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Examines the active aspect of retrieval in several kinds of storage structures in natural and computational systems. In particular, investigates self‐adjusting data structures and self‐organization of memory structures. Also examines related issues, including the relationship between active retrieval and learning.

Examines the relationship between systems and their users from the knowledge discovery perspective. Recently knowledge discovery in databases has made important progress, but it may also bring some potential problems to database design, such as issues related to database security, as an unauthorized user may derive highly sensitive knowledge from unclassified data. There is a need for a comprehensive study on knowledge discovery in human‐computer symbiosis. Borrowing terms from algorithm design and artificial intelligence literature, proposes a notion called database‐user adversarial partnership. This notion is general enough to cover various knowledge discovery and security issues related to databases and their users. Furthermore, the notion of database‐user adversarial partnership can be further generalized into system‐user adversarial partnership. Opportunities provided by knowledge discovery techniques and potential social implications are discussed and illustrated by examples.

The purpose of this paper is to establish a new evaluation system to assess the degree of integration between industry and the internet. And use the gray correlation matrix method to evaluate the “internet + industry” integration degree of China’s provinces.

This paper establishes a new evaluation system to assess the degree of integration between industry and the internet using the matrix gray relational analysis method.

The main indexes and its rankings of the provinces’ integration degree and the rankings of the provinces’ integration degree are obtained.

The ranking of the degree of integration of various provinces in the country has certain guiding significance in promoting the development of “internet +” and “industry 4.0.”

Establishing a new model for the quantitative assessment of the degree of fusion, this method has a positive impact on the quantitative assessment of “internet + industrial” integration.

The purpose of this paper is to propose a new method based on nonlinear least squares (NLS) for solving the parameters of nonlinear grey Bernoulli model (NGBM(1,1)) and to verify the proposed model using the case of employee demand prediction of high-tech enterprises in China.

First of all, minimising the square sum of fitting error of grey differential equation of NGBM(1,1) is taken as the optimisation target and the parameters of classic grey model (GM(1,1)) are set as the initial value of parameter vector. Afterwards, the structural parameters and power exponents are solved by using the Gauss-Newton iteration algorithm so as to calculate the parameters of NGBM(1,1) under given rules for ceasing the algorithm. Finally, by taking the employee demand of high-tech enterprises in the state-level high-tech industrial development zone in China as examples, the validity of the new method is verified.

The results show that the parameter estimation algorithm based on the NLS method can effectively identify the power exponents of NGBM(1,1) and therefore can favourably adapt to the nonlinear fluctuations of sequences. In addition, the algorithm is superior to the GM(1,1) model, grey Verhulst model, and Quadratic-Exponential smoothing algorithm in terms of the simulation and prediction accuracy.

Under the framework of solving parameters based on NLS, various aspects of NGBM(1,1) remain to be further investigated including background value, initial condition and variable structural modelling methods.

The parameter estimation algorithm based on NLS can effectively identify the power exponent of NGBM(1,1) and therefore it can favourably adapt to the nonlinear fluctuation of sequences.

According to the basic principle of NLS, a new method for solving the parameters of NGBM(1,1) is proposed by using the Gauss-Newton iteration algorithm. Moreover, by conducting the modelling case about employees demand in high-tech enterprises in China, the effectiveness and superiority of the new method are verified.

Although the Nash nonlinear grey Bernoulli model (NNGBM(1, 1)) is incomparable with respect to its flexibility over traditional grey models, errors are still inevitable in forecasting. The purpose of this paper is to propose a Fourier residual modified Nash nonlinear grey Bernoulli model (FNNGBM(1, 1)) and use it to forecast the nonlinear time series of the international trade of Chinese high-tech products.

A Fourier series is used to modify the forecasting residual of the NNGBM(1, 1) model, so as to improve its forecasting ability. The parameters optimization of FNNGBM(1, 1) is formulated as a combinatorial optimization problem and is solved collectively using the concept of Nash equilibrium.

The simulation and practical application to fluctuation data both prove that FNNGBM(1, 1) could offer a more precise forecast than NNGBM(1, 1) and the Fourier residual GM(1, 1) (FGM(1, 1)). The import/export data of Chinese high-tech products will maintain rapid growth, with corresponding trade balance enlargement; however, there will be a concomitant decrease in the trade specialization coefficient.

This study is deliberately general in its scope and outlook: its focus is mainly on the overall condition of Chinese high-tech products trade. Future research is recommended to analyze specific industrial trade sectors and extraneous influencing factors.

