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Paleoclimate evolution of the North Pacific Ocean during the late Quaternary: Progress and challenges

Geosystems and Geoenvironment 2023年第1期2卷

作者： Zhong, Yi Lu, Zhengyao Wilson, David J. Zhao, Debo Liu, Yanguang Chen, Ting Gai, Congcong Gong, Xun Jiang, Zhaoxia Liu, Jiabo Liu, Qingsong ) Department of Ocean Science and Engineering Southern University of Science and Technology Shenzhen 518055 China Department of Physical Geography and Ecosystem Science Lund University Lund Sweden Institute of Earth and Planetary Sciences University College London and Birkbeck University of London London United Kingdom Key Laboratory of Marine Geology and Environment Institute of Oceanology Chinese Academy of Sciences Qingdao China Key Laboratory of Marine Geology and Metallogeny First Institute of Oceanography Ministry of Natural Resources (MNR) Qingdao China Chongqing Key Laboratory of Wetland Science Research of the Upper Yangtze River Chongqing Normal University Chongqing China Hubei Key Laboratory of Marine Geological Resources China University of Geosciences (Wuhan) Wuhan China Frontiers science Center for Deep Ocean Multispheres and Earth System Key Lab of Submarine Geosciences and Prospecting Techniques Ministry of Education College of Marine Geosciences Ocean University of China Qingdao 266100 China Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) Guangzhou China Shanghai Sheshan National Geophysical Observatory Shanghai China

High- and low-latitude climatic processes in the North Pacific Ocean are important components of the global climate system. For example, the interplay among North Pacific atmospheric circulation, ocean circulation, and biological productivity affects atmospheric carbon dioxide levels and marine oxygen concentrations. Here we review recent research on the North Pacific paleoclimatic and paleoceanographic evolution during the late Quaternary and its response to external forcings such as orbital insolation, ice-sheet extent, and greenhouse gas concentrations. First, we summarize the principles and application of relative paleointensity as a critical chronological tool in North Pacific paleoclimate research. Second, we illustrate the latest discoveries on the interaction between North Pacific Intermediate Water formation and high-to-low latitude teleconnection processes. Third, recent progress in linking dust fluxes and marine productivity and their global significance for the carbon cycle are presented. Finally, several key scientific problems are highlighted for future research on ocean-atmosphere-climate interactions in the North Pacific, pointing to the importance of combining paleo-records and modeling simulations. Overall, this review also aims to provide a broad insight into possible future changes of ocean-atmosphere circulation in the North Pacific region under a rapidly warming climate. © 2022

关键词： Atmospheric circulation data-model comparison High-low latitude connections Intermediate water formation North Pacific Ocean Paleoclimate evolution

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Design of Fine Management system for Civil Aviation Airspace Resources Based on Spatiotemporal Grid Model

Design of Fine Management System for Civil Aviation Airspace...

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IEEE International Conference on Civil Aviation Safety and Information technology (ICCASIT)

作者： Yinger Zheng Juqing Liu Jun Li Yubin Xu Qian Huang Yan Zhu Yanqiu Pei Big Data Application Center China Academy of Civil Aviation Science and Technology Beijing China College of Geoscience and Surveying Engineering China University of Mining and Technology Beijing China Research and Development Center China Academy of Civil Aviation Science and Technology Beijing China Service Lab Huawei Research Institute Huawei Technology Co. Ltd Beijing China

ISBN: (纸本)9781728125992

Along with the rapid development of aviation industry, airspace demand is increasing. However, the current airspace resources are tight and the utilization efficiency is low. Aiming at addressing this problem, this paper proposes a fine management system for civil aviation airspace resources based on spatiotemporal grid model. Relying on massive, multisource, multi-scale and multi-dimensional aviation big data, this study expands the time dimension of global discrete grid technology and establishes a global unified spatiotemporal grid model. On this basis, the calculation and analysis method of the spatiotemporal grid model is designed to carry out route management, conduct flight collision detection, allocate airspace resources, and then realize efficient and intelligent management, allocation and intelligent application of airspace resources. Finally, the scientificity and feasibility of the management system is verified through the practical application of civil aviation ADS-B data, meteorological data and route data.

