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Ground movements due to deep excavations in Shanghai: Design charts

Malcolm D. BOLTON,Sze-Yue LAM,Paul J. VARDANEGA,Charles W. W. NG,Xianfeng MA

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 3,   Pages 201-236 doi: 10.1007/s11709-014-0253-y

Abstract: research has clarified the sequence of ground deformation mechanisms that manifest themselves when excavationscapitalize on these advances, by analyzing an expanded database of ground movements associated with braced excavations

Keywords： Shanghai     excavations     mobilizable strength design     dimensionless groups     design charts    

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Advanced finite element analysis of a complex deep excavation case history in Shanghai

Yuepeng DONG, Harvey BURD, Guy HOULSBY, Yongmao HOU

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 1,   Pages 93-100 doi: 10.1007/s11709-014-0232-3

Abstract: North Square Shopping Center of the Shanghai South Railway Station is a large scale complex top-down deepconcrete floor slabs and beams, 4) the complex construction sequences, and 5) the shape effect of the deep

Keywords： advanced finite element analysis     deep excavations     case history     small-strain stiffness    

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Application of random set method in a deep excavation: based on a case study in Tehran cemented alluvium

Arash SEKHAVATIAN, Asskar Janalizadeh CHOOBBASTI

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 1,   Pages 66-80 doi: 10.1007/s11709-018-0461-y

Abstract: This paper studies an efficient user-friendly framework for dealing with uncertainties in a deep excavation

Keywords： uncertainty     reliability analysis     deep excavations     random set method     finite difference method    

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Digital image correlation-based structural state detection through deep learning

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 1,   Pages 45-56 doi: 10.1007/s11709-021-0777-x

Abstract: This paper presents a new approach for automatical classification of structural state through deep learning

Keywords： structural state detection     deep learning     digital image correlation     vibration signal     steel frame    

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7

Abstract: First, a new deep reinforcement learning (DRL) is developed, and it constructs an agent aiming at controllingSecond, a new structure of DRL is designed by combining deep deterministic policy gradient and long short-termACNN is also compared with other published machine learning (ML) and deep learning (DL) methods.

Keywords： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

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Development and deep-sea exploration of the Haidou-1

Frontiers of Engineering Management   Pages 546-549 doi: 10.1007/s42524-023-0260-6

Abstract: Development and deep-sea exploration of the Haidou-1

Keywords： hadal zone     autonomous and remotely-operated vehicle     integrated exploration operation     deep dive exceeding    

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Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

Frontiers of Structural and Civil Engineering doi: 10.1007/s11709-023-0942-5

Abstract: Hence, a gated recurrent unit (GRU)-based deep learning framework is proposed herein to dynamically predicteffective decision support for moving trajectory control and serve as a foundation for the application of deep

Keywords： dynamic prediction     moving trajectory     pipe jacking     GRU     deep learning    

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Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 930-939 doi: 10.1631/FITEE.1500125

Abstract: In this paper we propose a novel method to estimate head pose based on a deep convolutional neural network

Keywords： Head pose estimation     Deep convolutional neural network     Multiclass classification    

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Survey on deep learning for pulmonary medical imaging

Jiechao Ma, Yang Song, Xi Tian, Yiting Hua, Rongguo Zhang, Jianlin Wu

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 450-469 doi: 10.1007/s11684-019-0726-4

Abstract: As a promising method in artificial intelligence, deep learning has been proven successful in severalWith medical imaging becoming an important part of disease screening and diagnosis, deep learning-basedDeep learning has been widely applied in medical imaging for improved image analysis.This paper reviews the major deep learning techniques in this time of rapid evolution and summarizesLastly, the application of deep learning techniques to the medical image and an analysis of their future

Keywords： deep learning     neural networks     pulmonary medical image     survey    

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Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 496-506 doi: 10.1007/s11684-021-0828-7

Abstract: In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture

Keywords： XGBoost     deep neural network     healthcare     risk prediction    

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Stability analysis on Tingzikou gravity dam along deep-seated weak planes during earthquake

Weiping HE, Yunlong HE

Frontiers of Structural and Civil Engineering 2012, Volume 6, Issue 1,   Pages 69-75 doi: 10.1007/s11709-012-0146-x

Abstract: The stability of a gravity dam against sliding along deep-seated weak planes is a universal and importantThere is no recommended method for stability analysis of the dam on deep-seated weak planes under earthquakeis focused on searching a proper way to evaluate the seismic safety of the dam against sliding along deep-seatedweak planes and the probable failure modes of dam on deep-seated weak planes during earthquake.

