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arXiv 2023年

作者： Liu, Shengbo Wu, Wen Li, Shaofeng Luan, Tom H. Shen, Xuemin Frontier Research Center Peng Cheng Laboratory Shenzhen China School of Cyber Science and Engineering Xidian University Xi’an China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

We propose a digital twin-assisted adaptive preloading scheme to enhance bandwidth efficiency and user quality of experience (QoE) in short video streaming. We first analyze the relationship between the achievable throughput and video bitrate and critical factors that affect the preloading decision, including the buffer size and bitrate selection. We then construct a digital twin-assisted adaptive preloading framework for short video streaming. By collecting and analyzing user’s historical throughput and tracking behavior information, a throughput prediction model and a probabilistic model can be constructed to accurately predict future throughput and user behavior, respectively. Using the predicted information and real-time running status data from a short video application, we design a preloading strategy to enhance bandwidth efficiency while guaranteeing user QoE. Simulation results demonstrate the effectiveness of our proposed scheme comparing with the state-of-the-art preloading schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Video streaming

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An Artificial Immune System Algorithm for the Permutation Flow Shop Scheduling Problem with Sequence Dependent Setup Times

An Artificial Immune System Algorithm for the Permutation Fl...

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International Conference on Optimization and Applications (ICOA)

作者： Khadija Mesmar Maria Lebbar Said Aqil Zahra Asebriy Karam Allali ROSDM Research Team LMAID Laboratory of Applied Mathematics and Business Intelligence National School of Mines of Rabat Rabat Morocco Laboratory Artificial Intelligence and Complex Systems Engineering ENSAM Casablanca Hassan II University Casablanca Morocco Laboratory mathematics Computer sciences and modeling of complex systems EST Essaouira Cadi Ayyad University Essaouira Morocco Laboratory of Mathematics Computer Science and Applications FST Mohammadia Hassan II University Mohammadia Morocco

ISBN: (数字)9798350387353

ISBN: (纸本)9798350387360

This paper is concerned with a set of independent jobs in a permutation flow shop that have setup times on a set of machines. The M-IAIS algorithm, which is based on immunoglobulins and has been modified, is designed to reduce the makespan. A unique procedure known as B cell repertoire updating, which comprises size C of jobs that are taken out of the sequence and reinserted into all possible positions of the remaining sequences of jobs, has an impact on the M-IAIS algorithm's performance. To increase the convergence velocity, three iterations of the algorithm are suggested. Thorough testing was done, and the three versions' performances on a set (benchmark) are compared. Problem instances are described in Sistemas de Optimizacion Aplicada (http://***/problem-instances) In the paper, percentage deviation is considered to evaluate the performance of the proposed algorithms. Furthermore, the ensuing outcomes demonstrate its suitability for addressing for the Permutation Flow Shop Scheduling Problem with Sequence Dependent Setup Times.

关键词： Industries Job shop scheduling Artificial immune systems Benchmark testing Optimization Convergence

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Riding Over Two-Way Carrier: A Dual-Sided RIS-Enabled Symbiotic Backscatter System

Riding Over Two-Way Carrier: A Dual-Sided RIS-Enabled Symbio...

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IEEE Conference on Wireless Communications and Networking

作者： Xiaoyi Huang Haiyang Ding Gang Yang Maged Elkashlan Jules M. Moualeu Chau Yuen School of Information and Communications National University of Defense Technology Wuhan China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China China School of Electronic Engineering and Computer Science Queen Mary University of London London U.K. School of Electrical and Information Engineering University of the Witwatersrand Johannesburg South Africa School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

In this paper, we propose a two-way backscatter communication system assisted by an active and passive dualsided reconfigurable intelligent surface (RIS) where the active RIS element contains an amplifier while the passive one does not. By altering the switch status within each RIS element, different transmission and reflection coefficients can be achieved, enabling a binary backscatter modulation. Moreover, a maximal-ratio-combining (MRC)-based detector is proposed to decode the backscatter signal and the end-user's signal, and the corresponding symbol error rate (SER) and throughput are subsequently analyzed. Numerical results show that by avoiding the additive thermal noise within each RIS element, passive dual-sided RISenabled communications outperform the active dual-sided RISenabled communications in terms of SER, and it is also revealed that the throughput can be significantly improved through backscatter modulation.

关键词： Symbiosis Error analysis Communication systems Modulation Detectors Switches Reconfigurable intelligent surfaces Throughput Thermal noise Backscatter

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Modelling and Optimal Allocation of CCHP-Integrated-Energy-System Considering Low-Carbon and Economic Benefits: Methods and Vision

Modelling and Optimal Allocation of CCHP-Integrated-Energy-S...

