Inclusive and sustainable industrial development in China: An efficiency-based analysis for current status and improving potentials

Yuan, Qianqian; Cheng, Charles Fang Chin; Wang, Jiayu; Zhu, Tiantian; Wang, Ke

doi:10.1016/j.apenergy.2020.114876

Cited by 22 publications

(8 citation statements)

References 55 publications

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Section: Literature Reviewmentioning

confidence: 99%

“…The results suggested that to improve industrial competitiveness, industries should adopt more sustainable practices. Yuan et al(24) evaluated the inclusive and sustainable industrial development for 30 provinces in China, the data covers the period from 2011 to 2016. They found that Beijing and Tianjin are the benchmark provinces for promoting inclusive and sustainable industrial development.Liu et al (25) compared the sustainable development of industrial park between China and Canada and the authors found that industrial parks in Canada appear to be moving more slowly in their adoption of sustainable development.…”

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confidence: 99%

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Global Industrial Development: Insights From the Distribution Dynamics Approach for the Post Covid Era

Ma¹,

Shum

Han³

et al. 2021

Front. Public Health

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The spread of COVID-19 has significantly dampened global economic activity and has also wreaked havoc on the industrial sector. Understanding the disparity and convergence of global industrial outputs is important in assessing the effectiveness of concurrent development policies. This study investigates the spatial distribution of global industrial output to unveil the disparity in industrial development and the feasibility of achieving convergence over time. Stochastic kernel analyses are carried out for national regimes to study the overall pattern of industrialization for all the countries in the world. Countries are then classified into different groups to further analyse the geographical and income effects on industrial development. The results show that disparity between the Global North and the Global South will enlarge further in the future. Industrial development in the Global North will continue to prosper, while the industrial output in many countries in the Global South just cannot reach the global average.

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Section: Literature Reviewmentioning

confidence: 99%

mentioning

confidence: 99%

Global Industrial Development: Insights From the Distribution Dynamics Approach for the Post Covid Era

Ma¹,

Shum

Han³

et al. 2021

Front. Public Health

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“…Driven by this situation, China and the world urgently need a large number of artificial intelligence projects to be applied in the industrial field. Among them, deep learning is the core of artificial intelligence, and it is the mainstream technology that enables artificial intelligence to achieve prosperity from concept to prosperity [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Defect Detection of Mechanical Design Products Using Deep Neural Network

Jan

2022

Preprint

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In industrial production, defect detection is one of the key methods to control the quality of mechanical design products. Although defect detection algorithms based on traditional machine learning can greatly improve detection efficiency, manual feature extraction is required and the design process is complicated. With the rapid development of CNN, major breakthroughs have been made in computer vision. Therefore, building a surface defect detection algorithm for mechanical design products based on DCNNs plays a very important role in improving industrial production efficiency. This paper studies the surface defect detection algorithm of mechanical products based on deep convolutional neural network, focusing on solving two types of problems: defect recognition and defect segmentation. Aiming at the problem of defect recognition, this paper studies a defect recognition algorithm based on fully convolutional block detection. This algorithm introduces the idea of block detection into the ResNet fully convolutional neural network. While realizing the local discrimination mechanism, it overcomes the shortcomings of the traditional block detection receptive field. Compared with the original ResNet image classification algorithm, this algorithm has stronger generalization ability and detection ability of small defects. Aiming at the problem of defect segmentation, this paper studies a defect segmentation algorithm based on improved Deeplabv3+.

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“…The specific characteristics of different geographical regions based on the routes followed for economic development constitute considerable prerequisites for the sustainable economic growth [1,2]. This allows countries within a region or regions to focus independently on supporting specific types of investment that give their economies a competitive advantage.…”

Section: Introductionmentioning

confidence: 99%

Smart specialization and sustainable regional growth

Akberdina

2021

E3S Web Conf.

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Recent transition to the sustainable economy distinguished by the specialization and digitalization market the pathways for the regional development. This process is considerably helped by the profound social and political transformative potential which is subjected to social innovations and smart potential. This paper shows how the social innovations and smart specialization might influence the sustainable growth of countries and regions with a special focus on building an efficient economic, social and institutional environment for the benefits of all agents on the market. In addition, it argues that smart specialization might also contribute to the competitiveness and well-balanced sustainable development of regions and territories.

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Inclusive and sustainable industrial development in China: An efficiency-based analysis for current status and improving potentials

Cited by 22 publications

References 55 publications

Global Industrial Development: Insights From the Distribution Dynamics Approach for the Post Covid Era

Global Industrial Development: Insights From the Distribution Dynamics Approach for the Post Covid Era

Defect Detection of Mechanical Design Products Using Deep Neural Network

Smart specialization and sustainable regional growth

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