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Innovation self, Technology Learning and Elevation of Industry Competence — Case of Taiwan IC Industry

Lu Rui,Sheng Zhaohan

Strategic Study of CAE 2007, Volume 9, Issue 8,   Pages 35-39

Abstract: style="text-align: justify;">Following Taiwan IC industry development,  the paper analyzes its technologyinnovation and its elevation of industry competence by technology learning and innovation-self.

Keywords： technology learning     innovation-self     industry competence     IC industry    

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Ethical Principles and Governance Technology Development of AI in China Review

Wenjun Wu, Tiejun Huang, Ke Gong

Engineering 2020, Volume 6, Issue 3,   Pages 302-309 doi: 10.1016/j.eng.2019.12.015

Abstract:

Ethics and governance are vital to the healthy and sustainable development of artificial intelligence (AI). With the long-term goal of keeping AI beneficial to human society, governments, research organizations, and companies in China have published ethical guidelines and principles for AI, and have launched projects to develop AI governance technologies. This paper presents a survey of these efforts and highlights the preliminary outcomes in China. It also describes the major research challenges in AI governance research and discusses future research directions.

Keywords： AI ethical principles     AI governance technology     Machine learning     Privacy     Safety     Fairness    

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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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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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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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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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Learning from Academician Qian Xuesen

Song Jian

Strategic Study of CAE 2001, Volume 3, Issue 12,   Pages 1-7

Abstract: acute;s life and reviews his outstanding contributions to the development of China´s science and technologyyear ago Qian had made a penetrating exposition on the dialectical relationship between science and technology

Keywords： Qian Xuesen     Marxist philosophy     science and technology     engineering cybernetics     systems science     complex    

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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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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: CNN (ACNN) for fault diagnosis, which can automatically tune its three key hyper parameters, namely, learningFirst, a new deep reinforcement learning (DRL) is developed, and it constructs an agent aiming at controllingACNN 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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Automated synthesis of steady-state continuous processes using reinforcement learning

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2,   Pages 288-302 doi: 10.1007/s11705-021-2055-9

Abstract: The present work demonstrates how reinforcement learning can be used for automated flowsheet synthesis

Keywords： automated process synthesis     flowsheet synthesis     artificial intelligence     machine learning     reinforcementlearning    

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State-of-the-art applications of machine learning in the life cycle of solid waste management

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 4, doi: 10.1007/s11783-023-1644-x

Abstract:

● State-of-the-art applications of machine learning (ML) in solid waste

Keywords： Machine learning (ML)     Solid waste (SW)     Bibliometrics     SW management     Energy utilization     Life cycle    

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Communicative Learning: A Unified Learning Formalism Review

Luyao Yuan, Song-Chun Zhu

Engineering 2023, Volume 25, Issue 6,   Pages 77-100 doi: 10.1016/j.eng.2022.10.017

Abstract: learning paradigms, such as passive learning, active learning, algorithmic teaching, and so forth, andfacilitates the development of new learning methods., which endows CL with human-comparable learning efficiency.Finally, we present our contribution to the foundations of learning by putting forth hierarchies in learningand defining the halting problem of learning.

Keywords： Artificial intelligencehine     Cooperative communication     Machine learning     Pedagogy     Theory of mind    

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Title Author Date Type Operation

Innovation self, Technology Learning and Elevation of Industry Competence — Case of Taiwan IC Industry

Lu Rui,Sheng Zhaohan

Journal Article

Ethical Principles and Governance Technology Development of AI in China

Wenjun Wu, Tiejun Huang, Ke Gong

Journal Article

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

Journal Article

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

Journal Article

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

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

Learning from Academician Qian Xuesen

Song Jian

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

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

Journal Article

Automated synthesis of steady-state continuous processes using reinforcement learning

Journal Article

State-of-the-art applications of machine learning in the life cycle of solid waste management

Journal Article

Communicative Learning: A Unified Learning Formalism

Luyao Yuan, Song-Chun Zhu

Journal Article