关键词： Spatiotemporal grid Airspace resources Fine management En-route capacity civil aviation utilization efficiency grids Grid MANAGEMENT systemS time dimension

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Prospect of 5G Application in Civil Airport

Prospect of 5G Application in Civil Airport

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IEEE International Conference on Civil Aviation Safety and Information technology (ICCASIT)

作者： Ningning Le Yinger Zheng Qian Huang Yanqiu Pei Big Data Analysis and Application Center China Academy of Civil Aviation Science and Technology Beijing China Service Lab Huawei Research Institute Huawei Technology Co. Ltd Beijing China College of Geoscience and Surveying Engineering China University of Mining and Technology Beijing China

ISBN: (纸本)9781728125992

With the rapid growth of China's civil aviation transportation volume, the airport has entered the era of big data in which data is massive, diversified, and converted at high speeds. Achievements for intelligent application of big data based on 5G technology have become an indispensable component of smart airports. Based on the characteristics of 5G technology, this paper combines various state-of-art technologies including Discrete Global Grid systems, Complex Network, Artificial Intelligence, to prospect the application scenarios of 5G in airport, as efficient and secure wide-area wireless communication system, IoT-based smart monitoring, airport unmanned driving, high-speed entertainment experience, intelligent passenger service.

关键词： 5G New data technology Application prospect Civil airport Airports big data 5G mobile communication PASSENGER SERVICES Grid systems Prospecting Wireless communication systems High speed

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Errata to “On-Edge Multi-Task Transfer Learning: Model and Practice With data-Driven Task Allocation”

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IEEE Transactions on Parallel and Distributed systems 2020年第11期31卷 2569-2569页

作者： Qiong Chen Zimu Zheng Chuang Hu Dan Wang Fangming Liu National Engineering Research Center for Big Data Technology and System Huazhong University of Science and Technology Wuhan China Edge Cloud Innovation Lab Technical Innovation Department Cloud BU Huawei Technologies Company Ltd. Shenzhen China Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong

Presents corrections to author information for the above named paper.

关键词： Task analysis Resource management Technological innovation Computational modeling big data Service computing Computer science

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Taking the pulse of COVID-19:a spatiotemporal perspective

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International Journal of Digital Earth 2020年第10期13卷 1186-1211页

作者： Chaowei Yang Dexuan Sha Qian Liu Yun Li Hai Lan Weihe Wendy Guan Tao Hu Zhenlong Li Zhiran Zhang John Hoot Thompson Zifu Wang David Wong Shiyang Ruan Manzhu Yu Douglas Richardson Luyao Zhang Ruizhi Hou You Zhoua Cheng Zhong Yifei Tian Fayez Beaini Kyla Carte Colin Flynn Wei Liu Dieter Pfoser Shuming Bao Mei Li Haoyuan Zhang Chunbo Liu Jie Jiang Shihong Du Liang Zhao Mingyue Lu Lin Li Huan Zhou Andrew Ding NSF Spatiotemporal Innovation Center George Mason Univ.FairfaxVAUSA Department of Geography and GeoInformation Science George Mason Univ.FairfaxVAUSA Department of Geographical Sciences University of MarylandCollege ParkMDUSA Center for Geographic Analysis Harvard UniversityCambridgeMAUSA Geoinformation and Big Data Research Lab Department of GeographyUniversity of South CarolinaColumbiaSCUSA Chinese Academy of Surveying and Mapping BeijingPeople’s Republic of China School of Resource and Environmental Sciences Wuhan UniversityWuhanPeople’s Republic of China Cloud Computeand Storage OperationsInformation Technology ServicesGeorge Mason UniversityFairfaxVAUSA Department of Geography Pennsylvania State UniversityState CollegePAUSA School of Business Management East China Normal UniversityShanghaiPeople’s Republic of China School of Mathematical Sciences East China Normal UniversityShanghaiPeople’s Republic of China Department of Psychology George Mason UniversityFairfaxVAUSA mDepartment of Computer Science George Mason UniversityFairfaxVAUSA Department of Information Technology George Mason UniversityFairfaxVAUSA Department of Biology George Mason UniversityFairfaxVAUSA College of Land Science and Technology China Agricultural UniversityBeijingPeople’s Republic of China China Data Institute Ann ArborMIUSA Institute of Remote Sensing and GIS Peking UniversityBeijingPeople’s Republic of China Aerospace Information Research Institute Chinese Academy of SciencesBeijingPeople’s Republic of China School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and ArchitectureBeijingPeople’s Republic of China School of Geographical Sciences Nanjing University of Information Science&TechnologyNanjingPeople’s Republic of China School of Geodesy and Geomatics Wuhan UniversityWuhanPeople’s Republic of China wFaculty of Environment University of WaterlooWaterlooCanada

