Multi-scale 3D Convolution Network for Video Based Person Re-Identification

This paper proposes a two-stream convolution network to extract spatial and temporal cues for video based person Re-Identification (ReID). A temporal stream in this network is constructed by inserting several Multi-scale 3D (M3D) convolution layers into a 2D CNN network. The resulting M3D convolution network introduces a fraction of parameters into the 2D CNN, but gains the ability of multi-scale temporal feature learning. With this compact architecture, M3D convolution network is also more efficient and easier to optimize than existing 3D convolution networks. The temporal stream further involves Residual Attention Layers (RAL) to refine the temporal features. By jointly learning spatial-temporal attention masks in a residual manner, RAL identifies the discriminative spatial regions and temporal cues. The other stream in our network is implemented with a 2D CNN for spatial feature extraction. The spatial and temporal features from two streams are finally fused for the video based person ReID. Evaluations on three widely used benchmarks datasets, i.e., MARS, PRID2011, and iLIDS-VID demonstrate the substantial advantages of our method over existing 3D convolution networks and state-of-art methods.Comment: AAAI, 201

A statistical normalization method and differential expression analysis for RNA-seq data between different species

Background: High-throughput techniques bring novel tools but also statistical challenges to genomic research. Identifying genes with differential expression between different species is an effective way to discover evolutionarily conserved transcriptional responses. To remove systematic variation between different species for a fair comparison, the normalization procedure serves as a crucial pre-processing step that adjusts for the varying sample sequencing depths and other confounding technical effects. Results: In this paper, we propose a scale based normalization (SCBN) method by taking into account the available knowledge of conserved orthologous genes and hypothesis testing framework. Considering the different gene lengths and unmapped genes between different species, we formulate the problem from the perspective of hypothesis testing and search for the optimal scaling factor that minimizes the deviation between the empirical and nominal type I errors. Conclusions: Simulation studies show that the proposed method performs significantly better than the existing competitor in a wide range of settings. An RNA-seq dataset of different species is also analyzed and it coincides with the conclusion that the proposed method outperforms the existing method. For practical applications, we have also developed an R package named "SCBN" and the software is available at http://www.bioconductor.org/packages/devel/bioc/html/SCBN.html

Solving eigenvalue PDEs of metastable diffusion processes using artificial neural networks

In this paper, we consider the eigenvalue PDE problem of the infinitesimal generators of metastable diffusion processes. We propose a numerical algorithm based on training artificial neural networks for solving the leading eigenvalues and eigenfunctions of such high-dimensional eigenvalue problem. The algorithm is able to find multiple leading eigenpairs by solving a single training task. It is useful in understanding the dynamical behaviors of metastable processes on large timescales. We demonstrate the capability of our algorithm on a high-dimensional model problem, and on the simple molecular system alanine dipeptide.Comment: revision with minor change

Influence of elevated temperature on mechanical properties and durability of concrete

Concrete structures are exposed to high temperatures during fire. Bothe the mechanical properties and durability after exposed to elevated temperatures are of great importance in terms of the serviceability of buildings. In this project, the effects of elevated temperatures (20, 100, 200, 300, 400, 500 and 600 ℃ ) on the compressive strength, elastic modulus, fracture energy, water capillary absorption and chloride penetration have been studied. The influence of cooling methods on these properties has been also investigated. The results obtained indicate that when the temperature is below 400 ℃ for concrete A (W/C=0.4) and 300 ℃ for concrete B (W/C=0.5) with natural cooling, the compressive strength did not decrease immediately. But with water splashing cooling, the compressive strength of concrete lost approx. 20 % at 300 degree. The elastic modulus of concrete decreased gradually with the increasing of temperature. And there is no real difference between two types of cooling methods. When the temperature is over 400 degree only, the fracture energy decreased significantly. After exposed to elevated temperatures, concrete absorbed much more water and chloride ions, which bring a high risk for RC structures. This effect shall also be taken into consideration when concrete structures after fire is evaluated

Influence of frost damage on water penetration into neat and air entrained concrete

In service life, concrete can be damaged either by mechanical or environmental loads or by combined ones. These damages will strongly influence water movement in concrete which could later lead to more serious deteriorations. This paper applies neutron radiography to investigate the influence of frost damage on water penetration into concrete. In addition, the improvement of frost resistance by addition of air entrainment was investigated. The results indicate that it is possible to visualize penetration of water into the porous structure of concrete by neutron radiography. Further evaluation of the test data allows determining time-dependent moisture profiles quantitatively with high resolution. After concrete is damaged by freeze-thaw cycles water penetration into ordinary concrete is accelerated. It can be shown that frost damage is not equally distributed in specimens exposed to freeze-thaw cycles. Thermal gradients lead to more serious damage near the surface. The beneficial effect of air entrainment on frost resistance has been demonstrated. After 50 freeze-thaw cycles, air entrained concrete showed no measurable increase in water absorption. But layers near the surface of concrete absorbed slightly more water after 200 freeze-thaw cycles although the dynamic elastic modulus remained constant. Results presented in this paper help us to better understand mechanisms of frost damage of concrete

Research of the wrinkling elimination of stainless steel SUS304 by viscous pressure

Wrinkling is one of the most important factors influencing a forming precision of sheet metal, which brings difficulties to the forming process of sheet metal. In order to eliminate the wrinkling during the forming process, an accurate prediction is necessary. In this paper, the wrinkling elimination process was investigated based on the principle of the Yoshida Buckling Test (YBT) and viscous pressure forming. The experimental device was designed, and evaluation method of the wrinkling elimination rate was presented by the stainless steel SUS304. On this basis, the wrinkling elimination experiment was carried out, the influences of both the viscous medium molecular weight and the tensile state of wrinkle under the viscous pressure on the wrinkling elimination were obtained