检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Wang, Lan He, Ruiling Zhao, Lili Wang, Jia Geng, Zhengzi Ren, Tao Zhang, Guo Zhang, Peng Tang, Kaiqiang Gao, Chaofei Chen, Fei Zhang, Liting Zhou, Yonghe Li, Xin He, Fanbin Huan, Hui Wang, Wenjuan Liang, Yunxiao Tang, Juan Ai, Fang Wang, Tingyu Zheng, Liyun Zhao, Zhongwei Ji, Jiansong Liu, Wei Xu, Jiaojiao Liu, Bo Wang, Xuemei Zhang, Yao Yan, Qiong Lv, Muhan Chen, Xiaomei Zhang, Shuhua Wang, Yihua Liu, Yang Yin, Li Liu, Yanni Huang, Yanqing Liu, Yunfang Wang, Kun Su, Meiqin Bian, Li An, Ping Zhang, Xin Qian, Linxue Li, Shao Qi, Xiaolong Institute for TCM-X MOE Key Laboratory of Bioinformatics Bioinformatics Division BNRIST Department of Automation Tsinghua University Beijing China Department of Ultrasound Donggang Branch the First Hospital of Lanzhou University Lanzhou China The First Clinical Medical College of Lanzhou University Lanzhou China Department of Gastroenterology and Hepatology Tianjin Second People's Hospital Tianjin China Department of Ultrasound Beijing Friendship Hospital Capital Medical University Beijing China Department of Ultrasound The People's Hospital of Linxia Linxia China Department of Gastroenterology Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region Sichuan China Department of Gastroenterology The People's Hospital of Guangxi Zhuang Autonomous Region Nanning China Department of Control and Systems Engineering Nanjing University Nanjing China Department of Ultrasound The First Hospital of Lanzhou University Lanzhou China Department of Infectious Diseases The First Hospital of Lanzhou University Lanzhou China Department of Ultrasonography Tianjin Second People's Hospital Tianjin China Department of Infectious Disease Zigong First People's Hospital Zigong China Department of Ultrasound Zigong First People's Hospital Zigong China Department of Gastroscopy Zigong First People's Hospital Zigong China Department of Radiology Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Fifth Affiliated Hospital of Wenzhou Medical University Lishui China Ultrasound Diagnosis Center Shaanxi Provincial People's Hospital Xi'An China Department of Ultrasound Ditan Hospital Capital Medical University Beijing China Department of Gastroenterology The Affiliated Hospital of Southwest Medical University Luzhou China Department of Ultrasound The Affiliated Hospital of Southwest Medical University Luzhou China Department of Ultrasound North China University of Science and Technology Affiliated Hospital Tangshan China Depar

Objective: Bleeding from gastroesophageal varices (GEV) is a medical emergency associated with high mortality. We aim to construct an artificial intelligence-based model of two-dimensional shear wave elastography (2D-SWE) of the liver and spleen to precisely assess the risk of GEV and high-risk gastroesophageal varices (HRV). Design: A prospective multicenter study was conducted in patients with compensated advanced chronic liver disease. 305 patients were enrolled from 12 hospitals, and finally 265 patients were included, with 1136 liver stiffness measurement (LSM) images and 1042 spleen stiffness measurement (SSM) images generated by 2D-SWE. We leveraged deep learning methods to uncover associations between image features and patient risk, and thus conducted models to predict GEV and HRV. Results: A multi-modality Deep Learning Risk Prediction model (DLRP) was constructed to assess GEV and HRV, based on LSM and SSM images, and clinical information. Validation analysis revealed that the AUCs of DLRP were 0.91 for GEV (95% CI 0.90 to 0.93, p Copyright © 2023, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning

TechRxiv

引用

TechRxiv 2021年

作者： Fan, Rui Bowd, Christopher Christopher, Mark Brye, Nicole Proudfoot, James A. Rezapour, Jasmin Belghith, Akram Goldbaum, Michael H. Chuter, Benton Girkin, Christopher A. Fazio, Massimo A. Liebmann, Jeffrey M. Weinreb, Robert N. Gordon, Mae O. Kass, Michael A. Kriegman, David Zangwill, Linda M. Hamilton Glaucoma Center Viterbi Family Department of Ophthalmology Shiley Eye Institute University of California La Jolla San DiegoCA United States Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Department of Ophthalmology Universitätsmedizin der Johannes Gutenberg-Universität Mainz Rheinland-Pfalz Mainz Germany Department of Ophthalmology School of Medicine The University of Alabama at Birmingham BirminghamAL United States Department of Biomedical Engineering School of Engineering The University of Alabama at Birmingham BirminghamAL United States Bernard and Shirlee Brown Glaucoma Research Laboratory Edward S. Harkness Eye Institute Columbia University Medical Center New YorkNY United States Department of Ophthalmology and Visual Sciences Washington University School of Medicine Washington University St. LouisMO United States

Importance: Automated deep learning (DL) analyses of fundus photographs potentially can reduce the cost and improve the efficiency of reading center assessment of endpoints in clinical trials. Objective: To investigate the diagnostic accuracy of DL algorithms trained on fundus photographs from the Ocular Hypertension Treatment Study (OHTS) to detect primary open-angle glaucoma (POAG). Study Design: Diagnostic/prognostic Study Setting and Participants: 1,636 OHTS participants from 22 sites with a mean follow-up (range) of 10.7 (0.0, 14.3) years. 66,715 photographs from 3,272 eyes were used to train and test a ResNet-50 model to detect the OHTS Endpoint Committee POAG determination based on optic disc (n=287 eyes, 3,502 photographs) and/or visual field (n=198 eyes, 2,300 visual fields) changes. Three independent test sets were used to evaluate the generalizability of the model. Main Outcome and Measures: Areas under the receiver operating characteristic curve (AUROC) and sensitivities at fixed specificities were calculated to compare model performance. Evaluation of false-positive rates was used to determine whether the DL model detected POAG before the Endpoint Committee POAG determination. Results: The DL model achieved an AUROC (95% CI) of 0.88 (0.82, 0.92) for the overall OHTS POAG endpoint. For the OHTS endpoints based on optic disc changes or visual field changes, AUROCs were 0.91 (0.88, 0.94) and 0.86 (0.76, 0.93), respectively. False-positive rates (at 90% specificity) were higher in photographs of eyes that later developed POAG by disc or visual field (19.1%) compared to eyes that did not develop POAG (7.3%) during their follow-up. The diagnostic accuracy of the DL model developed on the optic disc endpoint applied to 3 independent datasets was lower with AUROC ranging from 0.74 to 0.79. Conclusion and Relevance: The model’s high diagnostic accuracy using OHTS photographs suggests that DL has the potential to standardize and automate POAG determination for cl

关键词： Ophthalmology

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Vertical Level Differences Between Left and Right Vocal Folds Using Artificial Intelligence System in Excised Canine Larynx

引用

Journal of Voice 2024年

作者： Kim, Jaewon Wang, Soo-Geun Lee, Jin-Choon Cheon, Yong-Il Shin, Sung-Chan Lim, Dong-Won Jang, Dae-Ik Bhattacharjee, Subrata Hwang, Yeong-Byn Choi, Heung-Kook Kwon, Ickhwan Kim, Seon-Jong Kwon, Soon-Bok Department of Cognitive Science Pusan National University Doctor's Course Busan South Korea Department of Otorhinolaryngology Head and Neck Surgery Pusan National University Yangsan Hospital Gyeongsangnam-do Yangsan South Korea Department of Otorhinolaryngology Head and Neck Surgery College of Medicine Pusan National University and Medical Research Institute Pusan National University Hospital Busan South Korea Department of Otorhinolaryngology Head and Neck Surgery Pusan National University School of Medicine Pusan National University Yangsan Hospital Gyeongsangnam-do Yangsan South Korea Department of Otorhinolaryngology Head and Neck Surgery Biomedical Research Institute Pusan National University School of Medicine Pusan National University Hospital Busan South Korea Department of Otorhinolaryngology Head and Neck Surgery Pusan National University Hospital Busan South Korea Department of Otorhinolaryngology Head and Neck Surgery Kosin University Gospel Hospital Kosin University College of Medicine Busan South Korea Department of Computer Engineering u-AHRC Inje University Gimhae South Korea Department of Digital Anti-Aging Healthcare u-AHRC Inje University Gimhae South Korea South Korea Artificial Intelligence Research Center JLK Inc. Seoul South Korea Platform Development Headquarters Autonomous A2Z Daegu South Korea Department of Applied IT and Engineering Pusan National University Gyeongsangnam-do Miryang South Korea Department of Humanities Language and Information Pusan National University Busan South Korea

