检索结果-内蒙古大学图书馆

Design of intelligent robot Platform based on Multi-sensor Fusion

Journal of Physics: Conference Series 2020年第1期1606卷

作者： Ya Dajin Lei Xiaochun Li Yue Chen Junyan Huang Rongcun Lan Lin School of computer and information security Guilin University of Electronic Technology Guilin 541004 China Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics Guilin 541004 China Guangxi Cooperative Innovation Center of cloud computing and Big Data Guilin University of Electronic Technology Guilin 541004 China

The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex environments, the indoor mobile robot that combines Inertial Measurement Unit (IMU) and encoder fusion is designed and implemented. In view of the limitations of the traditional single lidar scheme, a Multi-sensor Fusion scheme is proposed to achieve indoor map construction, path planning, multi-point navigation and other functions, and a MSIF KartoSLAM (Multi-sensor Information Fusion) algorithm is proposed, which combines the KartoSLAM algorithm and Multi-sensor information to achieve map construction in complex environments. Through comprehensive testing in the indoor environment, the results show that the Multi-sensor Fusion scheme is superior to the traditional single lidar scheme, and can achieve higher accuracy in mapping and navigation. At the same time, the robot platform can also be combined with the Internet of Things technology and integrated into intelligent housing system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Image reconstruction from photoacoustic projections

引用

Photonics Insights 2024年第3期3卷 145-209页

作者： Chao Tian Kang Shen Wende Dong Fei Gao Kun Wang Jiao Li Songde Liu Ting Feng Chengbo Liu Changhui Li Meng Yang Sheng Wang Jie Tian Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefeiChina School of Engineering Science University of Science and Technology of ChinaHefeiChina Department of Anesthesiology the First Affiliated Hospital of USTCDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiChina Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing HefeiChina College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjingChina School of Information Science and Technology ShanghaiTech UniversityShanghaiChina Shanghai Clinical Research and Trial Center ShanghaiChina CAS Key Laboratory of Molecular Imaging Institute of AutomationChinese Academy of SciencesBeijingChina School of Precision Instruments and Optoelectronics Engineering Tianjin UniversityTianjinChina Academy for Engineering and Technology Fudan UniversityShanghaiChina Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhenChina Department of Biomedical Engineering College of Future TechnologyPeking UniversityBeijingChina National Biomedical Imaging Center Peking UniversityBeijingChina Departments of Ultrasound State Key Laboratory of Complex Severe and Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina School of Engineering Medicine Beihang UniversityBeijingChina Key Laboratory of Big Data-Based Precision Medicine Beihang UniversityMinistry of Industry and Information TechnologyBeijingChina

Photoacoustic computed tomography(PACT)is a rapidly developing biomedical imaging modality and has attracted substantial attention in recent *** reconstruction from photoacoustic projections plays a critical role in image formation in *** we review six major classes of image reconstruction approaches developed in the past three decades,including delay and sum,filtered back projection,series expansion,time reversal,iterative reconstruction,and deep-learning-based *** principal ideas and implementations of the algorithms are summarized,and their reconstruction performances under different imaging scenarios are *** challenges,future directions,and perspectives for the development of image reconstruction algorithms in PACT are also *** review provides a self-contained reference guide for beginners and specialists in the photoacoustic community,to facilitate the development and application of novel photoacoustic image reconstruction algorithms.

关键词： optical imaging photoacoustic tomography image reconstruction deep learning

来源：评论

学校读者我要写书评

暂无评论

Effect of respiratory microflorae colonization on short and long-time outcomes of respiratory syncytial virus infection in children: A scoping review

Pediatric Discovery

引用

Pediatric Discovery 2024年第4期2卷

作者： Lidan Gan Enmei Liu Yu Deng Department of Respiratory Medicine Children's Hospital of Chongqing Medical University Chongqing China Ministry of Education Key Laboratory of Child Development and Disorders Children's Medical Big Data Intelligent Application Center Department of Respiratory Medicine Chongqing China National Clinical Research Center for Child Health and Disorders Chongqing China

Respiratory syncytial virus (RSV) is an essential cause of lower respiratory tract infection in children under 2 years of age, especially under 6 months. In decades, studies have shown that the respiratory tract microflorae with RSV infection were related to disease severity and played a role in the development of recurrent wheezing, but the effect of respiratory microflorae on RSV infection are still underestimated. This study aims to conclude the effect of respiratory microflorae colonization on RSV infectious disease severity and recurrent wheezing and provide suggestions for future research directions from the perspective of respiratory tract florae. We conducted a scoping review. Studies were eligible if they reported on the effect of microflorae on RSV infectious diseases among children. We exacted the following information: title, publication time, first author's country, and article type. We finally included 33 articles in this scoping review. The number of studies rapidly increased since 2013 and the highest number of hospitalizations were reported in children <2 years. More than half (69.70%) were conducted in America and most studies are original studies (57.58%). The Review highlighted that the respiratory microflorae played an important role in RSV infectious disease severity and recurrent wheezing. We found that Streptococcus pneumoniae (***), Haemophilus influenza (HI), Moraxella catarrhalis (***), and Staphylococcus aureus (SA) were the dominant profiles in children with RSV infection. Understanding the respective role of respiratory microflorae on RSV infection and its mechanisms would improve prevention and treatment strategies from the perspective of microflorae.

