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JSAP-OSA Joint Symposia, JSAP 2018

作者： Yu, Min-Wen Yang, Jhen-Hong Li, Ju-Hong Lu, Tien-Chang Lin, Tzy-Rong Chen, Kuo-Ping Institute of Lighting and Energy Photonics National Chiao-Tung University Taiwan Institute of Photonic System National Chiao-Tung University Taiwan Department of Photonics College of Electrical and Computer Engineering National Chiao Tung University Taiwan Institute of Optoelectronic Sciences National Taiwan Ocean University Taiwan Institute of Imaging and Biomedical Photonics National Chiao-Tung University Taiwan

ISBN: (纸本)9784863486942

Graphene and 2D materials have gathered great attention lately, due to its property of interface modification. Combining graphene with metals, it would be able to modulate the carrier concentration of metals and also plasmon frequency. In this abstract, the variation of Vg and plasma frequency (ωp) have been demonstrated successfully on gold films with graphene and without graphene. Forward scattering spectra of the slit-groove structures exists Fabry-Perot interference. This work could extend to the graphene modulated nanophotonics devices [1]. For example, the SPPs propagate on the graphene-metal surface can be utilized to develop graphene-plasmonic waveguide [2]. © 2018 OSA - The Optical Society. All rights reserved.

关键词： Graphene

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SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM

SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Vi...

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IEEE International Conference on Robotics and Automation

作者： Bruno Bodin Harry Wagstaff Sajad Saeedi Luigi Nardi Emanuele Vespa John Mawer Andy Nisbet Mikel Lujan Steve Furber Andrew J. Davison Paul H. J. Kelly Michael F. P. O'Boyle School of Informatics University of Edinburgh UK Department of Computing Imperial College London UK Electrical Engineering - Computer Systems Stanford University USA School of Computer Science University of Manchester UK

SLAM is becoming a key component of robotics and augmented reality (AR) systems. While a large number of SLAM algorithms have been presented, there has been little effort to unify the interface of such algorithms, or to perform a holistic comparison of their capabilities. This is a problem since different SLAM applications can have different functional and non-functional requirements. For example, a mobile phone-based AR application has a tight energy budget, while a UAV navigation system usually requires high accuracy. SLAMBench2 is a benchmarking framework to evaluate existing and future SLAM systems, both open and close source, over an extensible list of datasets, while using a comparable and clearly specified list of performance metrics. A wide variety of existing SLAM algorithms and datasets is supported, e.g. ElasticFusion, InfiniTAM, ORB-SLAM2, OKVIS, and integrating new ones is straightforward and clearly specified by the framework. SLAMBench2 is a publicly-available software framework which represents a starting point for quantitative, comparable and validatable experimental research to investigate trade-offs across SLAM systems.

关键词： Simultaneous localization and mapping Measurement Trajectory Benchmark testing User interfaces C++ languages

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Joint shape/texture representation learning for cardiovascular disease diagnosis from magnetic resonance imaging

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European heart journal. Imaging methods and practice 2024年第1期2卷 qyae042页

作者： Xiang Chen Yan Xia Erica Dall'Armellina Nishant Ravikumar Alejandro F Frangi School of Computing University of Leeds Woodhouse LS2 9JT Leeds UK. School of Medicine University of Leeds Woodhouse LS2 9JT Leeds UK. Christabel Pankhurst Institute The University of Manchester Oxford Rd M13 9PL Manchester UK. Department of Computer Science School of Engineering The University of Manchester Oxford Rd M13 9PL Manchester UK. Division of Informatics Imaging and Data Sciences School of Health Sciences The University of Manchester Oxford Rd M13 9PL Manchester UK. NIHR Manchester Biomedical Research Centre Manchester Academic Health Science Centre Oxford Rd M13 9PL Manchester UK. Medical Imaging Research Center (MIRC) University Hospital Gasthuisberg UZ Herestraat 49 - bus 7003 3000 Leuven Belgium. Department of Cardiovascular Sciences KU Leuven UZ Herestraat 49 - box 911 3000 Leuven Belgium. Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 postbus 2440 3001 Leuven Belgium. Alan Turing Institute British Library 96 Euston Rd. NW1 2DB London UK.

