and Environmental science 2020年第1期540卷

作者： Wayan Suparta Institute of Ocean and Earth Sciences University of Malaya 50603 Kuala Lumpur Malaysia Deparment of Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Institut Teknologi dan Kesehatan Jakarta Department of Electrical Engineering Bekasi City West Java 17411 Indonesia

The development of autonomous weather station systems using Raspberry Pi3 as a new alternative, named as 'Raspi-Met' to enhance conventional meteorological systems is reported in this paper. Today, a weather station with a compact size is required due to limited space and cost involved. Thus, this paper aims to design an application system using Raspberry Pi3 which is connected to Vaisala PTU300 sensors as Automatic Weather Station (AWS). The Python language under LINUX has been employed to design a graphical user interface (GUI) for a real-time monitoring system, acquisition process, and displaying three meteorological parameters at desired intervals. Data storage management and daily file in a text (*.txt) format have been created to archive historical data. The RTC module has also been developed and connected to Raspberry Pi3 to synchronize and maintain the time and date of the measurement system after the power is on. The system was installed at Carlini Base, Antarctica and has the ability to measure the surface pressure (P), temperature (T), and relative humidity (H). The results have been tested and validated that the system is capable as an AWS in the Antarctic Peninsula. The development of Raspi-Met system exhibits remarkable measurements of meteorological parameters for remote areas and the database organization becomes more efficient and practical.

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P086 The organization of sleep-wake patterns around daily schedules in college students

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Sleep Advances 2021年第SUPPLEMENT_1期2卷 A49-A49页

作者： Lu, S Klerman, E Stone, J McHill, A Barger, L Sano, A Czeisler, C Rajaratnam, S Phillips, A Turner Institute for Brain and Mental Health School of Psychological Sciences Monash University Clayton Australia Department of Neurology Massachusetts General Hospital Boston USA Division of Sleep and Circadian Disorders Departments of Medicine and Neurology Brigham and Women’s Hospital Boston USA Division of Sleep Medicine Harvard Medical School Boston USA Oregon Institute of Occupational Health Sciences Oregon Health and Science University Portland USA Department of Electrical and Computer Engineering Rice University Houston USA

A potential contributor to insufficient sleep among college students is their daily schedule, with sleep sacrificed for other waking activities. We investigated how daily schedules predict day-to-day sleep-wake timing in college students. 223 undergraduate college students (M±SD = 19.2±1.4 years, 37% females) attending a Massachusetts university in the US between 2013–2016 were monitored for approximately 30 days during semester. Sleep-wake timing was measured using daily online sleep diaries and wrist-actigraphy. Daily schedules were measured using daily online diaries that included self-reported timing and duration of academic, exercise-based, and extracurricular activities, and duration of self-study. Linear mixed models were used to examine the association between sleep-wake patterns and daily schedules at both the between-person and within-person levels. An earlier start time of the first-reported activity predicted earlier sleep onset (between and within: p<.001) and shorter total sleep time (within: p<.001) for the previous night, as well as earlier wake onset on the corresponding day (between and within: p<.001). A later end time of the last-reported activity predicted later sleep onset (within: p=.002) and shorter total sleep time (within: p=.02) on that night. A more intense daily schedule (i.e., greater total duration of reported activities) predicted an earlier wake onset time (between: p=.003, within: p<.001), a later sleep onset time (within: p<.001), a shortened total night-time sleep duration (between: p=.03, within: p<.001), and greater sleep efficiency (within: p<.001). These results indicate that college students may organize their sleep and wake times based on their daily schedule.

