检索结果-内蒙古大学图书馆

TechRxiv 2021年

作者： Fan, Rui Bowd, Christopher Christopher, Mark Brye, Nicole Proudfoot, James A. Rezapour, Jasmin Belghith, Akram Goldbaum, Michael H. Chuter, Benton Girkin, Christopher A. Fazio, Massimo A. Liebmann, Jeffrey M. Weinreb, Robert N. Gordon, Mae O. Kass, Michael A. Kriegman, David Zangwill, Linda M. Hamilton Glaucoma Center Viterbi Family Department of Ophthalmology Shiley Eye Institute University of California La Jolla San DiegoCA United States Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Department of Ophthalmology Universitätsmedizin der Johannes Gutenberg-Universität Mainz Rheinland-Pfalz Mainz Germany Department of Ophthalmology School of Medicine The University of Alabama at Birmingham BirminghamAL United States Department of Biomedical Engineering School of Engineering The University of Alabama at Birmingham BirminghamAL United States Bernard and Shirlee Brown Glaucoma Research Laboratory Edward S. Harkness Eye Institute Columbia University Medical Center New YorkNY United States Department of Ophthalmology and Visual Sciences Washington University School of Medicine Washington University St. LouisMO United States

Importance: Automated deep learning (DL) analyses of fundus photographs potentially can reduce the cost and improve the efficiency of reading center assessment of endpoints in clinical trials. Objective: To investigate the diagnostic accuracy of DL algorithms trained on fundus photographs from the Ocular Hypertension Treatment Study (OHTS) to detect primary open-angle glaucoma (POAG). Study Design: Diagnostic/prognostic Study Setting and Participants: 1,636 OHTS participants from 22 sites with a mean follow-up (range) of 10.7 (0.0, 14.3) years. 66,715 photographs from 3,272 eyes were used to train and test a ResNet-50 model to detect the OHTS Endpoint Committee POAG determination based on optic disc (n=287 eyes, 3,502 photographs) and/or visual field (n=198 eyes, 2,300 visual fields) changes. Three independent test sets were used to evaluate the generalizability of the model. Main Outcome and Measures: Areas under the receiver operating characteristic curve (AUROC) and sensitivities at fixed specificities were calculated to compare model performance. Evaluation of false-positive rates was used to determine whether the DL model detected POAG before the Endpoint Committee POAG determination. Results: The DL model achieved an AUROC (95% CI) of 0.88 (0.82, 0.92) for the overall OHTS POAG endpoint. For the OHTS endpoints based on optic disc changes or visual field changes, AUROCs were 0.91 (0.88, 0.94) and 0.86 (0.76, 0.93), respectively. False-positive rates (at 90% specificity) were higher in photographs of eyes that later developed POAG by disc or visual field (19.1%) compared to eyes that did not develop POAG (7.3%) during their follow-up. The diagnostic accuracy of the DL model developed on the optic disc endpoint applied to 3 independent datasets was lower with AUROC ranging from 0.74 to 0.79. Conclusion and Relevance: The model’s high diagnostic accuracy using OHTS photographs suggests that DL has the potential to standardize and automate POAG determination for cl

关键词： Ophthalmology

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Learning of long-horizon sparse-reward robotic manipulator tasks with base controllers

arXiv

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arXiv 2020年

作者： Wang, Guangming Xin, Minjian Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Engineering University of California San Diego La Jolla CA92093 United States Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Deep Reinforcement Learning (DRL) enables robots to perform some intelligent tasks end-to-end. However, there are still many challenges for long-horizon sparse-reward robotic manipulator tasks. On the one hand, a sparse-reward setting causes exploration inefficient. On the other hand, exploration using physical robots is of high cost and unsafe. In this paper, we propose a method of learning long-horizon sparse-reward tasks utilizing one or more existing traditional controllers named base controllers in this paper. Built upon Deep Deterministic Policy Gradients (DDPG), our algorithm incorporates the existing base controllers into stages of exploration, value learning, and policy update. Furthermore, we present a straightforward way of synthesizing different base controllers to integrate their strengths. Through experiments ranging from stacking blocks to cups, it is demonstrated that the learned state-based or image-based policies steadily outperform base controllers. Compared to previous works of learning from demonstrations, our method improves sample efficiency by orders of magnitude and improves the performance. Overall, our method bears the potential of leveraging existing industrial robot manipulation systems to build more flexible and intelligent controllers. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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Regular path-constrained time-optimal control problems in three-dimensional flow fields

arXiv

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arXiv 2019年

作者： Chertovskih, R. Karamzin, D. Khalil, N.T. Pereira, F.L. Electrical and Computer Engineering Department Faculty of Engineering University of Porto 4200-465 Portugal Federal Research Center "Computer Science and Control" Russian Academy of Science Moscow Russia

