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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Fang, Siyuan Fang, Zaojun Peng, Chengbin Zhang, Chi Yang, Guiling Ningbo University Ningbo Institute of Materials & Technology Engineering Chinese & Academy of Sciences Faculty of Electrical Engineering and Computer Science Ningbo China Chinese & Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials & Technology Engineering Ningbo China Ningbo University College of Science & Technology Ningbo China

ISBN: (纸本)9798350312201

Respiration is the most notable vital sign of humans so that it is usually employed to diagnose disease in medicine. Recently, a solution is proposed to decrease the cost of healthcare using flexible stretchable sensors to monitor respiration. However, the sensor is difficult to test millions of cycles on a real human body, which is essential to ensure accuracy and repeatability in practical applications. In this paper, a new humanoid thoracic cavity that mimics rib expansion/constriction is exhibited. Then, a position control based on Fuzzy PID method is presented. Focused on the scenario, the performance between the common PID method and the Fuzzy PID method is investigated. Firstly, the position control based on the Fuzzy PID method is constructed by utilizing position output error and its rate. Then, three gain parameters of PID are adjusted online according to the established fuzzy rules. Finally, the above two methods are compared by simulation and experiments. In a simulation, the fuzzy PID control algorithm improves the response speed, shortens the adjustment time, and meets the requirements of the system for high response and high accuracy. Besides, an experiment is carried out on a humanoid chest prototype. the results show that the control period of the presented method is shortened by about 50% v.s. the traditional PID under the step signal input. Tracking marked points using a laser tracker, the maximum tracking error is 0.0523 mm, the minimum error is 0.0450 mm, and the average error is 0.0473mm. Therefore, the presented method is validated to improve the performance of the humanoid chest. © 2023 IEEE.

关键词： Position control

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In-situ synthesis of zeolitic imidazolate framework-8 on an optical microbubble cavity for enhanced ethanol sensing

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Optics Express 2025年第11期33卷 23065-23074页

作者： Zhi, Yanyan Liu, Li Huang, Yan Sun, Li-Peng Wang, Wei Li, Jie Zhang, Jiejun Yao, Jianping Guan, Bai-Ou Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications Institute of Photonics Technology Jinan University Guangzhou510632 China College of Physics & Optoelectronic Engineering Jinan University Guangzhou510632 China Microwave Photonics Research Laboratory School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 6N5 Canada

Optical whispering-gallery-mode microcavities have been applied for ultra-sensitive detection of physical parameters and nano-scale analytes due to strong light-matter interactions. Surface treatments to enhance mode confinement or increase analyte interaction with the optical field are effective methods to improve the sensing performance. In this work, an optical microbubble cavity fabricated via heat-and-pull and arc discharge techniques is functionalized with zeolitic imidazolate framework-8 (ZIF-8), a subclass of metal-organic frameworks (MOFs), for concentration sensing of ethanol solutions. The bubble-shaped structure forms an internal microfluidic channel to sustain the analyte solution, which provides an excellent platform for trace detection. By growing a multilayer of MOFs on the inner surface of the microcavity, the sensitivity is significantly enhanced, with distinct behaviors observed when detecting ethanol solution concentrations lower or higher than 0.1%. Compared to a pure silica microbubble cavity, the sensitivity is enhanced by 47 times and 7 times at lower and higher concentrations, respectively. The knowledge gained on sensitivity enhancement of microcavities induced by surface functionalization will guide the combinations of novel materials and optical sensors for superior detection demands. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Microcavities

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Digital Twin Driven Intelligent Systems and Emerging Metaverse 1

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2023年

作者： Enis Karaarslan Ömer Aydin Ümit Cali Moharram Challenger

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Sensitivity Analysis in Self-Assembly Self-Repair System

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IFAC-PapersOnLine 2023年第2期56卷 9366-9373页

作者： Renzo Caballero Eric Feron Computer Electrical and Mathematical Science and Engineering King Abdullah University of Science and Technology (KAUST) K.S.A

We study a case of robot interaction where a robot arm partially repairs a 3D printer by adjusting one of the support columns in the structure of the 3D printer. The collaboration stability is challenged when we assume that the robot misplaced the column on the 3D printer, leading to a non-ideal 3D printer and compromising the quality of the printing process. Experiments are conducted to find and analyze the limits in which the system can maintain self-repair and self-assemble. Based on observations, we constructed and validated mathematical models to explain the results of the experiment and analyze the stability of the self-repair process.

