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Expanding chiral metamaterials for retrieving fingerprints via vibrational circular dichroism

Light(Science & Applications) 2023年第7期12卷 1401-1414页

作者： Cheng Xu Zhihao Ren Hong Zhou Jingkai Zhou Chong Pei Ho Nan Wang Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Center for Inteligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore institute of Microelectronics(IME) Agency for ScienceTechnology and Research(A*STAR)Singapore 138634Singapore NUS Graduate School for Integrative Science and Engineering Program(ISEP) National University of SingaporeSingapore 117456Singapore

Circular dichroism(CD)spectroscopy has been widely demonstrated for detecting chiral ***,the determination of chiral mixtures with various concentrations and enantiomeric ratios can be a challenging *** solve this problem,we report an enhanced vibrational circular dichroism(VCD)sensing platform based on plasmonic chiral metamaterials,which presents a 6-magnitude signal enhancement with a selectivity of chiral *** by coupled-mode theory,we leverage both in-plane and out-of-plane symmetry-breaking structures for chiral metamaterial design enabled by a two-step lithography process,which increases the near-field coupling strengths and varies the ratio between absorption and radiation loss,resulting in improved chiral light-matter interaction and enhanced molecular VCD ***,we demonstrate the thin-film sensing process of BSA andβ-lactoglobulin proteins,which contain secondary structures a-helix andβ-sheet and achieve a limit of detection down to zeptomole ***,we also,for the first time,explore the potential of enhanced VCD spectroscopy by demonstrating a selective sensing process of chiral mixtures,where the mixing ratio can be successfully differentiated with our proposed chiral *** findings improve the sensing signal of molecules and expand the extractable information,paving the way toward label-free,compact,small-volume chiral molecule detection for stereochemical and clinical diagnosisapplications.

关键词： chiral vibrational circular

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Guest Editorial: 5G Advanced

IEEE Communications Standards Magazine

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IEEE Communications Standards Magazine 2023年第1期7卷 2-3页

作者： Kunz, Andreas Samdanis, Konstantinos Alexandropoulos, George C. Song, Jaeseung Taleb, Tarik Electrical Engineering The University of Siegen Germany Aalto University Finland Huawei German Research Center Munich Germany University of Patras Greece Computer and Information Security Department Sejong University Korea Republic of Center of Wireless Communications The University of Oulu Finland

3GPP specified 5G and provided improvements in terms of the system performance and support for the integration of new scenarios for accommodating various vertical segments. The upcoming Release 18 defines “5G Advanced” as a milestone towards 6G, introducing several enhancements in terms of the network architecture, physical layer, new services, security, and automation.

关键词： Special issues and sections 5G mobile communicatoin 3GPP Performance evaluation Systems engineering and theory

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A survey and recent advances in black widow optimization: variants and applications

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Neural Computing and Applications 2024年 1-21页

作者： Shehab, Mohammad Shambour, Mohd Khaled Yousef Abu Hashem, Muhannad A. Al Hamad, Husam Ahmad Shannaq, Fatima Mizher, Manar Jaradat, Ghaith Sh. Daoud, Mohammad Abualigah, Laith College of Computer Sciences and Informatics Amman Arab University Amman11953 Jordan The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura University Makkah Saudi Arabia Department of Geomatics Architecture and Planning Faculty King Abdulaziz University Jeddah Saudi Arabia College of Engineering Al Ain University Abu Dhabi United Arab Emirates Research Center University of Tabuk Tabuk71491 Saudi Arabia Computer Science Department Al al-Bayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Applied science research center Applied science private university Amman11931 Jordan College of Engineering Yuan Ze University Taoyuan32003 Taiwan

Artificial Intelligence techniques, such as optimization algorithms, have become essential for success in many fields. Therefore, most researchers, especially in computer and engineering sciences, focused their efforts and abilities on adapting the optimization algorithms for solving various problems. This review introduces one of the recent nature-inspired optimization algorithms, called black widow optimization (BWO). This review highlights the main procedures of BWO, its strengths and weaknesses, the growth of BWO, the variants of BWO (i.e., binary, modification, and hybridization), and the efficiency of BWO in different fields and applications (i.e., feature selection, medical, image processing, engineering, IoT, power and energy, and networks). As a result, the review seeks to assist researchers who are interested in using the BWO to address their challenges. For instance, it could help manage large pilgrim crowds, enabling smoother ritual performances and overcoming potential difficulties they encounter. Also, it suggests new possible ways of enhancing the efficiency of the basic BWO. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Optimization

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Lumbar spine localisation method based on feature fusion

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 931-945页

作者： Yonghong Zhang Ning Hu Zhuofu Li Xuquan Ji Shanshan Liu Youyang Sha Xiongkang Song Jian Zhang Lei Hu Weishi Li Robotics Institute School of Mechanical Engineering and AutomationBeihang UniversityBeijingChina Beijing Zhuzheng Robot Co. LTDBeijingChina Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKnoxvilleTennesseeUSA Department of Orthopaedics Peking University Third HospitalBeijingChina Engineering Research Center of Bone and Joint Precision Medicine Ministry of EducationBeijingChina Beijing Key Laboratory of Spinal Disease Research BeijingChina School of Biological Science and Medical Engineering Beihang UniversityBeijingChina Department of Computer Science University of WarwickCoventryUK