This article concerns a class of time-optimal state constrained control problems with dynamics defined by an ordinary differential equation involving a three-dimensional steady flow vector field. The problem is solved via an indirect method based on the maximum principle in Gamkrelidze's form. The proposed computational method essentially uses a certain regularity condition imposed on the data of the problem. The property of regularity guarantees the continuity of the measure multiplier associated with the state constraint, and ensures the appropriate behavior of the corresponding numerical procedure which, in general, consists in computing the entire field of extremals for the problem in question. Several examples of vector fields are considered to illustrate the computational *** Codes 49K15, 49M05 Copyright © 2019, The Authors. All rights reserved.

关键词： Maximum principle

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Comparing relaxation mechanisms in quantum and classical transverse-field annealing

arXiv

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arXiv 2020年

作者： Albash, Tameem Marshall, Jeffrey Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM87131 United States Department of Physics and Astronomy Center for Quantum Information and Control CQuIC University of New Mexico AlbuquerqueNM87131 United States QuAIL NASA Ames Research Center Moffett FieldCA94035 United States USRA Research Institute for Advanced Computer Science Mountain ViewCA94043 United States

Annealing schedule control provides new opportunities to better understand the manner and mechanisms by which putative quantum annealers operate. By appropriately modifying the annealing schedule to include a pause (keeping the Hamiltonian fixed) for a period of time, we show it is possible to more directly probe the dissipative dynamics of the system at intermediate points along the anneal and examine thermal relaxation rates, for example, by observing the re-population of the ground state after the minimum spectral gap. We provide a detailed comparison of experiments from a D-Wave device, simulations of the quantum adiabatic master equation and a classical analogue of quantum annealing, spin-vector Monte Carlo, and we observe qualitative agreement, showing that the characteristic increase in success probability when pausing is not a uniquely quantum phenomena. We find that the relaxation in our system is dominated by a single time-scale, which allows us to give a simple condition for when we can expect pausing to improve the time-to-solution, the relevant metric for classical optimization. In the system studied here, only for short pauses is there expected to be an improvement. Finally, we also explore in simulation the role of temperature whilst pausing as a means to better distinguish quantum and classical models of quantum annealers. Copyright © 2020, The Authors. All rights reserved.

关键词： Annealing

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Max-min energy balance in wireless-powered hierarchical fog-cloud computing networks

Max-min energy balance in wireless-powered hierarchical fog-...

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作者： Liu, Jingxian Xiong, Ke Ng, Derrick Wing Kwan Fan, Pingyi Zhong, Zhangdui Letaief, Khaled Ben School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China School of Electrical Engineering and Telecommunications UNSW Sydney SydneyNSW2052 Australia Department of Electronic Engineering Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Hong Kong Peng Cheng Laboratory Shenzhen518055 China

This paper investigates the wireless-powered hierarchical fog-cloud computing networks, where multiple energy-constrained users harvest energy from a hybrid access point (HAP) firstly and then use their harvested energy to offload their computation tasks to fog/cloud servers via the HAP or compute their tasks locally. To pursue multi-user fairness, an optimization problem is formulated to maximize the minimal energy balance among all users by jointly optimizing time assignments, computation central processing unit (CPU) frequencies, and the computing mode selection. Since the problem is mixed-integer combinatorial non-convex, which is intractable, a generalized Benders decomposition (GBD)-based method is proposed, which guarantees the globally optimal solution. To release the high computational complexity of the proposed GBD-based method, a penalized successive convex approximation (P-SCA)-based algorithm is designed as an alternative to obtain a suboptimal solution with low computational complexity. Numerical results show that among different optimizable factors in the system, computing mode selection is the dominant one on affecting the system performance. Moreover, for each user, local computing is a better choice, if it is with relatively poor channel gain and small local computing delay. Otherwise, fog/cloud computing may be a better choice. Additionally, for the users with relatively high channel gains, if their local computing delays are less than those selecting fog computing, cloud computing should be a better choice. © 2002-2012 IEEE.