The sudden outbreak of the Coronavirus disease(COVID-19)swept across the world in early 2020,triggering the lockdowns of several billion people across many countries,including China,Spain,India,the U.K.,Italy,France,Germany,Brazil,Russia,and the *** transmission of the virus accelerated rapidly with the most confirmed cases in the U.S.,India,Russia,and *** response to this national and global emergency,the NSF Spatiotemporal Innovation center brought together a taskforce of international researchers and assembled implementation strategies to rapidly respond to this crisis,for supporting research,saving lives,and protecting the health of global *** perspective paper presents our collective view on the global health emergency and our effort in collecting,analyzing,and sharing relevant data on global policy and government responses,human mobility,environmental impact,socioeconomical impact;in developing research capabilities and mitigation measures with global scientists,promoting collaborative research on outbreak dynamics,and reflecting on the dynamic responses from human societies.

关键词： big data Earth system emergency geospatial sciences epidemics applications

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Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images

arXiv

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arXiv 2021年

作者： Sharifrazi, Danial Alizadehsani, Roohallah Roshanzamir, Mohamad Joloudari, Javad Hassannataj Shoeibi, Afshin Jafari, Mahboobeh Hussain, Sadiq Sani, Zahra Alizadeh Hasanzadeh, Fereshteh Khozeimeh, Fahime Khosravi, Abbas Nahavandi, Saeid Panahiazar, Maryam Zare, Assef Shariful Islam, Sheikh Mohammed Rajendra, U. Acharya Department of Computer Engineering School of Technical and Engineering Shiraz Branch Islamic Azad University Shiraz Iran Deakin University Geelong Australia Department of Engineering Fasa Branch Islamic Azad University Post Box No 364 Fasa Fars*** Iran Department of Computer Engineering Faculty of Engineering University of Birjand Birjand Iran Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran Faculty of Electrical and Computer Engineering Biomedical Data Acquisition Lab K. N. Toosi University of Technology Tehran Iran Electrical and Computer Engineering Faculty Semnan University Semnan Iran System Administrator Dibrugarh University Assam786004 India Rajaie Cardiovascular Medical and Research Center Iran University of Medical Sciences Tehran Iran Omid hospital Iran University of Medical Sciences Tehran Iran Institute for Computational Health Sciences University of California San Francisco United States Faculty of Electrical Engineering Gonabad Branch Islamic Azad University Gonabad Iran Institute for Physical Activity and Nutrition Deakin University Melbourne Australia Cardiovascular Division The George Institute for Global Health Australia Sydney Medical School University of Sydney Australia Department of Electronics and Computer Engineering Ngee Ann Polytechnic Singapore Department of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore Department of Bioinformatics and Medical Engineering Asia University Taiwan

