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Competitive Perimeter Defense of Conical Environments

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arXiv 2021年

作者： Bajaj, Shivam Torng, Eric Bopardikar, Shaunak D. Moll, Alexander Von Weintraub, Isaac Garcia, Eloy Casbeer, David W. the Department of Electrical and Computer Engineering Michigan State University United States the Department of Computer Science and Engineering Michigan State University United States Control Science Center Air Force Research Laboratory

We consider a perimeter defense problem in a planar conical environment in which a single vehicle, having a finite capture radius, aims to defend a concentric perimeter from mobile intruders. The intruders are arbitrarily released at the circumference of the environment and they move radially toward the perimeter with fixed speed. We present a competitive analysis approach to this problem by measuring the performance of multiple online algorithms for the vehicle against arbitrary inputs, relative to an optimal offline algorithm that has information about entire input sequence in advance. In particular, we establish two necessary conditions on the parameter space to guarantee (i) finite competitiveness of any algorithm and (ii) a competitive ratio of at least 2 for any algorithm. We then design and analyze three online algorithms and characterize parameter regimes in which they have finite competitive ratios. Specifically, our first two algorithms are provably 1, and 2-competitive, respectively, whereas our third algorithm exhibits different competitive ratios in different regimes of problem parameters. Finally, we provide a numerical plot in the parameter space to reveal additional insights into the relative performance of our algorithms. © 2021, CC BY.

关键词： Network security

Deep Learning Models for Intelligent Healthcare: Implementation and Challenges 7th

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Deep Learning Models for Intelligent Healthcare: Implementat...

7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Rehman, Sadaqat ur Tu, Shanshan Shah, Zubair Ahmad, Jawad Waqas, Muhammad Rehman, Obaid ur Kouba, Anis Abbasi, Qammer H. Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information Technology Beijing University of Technology Beijing100124 China Department of Computer Science Namal Institute Mianwali42250 Pakistan Department of Computer Science and Engineering Hammad Bin Khalifa University Doha Qatar School of Computing Edinburgh Napier University Edinburgh United Kingdom Department of Electrical Engineering Sarhad University of Science and IT Peshawar25000 Pakistan Department of Computer Science Prince Sultan University Riyadh Saudi Arabia James Watt School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom

ISBN: (纸本)9783030786083

The rapid developments of artificial intelligent (AI) is being transformed for its extensive use-cases, people-centered intelligent systems focusing on care delivery, research encounter complex problems related to improve the overall infrastructure and management of intelligent delivery service;for instance, bringing transformation in healthcare sector for monitoring patients with chronic disease. Most of these systems are driven by state-of-the-art learning algorithms i.e., Convolution Neural Network. The CNN algorithm is considered to be one of the most prominent architectures of DL. Recently, due to enormous growth in the amount of annotated data and the development of CNN hardware accelerator, further, boost the research on CNN and accomplished benchmark enactment on different applications. This paper presents cutting-edge applications of CNN for an intelligent healthcare system. We provide useful findings of different CNN features such as optimization, fast computation, design, activation function, and loss function. To our knowledge, this is the first comprehensive work to address the recent trends in the architecture of CNN, which offers insight to the underlying problems and provides the potential solutions for any given intelligent healthcare applications. © 2021, Springer Nature Switzerland AG.

关键词： Deep learning

Simple Multiuser Twin-Field Quantum Key Distribution Network

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Physical Review Applied 2022年第1期17卷 014025-014025页

作者： Xiaoqing Zhong Wenyuan Wang Reem Mandil Hoi-Kwong Lo Li Qian Center for Quantum Information and Quantum Control Department of Physics University of Toronto Toronto Ontario M5S 1A7 Canada Center for Quantum Information and Quantum Control Dept. of Electrical & Computer Engineering University of Toronto Toronto Ontario M5S 3G4 Canada Department of Physics University of Hong Kong Pokfulam Road Hong Kong

Twin-field quantum key distribution (TFQKD) systems have shown great promise for implementing practical long-distance secure quantum communication due to its measurement-device-independent nature and its ability to offer fundamentally superior rate-loss scaling than point-to-point QKD systems. A surge of research and development effort in the last two years has produced many variants of protocols and experimental demonstrations. In terms of hardware topology, TFQKD systems interfering quantum signals from two remotely phase-locked laser sources are in essence giant Mach-Zehnder interferometers (MZIs) requiring active phase stabilization. Such configurations are inherently unsuitable for a TFQKD network, where more than one user pair share the common quantum measurement station, because it is practically extremely difficult, if not impossible, to stabilize MZIs of largely disparate path lengths, a situation that is inevitable in a multi-user-pair TFQKD network. On the other hand, Sagnac interferometer-based TFQKD systems exploiting the inherent phase stability of the Sagnac ring can implement asymmetric TFQKD, and are therefore eminently suitable for implementing a TFQKD network. In this work, we experimentally demonstrate a proof-of-principle multi-user-pair Sagnac TFQKD network where three user pairs sharing the same measurement station can perform pairwise TFQKD through time multiplexing, with channel losses up to 58.00 dB, and channel loss asymmetry up to 15.00 dB. In some cases, the secure key rates still beat the rate-loss bound for point-to-point repeaterless QKD systems, even in this network configuration. Our demonstration of this multi-user-pair TFQKD network is a step in advancing quantum-communication network technologies.

