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The classification step used to assign the appropriate opacity to each voxel is very important in the volume rendering. A new classification algorithm for volume data, which is based on minimum cross entropy, is proposed in this paper. Firstly, the volume data is constructed from a series of sequential two-dimension industrial CT images and the histogram of the volume data is computed. Secondly, the histogram of the volume data is partitioned into different subsections through calculating the accumulated histogram of volume data according to the number of object classes. Thirdly, in each subsection a threshold is computed based on minimum cross entropy. Finally, the opacity of each voxel is assigned by a transfer function, which is split into subsection by these thresholds. Two experimental results from industrial CT images are presented. One is the volume data of vane and the other is volume data of electric drill, from which we can see that the volume rendering results for industrial components are smooth and the image data isn't lost when rotating great angles. In the mean time, this algorithm makes the simulated disassembly of the industrial components performed on the computer successfully.Index Terms -Classification, Histogram of volume data, minimum cross entropy, partition of the histogram

Robust real-time tracking of non-rigid objects is a challenging task. The difficulty in visual tracking is how to match targets from frame to frame quickly and reliably. Mean shift algorithm (MSA) is a typical nonparametric evaluation algorithm that needs great computation. Some scholars join Kalman filter to perform state prediction in the mean shift algorithm for reducing the computing of template matching. However, traditional Kalman filter sometimes can't track human movement very accurately because of the particularity of human joint. While wavelet moment has the multiresolution properties in addition to the invariant to the translation, scaling and rotation, so it is suitable for differentiating the details of the motion objects. Therefore, Kalman-mean shift tracking algorithm based on wavelet moment (W-K-MSA) is proposed in this paper. In this algorithm, a Kalman filter algorithm, which is used to estimate the motion parameters of targets, is improved based on wavelet moment features in the searching process. And searching window is adaptively changed, as a result, searching scope is reduced greatly, and the processing velocity and veracity is improved during model matching. The experimental results demonstrate that the proposed tracking algorithm is robust and practical.

The article delves into the unique reception of Alexander Herzen’s ‘My Past and Thoughts’ in Chinese literary studies. It is noted that this chronicle has received widespread recognition in China and continues to generate significant interest to this day. It analyzes the reasons, characteristics, and aspects of the Russian classic's influence on Chinese literature in different historical periods. It highlights that the reception of ‘My Past and Thoughts’ by Chinese readers and scholars is determined by two factors: the great value of the work itself and the fact that Herzen’s work met the needs of Chinese society in various historical periods. The article shows that the main feature of the reception of Herzen’s works by Chinese researchers has evolved from socio-political domination to cultural-aesthetic dominance. ‘My Past and Thoughts’ has influenced both the theory and practice of modern Chinese literature, and contemporary Chinese writers have created works inspired by Herzen's approach. For instance, Ba Jin wrote ‘Thoughts’ under the influence of Herzen’s work, while Yu Dafu developed a literary theory of memoirs inspired by it. The authors conclude that Herzen studies in China are pertinent and offer extensive prospects for further research.