This paper presents a novel method to explore the intrinsic morphological correlation between the bones of a shoulder joint (humerus and scapula). To model this correlation, canonical correlation analysis (CCA) is used. We also propose a technique to predict a three-dimensional (3D) bone shape from its adjoining segment at a joint based on partial least squares regression (PLS). The high dimensional 3D surface information of a bone is represented by a few variables using principal component analysis, which also captures the pattern of variability of the shapes in our datasets. Our results show that the humerus set and scapula set have highly linear morphological relationship and that the correlation information can be used as a classifier. In this study, primate shoulder bone datasets were categorised into two clusters: great apes (including humans) and monkeys. A leave one out experiment was performed to test the robustness of this prediction method. The prediction behaviour using this method shows statistically significantly better results than using the mean shape from the training set.

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The position accuracy adjustment is an important part of the position of space exploration vehicle. Aiming at this problem, a method of designing an automatic adjustment system for positioning accuracy of space exploration vehicle based on pseudo range differential positioning is proposed. By analyzing the function of each module of the system, the automatic adjustment system for positioning accuracy of space exploration vehicle is designed. On this basis, the object contour of the positioning image is located by the adaptive smoothing method. According to this theory, the geometric centre values of two contour points near the centre point in the contour range are calculated and the curvature angle is further calculated to get the curvature symbols. By describing the changing process of each feature in the positioning process with the transition between states, a hidden Markov model is constructed to effectively adjust the positioning accuracy. Experiments show that the proposed method can effectively improve the positioning accuracy of aircraft, effectively reduce the positioning error of the system and has good application value.