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Energy systems and electrical Power (ICESEP), International Conference on

作者： Maodong Li Kengweng Lao Wentao Lu Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macau S.A.R. China School of Information Science and Technology Fudan University Shanghai China

ISBN: (数字)9798350353563

ISBN: (纸本)9798350353570

Along with the development of smart energy, we take typical integrated energy systems (IES) into research considering various coupling modes and constraints, building a model of the IES for combined cooling, heating and power system, and propose the using of gas micro-turbine as a power supply. On this basis, the three dimension particle swarm optimization algorithm is applied to conduct operational and management research in one typical day, which provides a reference for the economic and low-carbon planning and operation of the IES, moreover demonstrates the superiority and effectiveness of the integrated energy systems compared to the traditional discrete energy systems. Furthermore, the paper gives the effective steps of allocation and optimization methods and vision of integrated energy systems.

关键词： Economics Couplings Power supplies Biological system modeling Buildings Optimization methods Planning

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Dual-Polarized Millimeter-Wave Multibeam Antenna Based on Substrate Integrated Coaxial Lines

Dual-Polarized Millimeter-Wave Multibeam Antenna Based on Su...

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UK, Europe, China Millimeter Waves and THz Technology Workshop (UCMMT)

作者： Yuliang Xu Chao Gu Fan Qin State Key Laboratory of Integrated Services Networks (ISN) Xidian University Xi’an China Centre for Wireless Innovation School of Electronics Electrical Engineering and Computer Science Queen’s University of Belfast Belfast UK

ISBN: (数字)9798331530228

ISBN: (纸本)9798331530235

In this paper, we propose a design for a dual-polarized millimeter-wave multibeam slot antenna array utilizing a substrate-integrated coaxial line (SICL) structure with four linear subarrays. The linear arrays, fed by a Butler matrix, operate at a centre frequency of 30 GHz with a bandwidth of 1.9 GHz. By tilting the radiating slots by ±45°, dual polarization is achieved for the resulting antenna. The proposed antenna configuration offers several advantages, including compact size, low profile, and ease of fabrication.

关键词： Butler matrices Fabrication Slot antennas Transmission line matrix methods Millimeter wave technology Bandwidth Terahertz materials Aperture antennas Linear antenna arrays Substrates

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An Amperometric High-Temperature Ammonia Sensor Based on a Baco0.4fe0.4zr0.1y0.1o3-δ-Δ Triple Conductor

SSRN

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SSRN 2024年

作者： Chen, Wenwen Zou, Jie Shan, Liang Zhang, Huanhuan Wang, Wentian Jian, Jiawen Yuan, Tao Zhang, Xin Zhou, Yucun Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315000 China Beijing Huairou Laboratory Beijing101400 China School of Materials and Chemistry University of Shanghai for Science and Technology Shanghai200093 China

Selective catalytic reduction (SCR) utilizing urea hydrolysis to generate ammonia (NH3) is the most efficient technology to reduce the emission of nitrogen oxides (NOx). NH3 detection is crucial in the closed-loop feedback system for the precise urea injection. In this work, a high-temperature NH3 sensor using a BaZr0.8Y0.2O3-δ (BZY) proton conductor as the electrolyte and a BaCo0.4Fe0.4Zr0.1Y0.1O3-δ (BCFZY) H+/e–/O2– triple conductor as the sensing electrode (SE) is reported. The effect of the micromorphology of the BCFZY SE on the sensing performance is investigated by varying the sintering temperature of SE. The sensor shows high sensitivity to NH3 with response currents of 0.39, 1.31, 3.03, and 1.81 μA/ppm at 350, 400, 450, and 500 °C, respectively. Furthermore, the sensor shows excellent selectivity and repeatability. This work demonstrates that the BCFZY based sensor has great potential for the high-temperature NH3 detection. © 2024, The Authors. All rights reserved.

关键词： Nitrogen oxides

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On the Performance of Multi-IRS-Assisted Networks Across Real Urban, Suburban, and Rural Environments

On the Performance of Multi-IRS-Assisted Networks Across Rea...

