Bi-Directional Generation for Unsupervised Domain Adaptation

Unsupervised domain adaptation facilitates the unlabeled target domain relying on well-established source domain information. The conventional methods forcefully reducing the domain discrepancy in the latent space will result in the destruction of intrinsic data structure. To balance the mitigation of domain gap and the preservation of the inherent structure, we propose a Bi-Directional Generation domain adaptation model with consistent classifiers interpolating two intermediate domains to bridge source and target domains. Specifically, two cross-domain generators are employed to synthesize one domain conditioned on the other. The performance of our proposed method can be further enhanced by the consistent classifiers and the cross-domain alignment constraints. We also design two classifiers which are jointly optimized to maximize the consistency on target sample prediction. Extensive experiments verify that our proposed model outperforms the state-of-the-art on standard cross domain visual benchmarks.Comment: 9 pages, 4 figure

Deep feature fusion via two-stream convolutional neural network for hyperspectral image classification

The representation power of convolutional neural network (CNN) models for hyperspectral image (HSI) analysis is in practice limited by the available amount of the labeled samples, which is often insufficient to sustain deep networks with many parameters. We propose a novel approach to boost the network representation power with a two-stream 2-D CNN architecture. The proposed method extracts simultaneously, the spectral features and local spatial and global spatial features, with two 2-D CNN networks and makes use of channel correlations to identify the most informative features. Moreover, we propose a layer-specific regularization and a smooth normalization fusion scheme to adaptively learn the fusion weights for the spectral-spatial features from the two parallel streams. An important asset of our model is the simultaneous training of the feature extraction, fusion, and classification processes with the same cost function. Experimental results on several hyperspectral data sets demonstrate the efficacy of the proposed method compared with the state-of-the-art methods in the field

Spectral feature fusion networks with dual attention for hyperspectral image classification

Recent progress in spectral classification is largely attributed to the use of convolutional neural networks (CNN). While a variety of successful architectures have been proposed, they all extract spectral features from various portions of adjacent spectral bands. In this paper, we take a different approach and develop a deep spectral feature fusion method, which extracts both local and interlocal spectral features, capturing thus also the correlations among non-adjacent bands. To our knowledge, this is the first reported deep spectral feature fusion method. Our model is a two-stream architecture, where an intergroup and a groupwise spectral classifiers operate in parallel. The interlocal spectral correlation feature extraction is achieved elegantly, by reshaping the input spectral vectors to form the socalled non-adjacent spectral matrices. We introduce the concept of groupwise band convolution to enable efficient extraction of discriminative local features with multiple kernels adopting to the local spectral content. Another important contribution of this work is a novel dual-channel attention mechanism to identify the most informative spectral features. The model is trained in an end-to-end fashion with a joint loss. Experimental results on real data sets demonstrate excellent performance compared to the current state-of-the-art

An efficient approach to acoustic emission source identification based on harmonic wavelet packet and hierarchy support vector machine

A new approach for acoustic emission (AE) source type identification based on harmonic wavelet packet (HWPT) feature extraction and hierarchy support vector machine (H-SVM) classifier is proposed for solving the fatigue damage identification problem of helicopter moving component. In this approach, HWPT is employed to extract the energy feature of AE signals on different frequency bands, as well as to reduce the dimensionality of original data features. We trained the H-SVM classifier on a subset of the experimental data for known AE source type, and then tested on the remaining set of data. Also, the pressure off experiment on specimen of carbon fiber materials is investigated. The experimental results indicate that the proposed approach can implement AE source type identification effectively, and achieves better performance on computational efficiency and identification accuracy than wavelet packet (WPT) feature extraction and RBF neural network classification

Fault Diagnosis for Wireless Sensor by Twin Support Vector Machine

Various data mining techniques have been applied to fault diagnosis for wireless sensor because of the advantage of discovering useful knowledge from large data sets. In order to improve the diagnosis accuracy of wireless sensor, a novel fault diagnosis for wireless sensor technology by twin support vector machine (TSVM) is proposed in the paper. Twin SVM is a binary classifier that performs classification by using two nonparallel hyperplanes instead of the single hyperplane used in the classical SVM. However, the parameter setting in the TSVM training procedure significantly influences the classification accuracy. Thus, this study introduces PSO as an optimization technique to simultaneously optimize the TSVM training parameter. The experimental results indicate that the diagnosis results for wireless sensor of twin support vector machine are better than those of SVM, ANN

Influence of different fibers on the change of pore pressure of self-consolidating concrete exposed to fire