关键词： Energy transfer

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Transfer Learning for EEG-Based Brain-computer Interfaces: A Review of Progress Made Since 2016

arXiv

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arXiv 2020年

作者： Wu, Dongrui Xu, Yifan Lu, Bao-Liang The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Qing Yuan Research Institute Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai200240 China

A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common non-invasive BCI modality, electroencephalogram (EEG), is sensitive to noise/artifact and suffers between-subject/within-subject non-stationarity. Therefore, it is difficult to build a generic pattern recognition model in an EEG-based BCI system that is optimal for different subjects, during different sessions, for different devices and tasks. Usually, a calibration session is needed to collect some training data for a new subject, which is time-consuming and user unfriendly. Transfer learning (TL), which utilizes data or knowledge from similar or relevant subjects/sessions/devices/tasks to facilitate learning for a new subject/session/device/task, is frequently used to reduce the amount of calibration effort. This paper reviews journal publications on TL approaches in EEG-based BCIs in the last few years, i.e., since 2016. Six paradigms and applications - motor imagery, event-related potentials, steady-state visual evoked potentials, affective BCIs, regression problems, and adversarial attacks - are considered. For each paradigm/application, we group the TL approaches into cross-subject/session, cross-device, and cross-task settings and review them separately. Observations and conclusions are made at the end of the paper, which may point to future research directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain computer interface

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User-configurable decision support system for clinical risk management

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Procedia computer science 2021年 190卷 463-470页

作者： Elena Kleymenova Mikhail Dronov Liubov Yashina Elena Matrosova Svetlana Payushchik Maria Nigmatkulova Vitaly Otdelenov General Medical Center of the Bank of Russia Sevastopolsky pr.66 Moscow 117593 Russia Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Vavilova str. 44 Moscow 119333 Russia Russian Medical Academy of Continuous Professional Education Barrikadnaya st. 2/1 Moscow 125993 Russia Faculty of Physics M.V. Lomonosov Moscow State University Leninskie Gory GSP-1 Moscow 119991 Russia Information Technology Department Moscow City University Vtoroy Selskohoziajstvenny proezd 4 Moscow 129226 Russia National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) Kashirskoe shosse 31 Moscow 115409 Russia

The paper describes an application of relational structure-independent database for the design of user-configurable information system aimed at the intellectual support of clinical risk management in a hospital. The system represents a clinical decision support system (CDSS) and includes three modules: prevention of hospital-acquired adverse events (HA-AE), HA-AE prevention processes and audit of HA-AE cases. Thanks to flexible system configuration and graphic user interface, the clinical experts are able to compose complex knowledge artifacts directly working with the system, without engagement of knowledge engineers for supporting knowledge formalization or highly skilled professionals to ensure the physical layer performance. The successful practical approval of CDSS in a medical facility opens up prospects for a new level of cognitive support for diagnostic and treatment processes, patient safety improvement and healthcare costs reduction.

关键词： decision support system clinical risk management structure-independent database

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Dynamic modeling and system identification of user engagement in mHealth interventions using a Bayesian approach for missing data imputation

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control engineering Practice 2025年 164卷

作者： Mohamed El Mistiri Steven De La Torre Benjamin M. Marlin Misha Pavel Predrag Klasnja Donna Spruijt-Metz Daniel E. Rivera Control Systems Engineering Laboratory in the Chemical Engineering Department School for Engineering of Matter Transport at Arizona State University Tempe 85282 AZ USA Herbert Wertheim School of Public Health & Human Longevity Science University of California San Diego La Jolla 92093 CA USA Manning College of Information and Computer Sciences University of Massachusetts Amherst Amherst 01003 MA USA Khoury College of Computer Sciences Northeastern University Boston 02115 MA USA Division of Biomedical and Health Informatics School of Information University of Michigan Ann Arbor 48109 MI USA Dornsife Center for Economic and Social Research University of Southern California Los Angeles 90089 CA USA