To eliminate unnecessary background information,such as soft tissues in original CT images and the adverse impact of the similarity of adjacent spines on lumbar image segmentation and surgical path planning,a two‐stage approach for localising lumbar segments is ***,based on the multi‐scale feature fusion technology,a non‐linear regression method is used to achieve accurate localisation of the overall spatial region of the lumbar spine,effectively eliminating useless background information,such as soft *** the second stage,we directly realised the precise positioning of each segment in the lumbar spine space region based on the non‐linear regression method,thus effectively eliminating the interference caused by the adjacent *** 3D Intersection over Union(3D_IOU)is used as the main evaluation indicator for the positioning *** an open dataset,3D_IOU values of 0.8339�0.0990 and 0.8559�0.0332 in the first and second stages,respectively is *** addition,the average time required for the proposed method in the two stages is 0.3274 and 0.2105 s ***,the proposed method performs very well in terms of both pre-cision and speed and can effectively improve the accuracy of lumbar image segmentation and the effect of surgical path planning.

关键词： CT image lumbar spatial orientation multi‐scale information fusion

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Seamless Distributed Power Management of DC Microgrid under Cyber Attacks with Bidirectional Power Flow

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Tran, Dat Thanh Kim, Kyeong-Hwa Lai, Jih-Sheng Seoul National University of Science and Technology Research Center for Electrical and Information Technology Department of Electrical and Information Engineering Seoul01811 Korea Republic of Department of Electrical and Computer Engineering BlacksburgVA24061 United States

A seamless distributed power management for the dc microgrid (DCMG) with bidirectional power flow is presented in this paper to achieve the overall system stabilization even under severe cyber attacks. First, a distributed secondary control (DSC) based on the V*-P droop curves is presented to ensure the power and voltage regulation for the DCMG system consisting of the electric vehicle (EV), wind turbine, battery, load, and utility grid agents under uncertain conditions. The proposed scheme automatically adjusts the utility grid droop curve to minimize electricity expenditure under electricity price change. To eliminate the negative effect of severe cyber attacks such as false data injection (FDI) and denial-of-service (DoS) in the distributed DCMG system, a resilient DSC based on the compensation term is utilized in the proposed scheme. In addition, by modifying the DSC structure of each power agent, the proposed scheme reduces the overshoot of the dc bus voltage even in the presence of the electricity price change, agent power variation, sudden utility grid disconnection, or critical state-of-charge (SOC) levels. Furthermore, the proposed distributed DCMG system utilizes only the unidirectional digital communication links (DCLs) to cut down the system cost and communication burden, which greatly simplifies communication structure. The efficiency and feasibility of the proposed distributed power management are validated by simulation and experimental results under various conditions. © 2025 IEEE.

关键词： Cyber attacks

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Grid-Induced Telluric Currents for Non-Contact Load Monitoring and Fault Detection

Grid-Induced Telluric Currents for Non-Contact Load Monitori...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Farris, Abigail C. Stump, William A. Johnson, Christopher S. Craven, Robert Van Neste, C.W. Tennessee Technological University Electrical and Computer Engineering Department CookevilleTN United States Tennessee Technological University Center for Energy Systems Research CookevilleTN United States

ISBN: (纸本)9798350316445

Grid-Induced ground currents occur when line-imbalances flow into the earth, creating a form of man-made telluric current. At the soil surface, a 2-dimensional, directional current density exists which follows the time varying load profile of the local power distribution system. When a fault occurs (either line-to-line or line-to-ground), a perturbation can be observed in the differential voltages measured in the soil, making grid-induced telluric currents a unique and mostly unexplored candidate for non-contact grid monitoring and fault detection. The directional nature of the induced telluric current provides information that can be used to localize a power-grid fault. Presented here is a non-invasive sensing technique that allows direct measurements of a substation's load profile at a distance of 0.8 kilometers. Identification of the direction of the induced current in the soil is explored. A discussion on the sensor's positional sensitivity is given. © 2023 IEEE.

关键词： Fault Detection Geomagnetic Disturbance (GMD) Non-intrusive load monitoring Telluric Currents

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Wide Area Control of Distributed Resources through 5G Communication to Provide Frequency Support 8

Wide Area Control of Distributed Resources through 5G Commun...

