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Intelligent Phase Contrast Meta-Microscope System

Nano Letters 2023年第24期23卷 11630-11637页

作者： Chu, Cheng Hung Chia, Yu-Hsin Hsu, Hung-Chuan Vyas, Sunil Tsai, Chen-Ming Yamaguchi, Takeshi Tanaka, Takuo Chen, Huei-Wen Luo, Yuan Yang, Pan-Chyr Tsai, Din Ping YongLin Institute of Health National Taiwan University Taipei10672 Taiwan Institute of Medical Device and Imaging National Taiwan University Taipei10051 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10051 Taiwan Department of Mechanical Engineering National Taiwan University Taipei10617 Taiwan Innovative Photon Manipulation Research Team RIKEN Center for Advanced Photonics Saitama351-0198 Japan Graduate Institute of Toxicology College of Medicine National Taiwan University Taipei100 Taiwan Genome and Systems Biology Degree Program National Taiwan University and Academia Sinica Taipei100 Taiwan Program for Precision Health and Intelligent Medicine National Taiwan University Taipei106319 Taiwan Department of Internal Medicine National Taiwan University Hospital National Taiwan University Taipei10002 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei11529 Taiwan Department of Electrical Engineering City University of Hong Kong Kowloon999077 Hong Kong Centre for Biosystems Neuroscience and Nanotechnology City University of Hong Kong Kowloon999077 Hong Kong The State Key Laboratory of Terahertz and Millimeter Waves City University of Hong Kong Kowloon99907 Hong Kong

Phase contrast imaging techniques enable the visualization of disparities in the refractive index among various materials. However, these techniques usually come with a cost: the need for bulky, inflexible, and complicated configurations. Here, we propose and experimentally demonstrate an ultracompact meta-microscope, a novel imaging platform designed to accomplish both optical and digital phase contrast imaging. The optical phase contrast imaging system is composed of a pair of metalenses and an intermediate spiral phase metasurface located at the Fourier plane. The performance of the system in generating edge-enhanced images is validated by imaging a variety of human cells, including lung cell lines BEAS-2B, CLY1, and H1299 and other types. Additionally, we integrate the ResNet deep learning model into the meta-microscope to transform bright-field images into edge-enhanced images with high contrast accuracy. This technology promises to aid in the development of innovative miniature optical systems for biomedical and clinical applications. © 2023 American Chemical Society.

关键词： Microscopes

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Analysis of DFIG differential protection based on Park transform

Analysis of DFIG differential protection based on Park trans...

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2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021

作者： De Queiroz, Janailson Maciel Barros, Luciano Sales Barbosa, Daniel Graduate Program on Electrical and Computer Engineering Federal Un. of Rio Grande Do Norte Natal Brazil Federal Un. of Paraíba João Department of Computer Systems Pessoa Brazil

ISBN: (纸本)9781665444217

In recent years, the use of wind energy in the world has grown. Consequently, the need for studies related to the impact of wind turbines on the electrical system has increased including protection of them and associated equipment. For DFIG-based wind turbines, differential protection has recently been proposed, however, there are few studies on this type of application and in this paper it proposes criteria in the decision-making using the Park transform in which, in addition to the restriction current, voltage level and current direction at the stator terminals are considered. In a DFIG operating with 1.51 MW tests of faults internal and external to the protection zone were made, of the single-phase and three-phase type with various levels of voltage drops. Interturn faults in the rotor and stator of the machine were also tested with various levels of defects. So, with the proper definition of the operating logic, it was possible to show the effectiveness of the protection. © 2021 IEEE.

关键词： Wind power

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Using Free Space Optics for Beamsteering of 5G Metasurface Antenna

Using Free Space Optics for Beamsteering of 5G Metasurface A...

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IEEE Photonics Conference (IPC)

作者： A. Bilal A. Quddious M. A. Antoniades A. Kanno P.T. Dat K. Inagaki T. Kawanishi S. Iezekiel Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus EMPHASIS Research Centre University of Cyprus Nicosia Cyprus Chair for RF and Photonics Engineering Technische Universität Dresden Germany Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada National Institute of Information and Communications Technology Tokyo Japan Graduate School of Engineering Nagoya Institute of Technology Aichi Japan Faculty of Science and Engineering Waseda University Tokyo Japan

Beamsteering of a sub-6 GHz 5G metasurface antenna is achieved via free space optical control. A scanning angle of 66 ° is demonstrated at 3.25 GHz. The antenna consists of varactor-based phase shifters, whose vo...

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Fixed-Length Arbitrary-Phase Tunable NRI-TL Metamaterial Phase Shifter for Antenna Beam-Steering Applications

Fixed-Length Arbitrary-Phase Tunable NRI-TL Metamaterial Pha...