Keywords： gravity dam     deep-seated weak planes     stability against sliding     earthquake    

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Theoretical and technological exploration of deep

Heping XIE, Yang JU, Shihua REN, Feng GAO, Jianzhong LIU, Yan ZHU

Frontiers in Energy 2019, Volume 13, Issue 4,   Pages 603-611 doi: 10.1007/s11708-019-0643-x

Abstract: Mining industries worldwide have inevitably resorted to exploiting resources from the deep undergroundTo exploit deep resources in the future, the concept of mining must be reconsidered and innovative newThe limits of mining depth need to be broken to acquire deep-coal resources in an environmentally friendlyFirst, this paper systematically explains deep fluidized coal mining.Finally, this paper presents a strategic roadmap for deep fluidized coal mining.

Keywords： coal resource     deep in situ     fluidized mining     theoretical system     key technologies     strategic roadmap    

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Efficient Identification of water conveyance tunnels siltation based on ensemble deep learning

Xinbin WU; Junjie LI; Linlin WANG

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 5,   Pages 564-575 doi: 10.1007/s11709-022-0829-x

Abstract: This paper introduces the idea of ensemble deep learning.

Keywords： water conveyance tunnels     siltation images     remotely operated vehicles     deep learning     ensemble learning    

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Deep eutectic solvent inclusions for high- composite dielectric elastomers

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 6,   Pages 996-1002 doi: 10.1007/s11705-022-2138-2

Abstract: successfully developed a novel strategy for improving the dielectric constant of polymeric elastomers via deeplow cost, convenient and environmentally benign synthesis process and high ionic conductivity from deepMoreover, we have proven the universality of our strategy by using different types of deep eutectic solventsIt is believed that low-cost, easy-synthesis and environmentally friendly deep eutectic solvents including

Keywords： composite materials     deep eutectic solvent     dielectric elastomer     high dielectric constant    

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Micro-hydromechanical deep drawing of metal cups with hydraulic pressure effects

Liang LUO, Zhengyi JIANG, Dongbin WEI, Xiaogang WANG, Cunlong ZHOU, Qingxue HUANG

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 1,   Pages 66-73 doi: 10.1007/s11465-018-0468-z

Abstract: Micro-hydromechanical deep drawing (MHDD), a typical microforming method, has been developed to take

Keywords： micro-hydromechanical deep drawing     microforming     size effects     lubrication     Voronoi    

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Title Author Date Type Operation

Ground movements due to deep excavations in Shanghai: Design charts

Malcolm D. BOLTON,Sze-Yue LAM,Paul J. VARDANEGA,Charles W. W. NG,Xianfeng MA

Journal Article

Advanced finite element analysis of a complex deep excavation case history in Shanghai

Yuepeng DONG, Harvey BURD, Guy HOULSBY, Yongmao HOU

Journal Article

Application of random set method in a deep excavation: based on a case study in Tehran cemented alluvium

Arash SEKHAVATIAN, Asskar Janalizadeh CHOOBBASTI

Journal Article

Digital image correlation-based structural state detection through deep learning

Journal Article

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Journal Article

Development and deep-sea exploration of the Haidou-1

Journal Article

Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

Journal Article

Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

Journal Article

Survey on deep learning for pulmonary medical imaging

Jiechao Ma, Yang Song, Xi Tian, Yiting Hua, Rongguo Zhang, Jianlin Wu

Journal Article

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Journal Article

Stability analysis on Tingzikou gravity dam along deep-seated weak planes during earthquake

Weiping HE, Yunlong HE

Journal Article

Theoretical and technological exploration of deep

Heping XIE, Yang JU, Shihua REN, Feng GAO, Jianzhong LIU, Yan ZHU

Journal Article

Efficient Identification of water conveyance tunnels siltation based on ensemble deep learning

Xinbin WU; Junjie LI; Linlin WANG

Journal Article

Deep eutectic solvent inclusions for high- composite dielectric elastomers

Journal Article

Micro-hydromechanical deep drawing of metal cups with hydraulic pressure effects

Liang LUO, Zhengyi JIANG, Dongbin WEI, Xiaogang WANG, Cunlong ZHOU, Qingxue HUANG

Journal Article