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European Conference on Antennas and Propagation, EuCAP

作者： Muhammad Qamar Kamil Yavuz Kapusuz Mohamed A. Thaha Akram Alomainy Queen Mary University of London: School of Electronic Engineering and Computer Science London United Kingdom Department of Information Technology IDLab/EM Group Ghent University/imec Ghent Belgium Department of Colorectal Surgery Royal London Hospital Barts Health NHS Trust London United Kingdom Blizard Institute National Bowel Research Centre Barts and the London School of Medicine & Dentistry Queen Mary University of London London United Kingdom

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

A novel compact camera-integrated dual-band im-plantable antenna designed specifically for wireless capsule endoscopy (WCE) is presented for the first time. The antenna operates in two critical frequency bands: the Wireless Medical Telemetry Service (WMTS) band at 610 MHz and the Industrial, Scientific, and Medical (ISM) band at 2400 MHz. By employing arc-shaped slots on arc-shaped patches, the antenna achieves significant miniaturization, with a total volume of just 92.3 mm 3, Performance evaluation was carried out using homogeneous phantom models that mimic various tissues, such as the small and large intestines, muscle, and stomach. At an implantation depth of 100 mm, the antenna exhibited gain values of −35.3 dBi for the stomach, −35.8 dBi for muscle, −37.5 dBi for the large intestine, and −56.9 dBi for the small intestine in the WMTS frequency band. In the ISM frequency band, the gains were −29.7 dBi for muscle, −30.2 dBi for the stomach, −33.2 dBi for the large intestine, and −55.6 dBi for the small intestine. The simulated impedance bandwidths were approximately 8 MHz at 610 MHz and 25 MHz at 2400 MHz, indicating consistent performance across different tissues. Furthermore, the isolation between antenna elements exceeded 25 dB, minimizing interference. The antenna's robust performance positions it as a promising candidate for future wireless capsule endoscopy applications.

关键词： Wireless communication Stomach Intestines Slot antennas Endoscopes Dual band Phantoms Muscles Telemetry Gain

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Fair Evaluation of Federated Learning Algorithms for Automated Breast Density Classification: The Results of the 2022 ACR-NCI-NVIDIA Federated Learning Challenge

arXiv

引用

arXiv 2024年

作者： Schmidt, Kendall Bearce, Benjamin Chang, Ken Coombs, Laura Farahani, Keyvan Elbatel, Marawan Mouheb, Kaouther Marti, Robert Zhang, Ruipeng Zhang, Yao Wang, Yanfeng Hu, Yaojun Ying, Haochao Xu, Yuyang Testagrose, Conrad Demirer, Mutlu Gupta, Vikash Akünal, Ünal Bujotzek, Markus Maier-Hein, Klaus H. Qin, Yi Li, Xiaomeng Kalpathy-Cramer, Jayashree Roth, Holger R. American College of Radiology United States The Massachusetts General Hospital United States University of Colorado United States National Institutes of Health National Cancer Institute United States Computer Vision and Robotics Institute University of Girona Spain Cooperative Medianet Innovation Center Shanghai Jiao Tong University China Shanghai AI Laboratory China Real Doctor AI Research Centre Zhejiang University China School of Public Health Zhejiang University China College of Computer Science and Technology Zhejiang University China University of North Florida College of Computing Jacksonville United States Mayo Clinic Florida Radiology United States Division of Medical Image Computing German Cancer Research Center Heidelberg Germany Electronic and Computer Engineering Hong Kong University of Science and Technology China NVIDIA United States

The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due to the differences in imaging characteristics across mammography systems, models built using data from one system do not generalize well to other systems. Though federated learning (FL) has emerged as a way to improve the generalizability of AI without the need to share data, the best way to preserve features from all training data during FL is an active area of research. To explore FL methodology, the breast density classification FL challenge was hosted in partnership with the American College of Radiology, Harvard Medical Schools' Mass General Brigham, University of Colorado, NVIDIA, and the national Institutes of Health national Cancer Institute. Challenge participants were able to submit docker containers capable of implementing FL on three simulated medical facilities, each containing a unique large mammography dataset. The breast density FL challenge ran from June 15 to September 5, 2022, attracting seven finalists from around the world. The winning FL submission reached a linear kappa score of 0.653 on the challenge test data and 0.413 on an external testing dataset, scoring comparably to a model trained on the same data in a central location. © 2024, CC BY.

