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STARS Assisted Semi-Grant-Free NOMA Communications

IEEE Transactions on Wireless Communications 2025年第6期24卷 4904-4919页

作者： Xie, Jin Yue, Xinwei Zhao, Jingjing Zou, Yixuan Liu, Yuanwei Liu, Rongke Ding, Zhiguo Key Laboratory of Information and Communication Systems China Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100101 China Beihang University School of Electronic and Information Engineering Beijing100191 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of Khalifa University Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

This paper investigates the performance of simultaneously transmitting and reflecting surface (STARS) assisted semi-grant-free non-orthogonal multiple access network with randomly distributed users. By deploying STARS, the transmit signals of grant-based user (GBU) and grant-free users (GFUs) can be exquisitely adjusted to reduce interference. We propose a maximum channel scheduling (MCS) protocol that allows a GFU to access GBU’s channel with the assistance of STARS. In particular, the impacts of perfect/imperfect successive interference cancellation (pSIC/ipSIC) on MCS protocol are taken into account. To characterize the performance of STARS aided MCS (STARS-MCS) network, we derive the expressions of outage probability for GBU and GFU with pSIC/ipSIC. By applying convolution theorem and Laplace transform, the asymptotic expressions of outage probability and diversity orders for GBU and GFU are attained. We further design a STARS-based power control (SPC) strategy to eliminate the outage probability error floor and improve the outage performance. Numerical results show that: 1) The performance of STARS-MCS outperforms the existing benchmarks in terms of outage probability and system throughput;2) The SPC strategy can effectively improve the performance of the STARS-MCS network and eliminate the outage probability error floor at high signal-to-noise ratios;and 3) By adjusting reflection and transmission coefficients of STARS, the outage performance of GBU and GFU can be greatly enhanced. © 2025 IEEE. All rights reserved.

关键词： Laplace transforms

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Carbon nanotube transistor technology for More-Moore scaling

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Nano research 2021年第9期14卷 3051-3069页

作者： Qing Cao Department of Materials Science and Engineering Department of Electrical and Computer EngineeringDepartment of Chemistry Seitz Materials Research LaboratoryUniversity of Illinois at Urbana-ChampaignUrbanaIL 61820USA

Scaling of silicon field-effect transistors has fueled the exponential development of microelectronics in the past 60 years,but is now close to its physical limits with the critical dimensions of state-of-the-art silicon devices approaching the sub-10 nm *** nanotubes have been suggested to hold great promise of replacing the central role of silicon in the next-generation logic switches with their unique geometrical and electrical *** this article,I firstly examine the scaling advantages of carbon nanotubes compared to silicon from technology-development perspective,and then review the latest progress on addressing the manufacturability issues for scaled carbon-nanotube transistors,from materials to device-integration ***,the possible pathways for nanotube transistors to transition into commercial applications are discussed.

关键词： carbon nanotube transistor scaling

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Prediabetes detection in unconstrained conditions using wearable sensors

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Clinical Nutrition Open science 2024年 58卷 163-174页

作者： Tatli, Dimitra Papapanagiotou, Vasileios Liakos, Aris Tsapas, Apostolos Delopoulos, Anastasios Multimedia Understanding Group Dpt. of Electrical and Computer Engineering Faculty of Engineering AUTH Greece Embedded Systems Laboratory Institute of Electrical and Micro Engineering EPFL Lausanne Switzerland IMPACT Research Group Dpt. of Medicine Karolinska Institutet Huddinge Sweden Diabetes Centre Second Medical Department at Ippokratio General Hospital Thessaloniki Greece

Prediabetes is a common health condition that often goes undetected until it progresses to type 2 diabetes. Early identification of prediabetes is essential for timely intervention and prevention of complications. This research explores the feasibility of using wearable continuous glucose monitoring along with smartwatches with embedded inertial sensors to collect glucose measurements and acceleration signals respectively, for the early detection of prediabetes. We propose a methodology based on signal processing and machine learning techniques. Two feature sets are extracted from the collected signals, based both on a dynamic modeling of the human glucose-homeostasis system and on the Glucose curve, inspired by three major glucose related blood tests. Features are aggregated per individual using bootstrap. Support Vector Machines are used to classify normoglycemic vs. prediabetic individuals. We collected data from 22 participants for evaluation. The results are highly encouraging, demonstrating high sensitivity and precision. This work is a proof of concept, highlighting the potential of wearable devices in prediabetes assessment. Future directions involve expanding the study to a larger, more diverse population and exploring the integration of CGM and smartwatch functionalities into a unified device. Automated eating detecting algorithms can also be used. © 2024 The Authors

