Two-Sample Tests for High Dimensional Means with Thresholding and Data Transformation

We consider testing for two-sample means of high dimensional populations by thresholding. Two tests are investigated, which are designed for better power performance when the two population mean vectors differ only in sparsely populated coordinates. The first test is constructed by carrying out thresholding to remove the non-signal bearing dimensions. The second test combines data transformation via the precision matrix with the thresholding. The benefits of the thresholding and the data transformations are showed by a reduced variance of the test thresholding statistics, the improved power and a wider detection region of the tests. Simulation experiments and an empirical study are performed to confirm the theoretical findings and to demonstrate the practical implementations.Comment: 64 page

The Moscow-Yan’an-Beijing Mode of Chinese Literary Theory

This paper examines the genealogy of Chinese literary theory under the Chinese Communist Party (CCP), in terms of Moscow-Yan’an-Beijing Modes from the inception of the CCP to the present. The focus of this paper is the state-sanctioned textbooks of literary theory and criticism from the beginning of the PRC to the present. The story of these textbooks tells us as much about the complex entanglement of Chinese Marxism or Maoism with Soviet Marxism, i.e. Leninism and Stalinism in the Mao era as about the powerful, on-going impact of that ideological lineage today

Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation

To alleviate the expensive human labeling, semi-supervised semantic segmentation employs a few labeled images and an abundant of unlabeled images to predict the pixel-level label map with the same size. Previous methods often adopt co-training using two convolutional networks with the same architecture but different initialization, which fails to capture the sufficiently diverse features. This motivates us to use tri-training and develop the triple-view encoder to utilize the encoders with different architectures to derive diverse features, and exploit the knowledge distillation skill to learn the complementary semantics among these encoders. Moreover, existing methods simply concatenate the features from both encoder and decoder, resulting in redundant features that require large memory cost. This inspires us to devise a dual-frequency decoder that selects those important features by projecting the features from the spatial domain to the frequency domain, where the dual-frequency channel attention mechanism is introduced to model the feature importance. Therefore, we propose a Triple-view Knowledge Distillation framework, termed TriKD, for semi-supervised semantic segmentation, including the triple-view encoder and the dual-frequency decoder. Extensive experiments were conducted on two benchmarks, \ie, Pascal VOC 2012 and Cityscapes, whose results verify the superiority of the proposed method with a good tradeoff between precision and inference speed

The Effects of Force on the Structure Deformation of Wing for Flapping-wing

This paper investigated the effects of aerodynamic force and inertial force on the structure deformation of wing. The aerodynamic force was tested from the wind tunnel experiment. The study indicated the quantity of aerodynamic force and inertial force is equal. The maximum deformation was produced by aerodynamic force or resultant force when wing is located on horizontal situation. The study of wing structure deformation provide guide for design and optimization of wing for flapping-wing.Keywords: Flapping-wing; aerodynamic force; inertial force; structure deformatio