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A Hierarchical Model of the Creativity Support System Based on Experimental Learning

Feng Qinchao,Jiang Xiaogan,Sun Jin

Strategic Study of CAE 2006, Volume 8, Issue 4,   Pages 19-23

Abstract: A hierarchical model of the creativity support system based on experimental learning is presented.

Keywords： creativity     cognition     creativity support system     experimental learning    

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Interactive visual labelling versus active learning: an experimental comparison Research

Mohammad CHEGIN, Jürgen BERNARD, Jian CUI, Fatemeh CHEGINI, Alexei SOURIN, Keith Keith, Tobias SCHRECK

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 4,   Pages 524-535 doi: 10.1631/FITEE.1900549

Abstract: Methods from supervised machine learning allow the classification of new data automatically and areThe quality of supervised maching learning depends not only on the type of algorithm used, but also onActive learning algorithms can automatically determine a subset of data instances for which labels wouldprovide useful input to the learning process.The results show that all three interactive visual labelling techniques surpass active learning algorithms

Keywords： Interactive visual labelling     Active learning     Visual analytics    

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MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1677-1

Abstract:

● MSWNet was proposed to classify municipal solid waste.

Keywords： Municipal solid waste sorting     Deep residual network     Transfer learning     Cyclic learning rate     Visualization    

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Stiffness analysis and experimental validation of robotic systems

Giuseppe CARBONE

Frontiers of Mechanical Engineering 2011, Volume 6, Issue 2,   Pages 182-196 doi: 10.1007/s11465-011-0221-3

Abstract: Therefore, this paper proposes procedures for carrying out both numerical and experimental estimationsThen, an experimental procedure for the evaluation stiffness performance is proposed as based on a newsoundness and engineering feasibility of both the proposed numerical formulation for stiffness analysis and experimental

Keywords： robotics     stiffness performance     numerical and experimental estimations    

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Spatial prediction of soil contamination based on machine learning: a review

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1

Abstract:

● A review of machine learning (ML) for spatial prediction of soil

Keywords： Soil contamination     Machine learning     Prediction     Spatial distribution    

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Numerical simulation and experimental research on the wheel brush sampling process of an asteroid sampler

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0732-0

Abstract: contact dynamics model between particles and sampling wheel brushes is established and a simulation and experimental

Keywords： asteroid sampling     wheel brush sampler     discrete element method     parameter calibration     experimental    

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Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 11, doi: 10.1007/s11783-023-1738-5

Abstract:

● A novel integrated machine learning method to analyze O3

Keywords： Ozone     Integrated method     Machine learning    

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Numerical and experimental analyses of methane leakage in shield tunnel

Frontiers of Structural and Civil Engineering   Pages 1011-1020 doi: 10.1007/s11709-023-0956-z

Abstract: Based on the numerical and experimental analysis results, a relationship between the safety level and

Keywords： shield tunnel     harmful gas leakage     numerical analysis     laboratory test    

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Machine learning in building energy management: A critical review and future directions

Frontiers of Engineering Management 2022, Volume 9, Issue 2,   Pages 239-256 doi: 10.1007/s42524-021-0181-1

Abstract: Over the past two decades, machine learning (ML) has elicited increasing attention in building energy

Keywords： building energy management     machine learning     integrated framework     knowledge evolution    

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Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2,   Pages 183-197 doi: 10.1007/s11705-021-2073-7

Abstract: exploration of the design variable space for such scenarios, an adaptive sampling technique based on machine learning

Keywords： machine learning     flowsheet simulations     constraints     exploration    

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An experimental characterization of human torso motion

Daniele CAFOLLA,I-Ming CHEN,Marco CECCARELLI

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 4,   Pages 311-325 doi: 10.1007/s11465-015-0352-z

Abstract:

The torso plays an important role in the human-like operation of humanoids. In this paper, a method is proposed to analyze the behavior of the human torso by using inertial and magnetic sensing tools. Experiments are conducted to characterize the motion performance of the human torso during daily routine operations. Furthermore, the forces acting on the human body during these operations are evaluated to design and validate the performance of a humanoid robot.

Keywords： experimental biomechanics     human torso     analysis     inertial sensor     characterization    

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Joint slip investigation based on finite element modelling verified by experimental results on wind turbine

Saleh YAGHOOBI, Ahmad SHOOSHTARI

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 3,   Pages 341-351 doi: 10.1007/s11709-017-0393-y

Abstract: joints are modelled and studied in the finite element program, and the results are verified by the experimental

Keywords： Joint slip     cyclic loading     Finite element modelling     Experimental joint behavior     damping ratios (   

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Machine learning for fault diagnosis of high-speed train traction systems: A review

Frontiers of Engineering Management doi: 10.1007/s42524-023-0256-2

Abstract: In recent years, machine learning has been widely used in various pattern recognition tasks and has demonstratedMachine learning has made considerably advancements in traction system fault diagnosis; however, a comprehensiveThis paper primarily aims to review the research and application of machine learning in the field ofThen, the research and application of machine learning in traction system fault diagnosis are comprehensivelydiagnosis under actual operating conditions are revealed, and the future research trends of machine learning

Keywords： high-speed train     traction systems     machine learning     fault diagnosis    

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

Frontiers of Structural and Civil Engineering   Pages 994-1010 doi: 10.1007/s11709-023-0942-5

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

Keywords： dynamic prediction     moving trajectory     pipe jacking     GRU     deep learning    

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Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature

Frontiers of Medicine 2023, Volume 17, Issue 4,   Pages 768-780 doi: 10.1007/s11684-023-0982-1

Abstract: illustrating the relationship between the phenotype and genotype of each HCM subtype by using machine learningMachine learning modeling based on personal whole-exome data identified 46 genes with mutation burden

Keywords： machine learning methods     hypertrophic cardiomyopathy     genetic risk    

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Title Author Date Type Operation

A Hierarchical Model of the Creativity Support System Based on Experimental Learning

Feng Qinchao,Jiang Xiaogan,Sun Jin

Journal Article

Interactive visual labelling versus active learning: an experimental comparison

Mohammad CHEGIN, Jürgen BERNARD, Jian CUI, Fatemeh CHEGINI, Alexei SOURIN, Keith Keith, Tobias SCHRECK

Journal Article

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal

Journal Article

Stiffness analysis and experimental validation of robotic systems

Giuseppe CARBONE

Journal Article

Spatial prediction of soil contamination based on machine learning: a review

Journal Article

Numerical simulation and experimental research on the wheel brush sampling process of an asteroid sampler

Journal Article

Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method

Journal Article

Numerical and experimental analyses of methane leakage in shield tunnel

Journal Article

Machine learning in building energy management: A critical review and future directions

Journal Article

Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet

Journal Article

An experimental characterization of human torso motion

Daniele CAFOLLA,I-Ming CHEN,Marco CECCARELLI

Journal Article

Joint slip investigation based on finite element modelling verified by experimental results on wind turbine

Saleh YAGHOOBI, Ahmad SHOOSHTARI

Journal Article

Machine learning for fault diagnosis of high-speed train traction systems: A review

Journal Article

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

Journal Article

Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature

Journal Article