Digital behavior change interventions (DBCIs) have been found to positively impact health behaviors and are becoming increasingly important as an emerging topic for control systems applications. However, their effectiveness is heavily dependent upon user engagement with both the digital tool (e.g., mHealth app, wearable activity tracker) and the behavior change intervention (e.g., exercise activity planning). In this paper, engagement refers to the unique interactions of a participant with either of these components resulting in digital traces (e.g., app page views). Furthermore, engagement in DBCIs will change over the course of the intervention in response to an individual’s environment, context, and psychological state. Intensive data collection enables modeling engagement in DBCIs as a dynamical system using fluid analogies, and applying prediction-error methods from system identification to estimate models. Missingness represents both a fundamental and practical concern in this application domain. This work addresses missingness using a novel Bayesian imputation method applied to data from the HeartSteps II physical activity intervention study. The benefits of this approach include the ability to impute missing data points more accurately than traditional methods and quantify uncertainty resulting from imputation and data scarcity; the latter is essential to the implementation of robust closed-loop interventions. The methods presented in this work provide insights into critical factors that impact engagement behavior over time and in context, ultimately benefiting the development of digital behavior change interventions relying on control engineering approaches.

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Quantum repeaters: From quantum networks to the quantum internet

arXiv

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arXiv 2022年

作者： Azuma, Koji Economou, Sophia E. Elkouss, David Hilaire, Paul Jiang, Liang Lo, Hoi-Kwong Tzitrin, Ilan NTT Basic Research Laboratories NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan NTT Research Center for Theoretical Quantum Physics NTT Corporation 3-1 Morinosato-Wakamiya Kanagawa Atsugi243-0198 Japan Department of Physics Virginia Tech BlacksburgVA24061 United States QuTech Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands Networked Quantum Devices Unit Okinawa Institute of Science and Technology Graduate University Okinawa Japan Quandela SAS 10 Boulevard Thomas Gobert Palaiseau91120 France Pritzker School of Molecular Engineering The University of Chicago ChicagoIL60637 United States Quantum Bridge Technologies Inc. 100 College Street TorontoONM5G 1L5 Canada Department of Physics University of Hong Kong Pokfulam Hong Kong Center for Quantum Information and Quantum Control Department of Physics Department of Electrical & Computer Engineering University of Toronto TorontoM5S 3G4 Canada Department of Physics University of Toronto Toronto Canada

A quantum internet is the holy grail of quantum information processing, enabling the deployment of a broad range of quantum technologies and protocols on a global scale. However, numerous challenges exist before the quantum internet can become a reality. Perhaps the most crucial of these is the realization of a quantum repeater, an essential component in the long-distance transmission of quantum information. As the analog of a classical repeater, extender, or booster, the quantum repeater works to overcome loss and noise in the quantum channels comprising a quantum network. Here, we review the conceptual frameworks and architectures for quantum repeaters, as well as the experimental progress towards their realization. We also discuss the various near-term proposals to overcome the limits to the communication rates set by point-to-point quantum communication. Finally, we overview how quantum repeaters fit within the broader challenge of designing and implementing a quantum internet. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum optics

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Reconfigurable Intelligent Surface Assisted Device-to-Device Communications

arXiv

引用

arXiv 2020年

作者： Chen, Yali Ai, Bo Zhang, Hongliang Niu, Yong Song, Lingyang Han, Zhu Poor, H. Vincent State Key Laboratory of Rail Traffic Control and Safety Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States Department of Electronics Engineering Peking University Beijing China Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States School of Engineering and Applied Science Princeton University NY United States

With the evolution of the 5G, 6G and beyond, device-to-device (D2D) communication has been developed as an energy-, and spectrum-efficient solution. In cellular network, D2D links need to share the same spectrum resources with the cellular link. A reconfigurable intelligent surface (RIS) can reconfigure the phase shifts of elements and create favorable beam steering, which can mitigate aggravated interference caused by D2D links. In this paper, we study a RIS-assisted single cell uplink communication network scenario, where the cellular link and multiple D2D links utilize direct propagation and reflecting one-hop propagation. The problem of maximizing the total system rate is formulated by jointly optimizing transmission powers of all links and discrete phase shifts of all elements. The formulated problem is an NP-hard mixed integer non-convex non-linear problem. To obtain practical solutions, we capitalize on alternating maximization and the problem is decomposed into two sub-problems. For the power allocation, the problem is a difference of concave functions (DC) problem, which is solved with the gradient descent method. For the phase shift, a local search algorithm with lower complexity is utilized. Simulation results show that deploying RIS and optimizing the phase shifts have a significant effect on mitigating D2D network interference. Copyright © 2020, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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