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IEEE Conference on Wireless Communications and Networking

作者： Muhammad Ibrahim Wajih Hassan Raza Muhammad Moiz Syed Ali Hassan Haejoon Jung Mikael Gidlund School of Electrical Engineering and Computer Science (SEECS) National University of Sciences & Technology (NUST) Islamabad Pakistan Department of Electronic Engineering Kyung Hee University Yongin South Korea Department of Information Systems and Technology Mid Sweden University Sundsvall Sweden

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Intelligent reflecting surface (IRS) is considered as a key technology for the sixth generation (6G) networks for creating a controlled environment for users to achieve higher data rates, throughput, and energy efficiency. IRS-assisted networks provide indirect line-of-sight (LoS) to non line-of-sight (NLoS) users, enabling them to achieve higher data rates. The purpose of this paper is to investigate the performance of IRS-assisted ultra-high frequency (UHF) networks in actual rural, sub-urban, and urban environment, in terms of rate coverage probability, spectral and energy efficiency. The actual building locations of all three locations with their heights are modeled as blockages. The analysis is carried out for different densities of BSs and IRS surfaces for different number of mobile users. Our analysis underlines the difference between the coverage probability of 2D versus 3D building areas. It also shows that the deployment of IRS surfaces significantly increases the rate per unit area of the conventional BS networks in practical environments. Our simulation results provide the optimal number of IRS elements and mobile users to achieve a certain rate coverage probability with maximum energy efficiency. Our results also highlight the optimal number of BSs and IRS surfaces for each location that can be deployed to achieve higher energy efficiency.

关键词： 6G mobile communication Three-dimensional displays Simulation Buildings Urban areas Line-of-sight propagation Throughput

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Andes_gym: A Versatile Environment for Deep Reinforcement Learning in Power systems

arXiv

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arXiv 2022年

作者： Cui, Hantao Zhang, Yichen School of Electrical and Computer Engineering Oklahoma State University StillwaterOK United States Energy Systems Division Argonne National Laboratory LemontIL United States

This paper presents andes_gym, a versatile and high-performance reinforcement learning environment for power system studies. The environment leverages the modeling and simulation capability of ANDES and the reinforcement learning (RL) environment OpenAI Gym to enable the prototyping and demonstration of RL algorithms for power systems. The architecture of the proposed software tool is elaborated to provide the "observation" and "action" interfaces for RL algorithms. An example is shown to rapidly prototype a load-frequency control algorithm based on RL trained by available algorithms. The proposed environment is highly generalized by supporting all the power system dynamic models available in ANDES and numerous RL algorithms available for OpenAI Gym. © 2022, CC BY.

关键词： Reinforcement learning

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A Novel Approach for Improving Cloud Liquid Water Content Pro- Filing with Machine Learning

SSRN

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SSRN 2024年

作者： Amaireh, Anas Zhang, Yan Chan, Pak Wai Zrnic, Dusan School of Electrical and Computer Engineering and Advanced Radar Research Center University of Oklahoma 3190 Monitor Ave NormanOK73019 United States Hong Kong Observatory Nathan Rd Sim Sha Tsui 134A Hong Kong NOAA/OAR National Severe Storms Laboratory School of Meteorology the School of Electrical and Computer Engineering University of Oklahoma 120 David L. Boren Boulevard NormanOK73019 United States

Accurate prediction of Cloud Liquid Water Content (CLWC) is important in atmospheric science for understanding and forecasting weather phenomena, particularly in locations with complex microclimates. We cross-validated the Medium-Range Weather Forecasts (ECMWF) ERA5 data with high-precision radiosonde observations from the Hong Kong area. Machine learning (ML) techniques are used for interpolating radiosonde data to enhance data coverage and resolution and estimate CLWC. This is complemented by applying a metaheuristic algorithm for data cleansing, which enhances the correlation between the input features - temperature, pressure levels, relative humidity, and specific humidity - and the CLWC. Our approach, tested against various ML algorithms for robustness and performance, demonstrates marked improvements in the accuracy and reliability of CLWC *** methodology developed is designed to be applicable beyond Hong Kong's unique atmospheric conditions, demonstrating how similar machine learning approaches can be adapted for various climates globally. This enhances weather prediction models worldwide, highlighting the global significance of this work in atmospheric science. © 2024, The Authors. All rights reserved.

关键词： Decision trees

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Multimodal Effective Permittivity Model for Metasurfaces Embedded in Layered Media

arXiv

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arXiv 2024年

作者： Howard, Christopher T. Hunt, William D. Allen, Kenneth W. School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332-0250 United States Advanced Concepts Laboratory Georgia Tech Research Institute AtlantaGA30332-0866 United States

—The dielectric layers surrounding a metasurface have a large impact on its frequency and angular response. The notion of effective permittivity captures this dependence by suggesting that a layered dielectric environment will perturb metasurface resonances in the same manner as an infinite environment of that effective permittivity. A model for effective permittivity is presented in this work. In contrast to previous empirically derived models, this multi-term model is a robust approximation based on the modal expansion of fields at the metasurface. A simple dipole metasurface array is simulated to demonstrate the accuracy of the model, which is shown to be improved over other models. Finally, we show that it is possible for dielectric layers to produce an effective permeability different than unity, which must be considered in conjunction with higher-order equivalent circuit modeling to effectively predict metasurface impedance variation. © 2024, CC BY.

关键词： Equivalent circuits

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