The coronavirus (COVID-19) is currently the most common contagious disease which is prevalent all over the world. The main challenge of this disease is the primary diagnosis to prevent secondary infections and its spread from one person to another. Therefore, it is essential to use an automatic diagnosis system along with clinical procedures for the rapid diagnosis of COVID-19 to prevent its spread. Artificial intelligence techniques using computed tomography (CT) images of the lungs and chest radiography have the potential to obtain high diagnostic performance for Covid-19 diagnosis. In this study, a fusion of convolutional neural network (CNN), support vector machine (SVM), and Sobel filter is proposed to detect COVID-19 using X-ray images. A new X-ray image dataset was collected and subjected to high pass filter using a Sobel filter to obtain the edges of the images. Then these images are fed to CNN deep learning model followed by SVM classifier with ten-fold cross validation strategy. This method is designed so that it can learn with not many data. Our results show that the proposed CNN-SVM with Sobel filtering (CNN-SVM+Sobel) achieved the highest classification accuracy of 99.02% in accurate detection of COVID-19. It showed that using Sobel filter can improve the performance of CNN. Unlike most of the other researches, this method does not use a pre-trained network. We have also validated our developed model using six public databases and obtained the highest performance. Hence, our developed model is ready for clinical application. Copyright © 2021, The Authors. All rights reserved.

关键词： data mining

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Deep Learning in Digital Breast Tomosynthesis: Current Status, Challenges, and Future Trends

MedComm

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MedComm 2025年第6期6卷

作者： Ruoyun Wang Fanxuan Chen Haoman Chen Chenxing Lin Jincen Shuai Yutong Wu Lixiang Ma Xiaoqu Hu Min Wu Jin Wang Qi Zhao Jianwei Shuai Jingye Pan Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine Vision and Brain Health) Wenzhou Institute University of Chinese Academy of Sciences Wenzhou China Wenzhou Medical University Wenzhou China UCSC Baskin School of Engineering University of California Santa Cruz California USA Department of Anatomy Histology & Embryology School of Basic Medical Sciences Fudan University Shanghai China Department of Medicine Harvard Medical School and Brigham and Women's Hospital Boston Massachusetts USA Joint Research Centre on Medicine The Affiliated Xiangshan Hospital of Wenzhou Medical University Ningbo China Stony Brook University Stony Brook New York USA School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan China Key Laboratory of Intelligent Treatment and Life Support for Critical Diseases of Zhejiang Province Wenzhou China Department of Big Data in Health Science The First Affiliated Hospital of Wenzhou Medical University Wenzhou China Zhejiang Engineering Research Center for Hospital Emergency and Process Digitization Wenzhou China

The high-resolution three-dimensional (3D) images generated with digital breast tomosynthesis (DBT) in the screening of breast cancer offer new possibilities for early disease diagnosis. Early detection is especially important as the incidence of breast cancer increases. However, DBT also presents challenges in terms of poorer results for dense breasts, increased false positive rates, slightly higher radiation doses, and increased reading times. Deep learning (DL) has been shown to effectively increase the processing efficiency and diagnostic accuracy of DBT images. This article reviews the application and outlook of DL in DBT-based breast cancer screening. First, the fundamentals and challenges of DBT technology are introduced. The applications of DL in DBT are then grouped into three categories: diagnostic classification of breast diseases, lesion segmentation and detection, and medical image generation. Additionally, the current public databases for mammography are summarized in detail. Finally, this paper analyzes the main challenges in the application of DL techniques in DBT, such as the lack of public datasets and model training issues, and proposes possible directions for future research, including large language models, multisource domain transfer, and data augmentation, to encourage innovative applications of DL in medical imaging.

