检索结果-内蒙古大学图书馆

Traffic-Aware Two-Stage Queueing Communication Networks: Queue Analysis and Energy Saving

学校读者我要写书评

暂无评论

Traffic-Aware Two-Stage Queueing Communication Networks: Que...

作者： Qi, Nan Miridakis, Nikolaos I. Xiao, Ming Tsiftsis, Theodoros A. Yao, Rugui Jin, Shi Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Institute of Physical Internet School of Intelligent Systems Science & Engineering Jinan University Zhuhai Campus Zhuhai519070 China Department of Informatics and Computer Engineering University of West Attica Aegaleo12243 Greece School of Electrical Engineering of KTH Royal Institute of Technology Stockholm11428 Sweden School of Electronics and Information Northwestern Polytechnical University Xi'an710072 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China

To boost energy saving for the general delay-tolerant IoT networks, a two-stage, and single-relay queueing communication scheme is investigated. Concretely, a traffic-aware $N$-threshold and gated-service policy are applied at the relay. As two fundamental and significant performance metrics, the mean waiting time and long-term expected power consumption are explicitly derived and related with the queueing and service parameters, such as packet arrival rate, service threshold and channel statistics. Besides, we take into account the electrical circuit energy consumptions when the relay server and access point (AP) are in different modes and energy costs for mode transitions, whereby the power consumption model is more practical. The expected power minimization problem under the mean waiting time constraint is formulated. Tight closed-form bounds are adopted to obtain tractable analytical formulae with less computational complexity. The optimal energy-saving service threshold that can flexibly adjust to packet arrival rate is determined. In addition, numerical results reveal that: 1) sacrificing the mean waiting time not necessarily facilitates power savings;2) a higher arrival rate leads to a greater optimal service threshold;and 3) our policy performs better than the current state-of-the-art. © 2020 IEEE.

关键词： Energy conservation

学校读者我要写书评

暂无评论

iScience 2023年第9期26卷 107524页

作者： Iwane, Fumiaki Sobolewski, Aleksander Chavarriaga, Ricardo Millán, José del R. Department of Electrical and Computer Engineering The University of Texas at Austin Austin 78712 TX United States Department of Neurology The University of Texas at Austin Austin 78712 TX United States Learning Algorithms and Systems Laboratory (LASA) École Polytechnique Fédérale de Lausanne (EPFL) Lausanne 1015 Switzerland Wyss Center for Bio and Neuroengineering Campus Biotech Genève 1202 Switzerland École Polytechnique Fédérale de Lausanne (EPFL) Campus Biotech Genève 1202 Switzerland Centre for Artificial Intelligence Zurich University of Applied Sciences (ZHAW) Winterthur 8401 Switzerland Mulva Clinic for the Neurosciences The University of Texas at Austin Austin 78712 TX United States

Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. We report an experiment with sixteen participants over three sessions in which occasional visual rotations of varying magnitude occurred during a cursor reaching task. We designed a brain-computer interface (BCI) to detect ErrPs that provided real-time feedback. The individual ErrP-BCI decoders exhibited good transfer across sessions and scalability over the magnitude of errors. A non-linear relationship between the ErrP-BCI output and the magnitude of errors predicts individual perceptual thresholds to detect errors. We also reveal theta-gamma oscillatory coupling that co-varied with the magnitude of the required adjustment. Our findings open new avenues to probe and extend current theories of performance monitoring by incorporating continuous human interaction tasks and analysis of the ErrP complex rather than individual peaks. © 2023 The Author(s)

关键词： Cognitive neuroscience Neuroscience

Diffusive nonreciprocity and thermal diode

学校读者我要写书评

暂无评论

Physical Review B 2021年第1期103卷 014307-014307页

作者： Ying Li Jiaxin Li Minghong Qi Cheng-Wei Qiu Hongsheng Chen Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Hangzhou 310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China

Wave propagation and diffusion in linear materials preserve local reciprocity in terms of a symmetric Green's function. For wave propagations, the relation between the fields entering and leaving a system is more relevant than the detailed information about the fields inside it. In such cases, the global reciprocity of the scattering off a system through several ports is more important, which is defined as the symmetric transmission between the scattering channels. When a two-port system supports nonreciprocal (electromagnetic, acoustic) wave propagation, it is a (optical, phonon) diode directly following the definition. However, to date no concrete definition or discussion has been made on the global reciprocity of diffusive processes through a multiple-port system. It thus remains unclear what are the differences and relations between the three concepts, namely, local nonreciprocity, global nonreciprocity, and diode effect in diffusion. Here, we provide theoretical analysis on the frequency-domain Green's function and define the global reciprocity of heat diffusion through a two-port system, which has a different setup from that of a thermal diode. We further prove the equivalence between a heat transfer system with broken steady-state global reciprocity and a thermal diode, assuming no temperature-dependent heat generation. The validities of some typical mechanisms in breaking the diffusive reciprocity and making a thermal diode have been discussed. Our results set a general background for future studies on symmetric and asymmetric diffusive processes.

