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Progress in Machine Translation Review

Haifeng Wang,Hua Wu,Zhongjun He,Liang Huang,Kenneth Ward Church

Engineering 2022, Volume 18, Issue 11,   Pages 143-153 doi: 10.1016/j.eng.2021.03.023

Abstract:

After more than 70 years of evolution, great achievements have been made in machine translation.machine translation (NMT).In this article, we first review the history of machine translation from rule-based machine translationto example-based machine translation and statistical machine translation.We then describe various products and applications of machine translation.

Keywords： Machine translation     Neural machine translation     Simultaneous translation    

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Incorporating target language semantic roles into a string-to-tree translation model Article

Chao SU, Yu-hang GUO, He-yan HUANG, Shu-min SHI, Chong FENG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1534-1542 doi: 10.1631/FITEE.1601349

Abstract: The string-to-tree model is one of the most successful syntax-based statistical machine translation (paper, we propose two methods to use semantic roles to improve the performance of the string-to-tree translationWe then perform string-to-tree machine translation using the newly generated trees.Our methods enable the system to train and choose better translation rules using semantic informationOur experiments showed significant improvements over the state-of-the-art string-to-tree translation

Keywords： Machine translation     Semantic role     Syntax tree     String-to-tree    

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Challenges of human–machine collaboration in risky decision-making

Frontiers of Engineering Management 2022, Volume 9, Issue 1,   Pages 89-103 doi: 10.1007/s42524-021-0182-0

Abstract: The purpose of this paper is to delineate the research challenges of human–machine collaboration in riskyTechnological advances in machine intelligence have enabled a growing number of applications in human–machineTherefore, it is desirable to achieve superior performance by fully leveraging human and machine capabilitiesAfterward, we review the literature on human–machine collaboration in a general decision context, fromthe perspectives of human–machine organization, relationship, and collaboration.

Keywords： human–machine collaboration     risky decision-making     human–machine team and interaction     task allocation     human–machine relationship    

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Evaluation and prediction of slope stability using machine learning approaches

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 4,   Pages 821-833 doi: 10.1007/s11709-021-0742-8

Abstract: In this paper, the machine learning (ML) model is built for slope stability evaluation and meets the

Keywords： slope stability     factor of safety     regression     machine learning     repeated cross-validation    

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Research and application of visual location technology for solder paste printing based on machine vision

Luosi WEI, Zongxia JIAO

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 2,   Pages 184-191 doi: 10.1007/s11465-009-0034-9

Abstract: Using machine vision technology to complete the location mission is new and very efficient.This paper presents an integrated visual location system for solder paste printing based on machine vision

Keywords： machine vision     visual location     solder paste printing     VisionPro    

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Big data and machine learning: A roadmap towards smart plants

Frontiers of Engineering Management   Pages 623-639 doi: 10.1007/s42524-022-0218-0

Abstract: advanced data processing, storage and analysis, advanced process control, artificial intelligence and machineExploitation of the information contained in these data requires the use of advanced machine learning

Keywords： big data     machine learning     artificial intelligence     smart sensor     cyber–physical system     Industry 4.0    

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A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 3, doi: 10.1007/s11783-021-1472-9

Abstract:

• A spectral machine learning approach is proposed for predicting mixed

Keywords： Antibiotic contamination     Spectral detection     Machine learning    

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Coupling evaluation for material removal and thermal control on precision milling machine tools

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 1,   Pages 12-12 doi: 10.1007/s11465-021-0668-9

Abstract: Machine tools are one of the most representative machining systems in manufacturing.The energy consumption of machine tools has been a research hotspot and frontier for green low-carbonExperimental study indicates that TC is the main energy-consuming process of the precision milling machineIt can provide a foundation for energy-efficient, high-precision machining of machine tools.