Objectives: This study aimed to establish an artificial intelligence (AI) system to classify vertical level differences between vocal folds during vocalization and to evaluate the accuracy of the classification. Methods: We designed models with different depths between the right and left vocal folds using an excised canine larynx. Video files for the data set were obtained using a high-speed camera system and a color complementary metal oxide semiconductor camera with global shutter. The data sets were divided into training, validation, and testing. We used 20,000 images for building the model and 8000 images for testing. To perform deep learning multiclass classification and to estimate the vertical level difference, we introduced DenseNet121-ConvLSTM. Results: The model was trained several times using different numbers of epochs. We achieved the most optimal results at 100 epochs, and the batch size used during training was 16. The proposed DenseNet121-ConvLSTM model achieved classification accuracies of 99.5% and 88.0% for training and testing, respectively. After verification using an external data set, the overall accuracy, precision, recall, and f1-score were 90.8%, 91.6%, 90.9%, and 91.2%, respectively. Conclusions: The newly developed AI system may be an easy and accurate method for classifying superior and inferior vertical level differences between vocal folds. Thus, this AI system can be applied and may help in the assessment of vertical level differences in patients with unilateral vocal fold paralysis. © 2024 The Voice Foundation

关键词： AI system Canine larynx Deep learning Vertical level difference Vocal fold

来源：评论

学校读者我要写书评

暂无评论

High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware

arXiv

引用

arXiv 2021年

作者： Nelson, Jon Vuffray, Marc Lokhov, Andrey Y. Albash, Tameem Coffrin, Carleton Center for Non Linear Studies Los Alamos National Laboratory Los AlamosNM United States Advanced Network Science Initiative Los Alamos National Laboratory Los AlamosNM United States Theoretical Division Los Alamos National Laboratory Los AlamosNM United States Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM United States Department of Physics and Astronomy Center for Quantum Information and Control University of New Mexico AlbuquerqueNM United States

Quantum Annealing (QA) was originally intended for accelerating the solution of combinatorial optimization tasks that have natural encodings as Ising models. However, recent experiments on QA hardware platforms have demonstrated that, in the operating regime corresponding to weak interactions, the QA hardware behaves like a noisy Gibbs sampler at a hardware-specific effective temperature. This work builds on those insights and identifies a class of small hardware-native Ising models that are robust to noise effects and proposes a procedure for executing these models on QA hardware to maximize Gibbs sampling performance. Experimental results indicate that the proposed protocol results in high-quality Gibbs samples from a hardware-specific effective temperature. Furthermore, we show that this effective temperature can be adjusted by modulating the annealing time and energy scale. The procedure proposed in this work provides an approach to using QA hardware for Ising model sampling presenting potential new opportunities for applications in machine learning and physics simulation. Copyright © 2021, The Authors. All rights reserved.

关键词： Ising model

来源：评论

学校读者我要写书评

暂无评论

Spin-phonon interaction in yttrium iron garnet

arXiv

引用

arXiv 2021年

作者： Olsson, Kevin S. Choe, Jeongheon Rodriguez-Vega, Martin Khalsa, Guru Benedek, Nicole A. Fang, Bin Zhou, Jianshi Fiete, Gregory A. Li, Xiaoqin Department of Physics Center of Complex Quantum Systems The University of Texas at Austin AustinTX78712 United States Center for Dynamics and Control of Materials The University of Texas at Austin AustinTX78712 United States Department of Physics Northeastern University BostonMA02115 United States Department of Materials Science and Engineering Cornell University IthacaNY14853 United States Department of Mechanical Engineering The University of Texas at Austin AustinTX78712 United States Texas Materials Institute The University of Texas at Austin AustinTX78712 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Computer and Electrical Engineering University of Maryland College ParkMD20740 United States

