Filter Pruning For CNN With Enhanced Linear Representation Redundancy

Structured network pruning excels non-structured methods because they can take advantage of the thriving developed parallel computing techniques. In this paper, we propose a new structured pruning method. Firstly, to create more structured redundancy, we present a data-driven loss function term calculated from the correlation coefficient matrix of different feature maps in the same layer, named CCM-loss. This loss term can encourage the neural network to learn stronger linear representation relations between feature maps during the training from the scratch so that more homogenous parts can be removed later in pruning. CCM-loss provides us with another universal transcendental mathematical tool besides L*-norm regularization, which concentrates on generating zeros, to generate more redundancy but for the different genres. Furthermore, we design a matching channel selection strategy based on principal components analysis to exploit the maximum potential ability of CCM-loss. In our new strategy, we mainly focus on the consistency and integrality of the information flow in the network. Instead of empirically hard-code the retain ratio for each layer, our channel selection strategy can dynamically adjust each layer's retain ratio according to the specific circumstance of a per-trained model to push the prune ratio to the limit. Notably, on the Cifar-10 dataset, our method brings 93.64% accuracy for pruned VGG-16 with only 1.40M parameters and 49.60M FLOPs, the pruned ratios for parameters and FLOPs are 90.6% and 84.2%, respectively. For ResNet-50 trained on the ImageNet dataset, our approach achieves 42.8% and 47.3% storage and computation reductions, respectively, with an accuracy of 76.23%. Our code is available at https://github.com/Bojue-Wang/CCM-LRR

Effects of Preparation Conditions on the Yield and Embedding Ratio of Vinyl Silicone Oil Microcapsules

Self-healing materials could repair themselves without external influences when they are damaged. In this paper, microcapsules are prepared by in-situ polymerization method, utilizing vinyl silicone oil as core material, polyurea formaldehyde as wall material and polyvinyl alcohol as dispersant. The morphology and structure of the microcapsules are tested with scanning electron microscopy, optical microscopy and laser particle analyzer. Effect of the reaction temperature, stirring speed and polyvinyl alcohol concentration on the yield, embedding ratio, particle size and its distribution are studied. Results show that the microcapsules can be successfully prepared by in-situ polymerization method. Under the reaction condition of temperature 60 °C, stirring speed 1000 r/min, dispersant concentration 0.1 wt.%, the yield and embedding ratio of the microcapsule are found to be 52.5 % and 50.1 %, respectively. The prepared microcapsules have smooth surface, good dispersibility, narrow particle size distribution and the average particle size is 13 μm

Association between -238 but not -308 polymorphism of Tumor necrosis factor alpha (TNF-alpha)v and unexplained recurrent spontaneous abortion (URSA) in Chinese population

<p>Abstract</p> <p>Objectives</p> <p>TNF-alpha is a critical cytokine produced by Th1 cells while altered T helper 1 (Th1)-Th2 balance is found crucial for a successful pregnancy.</p> <p>Study Design</p> <p>A cohort of 132 Southern Chinese Han RSA patients and 152 controls constituted the subjects of this study. Two functional polymorphisms -308 and -238 of TNF-alpha were studied by association analysis.</p> <p>Results</p> <p>lack of association was found in TNF-alpha -308 SNP yet a significant difference was discovered in -238 polymorphism.</p> <p>Conclusion</p> <p>This study suggested that TNF-alpha may be a risk factor in Chinese RSA patients. However the ethnic differences may also contribute to the results.</p

A rapid and robust method for shot boundary detection and classification in uncompressed MPEG video sequences

Abstract Shot boundary and classification is the first and most important step for further analysis of video content. Shot transitions include abrupt changes and gradual changes. A rapid and robust method for shot boundary detection and classification in MPEG compressed sequences is proposed in this paper. We firstly only decode I frames partly in video sequences to generate DC images and then calculate the difference values of histogram of these DC images in order to detect roughly the shot boundary. Then, for abrupt change detection, shot boundary is precisely located by movement information of B frames. Shot gradual change is located by difference values of successive N I frames and classified by the alteration of the number of intra coding macroblocks (MBs) in P frames. All features such as the number of MBs in frames are extracted from uncompressed video sequences. Experiments have been done on the standard TRECVid video database and others to reveal the performance of the proposed method

Lycorine reduces mortality of human enterovirus 71-infected mice by inhibiting virus replication

Human enterovirus 71 (EV71) infection causes hand, foot and mouth disease in children under 6 years old and this infection occasionally induces severe neurological complications. No vaccines or drugs are clinical available to control EV71 epidemics. In present study, we show that treatment with lycorine reduced the viral cytopathic effect (CPE) on rhabdomyosarcoma (RD) cells by inhibiting virus replication. Analysis of this inhibitory effect of lycorine on viral proteins synthesis suggests that lycorine blocks the elongation of the viral polyprotein during translation. Lycorine treatment of mice challenged with a lethal dose of EV71 resulted in reduction of mortality, clinical scores and pathological changes in the muscles of mice, which were achieved through inhibition of viral replication. When mice were infected with a moderate dose of EV71, lycorine treatment was able to protect them from paralysis. Lycorine may be a potential drug candidate for the clinical treatment of EV71-infected patients

Novel methods of estimating relative pollen productivity; a key parameter for reconstruction of past land cover from pollen records

Reconstructing land cover from pollen data using mathematical models of the relationship between them has the potential to translate the many thousand pollen records produced over the last 100 years (over 2300 radiocarbon-dated pollen records exist for the UK alone) into formats relevant to ecologists, archaeologists and climate scientists. However, the reliability of these reconstructions depends on model parameters. A key parameter is Relative Pollen Productivity (RPP), usually estimated from empirical data using ‘Extended R Value analysis’ (ERV analysis). Lack of RPP estimates for many regions is currently a major limitation on reconstructing global land cover. We present two alternatives to ERV analysis, the Modified Davis Method and an iteration method, which use the same underlying model of the relationship between pollen and vegetation to estimate RPP from empirical data, but with different assumptions. We test them in simulation against ERV analysis, and use a case study of a problematic empirical dataset to determine whether they have the potential to increase the speed and geographic range of RPP estimation. The two alternative methods are shown to perform at least as well as ERV analysis in simulation. We also present new RPP estimates from southeastern sub-tropical China for nine taxa estimated using the Modified Davis Method. Adding these two methods to the ‘toolkit’ for land cover reconstruction from pollen records opens up the possibility to estimate a key parameter from existing datasets with less field time than using current methods. This can both speed up the inclusion of more of the globe in past land cover mapping exercises such as the PAGES Landcover6k working group and improve our understanding of how this parameter varies within a single taxon and the factors control that variation

Application of a Spectral Method to Simulate Quasi-Three-Dimensional Underwater Acoustic Fields

The solution and synthesis of quasi-three-dimensional sound fields have always been core issues in computational ocean acoustics. Traditionally, finite difference algorithms have been employed to solve these problems. In this paper, a novel numerical algorithm based on the spectral method is devised. The quasi-three-dimensional problem is transformed into a problem resembling a two-dimensional line source using an integral transformation strategy. Then, a stair-step approximation is adopted to address the range dependence of the two-dimensional problem; because this approximation is essentially a discretization, the range-dependent two-dimensional problem is further simplified into a one-dimensional problem. Finally, we apply the Chebyshev--Tau spectral method to accurately solve the one-dimensional problem. We present the corresponding numerical program for the proposed algorithm and describe some representative numerical examples. The simulation results ultimately verify the reliability and capability of the proposed algorithm.Comment: 43 pages, 20 figures. arXiv admin note: text overlap with arXiv:2112.1360