关键词： Modelling Robotics Non-Linear Control Systems Robust Control Mechatronic Systems

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Improved Emission Lifetime via Thermal Annealing for Ytterbium-doped High-Power Fiber Lasers

Improved Emission Lifetime via Thermal Annealing for Ytterbi...

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2024 Specialty Optical Fibers, SOF 2024

作者： Wang, Siyuan Meehan, Bailey Hawkins, Thomas W. Ballato, John Dragic, Peter D. Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign 208 N Wright St. Urbana61801 United States Department of Materials Science and Engineering Clemson University 91 Technology Drive Anderson29634 United States

Through a series of thermal annealing experiments, it is shown that Yb3+ emission properties could be further optimized, particularly as relates to the quantum efficiency. Achieving near-unity quantum efficiency is pa... 详细信息

关键词： Quantum efficiency

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RSRP Measurement Based Channel Autocorrelation Estimation for IRS-Aided Wideband Communication

RSRP Measurement Based Channel Autocorrelation Estimation fo...

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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Sun, He Zhu, Lipeng Mei, Weidong Zhang, Rui University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications 611731 China School of Science and Engineering Shenzhen Research Institute of Big Data China Chinese University of HongKong Guangdong Shenzhen518172 China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore

ISBN: (纸本)9798350368369

The passive and frequency-flat reflection of IRS, as well as the high-dimensional IRS-reflected channels, have posed significant challenges for efficient IRS channel estimation, especially in wideband communication systems with significant multi-path channel delay spread. To address these challenges, we propose a novel neural network (NN)-empowered framework for IRS channel autocorrelation matrix estimation in wideband orthogonal frequency division multiplexing (OFDM) systems. This framework relies only on the easily accessible reference signal received power (RSRP) measurements at users in existing wideband communication systems, without requiring additional pilot transmission. Based on the estimates of channel autocorrelation matrix, the passive reflection of IRS is optimized to maximize the average user received signal-to-noise ratio (SNR) over all subcarriers in the OFDM system. Numerical results verify that the proposed algorithm significantly outperforms existing power-measurement-based IRS reflection designs in wideband channels. © 2025 IEEE.

关键词： Signaling

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Joint Optimization of Cache-Assisted Offloading and Resource Allocation in Mobile Edge Computing

Joint Optimization of Cache-Assisted Offloading and Resource...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bi, Jing Sun, Zhe Yuan, Haitao Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9798350337020

Edge computing is a new architectural model that aims to offer computing, storage, and networking resources to support Internet of Things. Its primary strategy involves transferring computational tasks to the edge of network, which is closer to end-users. This paradigm facilitates offloading of computation, resulting in reduced latency and improved system performance. However, nodes located at the network edge have restricted energy and resources. As a result, running tasks entirely at the edge leads to higher energy consumption. This work proposes a novel three-tier offloading framework comprising of multiple mobile vehicles (MVs), a base station (BS), and a cloud data center (CDC). It jointly optimizes offloading rates of tasks, CPU computation rates of MVs, BS, and CDC, and the allocation of wireless bandwidth resources at MVs during partial computation offloading of tasks. It also considers limits of maximum computational resources and maximum delay of task execution. To further reduce the total system energy consumption, this work actively caches execution codes of tasks in MEC servers to reduce data transmission energy of MVs, which minimizes the total system energy consumption. This work develops a mixed integer nonlinear program and designs a mixed meta-heuristic algorithm with a multi-strategy adaptive particle swarm optimizer. Simulation results demonstrate that it outperforms various state-of-the-art algorithms by achieving lower energy consumption in fewer iterations. © 2023 IEEE.

关键词： cloud computing Computation offloading particle swarm optimization vehicular edge computing

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Performance Comparison of the Invasive Weed Optimization K-Means Algorithm With Particle Swarm Optimization K-Means for Banking Data 6

Performance Comparison of the Invasive Weed Optimization K-M...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Suwirmayanti, Ni Luh Gede Pivin Putra, I. Ketut Gede Darma Sudarma, Made Sukarsa, I. Made Setyaningsih, Emy Department of Computer Systems Faculty of Informatics and Computer Institut Teknologi dan Bisnis STIKOM Bali Bali Indonesia Department of Information Technology Faculty of Engineering Udayana University Jimbaran Hill Bali Indonesia Department of Electrical Engineering Faculty of Engineering Udayana University Jimbaran Hill Bali Indonesia Department of Computer Systems Engineering Faculty of Applied Science Universitas AKPRIND Indonesia Yogyakarta Indonesia