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European Conference on Antennas and Propagation, EuCAP

作者： Asif Bilal Abdul Quddious Atsushi Kanno Tetsuya Kawanishi Marco A. Antoniades Stavros Iezekiel EMPHASIS Research Centre University of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Chair for RF and Photonics Engineering Technische Universitat Dresden Dresden Germany National Institute of Information and Communications Technology Tokyo Japan Japan Graduate School of Engineering Nagoya Institute of Technology Aichi Japan School of Fundamental Science and Engineering Waseda University Tokyo Japan Department of Electrical Computer & Biomedical Engineering Ryerson University Toronto ON Canada

A fixed-length arbitrary-phase tunable phase shifter, based on the concept of negative-refractive-index transmission-line (NRI-TL) metamaterials for sub-6 GHz antenna beam steering applications is proposed. The design consists of a fixed microstrip transmission line which is reconfigured by loading varactor diodes in both the series and shunt branches. A continuously tunable phase of 210° at 3.2 GHz for the transmitted signal is achieved at the output by varying the biasing voltage from 0 – 7 V for the varactor diodes. The insertion loss varies from 0.9 – 2.5 dB for the design in the frequency range of 3.2 – 3.6 GHz. The total length of the tunable NRI-TL metamaterial phase shifter is λg/4.

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Downstream Task Performance of Pre-Trained Model For Outdoor Audio Event Classification

Downstream Task Performance of Pre-Trained Model For Outdoor...

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International Conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Theresia Herlina Rochadiani Yaya Heryadi Ilvico Sonata Lukas Wawan Suparta BINUS Graduate Program- Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Our surroundings’ auditory landscapes are a wealth of knowledge, providing insights into a range of outdoor pursuits. The automatic classification of these actions using audio event detection and classification (AEDC) systems has a great deal of potential applications in environmental monitoring, security, surveillance, and driverless cars. Even though AEDC has advanced significantly in indoor settings, difficulties still exist outside because of the variable and changing acoustic conditions brought on by elements like the weather, different sound sources, and ambient noise from traffic and industry. This study suggests an outdoor audio event categorization model based on convolutional neural networks (CNNs). The suggested model shows passable accuracy by utilizing adaptation to the downstream task using the ESC-50 dataset and transfer learning from a pre-trained model. The effectiveness of multi-class audio classification models in downstream tasks is analyzed in this paper, with an emphasis on the effect of an increasing number of output classes on accuracy. Three models—three, four, and five classes—with different output class configurations are used in the study, and their training and validation accuracies are assessed. Although the accuracy scores above 80% are commendable, the data show a discernible reduction in performance as the number of classes rises. Notably, the three-class model attains a validation accuracy exceeding 90%, whereas the four-class and five-class models exhibit reduced accuracies, falling below 90% and 85%, respectively.

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Constant Scaling Asymptotics of Communication Bounds in Covert Channels Against Selective Adversary

Constant Scaling Asymptotics of Communication Bounds in Cove...

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MILCOM, Military Communications Conference

作者： Xinchun Yu Shuangqin Wei Chenhao Ying Xiao-Ping Zhang Information and Data Science Institute Shenzhen International Graduate School Tsinghua University Shenzhen China School of Electrical Engineering and Computer Science Louisiana State University Baton Rouge USA School of Electronic Information and Electrical Engnieering Shanghai Jiao Tong University Shanghai China Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada

In the existing works on asymptotics of throughput of covert communications, an adversary is typically assumed to run a single binary hypothesis testing to determine the presence of active transmission, which is equivalent to distinguish between an induced mixture distribution by all codewords and the distribution with an inactive transmitter. In this paper, we show that both of the first and second order asymptotics are O(1) when the adversary can afford running parallel simple binary hypothesis testing against detection of each single codeword. The covert constraint in this case is given as an upper-bound δ on the total variation distance (TVD) between the simple distribution induced by each codeword and the one of pure noise. The result is drastically different in a negative way than the commonly known Square Root Law for covert communication over AWGN channels with a more benign adversary.

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Microengineered platforms for characterizing the contractile function of in vitro cardiac models

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Microsystems & Nanoengineering 2022年第1期8卷 29-50页

作者： Wenkun Dou Manpreet Malhi Qili Zhao Li Wang Zongjie Huang Junhui Law Na Liu Craig A.Simmons Jason T.Maynes Yu Sun Department of Mechanical and Industrial Engineering University of TorontoTorontoON M5S 3G8Canada Program in Molecular Medicine The Hospital for Sick ChildrenTorontoON M5G 1X8Canada Department of Biochemistry University of TorontoTorontoON M5S 1A8Canada Institute of Robotics and Automatic Information System and the Tianjin Key Laboratory of Intelligent Robotics Nankai UniversityTianjin 300350China School of Mechanical&Automotive Engineering Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Mechatronics Engineering and Automation Shanghai UniversityShanghai 200444China Institute of Biomedical Engineering University of TorontoTorontoON M5S 3G9Canada Translational Biology&Engineering Program Ted Rogers Centre for Heart ResearchTorontoON M5G 1M1Canada Department of Anesthesiology and Pain Medicine University of TorontoTorontoON M5S 1A8Canada Department of Anesthesia and Pain Medicine The Hospital for Sick ChildrenTorontoON M5G 1X8Canada Department of Electrical and Computer Engineering University of TorontoTorontoON M5S 3G4Canada Department of Computer Science University of TorontoTorontoON M5T 3A1Canada