关键词： Diffusion Heat transfer Metamaterials Diodes Green's function methods

Physics-based model for nonuniform thermionic electron emission from polycrystalline cathodes

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Chen, Dongzheng Jacobs, Ryan Morgan, Dane Petillo, John Vlahos, Vasilios Jensen, Kevin L. Booske, John Department of Materials Science and Engineering University of Wisconsin-Madison 1509 University Ave MadisonWI53706 United States Leidos 700 Technology Park Dr. BillericaMA01821 United States Viasat Space Systems 2040 E. Technology Circle TempeAZ85284 United States MSTD Naval Research Laboratory Code 6362 WashingtonDC20375 United States Department of Electrical and Computer Engineering University of Wisconsin-Madison 1415 Engineering Dr MadisonWI53706 United States

A new physics-based model is developed that predicts the emitted current from thermionic emission that accurately spans from the temperature-limited (TL) to the full-space-charge-limited (FSCL) regions. Experimental observations of thermionic electron emission demonstrate a smooth transition between TL and FSCL regions of the emitted-current-density-versus-temperature (J−T) (Miram) curve and the emitted-current-density-versus-voltage (J−V) curve. Knowledge of the temperature and shape of the TL-FSCL transition is important in evaluating the thermionic electron emission performance of cathodes, including predicting the lifetime. However, there have been no first-principles physics-based models that can predict the smooth TL-FSCL transition region for real thermionic cathodes without applying physically difficult to justify a priori assumptions or empirical phenomenological equations. Previous work detailing the nonuniform thermionic emission found that the effects of 3-D space charge, patch fields (electrostatic potential nonuniformity on the cathode surface based on local work function values), and Schottky barrier lowering can lead to a smooth TL-FSCL transition region from a model thermionic cathode surface with a checkerboard spatial distribution of work function values. In this work, we construct a physics-based nonuniform emission model for commercial dispenser cathodes for the first time. This emission model is obtained by incorporating the cathode surface grain orientation via electron backscatter diffraction (EBSD) and the facet-orientation-specific work function values from density functional theory (DFT) calculations. The model enables construction of two-dimensional emitted current density maps of the cathode surface and corresponding J − T and J − V curves. The predicted emission curves show excellent agreement with experiment, not only in TL and FSCL regions but, crucially, also in the TL-FSCL transition region. This model provides a method to predict t

关键词： Work function

Boost AI power: Data augmentation strategies with unlabelled data and conformal prediction, a case in alternative herbal medicine discrimination with electronic nose

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Liu, Li Zhan, Xianghao Wu, Rumeng Guan, Xiaoqing Wang, Zhan Zhang, Wei Pilanci, Mert Wang, You Luo, Zhiyuan Li, Guang The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Department of Bioengineering Stanford University StanfordCA94305 United States The Computer Learning Research Center Royal Holloway University of London Egham Hill Surrey EghamTW20 0EX United Kingdom Department of Electrical Engineering Stanford University StanfordCA94305 United States

Electronic nose has been proven effective in alternative herbal medicine classification, but due to the nature of supervised learning, previous research heavily relies on the labelled training data, which are time-costly and labor-intensive to collect. To alleviate the critical dependency on the training data in real-world applications, this study aims to improve classification accuracy via data augmentation strategies. The effectiveness of five data augmentation strategies under different training data inadequacy are investigated in two scenarios: the noise-free scenario where different availabilities of unlabelled data were considered, and the noisy scenario where different levels of Gaussian noises and translational shift were added to represent sensor drifts. The five augmentation strategies, namely noise-adding data augmentation, semi-supervised learning, classifier-based online learning, Inductive Conformal Prediction (ICP) online learning and our novel ensemble ICP online learning (EICP) proposed in this study, are compared against supervised learning baselines, with Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) as the classifiers. This study provides a systematic analysis of different augmentation strategies. Our novel strategy, EICP, outperforms the others by showing non-decreasing classification accuracy on all tasks and a significant improvement on most simulated tasks (25 out of 36 tasks, p ≤ 0.05), which demonstrated both effectiveness and robustness in boosting the classification model generalizability. This strategy can be employed in other machine learning applications. Copyright © 2021, The Authors. All rights reserved.

关键词： Electronic nose

A Secure and Robust Scheme for Sharing Confidential Information in IoT systems

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Bu, Lake Isakov, Mihailo Kinsy, Michel A. Adaptive and Secure Computing Systems Laboratory Department of Electrical and Computer Engineering Boston University Boston United States

In Internet of Things (IoT) systems with security demands, there is often a need to distribute sensitive information (such as encryption keys, digital signatures, or login credentials, etc.) among the devices, so that it can be retrieved for confidential purposes at a later moment. However, this information cannot be entrusted to any one device, since the failure of that device or an attack on it will jeopardize the security of the entire network. Even if the information is divided among devices, there is still the danger that an attacker can compromise a group of devices and expose the sensitive information. In this work, we design and implement a secure and robust scheme to enable the distribution of sensitive information in IoT networks. The proposed approach has two important properties: (1) it uses Threshold Secret Sharing (TSS) to split the information into pieces distributed among all devices in the system - and so the information can only be retrieved collaboratively by groups of devices;and (2) it ensures the privacy and integrity of the information, even when attackers hijack a large number of devices and use them in concert - specifically, all the compromised devices can be identified, the confidentiality of information is kept, and authenticity of the secret can be guaranteed. Copyright © 2019, The Authors. All rights reserved.

