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Unsupervised domain adaptation object detection not only mitigates model terrible performance resulting from domain gap, but also has the ability to apply knowledge trained on a definite domain to a distinct domain. However, aligning the whole feature may confuse the object and background information, making it challenging to extract discriminative features. This paper aims to propose an improved approach which is called intrinsic feature extraction domain adaptation (IFEDA) to extract discriminative features effectively.

IFEDA consists of the intrinsic feature extraction (IFE) module and object consistency constraint (OCC). The IFE module, designed on the instance level, mainly solves the issue of the difficult extraction of discriminative object features. Specifically, the discriminative region of the objects can be paid more attention to. Meanwhile, the OCC is deployed to determine whether category prediction in the target domain brings into correspondence with it in the source domain.

Experimental results demonstrate the validity of our approach and achieve good outcomes on challenging data sets.

Limitations to this research are that only one target domain is applied, and it may change the ability of model generalization when the problem of insufficient data sets or unseen domain appeared.

This paper solves the issue of critical information defects by tackling the difficulty of extracting discriminative features. And the categories in both domains are compelled to be consistent for better object detection.

Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030, this paper aims to establish a cross-validation-based linear model selection system, which can consider many factors to avoid missing useful information and select the best model according to estimated out-of-sample forecast performances.

With the nine identified influencing factors of electricity demand, this system first determines the parameters in four alternative fitting procedures, where for each procedure a lot of cross-validation is performed and the most frequently selected value is determined. Then, through comparing the out-of-sample performances of the traditional multiple linear regression and the four selected alternative fitting procedures, the best model is selected in view of forecast accuracy and stability and used for forecasting under four scenarios. Besides the baseline scenario, this paper investigates lower and higher economic growth and higher consumption share.

The results show the following: China will consume 7,120.49 TWh, 9,080.38 TWh and 11,649.73 TWh of electricity in 2020, 2025 and 2030, respectively; there is hardly any possibility of decoupling between economic development level and electricity demand; and shifting China from an investment-driven economy to a consumption-driven economy is greatly beneficial to save electricity.

Following insights are obtained: reasonable infrastructure construction plans should be made for increasing electricity demand; increasing electricity demand further challenges China’s greenhouse gas reduction target; and the fact of increasing electricity demand should be taken into account for China’s prompting electrification policies.

This study aims to build an indigenous Chinese management model based on Chinese culture.

This study adopts new institutionalism as its theoretical foundation, examines the core values of Chinese civilization in retrospect and identifies the key features of a Chinese management model. In this study, the authors develop a “glacier model” and test its reliability with the Haier Group.

This study proposes a new definition for a management model: a knowledge system based on institutional civilization that reflects management theory and practice. It analyzes the institutional environment of Chinese civilization: the recessive bottom-most layers are CBTLG (Confucianism, Taoism, Buddhism, legalism and Guan theory) and MDSX (Mao Zedong thought, Deng Xiaoping theory, scientific thoughts of development and Xi Jinping thought), the dominant principles are “Socialism and Mixed Economy” and the core values of Chinese culture compose the layer between them. This study concludes that the distinguishing features of Chinese management are harmonious management, the order-diversity pattern and Tai Chi management.

This paper only discussed the management model of China. Based on the conclusions of this paper, in the future, researchers comparative studies on Chinese management and other countries’ management models with glacier model. By so doing, people can have a more comprehensive understanding of management models of different cultures.

The management characteristics contained in Chinese culture can provide more abundant knowledge for understanding current organizational management issues. A better understanding of the characteristics of a Chinese management model based on Chinese civilization is conducive to foreign investment or cross-cultural cooperation between Chinese and foreign enterprises.

This study provides a new perspective in studying Chinese management. The theoretical values of the glacier model are as follows: it is rooted in a Chinese management context; it makes up for the insufficiency in the current study of institutionalism; and it guides cross-cultural communication and management. The authors hope that the study attracts the attention of more scholars. Any civilization of any region or country can construct its own management model using the frame of the glacier model.