The focus of this paper is given to investigate the effect of different fibers on the pore pressure of fiber reinforced self-consolidating concrete under fire. The investigation on the pore pressure-time and temperature relationships at different depths of fiber reinforced self-consolidating concrete beams was carried out. The results indicated that micro PP fiber is more effective in mitigating the pore pressure than macro PP fiber and steel fiber. The composed use of steel fiber, micro PP fiber and macro PP fiber showed clear positive hybrid effect on the pore pressure reduction near the beam bottom subjected to fire. Compared to the effect of macro PP fiber with high dosages, the effect of micro PP fiber with low fiber contents on the pore pressure reduction is much stronger. The significant factor for reduction of pore pressure depends mainly on the number of PP fibers and not only on the fiber content. An empirical formula was proposed to predict the relative maximum pore pressure of fiber reinforced self-consolidating concrete exposed to fire by considering the moisture content, compressive strength and various fibers. The suggested model corresponds well with the experimental results of other research and tends to prove that the micro PP fiber can be the vital component for reduction in pore pressure, temperature as well spalling of concrete.National Natural Science Foundation of China (Grant: 51121005), DUT and Fundaçãopara a Ciência e a Tecnologia (SFRH/BPD/22680/2005), the FEDER Funds through “Programa Operacional Factores de Competitividade - COMPETE" and by Portuguese Funds through FCT-within the Projects PEst-CMAT/UI0013/2011 and PTDC/MAT/112273/2009

Knowledge, attitudes and practices relating to antibiotic use and antibiotic resistance among backyard pig farmers in rural Shandong province, China

China is among the world's largest consumers of antibiotics for livestock, and the demand for meat protein continues to rise. Pig production takes place at a range of facilities, including backyard pig farms. The aim of this study was to describe the knowledge, attitudes and practices of backyard pig farmers concerning antibiotic use and resistance, and to observe household storage of antibiotics for use in pigs. We conducted a cross-sectional questionnaire survey among 271 rural residents with backyard pig farms in 12 villages in one town in Shandong province. The median number of pigs per backyard farm was 14, and 82 % (222/271) of participants reported not having had any training about raising pigs. Eighteen percent of participants (48/271) reported always or often adding antibiotics to feed to keep pigs healthy and prevent diseases, and a third (88/271) of participants believed that pigs should be given antibiotics when they stop eating. Thirty percent (82/271) reported having bought antibiotics in the previous year without having first spoken with a veterinarian. Antibiotics accounted for over half of all medicines stored (55 %, 197/358), and were observed in 31 % of all households (83/271). Less than half of participants (45 %, 37/83) from households in which antibiotics for pig use were found knew that they were storing antibiotics. The most common class of antibiotics stored for use in pigs was (Q)J01C betalactam antibiotics, penicillins (19 %, 37/197), followed by (Q)J01F macrolides, lincosamides and streptogramins (14 %, 28/197), and (Q)J01M quinolones (12 %, 25/197). These results provide important insights into how backyard pig farmers are using antibiotics in rural China and suggest potential targets for interventions to reduce unnecessary and inappropriate use

The Intracellular Virus-Containing Compartments in Primary Human Macrophages Are Largely Inaccessible to Antibodies and Small Molecules

HIV-1 assembly and release occurs at the plasma membrane of human T lymphocytes and model epithelial cell lines, whereas in macrophages intracellular sites of virus assembly or accumulation predominate. The origin of the intracellular virus-containing compartment (VCC) has been controversial. This compartment is enriched in markers of the multivesicular body, and has been described as a modified endosomal compartment. Several studies of this compartment have revealed the presence of small channels connecting to the plasma membrane, suggesting that instead of an endosomal origin the compartment is a modified plasma membrane compartment. If the compartment is accessible to the external environment, this would have important implications for antiviral immune responses and antiviral therapy. We performed a series of experiments designed to determine if the VCC in macrophages was open to the external environment and accessible to antibodies and small molecules. The majority of VCCs were found to be inaccessible to exogenously-applied antibodies to tetraspanins in the absence of membrane permeabilization, while tetraspanin staining was readily observed following membrane permeabilization. Cationized ferritin was utilized to stain the plasma membrane, and revealed that the majority of virus-containing compartments were inaccessible to ferritin. Low molecular weight dextrans could access only a very small percentage of VCCs, and these tended to be more peripheral compartments. We conclude that the VCCs in monocyte-derived human macrophages are heterogeneous, but the majority of VCCs are closed to the external environment

The Survey of H5N1 Flu Virus in Wild Birds in 14 Provinces of China from 2004 to 2007

The highly pathogenic H5N1 avian influenza emerged in the year 1996 in Asia, and has spread to Europe and Africa recently. At present, effective monitoring and data analysis of H5N1 are not sufficient in Chinese mainland.)) were obviously higher than those in other 13 provinces. The results of sequence analysis indicated that the 17 strains isolated from wild birds were distributed in five clades (2.3.1, 2.2, 2.5, 6, and 7), which suggested that genetic diversity existed among H5N1 viruses isolated from wild birds. The five isolates from Qinghai came from one clade (2.2) and had a short evolutionary distance with the isolates obtained from Qinghai in the year 2005.We have measured the prevalence of H5N1 virus in 56 species of wild birds in 14 provinces of China. Continuous monitoring in the field should be carried out to know whether H5N1 virus can be maintained by wild birds