Nonlinear modelling and transient dynamics analysis of a hoist equipped with a two-stage planetary gear transmission system

A system-level nonlinear dynamic model for a two-stage planetary gear transmission system of a hoist is established with the consideration of time-varying meshing stiffness, backlash, damping, and bearing stiffness. Vibrational test results are also presented in accordance with simulation results computed from the dynamic model, and engagement-impacting dynamic simulations are achieved by adapting a dynamic explicit algorithm based on this model. Accordingly, variation in the contact state in relation to the engaging position is obtained together with vibration characteristics of the transmission system. This study provides a theoretical basis for the reduction of vibration and noise for the transmission system

Video classification based on spatial gradient and optical flow descriptors

Feature point detection and local feature extraction are the two critical steps in trajectory-based methods for video classification. This paper proposes to detect trajectories by tracking the spatiotemporal feature points in salient regions instead of the entire frame. This strategy significantly reduces noisy feature points in the background region, and leads to lower computational cost and higher discriminative power of the feature set. Two new spatiotemporal descriptors, namely the STOH and RISTOH are proposed to describe the spatiotemporal characteristics of the moving object. The proposed method for feature point detection and local feature extraction is applied for human action recognition. It is evaluated on three video datasets: KTH, YouTube, and Hollywood2. The results show that the proposed method achieves a higher classification rate, even when it uses only half the number of feature points compared to the dense sampling approach. Moreover, features extracted from the curvature of the motion surface are more discriminative than features extracted from the spatial gradient

Improving Pedestrian Attribute Recognition With Weakly-Supervised Multi-Scale Attribute-Specific Localization

Pedestrian attribute recognition has been an emerging research topic in the area of video surveillance. To predict the existence of a particular attribute, it is demanded to localize the regions related to the attribute. However, in this task, the region annotations are not available. How to carve out these attribute-related regions remains challenging. Existing methods applied attribute-agnostic visual attention or heuristic body-part localization mechanisms to enhance the local feature representations, while neglecting to employ attributes to define local feature areas. We propose a flexible Attribute Localization Module (ALM) to adaptively discover the most discriminative regions and learns the regional features for each attribute at multiple levels. Moreover, a feature pyramid architecture is also introduced to enhance the attribute-specific localization at low-levels with high-level semantic guidance. The proposed framework does not require additional region annotations and can be trained end-to-end with multi-level deep supervision. Extensive experiments show that the proposed method achieves state-of-the-art results on three pedestrian attribute datasets, including PETA, RAP, and PA-100K.Comment: Accepted by ICCV 201

Testing for homogeneity of gametic disequilibrium across strata

Copyright © 2007 Yin et al. Background: Assessing the non-random associations of alleles at different loci, or gametic disequilibrium, can provide clues about aspects of population histories and mating behavior and can be useful in locating disease genes. For gametic data which are available from several strata with different allele probabilities, it is necessary to verify that the strata are homogeneous in terms of gametic disequilibrium. Results: Using the likelihood score theory generalized to nuisance parameters we derive a score test for homogeneity of gametic disequilibrium across several independent populations. Simulation results demonstrate that the empirical type I error rates of our score homogeneity test perform satisfactorily in the sense that they are close to the pre-chosen 0.05 nominal level. The associated power and sample size formulae are derived. We illustrate our test with a data set from a study of the cystic fibrosis transmembrane conductance regulator gene. Conclusion: We propose a large-sample homogeneity test on gametic disequilibrium across several independent populations based on the likelihood score theory generalized to nuisance parameters. Our simulation results show that our test is more reliable than the traditional test based on the Fisher's test of homogeneity among correlation coefficients. © 2007 Yin et al; licensee BioMed Central Ltd.This research was supported by the National Natural Science Foundation of China (Grant Numbers 10431010 and 10701022), National 973 Key Project of China (2007CB311002), NCET-04-0310, EYTP, the Jilin Distinguished Young Scholars Program (Grant Number 20030113) and the Program Innovative Research Team (PCSIRT) in University (#IRT0519). The work of ML Tang was fully supported by a grant from the Research Grant Council of the Hong Kong Special Administration (Project no. HKBU261007)

Data-Driven Transferred Energy Management Strategy for Hybrid Electric Vehicles via Deep Reinforcement Learning

Real-time applications of energy management strategies (EMSs) in hybrid electric vehicles (HEVs) are the harshest requirements for researchers and engineers. Inspired by the excellent problem-solving capabilities of deep reinforcement learning (DRL), this paper proposes a real-time EMS via incorporating the DRL method and transfer learning (TL). The related EMSs are derived from and evaluated on the real-world collected driving cycle dataset from Transportation Secure Data Center (TSDC). The concrete DRL algorithm is proximal policy optimization (PPO) belonging to the policy gradient (PG) techniques. For specification, many source driving cycles are utilized for training the parameters of deep network based on PPO. The learned parameters are transformed into the target driving cycles under the TL framework. The EMSs related to the target driving cycles are estimated and compared in different training conditions. Simulation results indicate that the presented transfer DRL-based EMS could effectively reduce time consumption and guarantee control performance.Comment: 25 pages, 12 figure

Lactobacillus pentosus expressing porcine lactoferrin elevates antibacterial activity and improves the efficacy of vaccination against Aujeszky’s disease

In this study, Lactobacillus pentosus expressing porcine lactoferrin (pLF) was tested for in vitro antibacterial activity and for its ability to enhance immunity induced by an orally administered Aujeszky’s disease virus (ADV) vaccine. The cDNA encoding N-terminus of pLF was cloned into a Lactobacillus-specific plasmid to produce L. pentosus pLF expressing transformants (pPG612.1-pLFN/ L. pentosus). The antimicrobial activity of the recombinant pLF protein inhibited bacterial growth in vitro. The supernatant of pPG612.1-pLF-N/L. pentosus had an inhibitory effect on Staphylococcus aureus strain CVCC26003, Bacillus subtilis strain CVCC63501, Escherichia coli strain CVCC10141 and Salmonella enterica ssp. enterica Choleraesuis strain CVCC79102, while it did not inhibit the growth of Lactobacillus casei strain ATCC393. A mouse model was established to test the effectiveness of the orally administered probiotic L. pentosus recombinant strain in the gastrointestinal tract. Mice were immunised with an attenuated porcine Aujeszky’s disease virus (ADV) vaccine. Serum antibody levels determined using a mouse Aujeszky’s disease IgG ELISA showed that IgG levels were significantly higher in the pPG612.1-pLFN/L. pentosus group than in the PBS and Lactobacillus pentosus groups at days 7 and 21 (P < 0.01) and at day 14 (P < 0.05), indicating that this oral recombinant strain can improve the effectiveness of the vaccine and play a role in immune enhancement through humoral immunity. These results suggest that the recombinant Lactobacillus pentosus not only has the beneficial characteristics of lactic acid bacteria but also produces biologically functional lactoferrin