ISBN: (纸本)9798331539603

Banking produces extensive and diverse data, so a clustering process is needed to understand customer behavior patterns and transactions more effectively. This clustering has been widely utilized with the K-Means algorithm due to its simplicity and efficiency. However, this algorithm is limited in determining the optimal cluster center, affecting the accuracy of the clustering results. This study proposes applying two metaheuristic algorithms, Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO), as additional solutions combined with K-Means. These two algorithms were chosen because of their ability to find global solutions and convergence speed to handle large and complex banking data. The results show the superiority of IWOKM compared to PSOKM in terms of SSE and DBI. From the SSE value, IWOKM produces a lower value (3029.77), which indicates that this method is better at minimizing clustering errors and producing more accurate clustering than PSOKM (80007.09). From the DBI value, IWOKM also produces a better value (1.6684) than PSOKM (1.6782), which shows that the clusters produced by IWOKM are more compact and more separated. However, in terms of computation time, PSOKM is more efficient, with a faster average computation time. Although IWOKM produces better clustering quality, PSOKM offers advantages in terms of processing speed. This finding confirms that the selection of the IWO algorithm is more appropriate for use on datasets with characteristics such as the German Credit Dataset. © 2024 IEEE.

关键词： Invasive weed optimization

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A Novel Via-Based Magnetic Coupling Solution to Improving Illumination of Artificial Magnetic Conductor by Antenna-on-Chip

A Novel Via-Based Magnetic Coupling Solution to Improving Il...

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Microwave, Antennas & Circuits (ICMAC), International Conference on

作者： Yiyang Yu Atif Shamim Electrical and Computer Engineering Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (数字)9798331518424

ISBN: (纸本)9798331518431

Antenna-on-Chip (AoC) is one of the most promising solutions in upcoming 6G era. However, AoC suffers from low gain usually due to the highly conductive silicon substrate in mainstream complementary-metal-oxide-semiconductor (CMOS) processes. Artificial magnetic conductors (AMC) embedded within the stack-up of standard CMOS processes have been widely used to enhance the gain by isolating the AoC from the Si substrate and providing constructive reflection. Nonetheless, the ultra-thin stack-up of standard CMOS processes causes that only the AMC unit cells nearby the AoC can be illuminated well while the outermost part is illuminated poorly, which prevents the AMC from its optimal reflection performance. To mitigate the issue, this paper proposes a novel via-based magnetic coupling enhancement structures (H-CES- V) to improve the AMC illumination by coupling the energy from well-illuminated unit cells to outermost unit cells magnetically. Compared to conventional AMC, the gain can be improved by 1.5 dBi with the proposed structure. Finally, the proposed AMC-backed AoC with H-CES- V shows a boresight gain of 7 dBi (12 dBi better than a standalone AoC without AMC), and a radiation efficiency of 59 % at 94 GHz.

关键词： Couplings Lighting Conductors CMOS process Silicon Gain Antennas Substrates Magnetic circuits Standards

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Electricity Demand Prediction through Artificial Intelligence Methods

Electricity Demand Prediction through Artificial Intelligenc...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Kumar, Neeraj Mittal, Tanusha Al-Jawahry, Hassan M. Bansal, Saloni Deepak, A. Deepika, N.M. Kaushik, Rohit Department of Electrical Engineering Doon Institute of Engineering and Technology Uttarakhand Rishikesh India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Engineering and Applications GLA University Mathura India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamilnadu Chennai India Institute of Aeronautical Engineering Dundigal Hyderabad India Faculty of Management SRM Institute of Science and Technology NCR Campus India

ISBN: (纸本)9798350355338

Recently accurate predictions of electricity demands have emerged from the Liberalization and commercialization of the energy area. The future energy or intelligent grid market. A better request-side management method and a shift of mindset are required for a more credible system scale estimate of up to one year. However, electricity is difficult to forecast as elements, including sociological and environmental activity and climatic influences, are affected. The two methodologies utilized to predict cargo, in general, are artificial intelligence and analytical procedures. All analytical methodologies are frequently used in regression literature: linear regression, Box-Jenkins’ methodology, and nonparametric methods. The analytical approaches function effectively in everyday settings regarding meteorological, sociological, and psychological problems but don’t give satisfying outcomes. Consequently, the period of time does not change on the basis of economic developments. Inference systems tactics are among the artificial intelligence systems. © 2024 IEEE.

关键词： Demand response

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