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Improving positioning accuracy of the mobile laser scanning in GPS-denied environments: An experimental case study

arXiv

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arXiv 2019年

作者： Liu, Wi Li, Zhixiong Sun, Shuaishuai Malekian, Reza Ma, Zhenjun Li, Weihua School of Mechanical and Electrical Engineering China University of Mining and Technology Xuzhou221116 China Jiangsu Collaborative Innovation Center of Intelligent Mining Equipment China University of Mining and Technology Xuzhou210008 China School of Engineering Ocean University of China Tsingdao266100 China School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong WollongongNSW2522 Australia New Industry Creation Hatchery Center Tohoku University Sendai980-8577 Japan Department of Computer Science and Media Technology Malmö University Malmö20506 Sweden

The positioning accuracy of the mobile laser scanning (MLS) system can reach the level of centimeter under the conditions where GPS works normally. However, in GPS-denied environments this accuracy can be reduced to the decimeter or even the meter level because the observation mode errors and the boresight alignment errors of MLS cannot be calibrated or corrected by the GPS signal. To bridge this research gap, this paper proposes a novel technique that appropriately incorporates the robust weight total least squares (RWTLS) and the full information maximum likelihood optimal estimation (FIMLOE) to improve the positioning accuracy of the MLS system under GPS-denied environment. First of all, the coordinate transformation relationship and the observation parameters vector of MLS system are established. Secondly, the RWTLS algorithm is used to correct the 3D point observation model;then the uncertainty propagation parameter vector and the boresight alignment errors between the laser scanner frame and the IMU frame are calibrated by FIMLOE. Lastly, experimental investigation in indoor scenarios was performed to evaluate the effectiveness of the proposed method. The experimental results demonstrate that the proposed method is able to significantly improve the positioning accuracy of an MLS system in GPS-denied environments. Copyright © 2019, The Authors. All rights reserved.

关键词： Global positioning system

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Automated Abdominal Aortic Calcification Assessment and Major Adverse Cardiovascular Events in People Undergoing Osteoporosis Screening

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Heart, Lung and Circulation 2024年 33卷 S394-S395页

作者： C. Smith M. Sim Z. Illyas S. Gilani D. Suter S. Reid B. Monchka M. Jafari Jozani G. Figtree J. Schousboe W. Leslie J. Lewis Nutrition & Health Innovation Research Institute Edith Cowan University Perth WA Australia Medical School University of Western Australia Perth WA Australia Centre for AI&ML School of Science Edith Cowan University Perth WA Australia Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada George and Fay Yee Centre for Healthcare Innovation University of Manitoba Winnipeg MB Canada Department of Statistics University of Manitoba Winnipeg MB Canada Faculty of Health and Medicine The University of Sydney Sydney NSW Australia Kolling Institute of Medical Research St Leonards NSW Australia Park Nicollet Clinic and HealthPartners Institute HealthPartners Minneapolis MN USA Division of Health Policy and Management University of Minnesota Minneapolis MN USA Departments of Medicine and Radiology University of Manitoba Winnipeg MB Canada Centre for Kidney Research Children's Hospital at Westmead School of Public Health Sydney Medical School The University of Sydney Sydney NSW Australia

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Author Correction: Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach

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NPJ digital medicine 2024年第1期7卷 93页

作者： Rohaid Ali Ian D Connolly Oliver Y Tang Fatima N Mirza Benjamin Johnston Hael F Abdulrazeq Rachel K Lim Paul F Galamaga Tiffany J Libby Neel R Sodha Michael W Groff Ziya L Gokaslan Albert E Telfeian John H Shin Wael F Asaad James Zou Curtis E Doberstein Department of Neurosurgery Rhode Island Hospital and The Warren Alpert Medical School of Brown University Providence RI USA. ali.rohaid@***. Norman Prince Neurosciences Institute Providence RI USA. ali.rohaid@***. Department of Neurosurgery Massachusetts General Hospital Boston MA USA. Department of Neurosurgery Rhode Island Hospital and The Warren Alpert Medical School of Brown University Providence RI USA. Department of Dermatology The Warren Alpert Medical School of Brown University Providence RI USA. Department of Neurosurgery Brigham and Women's Hospital Boston MA USA. Norman Prince Neurosciences Institute Providence RI USA. Department of Surgery & Division of Cardiothoracic Surgery Rhode Island Hospital and The Warren Alpert Medical School of Brown University Providence RI USA. Ratcliffe Harten Galamaga LLP Providence RI USA. Departments of Electrical Engineering Biomedical Data Science and Computer Science Stanford University Stanford CA USA. Chan Zuckerberg Biohub San Francisco CA USA.

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