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The purpose of this study is to achieve multi-variety and small-batch assembly through direct cooperation between equipment and people and to improve assembly efficiency as well as flexibility.

Firstly, the concept of the human–computer interaction is designed. Secondly, the machine vision technology is studied theoretically. Skin color filter based on hue, saturation and value color model is put forward to screen out images that meet the skin color characteristics of the worker, and a multi-Gaussian weighted model is built to separate moving objects from its background. Both of them are combined to obtain the final images of the target objects. Then, the key technology is applied to the smart assembly workbench. Finally, experiments are conducted to evaluate the role of the human–computer interaction features in improving productivity for the smart assembly workbench.

The result shows that multi-variety and small-batch considerable increases assembly time and the developed human–computer interaction features, including prompting and introduction, effectively decrease assembly time.

This study proves that the machine vision technology studied in this paper can effectively eliminate the interferences of the environment to obtain the target image. By adopting the human–computer interaction features, including prompting and introduction, the efficiency of manual operation is improved greatly, especially for multi-variety and small-batch assembly.

The purpose of this paper is to propose a new video prediction-based methodology to solve the manufactural occlusion problem, which causes the loss of input images and uncertain controller parameters for the robot visual servo control.

This paper has put forward a method that can simultaneously generate images and controller parameter increments. Then, this paper also introduced target segmentation and designed a new comprehensive loss. Finally, this paper combines offline training to generate images and online training to generate controller parameter increments.

The data set experiments to prove that this method is better than the other four methods, and it can better restore the occluded situation of the human body in six manufactural scenarios. The simulation experiment proves that it can simultaneously generate image and controller parameter variations to improve the position accuracy of tracking under occlusions in manufacture.

The proposed method can effectively solve the occlusion problem in visual servo control.

We address the question of how the Internet promotes international trade volume, and especially, whether the global human resources affect the bilateral international trade during the technology development across countries.

A dynamic panel causality analysis is carried out to demonstrate empirically that the causality of the Internet diffusion on the international trade volumes. Evidence shows a significant positive effect of the Internet on international trade volume from time-series and cross-sectional regressions. Furthermore, the magnitude of elasticity is discussed.

There is strong evidence that the Internet stimulates international trade for all countries. Growth of trade volumes changes over time with heteroscedastic responses. The positive impacts of the growth of GDP are diluted by the growth of global human resources.

The data on the number of web hosts is not necessarily correlated to where the site is actually located. We contribute to the new Internet measurement which helps to explain the information transferring that stimulates the international trade and examine the global human resources.