关键词： Cryptography

Patient contrastive learning: A performant, expressive, and practical approach to ECG modeling

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Diamant, Nathaniel Reinertsen, Erik Song, Steven Aguirre, Aaron Stultz, Collin Batra, Puneet Research Laboratory of Electronics MIT Data Sciences Platform Broad Institute of MIT and Harvard Division of Cardiology Massachusetts General Hospital Center for Systems Biology Massachusetts General Hospital Research Institute Harvard Medical School Wellman Center for Photomedicine Massachusetts General Hospital Research Institute Harvard Medical School Department of Electrical Engineering and Computer Science MIT Harvard-MIT Division of Health Sciences and Technology

Supervised machine learning applications in health care are often limited due to a scarcity of labeled training data. To mitigate this effect of small sample size, we introduce a pre-training approach, Patient Contrastive Learning of Representations (PCLR), which creates latent representations of ECGs from a large number of unlabeled examples. The resulting representations are expressive, performant, and practical across a wide spectrum of clinical tasks. We develop PCLR using a large health care system with over 3.2 million 12-lead ECGs, and demonstrate substantial improvements across multiple new tasks when there are fewer than 5,000 labels. We release our model to extract ECG representations at https://***/broadinstitute/ml4h/tree/master/model_zoo/PCLR. Copyright © 2021, The Authors. All rights reserved.

关键词： Supervised learning

A reconfigurable quantum local area network over deployed fiber

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Alshowkan, Muneer Williams, Brian P. Evans, Philip G. Rao, Nageswara S.V. Simmerman, Emma M. Lu, Hsuan-Hao Lingaraju, Navin B. Weiner, Andrew M. Marvinney, Claire E. Pai, Yun-Yi Lawrie, Benjamin J. Peters, Nicholas A. Lukens, Joseph M. Quantum Information Science Group Oak Ridge National Laboratory Oak RidgeTN37831 United States Autonomous and Complex Systems Group Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Applied Physics Stanford University StanfordCA94305 United States School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Materials Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

Practical quantum networking architectures are crucial for scaling the connection of quantum resources. Yet quantum network testbeds have thus far underutilized the full capabilities of modern lightwave communications, such as flexible-grid bandwidth allocation. In this work, we implement flex-grid entanglement distribution in a deployed network for the first time, connecting nodes in three distinct campus buildings time-synchronized via the Global Positioning System (GPS). We quantify the quality of the distributed polarization entanglement via log-negativity, which offers a generic metric of link performance in entangled bits per second. After demonstrating successful entanglement distribution for two allocations of our eight dynamically reconfigurable channels, we demonstrate remote state preparation—the first realization on deployed fiber—showcasing one possible quantum protocol enabled by the distributed entanglement network. Our results realize an advanced paradigm for managing entanglement resources in quantum networks of ever-increasing complexity and service demands. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum entanglement

Reliability of Neural Networks Based on Spintronic Neurons

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Raimondo, Eleonora Giordano, Anna Grimaldi, Andrea Puliafito, Vito Carpentieri, Mario Zeng, Zhongming Tomasello, Riccardo Finocchio, Giovanni Department of Mathematical and Computer Sciences Physical Sciences and Earth Sciences University of Messina MessinaI-98166 Italy Department of Engineering University of Messina MessinaI-98166 Italy Department of Electrical and Information Engineering Polytechnic of Bari via Orabona 4 Bari70125 Italy Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-tech and Nano-bionics Chinese Academy of Sciences Ruoshui Road 398 Suzhou215123 China Institute of Applied and Computational Mathematics FORTH Crete HeraklionGR-70013 Greece

Spintronic technology is emerging as a direction for the hardware implementation of neurons and synapses of neuromorphic architectures. In particular, a single spintronic device can be used to implement the nonlinear activation function of neurons. Here, we present how to implement spintronic neurons with sigmoidal and rectified linear unit (ReLU)-like activation functions. We then perform a numerical experiment showing the reliability of neural networks made by spintronic neurons, all having different activation functions to emulate device-to-device variations in a possible hardware implementation of the network. Therefore, we consider a "vanilla" neural network implemented to recognize the categories of the Mixed National Institute of Standards and Technology database, and we show an average accuracy of 98.87% in the test dataset, which is very close to 98.89% as obtained for the ideal case (all neurons have the same sigmoid activation function). Similar results are obtained with neurons having a ReLU-like activation function. © 2021, CC BY.

关键词： Neurons