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arXiv 2024年

作者： Yao, Junteng Wu, Tuo Zhou, Liaoshi Jin, Ming Pan, Cunhua Elkashlan, Maged Adachi, Fumiyuki Karagiannidis, George K. Al-Dhahir, Naofal Yuen, Chau The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Tohoku University Sendai Japan The Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece Lebanon Lebanon The Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX75080 United States

In this paper, we analyze the role of fluid antenna systems (FAS) in multi-user systems with hardware impairments (HIs). Specifically, we investigate a scenario where a base station (BS) equipped with multiple fluid antennas communicates with multiple users (CUs), each equipped with a single fluid antenna. Our objective is to maximize the minimum communication rate among all users by jointly optimizing the BS's transmit beamforming, the positions of its transmit fluid antennas, and the positions of the CUs' receive fluid antennas. To address this non-convex problem, we propose a block coordinate descent (BCD) algorithm integrating semidefinite relaxation (SDR), rank-one constraint relaxation (SRCR), successive convex approximation (SCA), and majorization-minimization (MM). Simulation results demonstrate that FAS significantly enhances system performance and robustness, with notable gains when both the BS and CUs are equipped with fluid antennas. Even under low transmit power conditions, deploying FAS at the BS alone yields substantial performance gains. However, the effectiveness of FAS depends on the availability of sufficient movement space, as space constraints may limit its benefits compared to fixed antenna strategies. Our findings highlight the potential of FAS to mitigate HIs and enhance multi-user system performance, while emphasizing the need for practical deployment considerations. © 2024, CC BY.

关键词： Receiving antennas

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The development of microfabricated solenoids with magnetic cores for micromagnetic neural stimulation

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Microsystems & Nanoengineering 2021年第6期7卷 97-106页

作者： Adam Khalifa Mohsen Zaeimbashi Tony X.Zhou Seyed Mahdi Abrishami Neville Sun Seunghyun Park TamaraŠumarac Jason Qu Inbar Zohar Amir Yacoby Sydney Cash Nian X.Sun Department of Neurology Massachusetts General HospitalHarvard Medical SchoolBostonMAUSA Department of Electrical and Computer Engineering Northeastern UniversityBostonMAUSA Research Laboratory of Electronics Massachusetts Institute of TechnologyCambridgeMAUSA Department of Physics Harvard UniversityCambridgeMAUSA Department of Chemical and Biological Physics Weizmann Institute of ScienceRehovotIsrael

electrical stimulation via invasive microelectrodes is commonly used to treat a wide range of neurological and psychiatric *** its remarkable success,the stimulation performance is not sustainable since the electrodes become encapsulated by gliosis due to foreign body *** stimulation overcomes these limitations by eliminating the need for a metal-electrode ***,we demonstrate a novel microfabricated solenoid inductor(80µm×40µm)with a magnetic core that can activate neuronal *** characterization and proof-of-concept of the device raise the possibility that micromagnetic stimulation solenoids that are small enough to be implanted within the brain may prove to be an effective alternative to existing electrode-based stimulation devices for chronic neural interfacing applications.

关键词： magnetic neural overcome

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Optimization of Microwave Resonant Cavity Flowmeter Design for High Temperature Fluid Sensing Applications

Optimization of Microwave Resonant Cavity Flowmeter Design f...

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IEEE International Conference on Electro-Information Technology

作者： Tianyang Fang Jafar Saniie Sasan Bakhtiari Alexander Heifetz Department of Electrical and Computer Engineering ECASP Research Laboratory Illinois Institute of Technology Chicago IL U.S.A. Nuclear Science and Engineering Division Argonne National Laboratory Lemont IL U.S.A.

This paper investigates optimization of parameters to enhance performance of a microwave resonant cavity transducer for high temperature fluid flow sensing in advanced reactors. The cylindrical microwave cavity flowmeter is a novel sensor that measures fluid flow velocity through deflection of the cavity wall due to dynamic fluid pressure. This sensor is designed to operate in harsh environments of a nuclear reactor because sensor material is resilient to high temperatures, ionizing radiation, and corrosion. Parameters that determine performance characteristics of the transducer include dimensions of the microwave cavity, cavity electromagnetic excitation method, and cavity material. We investigate transducer design through computer simulations, with the objective of maximizing cavity Q-factor.

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Review of Inference Time Prediction Approaches of DNN: Emphasis on Service robots with cloud-edge-device architecture

Review of Inference Time Prediction Approaches of DNN: Empha...