Spin-phonon interaction is an important channel for spin and energy relaxation in magnetic insulators. Understanding this interaction is critical for developing magnetic insulator-based spintronic devices. Quantifying this interaction in yttrium iron garnet (YIG), one of the most extensively investigated magnetic insulators, remains challenging because of the large number of atoms in a unit cell. Here, we report temperature-dependent and polarization-resolved Raman measurements in a YIG bulk crystal. We first classify the phonon modes based on their symmetry. We then develop a modified mean-field theory and define a symmetry-adapted parameter to quantify spin-phonon interaction in a phononmode specific way for the first time in YIG. Based on this improved mean-field theory, we discover a positive correlation between the spin-phonon interaction strength and the phonon frequency. Copyright © 2021, The Authors. All rights reserved.

关键词： Phonons

来源：评论

学校读者我要写书评

暂无评论

Industry 4.0 in Germany, Austria and Hungary: Interpretation, strategies and readiness models 16

Industry 4.0 in Germany, Austria and Hungary: Interpretation...

引用

16th IMEKO TC10 Conference 2019 on Testing, Diagnostics and Inspection as a Comprehensive Value Chain for Quality and Safety

作者： Nick, Gábor Gallina, Viola Szaller, Ádám Várgedő, Tamás Schumacher, Andreas Centre of Excellence in Production Informatics and Control Institute for Computer Science and Control Hungarian Academy of Sciences Budapest Hungary Fraunhofer Austria Research GmbH Wien Austria Széchenyi István University Research Center of Vehicle Industry Győr Hungary University of Technology and Economics Department of Manufacturing Science and Engineering Budapest Hungary

ISBN: (纸本)9789299008416

Global economy increasingly responds to trends of industrial digitization and start to develop their own digitalization strategies e.i. through application of Industry 4.0 concepts. Thereby, initiatives and developments are often carried out on a company-, industry- or country-level, which can result in a lack of international co-operation and utilization of synergy-effects. To analyse the Industry 4.0 development status on a macro level and to enhance transnational developments, in the first part of this study we introduce the national Industry 4.0 platforms of three EU member states – the frontrunner Germany, the solidly rising Austria and Hungary that is in the process of catching up. Our analysis are carried out in four dimensions: economic background, country-specific Industry 4.0 interpretation, and local platforms as well as initiatives. To analyse the actual Industry 4.0 development status of industrial enterprises and of development platforms, existing Industry 4.0 maturity models form all three countries are presented and compared. Our analysis helped to capture the different phases of digitization and Industry 4.0 in Germany, Austria and Hungary in regard to defined goals and strategies and further of resulting problems with respect to Industry 4.0. Building on our comparison-studies and captured problems, decision makers should be enabled to carry out transnational Industry 4.0 projects and initiatives more effectively. © 2019 International Measurement Confederation (IMEKO). All rights reserved.

关键词： Industry 4.0

来源：评论

学校读者我要写书评

暂无评论

Randomised benchmarking for characterizing and forecasting correlated processes

arXiv

引用

arXiv 2023年

作者： Zhang, Xinfang Wu, Zhihao White, Gregory A.L. Xiang, Zhongcheng Hu, Shun Peng, Zhihui Liu, Yong Zheng, Dongning Fu, Xiang Huang, Anqi Poletti, Dario Modi, Kavan Wu, Junjie Deng, Mingtang Guo, Chu Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Physics and Astronomy Monash University VIC3800 Australia Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute of Physics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster and Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Quantum for NSW Sydney2000 Australia

The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning algorithms, we develop a method to learn the details of temporally correlated noise. In particular, we can learn the time-independent evolution operator of system plus bath and this leads to (i) the ability to characterize the degree of non-Markovianity of the dynamics and (ii) the ability to predict the dynamics of the system even beyond the times we have used to train our model. We exemplify this by implementing our method on a superconducting quantum processor. Our experimental results show a drastic change between the Markovian and non-Markovian regimes for the learning accuracies. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

A New Active Disturbance Rejection controller Design Based on Fractional Extended State Observer

A New Active Disturbance Rejection Controller Design Based o...