关键词： Optical quantum information processing Quantum communication Quantum cryptography Quantum networks Quantum optics Communication networks Optical fibers Optical interferometry

Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman Problems

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arXiv 2023年

作者： Xiao, Yubin Wang, Di Li, Boyang Chen, Huanhuan Pang, Wei Wu, Xuan Li, Hao Xu, Dong Liang, Yanchun Zhou, You The Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education College of Computer Science and Technology Jilin University Changchun130012 China The Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly Nanyang Technological University 639798 Singapore The School of Computer Science and Engineering Nanyang Technological University 639798 Singapore The School of Computer Science University of Science & Technology of China Hefei230026 China The School of Mathematical and Computer Sciences Heriot-Watt University EdinburghEH14 4AS United Kingdom College of Computer National University of Defense Technology Hunan Changsha410073 China The Department of Electrical Engineering and Computer Science Bond Life Sciences Center University of Missouri Columbia United States The School of Computer Science Zhuhai College of Science and Technology Zhuhai519000 China

The Traveling Salesman Problem (TSP) is a well-known combinatorial optimization problem with broad real-world applications. Recently, neural networks have gained popularity in this research area because as shown in the literature, they provide strong heuristic solutions to TSPs. Compared to autoregressive neural approaches, non-autoregressive (NAR) networks exploit the inference parallelism to elevate inference speed but suffer from comparatively low solution quality. In this paper, we propose a novel NAR model named NAR4TSP, which incorporates a specially designed architecture and an enhanced reinforcement learning strategy. To the best of our knowledge, NAR4TSP is the first TSP solver that successfully combines RL and NAR networks. The key lies in the incorporation of NAR network output decoding into the training process. NAR4TSP efficiently represents TSP encoded information as rewards and seamlessly integrates it into reinforcement learning strategies, while maintaining consistent TSP sequence constraints during both training and testing phases. Experimental results on both synthetic and real-world TSPs demonstrate that NAR4TSP outperforms five state-of-the-art models in terms of solution quality, inference speed, and generalization to unseen scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Traveling salesman problem

Correction to: Deep mantle melting, global water circulation and its implications for the stability of the ocean mass

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Progress in Earth and Planetary Science 2021年第1期8卷 1-3页

作者： Karato, Shun-ichiro Karki, Bijaya Park, Jeffrey Department of Earth and Planetary Sciences Yale University New Haven USA School of Electrical Engineering and Computer Science Department of Geology and Geophysics Center for Computation and Technology Louisiana State University Baton Rouge USA

An amendment to this paper has been published and can be accessed via the original article.

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Improving the speed of variational quantum algorithms for quantum error correction

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arXiv 2023年

作者： Zoratti, Fabio De Palma, Giacomo Kiani, Bobak Nguyen, Quynh T. Marvian, Milad Lloyd, Seth Giovannetti, Vittorio Scuola Normale Superiore PisaI-56126 Italy Department of Mathematics University of Bologna Bologna40126 Italy Department of Electrical Engineering and Computer Science MIT 77 Massachusetts Avenue CambridgeMA02139 United States Department of Electrical and Computer Engineering Center for Quantum Information and Control University of New Mexico United States Department of Mechanical Engineering MIT 77 Massachusetts Avenue CambridgeMA02139 United States Turing Inc. CambridgeMA02139 United States NEST Scuola Normale Superiore Istituto Nanoscienze-CNR PisaI-56126 Italy

We consider the problem of devising a suitable Quantum Error Correction (QEC) procedures for a generic quantum noise acting on a quantum circuit. In general, there is no analytic universal procedure to obtain the encoding and correction unitary gates, and the problem is even harder if the noise is unknown and has to be reconstructed. The existing procedures rely on Variational Quantum Algorithms (VQAs) and are very difficult to train since the size of the gradient of the cost function decays exponentially with the number of qubits. We address this problem using a cost function based on the Quantum Wasserstein distance of order 1 (QW1). At variance with other quantum distances typically adopted in quantum information processing, QW1 lacks the unitary invariance property which makes it a suitable tool to avoid to get trapped in local minima. Focusing on a simple noise model for which an exact QEC solution is known and can be used as a theoretical benchmark, we run a series of numerical tests that show how, guiding the VQA search through the QW1, can indeed significantly increase both the probability of a successful training and the fidelity of the recovered state, with respect to the results one obtains when using conventional approaches. © 2023, CC BY-SA.