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IEEE International Conference on Robotics and Biomimetics

作者： Tian Xiang Qiwei Meng Ji Zhang Beibei Zhang Wei Song Anhuan Xie Jason Gu Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou China Department of Mechanical and Automation Engineering T Stone Robotics Institute The Chinese University of Hong Kong HKSAR China Research Center for Intelligent Computing Software Research Institute of Intelligent Computing Zhejiang Laboratory Hangzhou China Electrical and Computer Engineering Dalhousie University Halifax Canada

In recent years, the global robot market has witnessed substantial growth, particularly in the domain of service robots. Despite their expanding presence, service robots encounter limitations when operating autonomously in unstructured environments, primarily due to their constrained computational capacities. As a solution, the fusion of cloud and edge computing resources becomes imperative to expedite task inference and enhance scenario perception capabilities. The integration of cloud-edge-device models holds significant promise in bolstering the operational efficiency of robots. This entails the dynamic partitioning of intricate robotic tasks, executed collaboratively across cloud, edge, and device resources. In this landscape, deep neural network (DNN) models play a pivotal role in facilitating a wide array of robotic tasks. The inference time for each layer of a DNN model in actual deployment, emerges as a critical determinant in the model’s partitioning strategy. It also serves as an important metric influencing the model’s suitability for a specific hardware platform. This article presents an overview of recent advancements in predicting inference and training time of DNN models, summarizes the related methods, and finally discusses the challenges in this field and the research that can be studied in the future.

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Directly wireless communication of human minds via non-invasive brain-computer-metasurface platform

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eLight 2022年第1期2卷 132-142页

作者： Qian Ma Wei Gao Qiang Xiao Lingsong Ding Tianyi Gao Yajun Zhou Xinxin Gao Tao Yan Che Liu Ze Gu Xianghong Kong Qammer HAbbasi Lianlin Li Cheng‑Wei Qiu Yuanqing Li Tie Jun Cui Institute of Electromagnetic Space Southeast UniversityNanjing 210096China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China State Key Laboratory of Millimeter Wave Southeast UniversityNanjing 210096China Center of Intelligent Metamaterials Pazhou Laboratory Guangzhou 510330China Research Center for Brain-Computer Interface Pazhou LabGuangzhou 510330China Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore University of Glasgow James Watt School of EngineeringGlasgow G128QQUK State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsPeking UniversityBeijing 100871China

Brain-computer interfaces(BCIs),invasive or non-invasive,have projected unparalleled vision and promise for assisting patients in need to better their interaction with the *** by the BCI-based rehabilitation technologies for nerve-system impairments and amputation,we propose an electromagnetic brain-computer-metasurface(EBCM)paradigm,regulated by human’s cognition by brain signals directly and *** experimentally show that our EBCM platform can translate human’s mind from evoked potentials of P300-based electroencephalography to digital coding information in the electromagnetic domain non-invasively,which can be further processed and transported by an information metasurface in automated and wireless *** wireless communications of the human minds are performed between two EBCM operators with accurate text ***,several other proof-of-concept mind-control schemes are presented using the same EBCM platform,exhibiting flexibly-customized capabilities of information processing and synthesis like visual-beam scanning,wave modulations,and pattern encoding.

关键词： communication computer surface

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Software-Defined Ultrasonic Communication System using PPM-EMAT with High Transmission Rate

Software-Defined Ultrasonic Communication System using PPM-E...

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IEEE Symposium (IUS) Ultrasonics

作者： Xin Huang Jafar Saniie Sasan Bakhtiari Alexander Heifetz Department of Electrical and Computer Engineering ECASP Research Laboratory Illinois Institute of Technology Chicago IL U.S.A Nuclear Science and Engineering Division Argonne National Laboratory Lemont IL U.S.A.

A novel approach to ultrasonic communication systems introduces a software-defined system that utilizes Periodic-permanent-magnet electromagnetic acoustic transducers (PPM-EMATs) as transmitters and receivers. Traditional systems had limitations in adaptability and flexibility. The software-defined system provides enhanced versatility, adaptability, and portability, allowing customization for diverse applications. The use of PPM-EMATs is explored for optimizing energy transfer through metal plate channels, generating shear horizontal waves. Experimental tests validate the efficiency of PPM-EMATs, showing successful communication at a 10-kbps bitrate using ASK modulation with a high signal-to-noise ratio (SNR). The research highlights the potential of PPM-EMAT technology in high-speed software-defined ultrasonic communication systems.

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POVNav: A Pareto-Optimal Mapless Visual Navigator

arXiv

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arXiv 2023年

作者： Pushp, Durgakant Chen, Zheng Luo, Chaomin Gregory, Jason M. Liu, Lantao Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States The Department of Electrical and Computer Engineering Mississippi State University MS39762 United States DEVCOM Army Research Laboratory United States

Mapless navigation has emerged as a promising approach for enablingautonomous robots to navigate in environments where pre-existing maps may beinaccurate, outdated, or unavailable. In this work, we propose an image-basedlocal representation of the environment immediately around a robot to parsenavigability. We further develop a local planning and control framework, aPareto-optimal mapless visual navigator (POVNav), to use this representationand enable autonomous navigation in various challenging and real-worldenvironments. In POVNav, we choose a Pareto-optimal sub-goal in the image byevaluating all the navigable pixels, finding a safe visual path, and generatingactions to follow the path using visual servo control. In addition to providingcollision-free motion, our approach enables selective navigation behavior, suchas restricting navigation to select terrain types, by only changing thenavigability definition in the local representation. The ability of POVNav tonavigate a robot to the goal using only a monocular camera without relying on amap makes it computationally light and easy to implement on various roboticplatforms. Real-world experiments in diverse challenging environments, rangingfrom structured indoor environments to unstructured outdoor environments suchas forest trails and roads after a heavy snowfall, using various imagesegmentation techniques demonstrate the remarkable efficacy of our proposedframework. © 2023, CC BY-NC-SA.