关键词： Learning algorithms

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Efficient Quantum State Tracking in Noisy Environments

arXiv

引用

arXiv 2022年

作者： Rambach, Markus Youssry, Akram Tomamichel, Marco Romero, Jacquiline Australian Research Council Centre of Excellence for Engineered Quantum Systems School of Mathematics and Physics University of Queensland QLD4072 Australia University of Technology Sydney Centre for Quantum Software and Information UltimoNSW2007 Australia Quantum Photonics Laboratory Centre for Quantum Computation and Communication Technology RMIT University MelbourneVIC3000 Australia Department of Electrical and Computer Engineering Centre for Quantum Technologies National University of Singapore Singapore119077 Singapore

Quantum state tomography, which aims to find the best description of a quantum state-the density matrix, is an essential building block in quantum computation and communication. Standard techniques for state tomography are incapable of tracking changing states and often perform poorly in the presence of environmental noise. Although there are different approaches to solve these problems theoretically, experimental demonstrations have so far been sparse. Our approach, matrix-exponentiated gradient tomography, is an online tomography method that allows for state tracking, updates the estimated density matrix dynamically from the very first measurements, is computationally efficient, and converges to a good estimate quickly even with noisy data. The algorithm is controlled via a single parameter, its learning rate, which determines the performance and can be tailored in simulations to the individual experiment. We present an experimental implementation of matrix-exponentiated gradient tomography on a qutrit system encoded in the transverse spatial mode of photons. We investigate the performance of our method on stationary and evolving states, as well as significant environmental noise, and find fidelities of around 95% in all cases. © 2022, CC BY.

关键词： Tomography

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Generic Hardware Realization of K Nearest Neighbors on FPGA

Generic Hardware Realization of K Nearest Neighbors on FPGA

引用

International Conference on Microelectronics, ICM

作者： Mohammed H. Yacoub Samar M. Ismail Lobna A. Said Ahmed H. Madian Ahmed G. Radwan Nanoelectronics Integrated Systems Center (NISC) Nile University Giza Egypt School of Engineering and Computer Science University of Hertfordshire (UH-GAF) Egypt Radiation Engineering Department National Centre for Radiation Research and Technology Cairo Egypt Engineering Mathematics and Physics Department Faculty of Engineering Cairo University Giza Egypt School of Engineering and Applied Sciences Nile University Giza Egypt

ISBN: (纸本)9781665493253

K Nearest Neighbors (KNN) algorithm is a straight-forward yet powerful Machine Learning (ML) tool widely used in classification, clustering, and regression applications. In this work, KNN is applied, with three distance metrics, to classify different datasets, experimentally testing each distance metric effect on the classification performance. A static K is applied for the whole dataset optimally chosen based on a 5-fold cross-validation. A reconfigurable hardware realization on field programmable gate array (FPGA) of each distance metric applying selection sort algorithm is proposed. The FPGA realization reaches a throughput up to 4.44 Gbit/sec while only occupying 1% of the Genesys 2 Kintex-7 board area. The algorithm managed to classify all the tested datasets with above 90% accuracy.

关键词： Measurement Software algorithms Euclidean distance Chebyshev approximation Throughput Hardware Software

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ARUSH:Automated Runtime Universal Scanner for Hybrid Cloud computing

ARUSH:Automated Runtime Universal Scanner for Hybrid Cloud c...

引用

2021 IEEE Globecom Workshops, GC Wkshps 2021

作者： Luthra, Jatin Choudhary, Arjun Sharma, Abhishek Jayakody, Dushantha Nalin K. The LNM Institute of Information Technology Jaipur India Sardar Patel University of Police Security and Criminal Justice Centre for Cyber Security Jodhpur India Sri Lanka Technological Campus Centre for Telecommunication Research School of Engineering Padukka Sri Lanka School of Computer Science and Robotics National Research Tomsk Polytechnic University Tomsk Russia Sciences and Technologies Department Universidade Aut onoma de Lisboa Lisboa1169-023 Portugal Autonoma TechLab Lisboa1169-023 Portugal

ISBN: (纸本)9781665423908

With the shift of leading companies to the cloud, so comes the risk of data leaks and breaches because of many possible misconfigurations in the setup of various cloud computing environments. Though many solutions have come up, each is platform-specific, and none of them targets multiple or hybrid cloud platforms all together. This work proposes one such solution where three major public cloud platforms are supported, and the main focus is on the storage services provided by them. Since there is no such open-source solution that supports multiple cloud platforms, the program in this work is supposed to provide such a solution. Each cloud platform provides native SDK libraries for issuing API calls to the platform. These API calls aim to query the currently employed configuration for the storage services at the very least if not change. The solution can combine all the libraries into a single driver program. The program can facilitate security management of storage accounts across multiple as well hybrid cloud services and opens possibilities for automation and routine security and audit checks. © 2021 IEEE.