关键词： Continuous glucose monitors Machine learning Prediabetes Signal processing

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Impact of dissolution and precipitation on pore structure in CO_(2)sequestration within tight sandstone reservoirs

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Petroleum science 2025年第2期22卷 868-883页

作者： Hui Gao Kai-Qing Luo Chen Wang Teng Li Zhi-Lin Cheng Liang-Bin Dou Kai Zhao Nan Zhang Yue-Liang Liu School of Petroleum Engineering Xi'an Shiyou UniversityXi'an710065ShaanxiChina Engineering Research Center of Development and Management for Low to Ultra-Low Permeability Oil&Gas Reservoirs in West China Ministry of EducationXi'an710065ShaanxiChina Xi'an Key Laboratory of Tight Oil(shale Oil)Development Xi'an710065ShaanxiChina Department of Electrical Engineering and Computer Science University of StavangerStavanger4036Norway School of Petroleum Engineering China University of Petroleum(Beijing)Beijing102249China

Complex physical and chemical reactions during CO_(2)sequestration alter the microscopic pore structure of geological formations,impacting sequestration *** investigate CO_(2)sequestration dynamics,comprehensive physical simulation experiments were conducted under varied pressures,coupled with assessments of changes in mineral composition,ion concentrations,pore morphology,permeability,and sequestration capacity before and after ***,a method using NMR T2spectra changes to measure pore volume shift and estimate CO_(2)sequestration is *** quantifies CO_(2)needed for mineralization of soluble ***,when CO_(2)dissolves in crude oil,the precipitation of asphaltene compounds impairs both seepage and storage ***,the impact of dissolution and precipitation is closely associated with storage pressure,with a particularly pronounced influence on smaller *** pressure levels rise,the magnitude of pore alterations progressively *** a pressure threshold of 25 MPa,the rate of change in small pores due to dissolution reaches a maximum of 39.14%,while precipitation results in a change rate of-58.05%for small *** observed formation of dissolution pores and micro-cracks during dissolution,coupled with asphaltene precipitation,provides crucial insights for establishing CO_(2)sequestration parameters and optimizing strategies in low permeability reservoirs.

关键词： Dissolution Precipitation Pore structure CO_(2)sequestration Unconventional reservoirs

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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of Structural and Civil engineering 2024年第3期18卷 393-410页

作者： Tram BUI-NGOC Duy-Khuong LY Tam T TRUONG Chanachai THONGCHOM T.NGUYEN-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer Science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat School of Engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

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VISION-iT:A Framework for Digitizing Bubbles and Droplets

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Energy and AI 2024年第1期15卷 26-35页

作者： Youngjoon Suh Sanghyeon Chang Peter Simadiris Tiffany B.Inouye Muhammad Jahidul Hoque Siavash Khodakarami Chirag Kharangate Nenad Miljkovic Yoonjin Won Department of Mechanical and Aerospace Engineering University of CaliforniaIrvine4200 Engineering GatewayCA 92617-2700USA Department of Electrical Engineering and Computer Science University of CaliforniaIrvine5200 Engineering HallCA 92617-2700USA Department of Mechanical Science and Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Mechanical and Aerospace Engineering Department Case Western Reserve UniversityClevelandOH44106USA Department of Electrical and Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL61801USA Materials Research Laboratory University of Illinois at Urbana-ChampaignUrbanaIL61801USA International Institute for Carbon Neutral Energy Research(WPI-12CNER) Kyushu University744 Moto-okaNishi-kuFukuoka 819-0395Japan

Quantifying the nucleation processes involved in liquid-vapor phase-change phenomena,while dauntingly challenging,is central in designing energy conversion and thermal management *** technological advances in the deep learning and computer vision field offer the potential for quantifying such complex two-phase nucleation processes at unprecedented *** leveraging these new technologies,a multiple object tracking framework called“vision inspired online nuclei tracker(VISION-iT)”has been proposed to extract large-scale,physical features residing within boiling and condensation ***,extracting high-quality features that can be integrated with domain knowledge requires detailed discussions that may be field-or case-specific *** this regard,we present a demonstration and discussion of the detailed construction,algorithms,and optimization of individual modules to enable adaptation of the framework to custom *** concepts and procedures outlined in this study are transferable and can benefit broader audiences dealing with similar problems.

