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According to the grey uncertainty and the connotation of different types weights, the purpose of this paper is to establish the pattern of multi-dimensional grey fuzzy decision making with feedback based on weight vector and weight matrix, and applies this pattern to evaluate the regional financial innovation ability.

At first, this paper analyzes the connotation of financial innovation ability and establishes the evaluation system of regional financial innovation ability. Second, the formula of computing the multi-objective weighted comprehensive value based on weight vector and weight matrix is put forward. In view of the object function with supervised factor and stability coefficient, this paper gives the formulas to compute weight vector and weight matrix. Moreover, the algorithm of the multi-dimensional grey fuzzy decision making pattern with feedback based on weight vector and weight matrix is expressed. At last, this paper uses the presented pattern to evaluate the financial innovation ability of thirty-one provinces in China.

The results are convincing: the development of regional financial innovation is not balanced in China, having obvious spatial clustering feature. The comparisons of evaluation results based on different forms of weights show that the calculating convergence speed of the pattern presented in this paper is fast. The pattern enhances the rationality of the demarcation point between categories, and the convergence within categories, making the evaluation more reasonable.

The method exposed in the paper can be used at evaluating the regional financial innovation ability and even for other similar evaluation problem.

The paper succeeds in realising both the pattern of multi-dimensional grey fuzzy decision making with feedback and evaluating the regional financial innovation ability by using the newest developed theories: weighted grey and fuzzy recognition theory based on weight vector and weight matrix.

This paper aims to present a numerical model to investigate the mixed lubrication performances of journal-thrust coupled bearings (or coupled bearings).

The coupled hydrodynamic effect (or coupled effect) between the journal and the thrust bearing is considered by ensuring the continuity of the hydrodynamic pressure and the flow field at the common boundary. The mixed lubrication performances of the coupled bearing are comparatively studied for the cases of considering and not considering coupled effect.

The simulated results show that the hydrodynamic pressure distributions for both the journal and thrust bearing are modified due to the coupled effect. The decreased load capacity of the journal bearing and the increased load capacity of the thrust bearing can be observed when the coupled effect is considered. And the coupled effect can facilitate in reducing the asperity contact load for both the journal and thrust bearing. Additionally, the interaction between the mixed lubrication behaviors, especially for the friction coefficient, of the journal and the thrust bearing is significant in the elastohydrodynamic lubrication regime, while it becomes weak in the mixed lubrication regime.

The developed model can reveal the mutual effects of the mixed lubrication behavior between the journal and the thrust bearing.

The purpose of the paper is to present a novel cross-modal sensor whose tactile is computed by the visual information. The proposed sensor can measure the forces of robotic grasping.

The proposed cross-modal tactile sensor consists of a transparent elastomer with markers, a camera, an LED circuit board and supporting structures. The model and performance of the elastomer are analyzed. Then marker recognition method is proposed to determine the movements of the marker on the surface, and the force calculation algorithm is presented to compute the three-dimension force.

Experimental results demonstrate that the proposed tactile sensor can accurately measure robotic grasping forces.

The proposed cross-modal tactile sensor determines the robotic grasping forces by the images of markers. It can give more information of the force than traditional tactile sensors. Meanwhile, the proposed algorithms for forces calculation determine the superior results.