关键词： Libraries

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Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks

引用

computers, Materials & Continua 2021年第9期68卷 3147-3165页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Lee Ching Kwang Rizaludin Kaspin Bhawani Shankar Chowdhry Rajkumar Buyya Satya Prasad Majumder Manoj Gupta Shuaib Memon Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation CentreCyberjaya63000SelangorMalaysia National Center of Robotics and Automation Mehran University of Engineering&TechnologyJamshoroPakistan Department of Computer Science and Engineering Hanyang UniversitySeoul04763South Korea School of Electrical and Electronic Engineering Nanyang Technological University639798Singapore Cloud Computing and Distributed Systems Laboratory The University of MelbourneMelbourneVIC 3053Australia Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology(BUET)Dhaka1205Bangladesh Department of Electronics and Communication Engineering JECRC UniversityVidhaniJaipur303905India Auckland Institute of Studies Mt AlbertAucklandNew Zealand

In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy ***,SDNs are vulnerable to distributed denial of service(DDoS)attacks that interfere with legitimate use of the *** ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high *** propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of DDoS *** a number of input parameters,our model has two distinct ***,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating ***,it recommends an optimal number of smart backup controllers for use with different levels of DDoS *** goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the *** simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost.

关键词： SDN automated controller placement SBC ILP DDoS attack

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A Van der Waals Moiré Bilayer Photonic Crystal Cavity

arXiv

引用

arXiv 2025年

作者： Spencer, Lesley Coste, Nathan Ni, Xueqi Park, Seungmin Schaeper, Otto C. Kim, Young Duck Taniguchi, Takashi Watanabe, Kenji Toth, Milos Zalogina, Anastasiia Tang, Haoning Aharonovich, Igor School of Mathematical and Physical Sciences University of Technology Sydney UltimoNSW2007 Australia ARC Centre of Excellence for Transformative Meta-Optical Systems University of Technology Sydney UltimoNSW2007 Australia Department of Physics National University of Singapore 119077 Singapore Department of Physics Kyung Hee University Seoul02447 Korea Republic of International Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Research Center for Functional Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States

Enhancing light-matter interactions with photonic structures is critical in classical and quantum nanophotonics. Recently, Moiré twisted bilayer optical materials have been proposed as a promising means towards a tunable and controllable platform for nanophotonic devices, with proof of principle realisations in the near infrared spectral range. However, the realisation of Moiré photonic crystal (PhC) cavities has been challenging, due to a lack of advanced nanofabrication techniques and availability of standalone transparent membranes. Here, we leverage the properties of the van der Waals material hexagonal Boron Nitride to realize Moiré bilayer PhC cavities. We design and fabricate a range of devices with controllable twist angles, with flatband modes in the visible spectral range (~ 450 nm). Optical characterization confirms the presence of spatially periodic cavity modes originating from the engineered dispersion relation (flatband). Our findings present a major step towards harnessing a two-dimensional van der Waals material for the next-generation of on chip, twisted nanophotonic systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Van der Waals forces

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Convex Optimization for Nonequilibrium Steady States on a Hybrid Quantum Processor

引用

Physical Review Letters 2023年第24期130卷 240601-240601页

作者： Jonathan Wei Zhong Lau Kian Hwee Lim Kishor Bharti Leong-Chuan Kwek Sai Vinjanampathy Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 Singapore 117543 Joint Center for Quantum Information and Computer Science and Joint Quantum Institute NIST/University of Maryland College Park Maryland 20742 USA Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (A*STAR) 1 Fusionopolis Way No. 16-16 Connexis Singapore 138632 Republic of Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit Singapore UMI 3654 Singapore National Institute of Education Nanyang Technological University 1 Nanyang Walk Singapore 637616 Singapore School of Electrical and Electronic Engineering Block S2.1 50 Nanyang Avenue Singapore 639798 Singapore Department of Physics Indian Institute of Technology-Bombay Powai Mumbai 400076 India Centre of Excellence in Quantum Information Computation Science and Technology Indian Institute of Technology Bombay Powai Mumbai 400076 India

Finding the transient and steady state properties of open quantum systems is a central problem in various fields of quantum technologies. Here, we present a quantum-assisted algorithm to determine the steady states of open system dynamics. By reformulating the problem of finding the fixed point of Lindblad dynamics as a feasibility semidefinite program, we bypass several well-known issues with variational quantum approaches to solving for steady states. We demonstrate that our hybrid approach allows us to estimate the steady states of higher dimensional open quantum systems and discuss how our method can find multiple steady states for systems with symmetries.