关键词： Deep learning computer vision Nucleation Heat transfer Phase-change phenomena

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Movable surface acoustic wave tweezers: a versatile toolbox for micromanipulation

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Microsystems & Nanoengineering 2024年第5期10卷 367-380页

作者： Xianming Qin Xianglian Liu Shuo Liu Chuanyu Zhang Ningning Bai Xue Li Weidong Wang Dan Liu Qiqi Yang Ruiguo Yang Yajing Shen Xueyong Wei School of Mechano-Electronic Engineering Xidian UniversityXi'an 710071China State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong UniversityXi'an 710049China State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipment Xidian UniversityXian 710071China State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and National Clinical Research Center for Digestive Diseases Xijing Hospital of Digestive DiseasesFourth Military Medical UniversityXi'an 710032China Department of Biomedical Engineering and Institute for Quantitative Health Science and Engineering(IQ)Michigan State UniversityEast LansingMI 48824USA Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina

Surface acoustic wave(SAW)tweezers are a promising multifunctional micromanipulation method that controls microscale targets via patterned acoustic *** to their device structure and bonding process,most SAW tweezers have limitations in terms of controlling the position and motion of the acoustic traps,as they generate an acoustic field with a fixed region and adjust the manipulation effects via signal *** address this challenge,we propose movable SAW tweezers with a multilayer structure,achieving dynamic control of their wave field and acoustic trap positions;we demonstrate their precise manipulation functions,such as translation,in-plane rotation,out-of-plane rotation,and cluster formation,on a wide spectrum of samples,including particles,bubbles,droplets,cells,and *** method not only improves the degree of freedom and working range of SAW tweezers but also allows for precise and selective manipulation of microtargets via microtools and localized *** to their flexibility,versatility,and biocompatibility,the movable SAW tweezers can be a practical platform for achieving arbitrary manipulation of microscale targets and have the potential to play significant roles in biomedical microrobotics.

关键词： wave precise rotation

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Thermal Analysis of Photodetectors in Steady-State

Thermal Analysis of Photodetectors in Steady-State

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2024 Laser Applications to Chemical, Security and Environmental Analysis, LACSEA 2024 - Part of Optica Sensing Congress

作者： Anjum, Ishraq Md Hastings, Alexander S. Tulchinsky, David A. Williams, Keith J. Menyuk, Curtis R. Simsek, Ergun Department of Computer Science and Electrical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States U.S. Naval Research Laboratory WashingtonDC20375 United States

ISBN: (纸本)9781957171371

This study introduces a method to approximate temperature distribution in steady-state photodetectors under optical excitation. Findings underscore the influence of temperature on key attributes, revealing overestimation with constant temperature assumptions. Insights aid in optimizing photodetector performance. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Photodetectors

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Cross-Modality Image Transformation Using Generative Adversarial Network 24th

Cross-Modality Image Transformation Using Generative Adversa...

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24th Conference on Man-Machine-Environment System engineering, MMESE 2024

作者： Liu, Haoting Yu, Shiqi Hou, Qingwen Chen, Shuai Guo, Kuiyuan Wang, Xu Li, Qing Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China CATARC Technology Co. Ltd. Shenzhen518118 China

ISBN: (纸本)9789819771387

A cross-modality image transformation method using the Generative Adversarial Network (GAN) is proposed in this paper. First, the preprocessing methods are performed to the original image data. The computational steps include adjusting image size and suppressing image noises. Second, a kind of GAN is constructed. Both the generator network and discriminator network are created. Third, the GAN is trained and the back propagation optimization is performed continuously. Finally, the trained GAN can be used for data enhancement. To test the effects of computational steps above, the image transformation from the visible light image to other noise-contaminated image is performed. Lots of experiments have illustrated the correctness of our method. © Beijing KeCui Man-Machine-Environment System engineering Technology research Academy 2024.

关键词： Generative adversarial networks

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Medical image registration and its application in retinal images:a review

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Visual Computing for Industry,Biomedicine,and Art 2024年第1期7卷 142-164页

作者： Qiushi Nie Xiaoqing Zhang Yan Hu Mingdao Gong Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Singapore Eye Research Institute Singapore 169856Singapore State Key Laboratory of Ophthalmology Optometry and Visual ScienceEye HospitalWenzhou Medical UniversityWenzhou 325027China

Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse informa-tion of images,which may be captured under different times,angles,or *** several surveys have reviewed the development of medical image registration,they have not systematically summarized the existing med-ical image registration *** this end,a comprehensive review of these methods is provided from traditional and deep-learning-based perspectives,aiming to help audiences quickly understand the development of medical image *** particular,we review recent advances in retinal image registration,which has not attracted much *** addition,current challenges in retinal image registration are discussed and insights and prospects for future research provided.

关键词： computer-aided diagnosis Medical image registration Deep learning Generative model Transformer Retina

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