Aims:Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide. Cardiac image and mesh are two primary modalities to present the shape and structure of the heart and have been demonstrated to be efficient in CVD prediction and diagnosis. However, previous research has been generally focussed on a single modality (image or mesh), and few of them have tried to jointly consider the image and mesh representations of heart. To obtain efficient and explainable biomarkers for CVD prediction and diagnosis, it is needed to jointly consider both representations. Methods and results:We design a novel multi-channel variational auto-encoder, mesh-image variational auto-encoder, to learn joint representation of paired mesh and image. After training, the shape-aware image representation (SAIR) can be learned directly from the raw images and applied for further CVD prediction and diagnosis. We demonstrate our method on data from UK Biobank study and two other datasets via extensive experiments. In acute myocardial infarction prediction, SAIR achieves 81.43% accuracy, significantly higher than traditional biomarkers like metadata and clinical indices (left ventricle and right ventricle clinical indices of cardiac function like chamber volume, mass, and ejection fraction). Conclusion:Our mesh-image variational auto-encoder provides a novel approach for 3D cardiac mesh reconstruction from images. The extraction of SAIR is fast and without need of segmentation masks, and its focussing can be visualized in the corresponding cardiac meshes. SAIR archives better performance than traditional biomarkers and can be applied as an efficient supplement to them, which is of significant potential in CVD analysis.

关键词： CVD diagnosis CVD prediction cardiac biomarker mesh reconstruction multi-channel VAE

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Effect of different FOU shapes on the performance in interval type-2 fuzzy PI control systems

Effect of different FOU shapes on the performance in interva...

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2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017

作者： Ming, Chun Yip, Tommy Tan, Woei Wan Nie, Maowen Department of Electrical and Computer Engineering National University of Singapore Singapore117576 Singapore Department of Social and Cognitive Computing Institute of High Performance Computing Singapore138632 Singapore

ISBN: (纸本)9781509060344

The control performance of type-2 fuzzy logic controller (IT2-FLCs) is heavily dependent on the choice of antecedent and consequent sets. However, there are no clear guidelines on how to choose suitable FOU shape to achieve the desired control requirements. This paper aims to explore how differences in FOU shapes affect the control performance by analysing three different types of antecedent fuzzy sets. They are the triangular top wide, triangular bottom wide and the trapezoidal fuzzy sets. Analytical structures of these controllers are derived. The analytical structures of the triangular bottom wide and trapezoidal controllers show more common features than triangular top wide controller. Based on the characteristics of the analytical structure, it may be hypothesised that the control performances of IT2-FLCs that use triangular bottom wide and trapezoidal antecedent IT2 fuzzy sets would be more similar than an IT2-FLC constructed by triangular top wide antecedent IT2 fuzzy sets. The hypothesis is then verified by simulation results. © 2017 IEEE.

关键词： Controllers

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A deep learning system for detecting systemic lupus erythematosus from retinal images

Cell Reports Medicine

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Cell Reports Medicine 2025年

作者： Tingyao Li Shiqun Lin Zhouyu Guan Yukun Zhou Dian Zeng Zheyuan Wang Yan Zhou Pinqi Fang Shujie Yu Ruhan Liu Xiang Chen Yan-Ran (Joyce) Wang Yuwei Lu Jia Shu Yiming Qin Yiting Wu Yilan Wu Chan Wu Shangzhu Zhang Jie Shen Bin Sheng Shanghai International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Center for Diabetes Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Furong Laboratory Central South University Changsha Hunan China Institute for Proactive Healthcare Shanghai Jiao Tong University Shanghai China Department of Ophthalmology Peking Union Medical College Hospital Peking Union Medical College Chinese Academy of Medical Sciences Beijing China Beijing Key Laboratory of Fundus Diseases Intelligent Diagnosis & Drug/Device Development and Translation Beijing China Centre for Medical Image Computing University College London London UK NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust London UK Institute of Ophthalmology University College London London UK School of Clinical Medicine Beijing Tsinghua Changgung Hospital Tsinghua Medicine Tsinghua University Beijing China Medical Records and Statistics Office Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China School of Medicine Stanford University Stanford CA USA Department of Rheumatology and Clinical Immunology Chinese Academy of Medical Sciences & Peking Union Medical College National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID) Ministry of Science & Technology State Key Laboratory of Complex Severe and Rare Diseases Peking Union Medical College Hospital (PUMCH) Key Laboratory of Rheumatology and Clinical Immunology Ministry of Education Beijing China