关键词： childhood asthma disease severity microflorae recurrent wheezing respiratory syncytial virus

来源：评论

学校读者我要写书评

暂无评论

An improved Chinese text multi-label classification method based on CNN

引用

Journal of Physics: Conference Series 2020年第1期1619卷

作者： Yuanxia Xin Zhi Zhang Collage of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 Hubei China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430065 Hubei China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan 430065 Hubei China

Text multi-label classification technology can accurately and quickly classify text information into related categories or topics, and help people quickly locate the required content in massive information resources, which is of great significance in application. As the traditional classification algorithm is faced with the problems of low classification accuracy due to the low correlation of data labels, unbalanced label data and few short text feature words, this paper firstly performs hierarchical pre-processing on label data to transform multi-label classification into hierarchical text multi-classification. At the same time, an improved multi-label classification algorithm Multi-label Convolutional Neural Networks (ML-CNN) is proposed. Based on the TensorFlow framework, a CNN model is designed and different training models are constructed for each level of label classification. According to the number of classification levels, the output of the upper level label is stitched to the original input tail as the next level of input. Experiments on the description information of 500,000 Chinese products with labels, show that the improved algorithm will significantly improve the classification accuracy and the accuracy of each level can reach more than 88%, which proves the feasibility and effectiveness of the algorithm.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Circulating proteins and peripheral artery disease risk: observational and Mendelian randomization analyses

引用

European Heart Journal Open 2023年第3期3卷 oead056页

作者： Yuan, Shuai Titova, Olga E. Zhang, Ke Chen, Jie Li, Xue Klarin, Derek Åkesson, Agneta Damrauer, Scott M. Larsson, Susanna C. Unit of Cardiovascular and Nutritional Epidemiology Institute of Environmental Medicine Karolinska Institutet Nobels väg 13 Solna Stockholm 171 65 Sweden Unit of Medical Epidemiology Department of Surgical Sciences Uppsala University Uppsala Sweden Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province School of Life Sciences Westlake University Hangzhou China Westlake Intelligent Biomarker Discovery Lab Westlake Laboratory of Life Sciences and Biomedicine Hangzhou China Department of Big Data in Health Science School of Public Health Center of Clinical Big Data and Analytics The Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou China VA Palo Alto Healthcare System 4951 Arroyo Rd Livermore 94550 CA United States Department of Surgery Stanford University School of Medicine Stanford University Palo Alto CA United States Corporal Michael J. Crescenz VA Medical Center Philadelphia PA United States Department of Surgery Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA United States

Aims We conducted observational and Mendelian randomization (MR) analyses to explore the associations between blood proteins and risk of peripheral artery disease (PAD).;Methods and results The observational cohort analyses included data on 257 proteins estimated in fasting blood samples from 12 136 Swedish adults aged 55–94 years who were followed up for incident PAD via the Swedish Patient Register. Mendelian randomization analyses were undertaken using cis-genetic variants strongly associated with the proteins as instrumental variables and genetic association summary statistic data for PAD from the FinnGen study (11 924 cases and 288 638 controls) and the Million Veteran Program (31 307 cases and 211 753 controls). The observational analysis, including 86 individuals diagnosed with incident PAD during a median follow-up of 6.6-year, identified 13 proteins [trefoil factor two, matrix metalloproteinase-12 (MMP-12), growth differentiation factor 15, V-set and immunoglobulin domain-containing protein two, N-terminal prohormone brain natriuretic peptide, renin, natriuretic peptides B, phosphoprotein associated with glycosphingolipid-enriched microdomains one, C-C motif chemokine 15, P-selectin, urokinase plasminogen activator surface receptor, angiopoietin-2, and C-type lectin domain family five member A] associated with the risk of PAD after multiple testing correction. Mendelian randomization analysis found associations of T-cell surface glycoprotein CD4, MMP-12, secretoglobin family 3A member 2, and ADM with PAD risk. The observational and MR associations for T-cell surface glycoprotein CD4 and MMP-12 were in opposite directions. Conclusion This study identified many circulating proteins in relation to the development of incident PAD. Future studies are needed to verify our findings and assess the predictive and therapeutic values of these proteins in PAD. © The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.