Emerging heart-on-a-chip platforms are promising approaches to establish cardiac cell/tissue models in vitro for research on cardiac physiology,disease modeling and drug cardiotoxicity as well as for therapeutic *** still exist in obtaining the complete capability of in situ sensing to fully evaluate the complex functional properties of cardiac cell/tissue *** to contractile strength(contractility)and beating regularity(rhythm)are particularly important to generate accurate,predictive *** new platforms and technologies to assess the contractile functions of in vitro cardiac models is essential to provide information on cell/tissue physiologies,drug-induced inotropic responses,and the mechanisms of cardiac *** this review,we discuss recent advances in biosensing platforms for the measurement of contractile functions of in vitro cardiac models,including single cardiomyocytes,2D monolayers of cardiomyocytes,and 3D cardiac *** characteristics and performance of current platforms are reviewed in terms of sensing principles,measured parameters,performance,cell sources,cell/tissue model configurations,advantages,and *** addition,we highlight applications of these platforms and relevant discoveries in fundamental investigations,drug testing,and disease ***,challenges and future outlooks of heart-on-a-chip platforms for in vitro measurement of cardiac functional properties are discussed.

关键词： cardiac contractile regularity

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Robust Deep Joint Source Channel Coding with Time-Varying Noise

Robust Deep Joint Source Channel Coding with Time-Varying No...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Weida Wang Xinchun Yu Xinyi Tong Runpeng Yu Xiao-Ping Zhang Shao–Lun Huang Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China Institute of Data Science National University of Singapore Singapore Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada

Deep Joint Source-Channel Coding (JSCC) has gained increased attention, asserting its significance in the communication field. However, existing Deep JSCC techniques struggle to mitigate time-varying noise due to the deep neural networks being trained beforehand and fixed. To address this issue, we propose a robust deep JSCC scheme. Firstly, a multi-network parallel structure, as well as error-correcting codes, is introduced to effectively exploit label information. Secondly, a closed-form linear encoder and decoder pair is employed at the input and output ends of the channel to deal with the varying noise, which releases the neural network from dealing with a large range of varying noise levels. Thirdly, a transfer learning algorithm is utilized for estimating real-time noise statistics, which outperforms conventional estimation methods when noise statistics are time-dependent. These three components are effectively integrated as a comprehensive transmission system. Experimental results demonstrate that our optimized scheme outperforms existing approaches in the literature.

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Deep Learning Model for Classifying Public Opinions on Energy Sector IHSG Stocks on the Twitter Social Media Platform

Deep Learning Model for Classifying Public Opinions on Energ...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Bambang Sulistio Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

Capital market transactions provide an opportunity for investors to acquire ownership of company shares and capital gains, as well as dividends. However, alongside the benefits, there are risks of capital loss and liquidation, leading to stress and depression due to profit targets and decision-making errors. To mitigate the risk of decision-making errors in investment, data analysis is needed, including sentiment analysis, which influences stock prices. This study aims to develop a new deep learning model to classify Indonesian public opinion on JCI stocks, especially the Energy sector, obtained from the Twitter social media platform. The model will perform sentiment analysis and categorize opinions as negative, neutral, or positive. We created a dataset that was trained using Bidirectional Encoder Representations from Transformers (BERT) to summarize the analysis of public sentiment above so that it can assist investors in studying public sentiment as a reference for investing with a yield precision of 76%, Recall of 77%, and F1-score on 76%.

关键词： Deep learning Sentiment analysis Analytical models Social networking (online) Blogs Decision making Text categorization Bidirectional control Transformers Encoding

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Bilevel optimization for machine learning: Algorithm design and convergence analysis

arXiv

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arXiv 2021年

作者： Ji, Kaiyi Graduate Program in Department of Electrical and Computer Engineering Ohio State University

Bilevel optimization has become a powerful framework in a variety of machine learning applications including signal processing, meta-learning, hyperparameter optimization, reinforcement learning and network architecture search. There are generally two classes of bilevel optimization formulations for modern machine learning: 1) problem-based bilevel optimization, whose inner-level problem is formulated as finding a minimizer of a given loss function;and 2) algorithm-based bilevel optimization, whose inner-level solution is an output of a fixed algorithm. For the first problem class, two popular types of gradient-based algorithms have been proposed to estimate the gradient of the outer-level objective (hypergradient) via approximate implicit differentiation (AID) and iterative differentiation (ITD). Algorithms for the second problem class include the popular model-agnostic meta-learning (MAML) and almost no inner loop (ANIL). Although bilevel optimization algorithms have been widely used, their convergence rate and fundamental limitations have not been well explored. Copyright © 2021, The Authors. All rights reserved.

关键词： Network architecture

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