关键词： early breast cancer screening digital breast tomosynthesis deep learning public database medical image analysis

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The Design and Implementation of an Augmented Reality Scheme Based on Netty Communication

引用

Journal of Physics: Conference Series 2020年第1期1575卷

作者： Yongping Gao Jie Wang Jingzhong Zhang Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang 330013 Jiangxi China Jiangxi Engineering Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang 330013 Jiangxi China Jiangxi ZhongYe Light Culture Technology Limited Company Nanchang 330006 Jiangxi China

This paper introduces a whole project of augmented reality interaction mode based on netty communication method, determines the main technical difficulties in the implementation process, and finds the solution by means of system architecture design and communication protocol development. In this paper, the netty framework is adopted to deal with network IO and business logic, and the communication between each terminal device, virtual environment and server is established through long connection, This paper adopts the netty framework to deal with network IO and business logic, establishes communication between each terminal device and virtual environment and server through long connection, so as to realize fast and natural real-time interaction between various interactive devices and other augmented reality devices and virtual environments under multiple users. It can also solve the problem of high concurrency of real-time communication between various devices and the virtual environment in augmented reality.

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Navigation with low-sampling-rate GPS and smartphone sensors: A data-driven learning-based approach

Navigation with low-sampling-rate GPS and smartphone sensors...

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IET 8th International Conference on Wireless, Mobile &Multimedia Networks

作者： Jiahui Qi Hang Li Feng Yin Bo Ai Hervin Hidayat Putra Shuguang Cui School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044 China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing 100044 China Electrical and Informatics Engineering School Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9781839531637

For vehicle navigation, an inertial navigation system (INS) is often used to assist the global positioning system (GPS); but the positioning accuracy is well known to be sensitive to both the GPS sampling rate and inertial sensor error aggregation. As such, many practical navigation systems adopt both highend INS and high GPS sampling rate, which costs more for hardware on the one hand and demands excessive energy consumption and communications on the other hand. In this work, we propose a learning-based approach that is capable of providing the same level of positioning accuracy but using merely cheap, low-end mobile inertial sensors and integrated GPS with very low sampling rate. The proposed approach consists of a Kalman filter and two multilayer neural networks to realize 3-dimensional, high-precision vehicle navigation. The key to the impressive outcome is the combination of the classic statespace Kalman filter with a new data-driven machine learning mechanism. The proposed approach is evaluated with real trajectory data collected on campus of CUHKSZ, and the results show that it can achieve a positioning error around 8m when the GPS sampling interval is as large as 30s (30 times of nowadays regular sampling interval). Apart from this, the proposed approach also demonstrates good adaptiveness to changing trajectories.

关键词： VEHICLE NAVIGATION SMARTPHONES KALMAN FILTER MULTILAYER NEURAL NETWORK LOW-SAMPLING-RATE GPS Global Positioning systems positioning accuracy Multilayer neural networks Vehicle navigation navigation Kalman filters sampling rate energy consumption location error data driven trajectory data Smartphone Navigation systems hybrid navigation systems Instruments Division

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An overview on visualization of ontology alignment and ontology entity 5th

An overview on visualization of ontology alignment and ontol...

引用

5th Euro-China Conference on Intelligent data Analysis and Applications, ECC 2018

作者： Chen, Jie Xue, Xingsi Huang, Lili Ren, Aihong College of Information Science and Engineering Fujian University of Technology FuzhouFujian350118 China Intelligent Information Processing Research Center Fujian University of Technology FuzhouFujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications FuzhouFujian350118 China Fujian Key Lab for Automotive Electronics and Electric Drive Fujian University of Technology FuzhouFujian350118 China College of Humanities and Law Fujian Agriculture and Forestry University FuzhouFujian350002 China School of Mathematics and Information Science Baoji University of Arts and Sciences BaojiShaanxi721013 China

ISBN: (纸本)9783030037659

Visualization of ontology alignment and ontology entity is becoming a method to help Solve the problem of semantic heterogeneity. This paper first introduces the basic concepts of ontology and ontology matching, and then illustrates the importance of ontology visualization technique. The existing partial visualization tools are discussed respectively in two aspects of visualization of ontology alignment and visualization entity on ontology. Finally, four researching directions on ontology visualization technique are pointed out for the future work. © Springer Nature Switzerland AG 2019.

关键词： Ontology

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