关键词： Cohort Mendelian randomization Protein Peripheral artery disease

来源：评论

学校读者我要写书评

暂无评论

Enhancing Sequential Personalized Product Search with External Out-of-sequence Knowledge

引用

ACM Transactions on Information Systems 1000年

作者： Jiongnan Liu Zhicheng Dou Jian-Yun Nie Zhenlin Chen Guoyu Tang Sulong Xu Ji-Rong Wen Gaoling School of Artificial Intelligence Renmin University of China China DIRO University de Montreal Canada *** Inc China Gaoling School of Artificial Intelligence Renmin University of China China Engineering Research Center of Next-Generation Intelligent Search and Recommendation Ministry of Education China and Beijing Key Laboratory of Big Data Management and Analysis Methods China

A key challenge in personalized product search is to capture user’s preferences. Recent work attempted to model sequences of user historical behaviors, i.e., product purchase histories, to build user profiles and to personalize results accordingly. Although these approaches have demonstrated promising retrieval performances, we notice that most of them focus solely on the intra-sequence interactions between items. However, as there is usually a small amount of historical behavior data, the user profiles learned by these approaches could be very sensitive to the noise included in it. To tackle this problem, we propose incorporating out-of-sequence external information to enhance user modeling. More specifically, we inject the external item-item relations (e.g., belonging to the same brand), and query-query relations (e.g., the semantic similarities between them), into the intra-sequence interaction to learn better user profiles. In addition, we devise two auxiliary decoders, with the historical item sequence reconstruction task and the global item similarity prediction task, to further improve the reliability of user modeling. Experimental results on two datasets from simulated and real user search logs respectively show that the proposed personalized product search method outperforms existing approaches.

关键词： personalized product search sequential model graph

来源：评论

学校读者我要写书评

暂无评论

Linked data Crowdsourcing Quality Assessment based on Domain Professionalism

引用

Journal of Physics: Conference Series 2019年第5期1187卷

作者： Lu Yang Li Huang Zhenzhen Liu School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

With the rapid development of Internet technology, crowdsourcing, as a flexible, effective and low-cost problem-solving method, has begun to receive more and more attention. The use of crowdsourcing to evaluate the quality of linked data has also become a research hotspot. This paper proposes the concept of Domain Specialization Test (DST), which uses domain professional testing tasks DSTs to evaluate the professionalism of workers, and combines the idea of Mini-batch Gradient Descent (MBGD) to improve the EM algorithm, and the MBEM algorithm is proposed to achieve efficient and accurate evaluation of task results. The experimental results show that the proposed method can screen out the appropriate workers for the linked data crowdsourcing task and improve the accuracy and iteration efficiency of the results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Emergency Event Matching using Hierarchical Blocking Method

引用

Journal of Physics: Conference Series 2019年第5期1187卷

作者： Chang Wen Yu Liu College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

With the extensive application of the knowledge base (KB), how to complete it is a hot topic on Semantic Web. However, many problems go with the big data, and the event matching is one of these problems, which is finding out the entities referring to the same things in the real world and also the key point in the extending process. To enrich the emergency knowledge base (E-SKB) we constructed before, we need to filter out the news from several web pages and find the same news to avoid data redundancy. In this paper, we proposed a hierarchy blocking method to reduce the times of comparisons and narrow down the scope by extracting the news properties as the blocking keys. The method transforms the event matching problem into a clustering problem. Experimental results show that the proposed method is superior to the existing text clustering algorithm with high precision and less comparison times.

关键词：

来源：评论

学校读者我要写书评

暂无评论

One for Multiple: Physics-informed Synthetic data Boosts Generalizable Deep Learning for Fast MRI Reconstruction

