Abstract-According to the features of Palm bio-impedance spectroscopy (BIS) data, this paper suggests a kind of effective feature model of palm BIS data-elliptical model. The model combines immune clone algorithm and least squares method, establishes a palm BIS feature selection algorithm, and uses the algorithm to obtain the optimal feature subset that can completely represent the palm BIS data, and then use several classification algorithms for classification and comparison. The experimental results show that accuracy of the feature subset obtained through the algorithm in SVM classification algorithm test can reach 93.2, thereby verifying the algorithm is a valid and reliable palm BIS feature selection algorithm.

Objectives The humerus fracture is one of the most commonly occurring fractures. In this research, we attempted to evaluate and compare the extent of malrotation and biomechanical environment after surgical treatment of humeral shaft fractures. Methods A finite element (FE) model of the shoulder was built based on Computed Tomography (CT) data of a patient with a humeral shaft fracture. The muscle group around the shoulder joint was simulated by spring elements. The changes of shoulder stresses under rotation were analyzed. The biomechanics of the normal shoulder and postoperative malrotation of the humeral shaft was analyzed and compared. Results During rotations, the maximum stress was centered in the posterosuperior part of the glenoid for the normal shoulder. The von Mises shear stresses were 4.40 MPa and 4.89 MPa at 40° of internal and external rotations, respectively. For internal rotation deformity, the shear contact forces were 7–9 times higher for the shoulder internally rotated 40° than for the normal one. For external rotation deformity, the shear contact forces were about 3–5 times higher for the shoulder with 40° external rotation than the normal one. Conclusion Postoperative malrotation of humeral shaft fracture induced the changes of the biomechanical environment of the shoulders. The peak degree of malrotation was correlated with increased stresses of shoulders, which could be paid attention to in humeral shaft fracture treatment. We hoped to provide information about the biomechanical environment of humeral malrotation.

Abstract-this article presents an improved classifier vehicle identification algorithm to improve the efficiency of the existing vehicle recognition algorithm. First, using edge orientation histograms to extract image characteristics, then, Error correction coding is applied to the classification of classifier, the multi-class classification problems turned into multiple binary classification problems. A large number of experimental analysis shows that the improved vehicle identification algorithm has good recognition performance and robustness. Therefore, the algorithm which this article used has high theoretical and practical value.