Systemic lupus erythematosus (SLE) is a serious autoimmune disorder predominantly affecting women. However, screening for SLE and related complications poses significant challenges globally, due to complex diagnostic criteria and public unawareness. Since SLE-related retinal involvement could provide insights into disease activity and severity, we develop a deep learning system (DeepSLE) to detect SLE and its retinal and kidney complications from retinal images. In multi-ethnic validation datasets comprising 247,718 images from China and UK, DeepSLE achieves areas under the receiver operating characteristic curve of 0.822–0.969 for SLE. Additionally, DeepSLE demonstrates robust performance across subgroups stratified by gender, age, ethnicity, and socioeconomic status. To ensure DeepSLE’s explainability, we conduct both qualitative and quantitative analyses. Furthermore, in a prospective reader study, DeepSLE demonstrates higher sensitivities compared with primary care physicians. Altogether, DeepSLE offers digital solutions for detecting SLE and related complications from retinal images, holding potential for future clinical deployment.

关键词： systemic lupus erythematosus retinal imaging deep learning lupus retinopathy lupus nephritis color fundus photography health equity multi-ethnic validation opportunistic screening reader study

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Evolution of interlayer and intralayer magnetism in three atomically thin chromium trihalides

arXiv

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arXiv 2019年

作者： Kim, Hyun Ho Yang, Bowen Li, Siwen Jiang, Shengwei Jin, Chenhao Tao, Zui Nichols, George Sfigakis, Francois Zhong, Shazhou Li, Chenghe Tian, Shangjie Cory, David G. Miao, Guo-Xing Shan, Jie Mak, Kin Fai Lei, Hechang Sun, Kai Zhao, Liuyan Tsen, Adam W. Institute for Quantum Computing Department of Chemistry Department of Physics and Astronomy Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics University of Michigan 450 Church Street Ann ArborMI48109 United States School of Applied and Engineering Physics Department of Physics Kavli Institute at Cornell for Nanoscale Science IthacaNY14853 United States Department of Physics Beijing Key Laboratory of Opto-electronic Functional Materials & Micro-Nano Devices Renmin University of China Beijing100872 China

We conduct a comprehensive study of three different magnetic semiconductors, CrI3, CrBr3, and CrCl3, by incorporating both few- and bi-layer samples in van der Waals tunnel junctions. We find that the interlayer magnetic ordering, exchange gap, magnetic anisotropy, as well as magnon excitations evolve systematically with changing halogen atom. By fitting to a spin wave theory that accounts for nearest neighbor exchange interactions, we are able to further determine a simple spin Hamiltonian describing all three systems. These results extend the 2D magnetism platform to Ising, Heisenberg, and XY spin classes in a single material family. Using magneto-optical measurements, we additionally demonstrate that ferromagnetism can be stabilized down to monolayer in more isotropic CrBr3, with transition temperature still close to that of the bulk. Copyright © 2019, The Authors. All rights reserved.

关键词： Van der Waals forces

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Quantum circuit designs of integer division optimizing T-count and T-depth

arXiv

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arXiv 2018年

作者： Thapliyal, Himanshu Muñoz-Coreas, Edgard Varun, T.S.S. Humble, Travis S. Department of Electrical and Computer Engineering University of Kentucky LexingtonKY United States Quantum Computing Institute Oak Ridge National Laboratory TN United States

Quantum circuits for mathematical functions such as division are necessary to use quantum computers for scientific computing. Quantum circuits based on Clifford+T gates can easily be made fault-tolerant but the T gate is very costly to implement. The small number of qubits available in existing quantum computers adds another constraint on quantum circuits. As a result, reducing T-count and qubit cost have become important optimization goals. The design of quantum circuits for integer division has caught the attention of researchers and designs have been proposed in the literature. However, these designs suffer from excessive T gate and qubit costs. Many of these designs also produce significant garbage output resulting in additional qubit and T gate costs to eliminate these outputs. In this work, we propose two quantum integer division circuits. The first proposed quantum integer division circuit is based on the restoring division algorithm and the second proposed design implements the non-restoring division algorithm. Both proposed designs are optimized in terms of T-count, T-depth and qubits. Both proposed quantum circuit designs are based on (i) a quantum subtractor, (ii) a quantum adder-subtractor circuit, and (iii) a novel quantum conditional addition circuit. Our proposed restoring division circuit achieves average T-count savings from 79.03% to 91.69% compared to the existing works. Our proposed non-restoring division circuit achieves average T-count savings from 49.75% to 90.37% compared to the existing works. Further, both our proposed designs have linear T-depth. Copyright © 2018, The Authors. All rights reserved.

