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The purpose of this paper is to propose a new fuel-balanced formation keeping reference trajectories planning method based on selecting the virtual reference center(VRC) in a fuel-balanced sense in terms of relative eccentricity and inclination vectors (E/I vectors).

By using the geometrical intuitive relative E/I vectors theory, the fuel-balanced VRC selection problem is reformulated as the geometrical problem to find the optimal point to equalize the distances between the VRC and the points determined by the relative E/I vectors of satellites in relative E/I vectors plane, which is solved by nonlinear programming method.

Numerical simulations demonstrate that the new proposed fuel-balanced formation keeping strategy is valid, and the new method achieves better fuel-balanced performance than the traditional method, which keeps formation with respect to geometrical formation center.

The new fuel-balanced formation keeping reference trajectories planning method is valid for formation flying mission whose member satellite is in circular or near circular orbit in J2 perturbed orbit environment.

The new fuel-balanced formation keeping reference trajectories planning method can be used to solve formation flying keeping problem, which involves multiple satellites in the formation.

The fuel-balanced reference trajectories planning problem is reformulated as a geometrical problem, which can provide insightful way to understand the dynamic nature of the fuel-balanced reference trajectories planning issue.

The purpose of this paper is to explore financial quality problems, based on the dynamics of the ownership structure, in the privatization process to clarify the internal relation among the ownership’s attribution of the commercial mixed ownership company, the company’s performance and its financial relationships. This paper also examines the mixed ownership enterprise’s potential problems during the development process.

Adopting the single case study method, the authors selected the mixed ownership public company Hubei Sanxia New Building Materials Co., Ltd. (stock code: 600293) to explore, from a privatization perspective, the impact of mixed ownership on financial quality.

The study found that Sanxia experienced tight cash flow and heavy debt burdens due to the privatization and that its controlling shareholders used non-operating income to support Sanxia, thus characterizing the dual role of “the grabbing hand” and “the helping hand.” Sanxia’s privatization process highlighted the volatility of performance, the exception of monetary funds and the existence of accounting fraud rather than the prosperous development of the capital combination.

These findings provided case support that privatization negatively affects the financial quality of the company. Previous studies have indicated that there should be greater focus more on the issue that state-owned shares rebound during the process of privatization and that, with respect to commercial mixed ownership reform of state-owned enterprises, such reform must avoid the passive transfer of corporate control, ensure the fairness of the related transactions, prevent the loss of state-owned assets and preclude the controlling shareholders from seizing interests of listed companies.

The lifetime of flip chip solder joints can be greatly increased by applying underfill encapsulation. This paper presents a case study where the thermal cycle lifetime was increased by more than 20 times, that is from ∼100 cycles to more than 2,000 cycles for a chip size of 5.6mm × 6.3mm. By combining electrical, acoustic and metallographic investigation, the degradation of the solder joints was monitored, some important factors relevant to solder joint reliability were analysed and discussed. Delamination was found not to be the dominant failure mode.

The purpose of this paper is to investigate the diffusion patterns of knowledge in inspiring technological innovations and to enable monitoring development trends of technological innovations based on patent data analysis, thus, to manage knowledge wisely to innovate.

The notion of knowledge innovation potential (KIP) is proposed to measure the innovativeness of knowledge by the cumulative number of patents originated from its inspiration. KIP calculating formula is regressed in forms of two specific diffusion models by conducting a series of empirical studies with the patent-based indicators involving forward and backward citation numbers to reveal knowledge managing strategies regarding innovative activities.

Two specific diffusion models for regressing KIP formula are compared by empirical studies with the result indicating the Gompertz model has higher accuracy than the Logistic model to describe the developing curve of technological innovations. Moreover, the analysis of patent-based indicators over diffusion stages also revealed that patents applied at earlier diffusion stages normally has higher forward citation numbers indicating higher innovativeness meanwhile the patents applied at the latter stages usually requiring more knowledge inflows observed by their larger non-patent citation and backward citation amounts.

Although there is a large body of literature concerning knowledge-based technological innovation, there still room for discussing the mechanism of how knowledge diffuses and inspired knowledge. To the best of authors' knowledge, this study is the first attempt to quantitate the innovativeness of knowledge in technological innovation from the knowledge diffusion perspective with findings to support rational knowledge management related to innovation activities.

The aim of this paper is to solve the problem of low accuracy of traditional fatigue crack growth (FCG) prediction methods.

The GMSVR model was proposed by combining the grey modeling (GM) and the support vector regression (SVR). Meanwhile, the GMSVR model parameter optimal selection method based on the artificial bee colony (ABC) algorithm was presented. The FCG prediction of 7075 aluminum alloy under different conditions were taken as the study objects, and the performance of the genetic algorithm, the particle swarm optimization algorithm, the n-fold cross validation and the ABC algorithm were compared and analyzed.

The results show that the speed of the ABC algorithm is the fastest and the accuracy of the ABC algorithm is the highest too. The prediction performances of the GM (1, 1) model, the SVR model and the GMSVR model were compared, the results show that the GMSVR model has the best prediction ability, it can improve the FCG prediction accuracy of 7075 aluminum alloy greatly.

A new prediction model is proposed for FCG combined the non-equidistant grey model and the SVR model. Aiming at the problem of the model parameters are difficult to select, the GMSVR model parameter optimization method based on the ABC algorithm was presented. the results show that the GMSVR model has better prediction ability, which increase the FCG prediction accuracy of 7075 aluminum alloy greatly.