Keywords： machine tools     cutting energy efficiency     thermal stability     machining accuracy     coupling evaluation    

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Energy saving design of the machining unit of hobbing machine tool with integrated optimization

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0694-2

Abstract: The machining unit of hobbing machine tool accounts for a large portion of the energy consumption during

Keywords： energy saving design     energy consumption     machining unit     integrated optimization     machine tool    

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Assessing compressive strengths of mortar and concrete from digital images by machine learning techniques

Frontiers of Structural and Civil Engineering   Pages 347-358 doi: 10.1007/s11709-022-0819-z

Abstract: In the present study, a new image-based machine learning method is used to predict concrete compressiveThese include support-vector machine model and various deep convolutional neural network models, namelyThe images and corresponding compressive strength were then used to train machine learning models toOverall, the present findings validated the use of machine learning models as an efficient means of estimating

Keywords： support vector machine     deep convolutional neural network     microscope     digital image     curing period    

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Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 1,   Pages 72-82 doi: 10.1007/s11709-013-0185-y

Abstract: A support vector machine (SVM) model has been developed for the prediction of liquefaction susceptibilityThe SVM, a novel learning machine based on statistical theory, uses structural risk minimization (SRM

Keywords： earthquake     cone penetration test     liquefaction     support vector machine (SVM)     prediction    

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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

Keywords： machine learning     flowsheet simulations     constraints     exploration    

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Assessment of different machine learning techniques in predicting the compressive strength of self-compacting

Frontiers of Structural and Civil Engineering   Pages 928-945 doi: 10.1007/s11709-022-0837-x

Abstract: compressive strength of SCC (CS of SCC) can be successfully predicted from mix design and curing age by a machineNine ML techniques, such as Linear regression (LR), K-Nearest Neighbors (KNN), Support Vector Machine

Keywords： compressive strength     self-compacting concrete     machine learning techniques     particle swarm optimization    

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Development of machine learning multi-city model for municipal solid waste generation prediction

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 9, doi: 10.1007/s11783-022-1551-6

Abstract:

● A database of municipal solid waste (MSW) generation in China was established.

Keywords： Municipal solid waste     Machine learning     Multi-cities     Gradient boost regression tree    

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A novel six-legged walking machine tool for

Jimu LIU, Yuan TIAN, Feng GAO

Frontiers of Mechanical Engineering 2020, Volume 15, Issue 3,   Pages 351-364 doi: 10.1007/s11465-020-0594-2

Abstract: maintenance of large parts in ships, trains, aircrafts, and so on create an increasing demand for mobile machineThis study proposes a novel six-legged walking machine tool consisting of a legged mobile robot and aportable parallel kinematic machine tool.advantage of the large workspace of the legged mobile platform and the high precision of the parallel machineFinally, an application scenario is shown in which the walking machine tool steps successfully over a

Keywords： legged robot     parallel mechanism     mobile machine tool     in-situ machining    

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Title Author Date Type Operation

Progress in Machine Translation

Haifeng Wang,Hua Wu,Zhongjun He,Liang Huang,Kenneth Ward Church

Journal Article

Incorporating target language semantic roles into a string-to-tree translation model

Chao SU, Yu-hang GUO, He-yan HUANG, Shu-min SHI, Chong FENG

Journal Article

Challenges of human–machine collaboration in risky decision-making

Journal Article

Evaluation and prediction of slope stability using machine learning approaches

Journal Article

Research and application of visual location technology for solder paste printing based on machine vision

Luosi WEI, Zongxia JIAO

Journal Article

Big data and machine learning: A roadmap towards smart plants

Journal Article

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

Journal Article

Coupling evaluation for material removal and thermal control on precision milling machine tools

Journal Article

Energy saving design of the machining unit of hobbing machine tool with integrated optimization

Journal Article

Assessing compressive strengths of mortar and concrete from digital images by machine learning techniques

Journal Article

Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

Journal Article

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

Journal Article

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting

Journal Article

Development of machine learning multi-city model for municipal solid waste generation prediction

Journal Article

A novel six-legged walking machine tool for

Jimu LIU, Yuan TIAN, Feng GAO

Journal Article