关键词： Learning theory Machine learning Open quantum systems & decoherence Quantum algorithms Nonequilibrium systems

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A predictive analytics approach for stroke prediction using machine learning and neural networks

引用

Healthcare Analytics 2022年 2卷 100032-100032页

作者： Dev, Soumyabrata Wang, Hewei Nwosu, Chidozie Shamrock Jain, Nishtha Veeravalli, Bharadwaj John, Deepu ADAPT SFI Research Centre Dublin Ireland School of Computer Science University College Dublin Ireland Beijing University of Technology Beijing China Beijing-Dublin International College Beijing China National College of Ireland Dublin Ireland Department of Electrical and Computer Engineering National University of Singapore Singapore School of Electrical and Electronic Engineering University College Dublin Ireland

The negative impact of stroke in society has led to concerted efforts to improve the management and diagnosis of stroke. With an increased synergy between technology and medical diagnosis, caregivers create opportunities for better patient management by systematically mining and archiving the patients’ medical records. Therefore, it is vital to study the interdependency of these risk factors in patients’ health records and understand their relative contribution to stroke prediction. This paper systematically analyzes the various factors in electronic health records for effective stroke prediction. Using various statistical techniques and principal component analysis, we identify the most important factors for stroke prediction. We conclude that age, heart disease, average glucose level, and hypertension are the most important factors for detecting stroke in patients. Furthermore, a perceptron neural network using these four attributes provides the highest accuracy rate and lowest miss rate compared to using all available input features and other benchmarking algorithms. As the dataset is highly imbalanced concerning the occurrence of stroke, we report our results on a balanced dataset created via sub-sampling techniques. © 2022 The Author(s)

关键词： electronic health records machine learning neural network predictive analytics stroke

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Towards 6G wireless communication networks:vision, enabling technologies, and new paradigm shifts

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Science China(Information Sciences) 2021年第1期64卷 5-78页

作者： Xiaohu YOU Cheng-Xiang WANG Jie HUANG Xiqi GAO Zaichen ZHANG Mao WANG Yongming HUANG Chuan ZHANG Yanxiang JIANG Jiaheng WANG Min ZHU Bin SHENG Dongming WANG Zhiwen PAN Pengcheng ZHU Yang YANG Zening LIU Ping ZHANG Xiaofeng TAO Shaoqian LI Zhi CHEN Xinying MA Chih-Lin I Shuangfeng HAN Ke LI Chengkang PAN Zhimin ZHENG Lajos HANZO Xuemin (Sherman) SHEN Yingjie Jay GUO Zhiguo DING Harald HAAS Wen TONG Peiying ZHU Ganghua YANG Jun WANG Erik G.LARSSON Hien Quoc NGO Wei HONG Haiming WANG Debin HOU Jixin CHEN Zhe CHEN Zhangcheng HAO Geoffrey Ye LI Rahim TAFAZOLLI Yue GAO H.Vincent POOR Gerhard P.FETTWEIS Ying-Chang LIANG National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast University Purple Mountain Laboratories Shanghai Institute of Fog Computing Technology (SHIFT) ShanghaiTech University Research Center for Network Communication Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications National Engineering Laboratory for Mobile Network Technologies Beijing University of Posts and Telecommunications National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China (UESTC) China Mobile Research Institute School of Electronics and Computer Science University of Southampton Department of Electrical and Computer Engineering University of Waterloo Global Big Data Technologies Centre (GBDTC) University of Technology Sydney School of Electrical and Electronic Engineering The University of Manchester LiFi Research and Development Centre Institute for Digital CommunicationsSchool of EngineeringThe University of Edinburgh Huawei Technologies Canada Co. Ltd. Huawei Technologies Department of Electrical Engineering (ISY) Link?ping University Institute of Electronics Communications & Information Technology (ECIT)Queen's University Belfast State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast University School of Electrical and Computer Engineering Georgia Institute of Technology 5G Innovation Centre University of Surrey Princeton University Vodafone Chair Mobile Communications Systems Technische Universit?t Dresden Center for Intelligent Networking and Communications (CINC) University of Electronic Science and Technology of China (UESTC)

The fifth generation(5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability,and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation(6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle(UAV) communication networks, thus achieving a space-airground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6GHz, millimeter wave(mmWave), terahertz(THz),and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence(AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable f

关键词： 6G vision network architecture air interface and transmission technologies space-air-ground-sea integrated network all spectra artificial intelligence network security

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