关键词： Cost functions

Dielectric Spectrum of Random Copolymerization Polypropylene Nanocomposites Doped with Nano Silica at Different Temperatures 7

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Dielectric Spectrum of Random Copolymerization Polypropylene...

7th IEEE International Conference on High Voltage engineering and Application, ICHVE 2020

作者： Men, Rujia Lei, Zhipeng Song, Jiancheng Han, Kunying Li, Lu Li, Chuangyang Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan030024 China Electrical Insulation Research Center Institute of Materials Science Electrical and Computer Engineering University of Connecticut Storrs CT06269 United States

ISBN: (纸本)9781728155111

Random copolymerization polypropylene (PPR), a recyclable thermoplastic material with a melting temperature of over 150°C and excellent mechanical properties, has potential to become the insulation materials used in high voltage cables. To investigate dielectric properties of PPR and its nanocomposites at different temperatures, especially the dielectric spectrum at high temperatures, film samples of PPR and its nanocomposites doped with different content of nano silica were prepared. The microscopic morphologies were observed firstly for analyzing the dispersion of nanoparticles. Then the dielectric spectrums were measured at temperatures of 30, 50, 70, 90, 110 and 130°C. After this, the effects of nanoparticle content, temperature and frequency on the relative permittivity and dielectric dissipation factors are discussed and the mechanism is analyzed. It can be concluded that relative permittivity of PPR and its nanocomposites are almost unaffected by temperature in the range of 30 - 110°C and remains relatively low values. When the temperature is below 110°C, the relative permittivity of the PPR nanocomposites increases with the increase of temperature;And when the temperature is 110°C or above, the value is related to the applied voltage frequency and the content of nanoparticles. And with the temperature rising, the dielectric dissipation factor of PPR nanocomposites have an evident increase at lower frequency, which contributes to the DC conductivity. © 2020 IEEE.

关键词： Nanocomposites

Joint Optimization of Resource Allocation and User Association in Multi-Frequency Cellular Networks Assisted by RIS

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arXiv 2023年

作者： Qiao, Yuanyuan Niu, Yong Han, Zhu Mao, Shiwen He, Ruisi Wang, Ning Zhong, Zhangdui Ai, Bo The 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 The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States The School of Information Engineering Zhengzhou University Zhengzhou450001 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China

Due to the development of communication technology and the rise of user network demand, a reasonable resource allocation for wireless networks is the key to guaranteeing regular operation and improving system performance. Various frequency bands exist in the natural network environment, and heterogeneous cellular network (HCN) has become a hot topic for current research. Meanwhile, Reconfigurable Intelligent Surface (RIS) has become a key technology for developing next-generation wireless networks. By modifying the phase of the incident signal arriving at the RIS surface, RIS can improve the signal quality at the receiver and reduce co-channel interference. In this paper, we develop a RIS-assisted HCN model for a multi-base station (BS) multi-frequency network, which includes 4G, 5G, millimeter wave (mmwave), and terahertz networks, and considers the case of multiple network coverage users, which is more in line with the realistic network characteristics and the concept of 6G networks. We propose the optimization objective of maximizing the system sum rate, which is decomposed into two subproblems, i.e., the user resource allocation and the phase shift optimization problem of RIS components. Due to the NP-hard and coupling relationship, we use the block coordinate descent (BCD) method to alternately optimize the local solutions of the coalition game and the local discrete phase search algorithm to obtain the global solution. In contrast, most previous studies have used the coalition game algorithm to solve the resource allocation problem alone. Simulation results show that the algorithm performs better than the rest of the algorithms, effectively improves the system sum rate, and achieves performance close to the optimal solution of the traversal algorithm with low complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Resource allocation

Dielectric Strength of Ethylene Propylene Rubber under Thermal and Mechanical Stress 7

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Dielectric Strength of Ethylene Propylene Rubber under Therm...

7th IEEE International Conference on High Voltage engineering and Application, ICHVE 2020

作者： Liu, Yang Men, Rujia Tian, Muqin Wang, Ye Han, Kunying Lei, Zhipeng Li, Chuangyang Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan030024 China Electrical Insulation Research Center Institute of Materials Science Electrical and Computer Engineering University of Connecticut Storrs CT06269 United States

ISBN: (纸本)9781728155111

In order to find out the effect of temperature and mechanical stress on the dielectric breakdown strength of Ethylene Propylene Rubber (EPR), AC breakdown tests of EPR samples were carried out at different temperatures and compressive stress. Two-parameter Weibull statistical distribution was used to analyze the breakdown strength. The experimental results show that the dielectric strength of EPR decreases with the increase of temperature when only temperature is applied. Under the same temperature, the breakdown strength of EPR firstly increases with the compressive stress rising, gradually reaches a maximum and finally shows a decreasing tendency. It's due to the effect of compressive stress on the intermolecular distance and thermal expansion of EPR. © 2020 IEEE.

关键词： Compressive stress