关键词： Visual servoing

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Machine Learning Approaches for Tackling Novel Coronavirus (COVID-19) Pandemic

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SN computer science 2021年第5期2卷 384页

作者： Rahman, Mohammad Marufur Islam, Md. Milon Manik, Md. Motaleb Hossen Islam, Md. Rabiul Al-Rakhami, Mabrook S. Department of Computer Science and Engineering Khulna University of Engineering and Technology Khulna 9203 Bangladesh Department of Electrical and Electronic Engineering Bangladesh Army University of Engineering and Technology Natore 6431 Bangladesh Research Chair of Pervasive and Mobile Computing Information Systems Department College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia

Novel coronavirus (COVID-19) has become a global problem in recent times due to the rapid spread of this disease. Almost all the countries of the world have been affected by this pandemic that made a major consequence on the medical system and healthcare facilities. The healthcare system is going through a critical time because of the COVID-19 pandemic. Modern technologies such as deep learning, machine learning, and data science are contributing to fight COVID-19. The paper aims to highlight the role of machine learning approaches in this pandemic situation. We searched for the latest literature regarding machine learning approaches for COVID-19 from various sources like IEEE Xplore, PubMed, Google Scholar, research Gate, and Scopus. Then, we analyzed this literature and described them throughout the study. In this study, we noticed four different applications of machine learning methods to combat COVID-19. These applications are trying to contribute in various aspects like helping physicians to make confident decisions, policymakers to take fruitful decisions, and identifying potentially infected people. The major challenges of existing systems with possible future trends are outlined in this paper. The researchers are coming with various technologies using machine learning techniques to face the COVID-19 pandemic. These techniques are serving the healthcare system in a great deal. We recommend that machine learning can be a useful tool for proper analyzing, screening, tracking, forecasting, and predicting the characteristics and trends of COVID-19. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： COVID-19 Forecasting Machine learning Novel coronavirus Prediction

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Photoexcitation enhances carrier mobility at low temperatures in narrow-gap HgCdTe films

Photoexcitation enhances carrier mobility at low temperature...

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International Conference on Infrared and Millimeter Waves

作者： Nils B. Refvik David N. Purschke Charles E. Jensen Wenwu Pan Howe R. J. Simpson Wen Lei Renjie Gu Jarek Antoszewski Gilberto A. Umana-Membreno Lorenzo Faraone Frank A. Hegmann Department of Physics University of Alberta Edmonton Canada Joint Attosecond Science Laboratory National Research Council of Canada University of Ottawa Ottawa Canada Department of Electrical Electronic and Computer Engineering The University of Western Australia Perth Australia

ISBN: (数字)9798350370324

ISBN: (纸本)9798350370331

The characterization of carrier dynamics in mercury cadmium telluride (HgCdTe) thin films is essential for novel applications in long-wave infrared detection. Here, we conduct a novel study of ultrahigh carrier mobilities in narrow-gap HgCdTe films as measured by both terahertz time-domain spectroscopy (THz-TDS) at equilibrium and time-resolved THz spectroscopy (TRTS) after ultrafast photoexcitation. The observed THz transmission through the photoexcited samples is accurately modelled by a three-layer thin-film formula. At low temperatures, the carrier mobility obtained by TRTS is significantly higher than that obtained by THz-TDS. We attribute this enhancement in the low-temperature photocarrier mobility to suppression of impurity scattering by photoexcited holes.

关键词： Temperature measurement Spectroscopy Semiconductor device measurement II-VI semiconductor materials Films Impurities Scattering Time-domain analysis Tellurium Cadmium compounds

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Technologies for Modulation of Visible Light and their Applications

arXiv

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arXiv 2024年

作者： Park, Sanghyo Notaros, Milica Mohanty, Aseema Kim, Donggyu Notaros, Jelena Mouradian, Sara Department of Physics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical & Computer Engineering Tufts University MedfordMA02155 United States Department of Electrical & Computer Engineering University of Washington SeattleWA98195 United States

Control over the amplitude, phase, and spatial distribution of visible-spectrum light underlies many technologies, but commercial solutions remain bulky, require high control power, and are often too slow. Active integrated photonics for visible light promises a solution, especially with recent materials and fabrication advances. In this review, we discuss three growing application spaces which rely on control of visible light: control and measurement of atomic quantum technologies, augmented-reality displays, and measurement and control of biological systems. We then review the commercial dynamic surfaces and bulk systems which currently provide visible-light modulation and the current state-of-the-art integrated solutions. Throughout the review we focus on speed, control power, size, optical bandwidth, and technological maturity when comparing technologies. Copyright © 2024, The Authors. All rights reserved.

关键词： Light modulation

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