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8th IEEE International Smart Cities Conference, ISC2 2022

作者： Hadjidemetriou, L. Akrytov, A. Kyriakou, K. Charalambous, C. Asprou, M. Ciornei, I. Ellinas, G. Panayiotou, C. Kios Research and Innovation Center of Excellence University of Cyprus Cyprus University of Cyprus Department of Electrical and Computer Engineering Cyprus

ISBN: (数字)9781665485616

ISBN: (纸本)9781665485616

Towards the green transition of modern power systems, a massive deployment of distributed energy resources (DERs) based on renewable sources is required. These DERs are grid integrated through power electronics converters which reduce the commitment of synchronous generators and as a result, the overall inertia of the system. Maintaining the frequency stability in such low-inertia power systems is a crucial aspect for the system operators;therefore, local control schemes are integrated with conventional generators and DERs to ensure fast reaction in case of frequency disturbances so as to preserve system stability. Existing practices for maintaining the frequency stability rely on the response of a local governor controller integrated with the synchronous generators. Some new approaches introduce frequency support services by DERs, by considering the droop control and virtual inertia concept within the inverter local controller. In another approach, wide area control schemes can also be utilized to further enhance the system stability. Such a wide area control scheme is introduced in this work to coordinate the operation of DERs through 5G communication for enabling fast frequency support services. Due to the fast dynamics of a power system, a reliable and high-speed communication is particularly important for the deployment of the proposed method. Therefore, an experimental hardware in the loop setup has been developed to investigate how the communication performance can affect the stability of the power system. Moreover, a benchmarking is implemented to evaluate the frequency stability when local controllers are providing support and when the proposed wide area controller is applied under a different communication infrastructure. Experimental results demonstrate that when a reliable 5G network is used, then a significant stability improvement can be achieved by the proposed wide area controller. © 2022 IEEE.

关键词： Controllers

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Deep Learning-Based Symbol Detection for Time-Varying Nonstationary Channels

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China Communications 2022年第3期19卷 158-171页

作者： Xuantao Lyu Wei Feng Ning Ge Xianbin Wang Research Center of Networks and Communications Peng Cheng LaboratoryShenzhen 518055China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China Department of Electrical and Computer Engineering The University of Western OntarioLondonON N6A 5B9Canada

The highly dynamic channel(HDC)in an extremely dynamic environment mainly has fast timevarying nonstationary *** this article,we focus on the most difficult HDC case,where the channel coherence time is less than the symbol *** this end,we propose a symbol detector based on a long short-term memory(LSTM)neural *** the sampling sequence of each received symbol as the LSTM unit's input data has the advantage of making full use of received information to obtain better *** addition,using the basic expansion model(BEM)as the preprocessing unit significantly reduces the number of neural network ***,the simulation part uses the highly dynamic plasma sheath channel(HDPSC)data measured from shock tube *** results show that the proposed BEM-LSTM-based detector has better performance and does not require channel estimation or channel model information.

关键词： highly dynamic channel deep neural network long short-term memory basis expansion model symbol detection

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The Immense Impact of Reverse Edges on Large Hierarchical Networks

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engineering 2024年第5期36卷 240-249页

作者： Haosen Cao Bin-Bin Hu Xiaoyu Mo Duxin Chen Jianxi Gao Ye Yuan Guanrong Chen Tamás Vicsek Xiaohong Guan Hai-Tao Zhang MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Jiangsu Key Laboratory of Networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electronic Engineering City University of Hong KongHong Kong 999077China Department of Biological Physics Eötvös UniversityBudapest 1117Hungary MOE Key Laboratory for Intelligent Networks and Network Security School of Automation Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so *** structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social *** study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific *** surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved *** overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization *** finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these *** study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

关键词： Synchronizability Large hierarchical networks Reverse edges Information flows Complex networks

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Swallowing Assessment using High-Resolution Cervical Auscultations and Transformer-based Neural Networks 46

Swallowing Assessment using High-Resolution Cervical Auscult...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Anwar, Ayman Khalifa, Yassin Lucatorto, Erin Coyle, James L. Sejdic, Ervin University of Toronto Faculty of Applied Science & Engineering Department of Electrical and Computer Engineering TorontoON Canada University of Pittsburgh Center for Research Computing and Information Technology Analytics PittsburghPA United States Cairo University Faculty of Engineering Systems and Biomedical Engineering Department Giza Egypt University of Pittsburgh School of Health and Rehabilitation Sciences Department of Communication Science and Disorders PittsburghPA United States University of Toronto North York General Hospital Faculty of Applied Science & Engineering Department of Electrical and Computer Engineering TorontoON Canada

ISBN: (纸本)9798350371499

Swallowing assessment is a crucial task to reveal swallowing abnormalities. There are multiple modalities to analyze swallowing kinematics, such as videofluoroscopic swallow studies (VFSS), which is the gold standard method, and high-resolution cervical auscultation (HRCA), which is a noninvasive technique that uses a triaxial accelerometer attached to the patient's neck. Deep learning models play an essential role in data driven analysis of swallowing landmarks using VFSS and/or HRCA as input data. Most of these models utilize convolutional and recurrent neural networks. Here, we investigate the ability of transformers to analyze swallowing kinematics;specifically upper esophageal sphincter opening and laryngeal vestibule closure using HRCA signals. We tested the model using an independent test dataset to assess the generalizability of the proposed network. The proposed network achieved an average detection accuracy higher than 90% and 85% for both segmentation tasks, which outperform the hybrid neural networks from the literature, and the model obtained high-performance measures for the independent dataset, showing the transformers' ability to generalize on unseen data. © 2024 IEEE.

关键词： Recurrent neural networks

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