An effective method is proposed to enhance the accuracy of NNGBM(1, 1) model in forecasting a small sample, nonlinear time series.

In recent years, continuous expansion of the scale of the new energy export industry in China caused a boycott of American and European countries. Export injury early warning research is an urgent task to develop the new energy industry in China. The purpose of this paper is to build an indicator system of exports injury early warning of the new energy industry in China and corresponding quantitative early warning models.

In consideration of the actual condition of the new energy industry in China, this paper establishes an indicator system according to four aspects: export price, export quantity, impact on domestic industry and impact on macro economy. Based on the actual data of new energy industry and its five sub-industries (solar, wind, nuclear power, smart grid and biomass) in China from 2003 to 2013, GM (1,1) model is used to predict early warning index values for 2014-2018. Then, the principal component analysis (PCA) is used to obtain the comprehensive early warning index values for 2003-2018. The 3-sigma principle is used to divide the early warning intervals according to the comprehensive early warning index values for 2003-2018 and their standard deviation. Finally, this paper determines alarm degrees for 2003-2018.

Overall export condition of the new energy industry in China is a process from cold to normal in 2003-2013, and the forecast result shows that it will be normal from 2014 to 2018. The export condition of the solar energy industry experienced a warming process, tended to be normal, and the forecast result shows that it will also be normal in 2014-2018. The biomass and other new energy industries and nuclear power industry show a similar development process. Export condition of the wind energy industry is relatively unstable, and it will be partially hot in 2014-2018, according to the forecast result. As for the smart grid industry, the overall export condition of it is normal, but it is also unstable, in few years it will be partially hot or partially cold. The forecast result shows that in 2014-2018, it will maintain the normal state. In general, there is a rapid progress in the export competitiveness of the new energy industry in China in the recent decade.

Export injury early warning research of the new energy industry can help new energy companies to take appropriate measures to reduce trade losses in advance. It can also help the relevant government departments to adjust industrial policies and optimize the new energy industry structure.

This paper constructs an index system that can measure the alarm degrees of the new energy industry. By combining the GM (1,1) model and the PCA method, the problem of warning condition detection under small sample data sets is solved.

The purpose of this paper is to investigate the relationship between corporate governance and earnings opacity in China.

Two corporate governance mechanisms form the basis of the analysis: 1) the board of directors and 2) the external audit function. OLS regression analysis is employed on a large sample from 2000 to 2014 with 20,235 firm-year observations.

Corporate governance is found to be associated with reduced levels of earnings opacity for Chinese listed companies. Furthermore, the association between corporate governance and reduced levels of earnings opacity strengthened after the implementation of various key reforms.

Chinese regulators are advised to proceed with caution as not all Western approaches to corporate governance are transferrable to the Chinese setting.

This study contributes to the literature by analyzing broad latent constructs of corporate governance in addition to individual observable dimensions in order to reveal that various key reforms have been successful in strengthening the link between governance and reporting quality for Chinese listed companies.

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework of grey system theory.

The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of grey model GM(1,1), such as even GM, original difference GM, even difference GM, discrete GM and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three-dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well.

The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper.

A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate.

The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section.

This paper aims to explore the relationship between ethical self-fashioning and citizenship practices in the ongoing revival of “Chinese Traditional Culture” pursued in tandem by the party-state and by private actors in present-day China.

Adopting an anthropological approach, the author draws from three sets of resources: (1) research literature on China’s political history and key texts of early Chinese thought, (2) contemporary state discourses on citizen formation, and (3) participant observation notes and interviews with organizers and followers of the Wu-Wei School (a pseudonym). The author conducts a textual analysis of primary and secondary literature and a critical discourse analysis of the ethnographic data and examines emerging themes.

Firstly, the author identifies a crucial dimension in the historical and cultural roots of Chinese citizenship practices: an enduring conception that binds individual ethical self-improvement with socio-political flourishing. Secondly, examining contemporary state discourses on “citizen quality” and “reviving China’s outstanding traditional culture”, the author showcases how party-state authorities call on individuals to self-reform for national rejuvenation. Thirdly, the author investigates how members of the Wu-Wei School construe their individual pursuits of ethical self-improvement as significant for societal progress.

Based on these findings, the author demonstrates the ways in which autochthonous conceptions of Chinese citizenship give a central place to private acts of self-fashioning. The author argues that the entanglement between individual ethics and citizenship practices constitutes a crucial but largely understudied dimension of Chinese citizenship.