arXiv

引用

arXiv 2023年

作者： Wang, Zi Yu, Xiaotong Wang, Chengyan Chen, Weibo Wang, Jiazheng Chu, Ying-Hua Sun, Hongwei Li, Rushuai Li, Peiyong Yang, Fan Han, Haiwei Kang, Taishan Lin, Jianzhong Yang, Chen Chang, Shufu Shi, Zhang Hua, Sha Li, Yan Hu, Juan Zhu, Liuhong Zhou, Jianjun Lin, Meijing Guo, Jiefeng Cai, Congbo Chen, Zhong Guo, Di Yang, Guang Qu, Xiaobo Department of Electronic Science Intelligent Medical Imaging R&D Center Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance National Institute for Data Science in Health and Medicine Xiamen University China Human Phenome Institute Fudan University China Philips Healthcare China Siemens Healthineers Ltd. China United Imaging Research Institute of Intelligent Imaging China Department of Nuclear Medicine Nanjing First Hospital China Shandong Aoxin Medical Technology Company China Department of Radiology The First Affiliated Hospital of Xiamen University China Department of Radiology Zhongshan Hospital Affiliated to Xiamen University China China Department of Cardiology Shanghai Institute of Cardiovascular Diseases Zhongshan Hospital Fudan University China Department of Radiology Zhongshan Hospital Fudan University China Department of Cardiovascular Medicine Heart Failure Center Ruijin Hospital Lu Wan Branch Shanghai Jiaotong University School of Medicine China Department of Radiology Ruijin Hospital Shanghai Jiaotong University School of Medicine China Medical Imaging Department The First Affiliated Hospital of Kunming Medical University China Xiamen Key Laboratory of Clinical Transformation of Imaging Big Data and Artificial Intelligence China Department of Applied Marine Physics and Engineering Xiamen University China Department of Microelectronics and Integrated Circuit Xiamen University China School of Computer and Information Engineering Xiamen University of Technology China Department of Bioengineering Imperial College London United Kingdom

Magnetic resonance imaging (MRI) is a widely used radiological modality renowned for its radiation-free, comprehensive insights into the human body, facilitating medical diagnoses. However, the drawback of prolonged scan times hinders its accessibility. The k-space undersampling offers a solution, yet the resultant artifacts necessitate meticulous removal during image reconstruction. Although Deep Learning (DL) has proven effective for fast MRI image reconstruction, its broader applicability across various imaging scenarios has been constrained. Challenges include the high cost and privacy restrictions associated with acquiring large-scale, diverse training data, coupled with the inherent difficulty of addressing mismatches between training and target data in existing DL methodologies. Here, we present a novel Physics-Informed Synthetic data learning framework for Fast MRI, called PISF. PISF marks a breakthrough by enabling generalized DL for multi-scenario MRI reconstruction through a single trained model. Our approach separates the reconstruction of a 2D image into many 1D basic problems, commencing with 1D data synthesis to facilitate generalization. We demonstrate that training DL models on synthetic data, coupled with enhanced learning techniques, yields in vivo MRI reconstructions comparable to or surpassing those of models trained on matched realistic datasets, reducing the reliance on real-world MRI data by up to 96%. Additionally, PISF exhibits remarkable generalizability across multiple vendors and imaging centers. Its adaptability to diverse patient populations has been validated through evaluations by ten experienced medical professionals. PISF presents a feasible and cost-effective way to significantly boost the widespread adoption of DL in various fast MRI applications. Importantly, it alleviates the ethical and practical challenges associated with in vivo human data acquisitions, opening new horizons for advancing fast MRI technologies. Copyright © 20

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Pattern recognition of UAV flight data based on semi-supervised clustering

引用

Journal of Physics: Conference Series 2019年第1期1195卷 012001-012001页

作者： Wang, N Liu, Y Z SH Xu Sun, SH W School of Management Science and Information Engineering Jilin University of Finance and EconomicsChina Laboratory of Logistics Industry Economy and Intelligent Logistics Jilin University of Finance and Economics China Jilin Big Data Research Center for Business Jilin University of Finance and EconomicsChina Jilin Province Key Laboratory of Fintech Jilin University of Finance and EconomicsChina Shenyang Woozoom Technology Co. LtdChina School of Management Science and Information Engineering Jilin University of Finance and EconomicsChina Laboratory of Logistics Industry Economy and Intelligent Logistics Jilin University of Finance and Economics China

UAV is an unmanned aerial vehicle controlled by a remote radio signal or a trajectory planning software carried itself. It is widely used in military, civil and scientific research fields. However, due to the lack of real-time decision-making ability, the UAV has high fault rate. The flight quality assessment of UAV and the construction of fault prediction model can be used for debugging and fault-removing to customer’s aircraft, and also to increase the added value of the civilian UAV products. Before building a fault prediction model, a very important step is to identify the pattern of sampled data. For each group of flight data, the efficiency and accuracy rate of manual quality evaluation and fault identification are not acceptable. Based on the UAV flight data accumulated in the big data platform of an UAV production company in Shenyang, Liaoning Province of China, this paper proposes a semi-supervised clustering technique to do automatic pattern recognition for the sampling points. According to the characteristics of UAV flight data, two different methods are designed to choose initial centroids. Meanwhile, we use the existing normal flight data to train distance thresholds to combine some clusters to eliminate the resulting error clustering. Real flight data or flight test data with manually added labels are used to run the proposed algorithms to verify the recognition results. The experimental results show that the proposed methods greatly improve the efficiency and accuracy of adding precise labels to the historical flight data and play a role in assisting the manual recognition of sampling points while strengthening the management and statistics.

关键词：

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：