引用

第三十八届中国控制会议

作者： Pengchong Chen Ying Luo Weijia Zheng Zhiqiang Gao Department of Mechanical Science and Engineering Huazhong University of Science and Technology Center for Advanced Control Technologies Department of Electrical and Computer Engineering Cleveland State University

An improved active disturbance rejection controller based on the fractional order extended state observer（FOESO）is proposed in this *** the proposed FOESO,a second order plant model is converted into a cascaded fractional order integrator(1/s,0<α<1).Thus,a stable closed-loop feedback control system with enough phase margin for stability can be realized using a simple proportional ***,the open-loop phase-frequency characteristic of the system is flat around the gain crossover frequency,namely,the system is robust to loop gain ***,without the differential action in the designed controller,the control system achieves the robustness to high-frequency noise.

关键词： Fractional order extended state observer fractional order active disturbance rejection robust noise

来源：评论

学校读者我要写书评

暂无评论

Learning of long-horizon sparse-reward robotic manipulator tasks with base controllers

arXiv

引用

arXiv 2020年

作者： Wang, Guangming Xin, Minjian Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Engineering University of California San Diego La Jolla CA92093 United States Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Deep Reinforcement Learning (DRL) enables robots to perform some intelligent tasks end-to-end. However, there are still many challenges for long-horizon sparse-reward robotic manipulator tasks. On the one hand, a sparse-reward setting causes exploration inefficient. On the other hand, exploration using physical robots is of high cost and unsafe. In this paper, we propose a method of learning long-horizon sparse-reward tasks utilizing one or more existing traditional controllers named base controllers in this paper. Built upon Deep Deterministic Policy Gradients (DDPG), our algorithm incorporates the existing base controllers into stages of exploration, value learning, and policy update. Furthermore, we present a straightforward way of synthesizing different base controllers to integrate their strengths. Through experiments ranging from stacking blocks to cups, it is demonstrated that the learned state-based or image-based policies steadily outperform base controllers. Compared to previous works of learning from demonstrations, our method improves sample efficiency by orders of magnitude and improves the performance. Overall, our method bears the potential of leveraging existing industrial robot manipulation systems to build more flexible and intelligent controllers. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Hydrogenation of Pyrolysis Oil from Loblolly Pine Residue

引用

Paper And Biomaterials 2020年第1期5卷 1-13页

作者： Ajoy Kanti Mondal Chengrong Qin Arthur JRagauskas Yonghao Ni Fang Huang College of Material Engineering Fujian Agriculture and Forestry UniversityFuzhouFujian Province350108China Guangxi Key Laboratory of Clean Pulp&Papermaking and Pollution Control NanningGuangxi Zhuang Autonomous Region530004China Department of Forestry Wildlifeand FisheriesCenter for Renewable CarbonUniversity of Tennessee Institute of AgricultureKnoxvilleTennessee37996USA Joint Institute for Biological Science Biosciences DivisionOak Ridge National LaboratoryOak RidgeTennessee37831USA Department of Chemical Engineering University of New BrunswickFrederictonE3B 5A3Canada Institute of Fuel Research and Development Bangladesh Council of Scientific and Industrial ResearchDhaka-1205Bangladesh

Loblolly pine residue prepared with and without zeolite ZSM-5 was pyrolyzed at 600℃ and the pyrolysis oil was hydrogenated using formic acid as a hydrogen source, in the presence of a Ru/activated carbon catalyst. As indicated by the pyrolysis yield, addition of the zeolite ZSM-5 increased the yield of light oil but decreased the yield of heavy oil. The pyrolysis oils were analyzed by 13C-,31P-,19F-nuclear magnetic resonance(NMR), and heteronuclear single quantum coherence or heteronuclear single quantum correlation nuclear magnetic resonance(HSQC-NMR), demonstrating that the zeolite ZSM-5 can efficiently induce decarboxylation reactions and decrease the content of aliphatic hydroxyl groups in the heavy oil by 57%.After hydrogenation of the pyrolysis oil, the aromatic carbon content decreased by 78%, with a significant increase in the aliphatic carbon content.

关键词： hydrogenation pyrolysis oil Loblolly pine residue zeolite ZSM-5

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：