关键词： Qubits

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Interface engineering of high efficiency perovskite solar cells based on ZnO nanorods using atomic layer deposition

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Nano Research 2017年第3期10卷 1092-1103页

作者： Shibin Li Peng Zhang Yafei Wang Hojjatollah Sarvari Detao Liu Jiang Wu Yajie Yang Zhiming Wang Zhi David Chen School of Optoelectronic Information University of Electronic Science and Technology of China Chengdu 610054 China Department of Electrical & Computer Engineering and Center for Nanoscale Science & Engineering University of Kentucky Lexington Kentucky 40506 USA Department of Electronic and Electrical Engineering University College London Torrington Place London WC I E 7JE UK Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu 610054 China

Despite the considerably improved efficiency of inorganic-organic metal hybrid perovskite solar cells （PSCs）, electron transport is still a challenging issue. In this paper, we report the use of ZnO nanorods prepared by hydrothermal self- assembly as the electron transport layer in perovskite solar cells. The efficiency of the perovskite solar cells is significantly enhanced by passivating the interfacial defects via atomic layer deposition of Al2O3 monolayers on the ZnO nanorods. By employing the Al2O3 monolayers, the average power conversion efficiency of methylammonium lead iodide PSCs was increased from 10.33% to 15.06%, and the highest efficiency obtained was 16.08%. We suggest that the passivation of defects using the atomic layer deposition of monolayers might provide a new pathway for the improvement of all types of PSCs..

关键词： perovskite solar cell ZnO nanorods oxygen vacancy Al2O3 monolayer charge recombination

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Lithium-Ion Batteries: Operando Magnetometry Probing the Charge Storage Mechanism of CoO Lithium-Ion Batteries (Adv. Mater. 12/2021)

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Advanced Materials 2021年第12期33卷

作者： Hongsen Li Zhengqiang Hu Qingtao Xia Hao Zhang Zhaohui Li Huaizhi Wang Xiangkun Li Fengkai Zuo Fengling Zhang Xiaoxiong Wang Wanneng Ye Qinghao Li Yunze Long Qiang Li Shishen Yan Xiaosong Liu Xiaogang Zhang Guihua Yu Guo-Xing Miao College of Physics Center for Marine Observation and Communications Qingdao University Qingdao 266071 China School of Physics State Key Laboratory of Crystal Materials Shandong University Jinan 250100 China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology (SIMIT) Chinese Academy of Sciences Shanghai 200050 China College of Material Science and Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 China Materials Science and Engineering Program and Department of Mechanical Engineering The University of Texas at Austin Austin TX 78712 USA Department of Electrical and Computer Engineering & Institute for Quantum Computing University of Waterloo Waterloo ON N2L 3G1 Canada

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A universal two-qubit photonic quantum processor

A universal two-qubit photonic quantum processor

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2018 Conference on Lasers and Electro-Optics, CLEO 2018

作者： Qiang, X. Zhou, X. Wang, J. Wilkes, C. Loke, T. Oagara, S. Kling, L. Marshall, G. Santagati, R. Wang, J.B. Oabrien, J.L. Thompson, M.G. Matthews, J.C.F. Quantum Engineering Technology Labs H. H. Wills Physics Laboratory and Department of Electrical and Electronic Engineering University of Bristol BS8 1FD United Kingdom State Key Laboratory of High Performance Computing NUDT Changsha410073 China State Key Laboratory of Optoelectronic Materials and Technologies and School of Physics Sun Yat-sen University Guangzhou510275 China School of Physics University of Western Australia CrawleyWA6009 Australia

We report a universal two-qubit silicon photonic quantum processor, able to initialise, operate and analyze arbitrary two-qubit states and processes applications in quantum information processing. © 2018 OSA.

ISBN: (纸本)9781943580422

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