A Deep Web Query Interfaces Classification Method Based on RBF Neural Network

This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial basic function neural network （RBFNN） algorithm to classify the query interfaces. The applied RBFNN is a kind of effective feed-forward artificial neural network, which has a simple networking structure but features with strength of excellent nonlinear approximation, fast convergence and global convergence. A TEL_8 query interfaces＇ data set from UIUC on-line database is used in our experiments, which consists of 477 query interfaces in 8 typical domains. Experimental results proved that the proposed approach can efficiently classify the query interfaces with an accuracy of 95.67%.     

Multiple feature fusion in convolutional neural networks for action recognition

Action recognition is important for understanding the human behaviors in the video, and the video representation is the basis for action recognition. This paper provides a new video representation based on convolution neural networks (CNN). For capturing human motion information in one CNN, we take both the optical flow maps and gray images as input, and combine multiple convolutional features by max pooling across frames. In another CNN, we input single color frame to capture context information. Finally, we take the top full connected layer vectors as video representation and train the classifiers by linear support vector machine. The experimental results show that the representation which integrates the optical flow maps and gray images obtains more discriminative properties than those which depend on only one element. On the most challenging data sets HMDB51 and UCF101, this video representation obtains competitive performance.     

Resonance Light-Scattering Spectroscopy Study on Interaction between Gold Colloid and Thiol Containing Pharmaceutical

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The c-myc coding DNA sequences of cyprinids （Teleostei： Cypriniformes）： Implications for phylogeny

The family Cyprinidae is one of the largest fish families in the world, which is widely distributed in East Asian, with obvious difference in characteristic size among species. The phylogeneUc analysis of cyprinid taxa based on the functionally important genes can help to understand the speciation and functional divergence of the Cyprinidae. The c-myc gene is an important gene regulating individual growth. In the present study, the sequence variations of the cyprinid c-myc gene and their phylogenetic significance were analyzed. The 41 complete sequences of the c-myc gene were obtained from cyprinids and outgroups through PCR amplification and clone. The coding DNA sequences of the c-myc gene were used to infer molecular phylogenetic relationships within the Cyprinidae. Myxocyprinus asiaticus （Catostomidae）, Misgurnus anguillicaudatus （CobiUdae） and Hemimyzon sinensis （Homalopteridae） were assigned to the outgroup taxa. Phylogenetic analyses using maximum parsimony （MP）, maximum likelihood （ML）, and Bayesian retrieved similar topology. Within the Cyprinidae, Leuciscini and Barbini formed the monophyletic lineage respectively with high nodal supports. Leuciscini comprises Xenocyprinae, CuItrinae, East Asian species of Leuciscinae and Danioninae, Gobioninae and Acheilognathinae, and Barbini contains Schizothoracinae, Barbinae, Cyprininae and Labeoninae. Danio rerio, D. myersi and Rasbora trilineata were supposed to separate from Leuciscinae and Barbini and to form another lineage. The positions of some Danioninae species were still unresolved. Analyses of both amino acid variation with parsimony information and two high variation regions indicated that there is no correlation between variations of single amino acid or high variation regions and characteristic size of cyprinids. In addition, the species with smaller size were usually found to be basal within clades in the tree, which might be the results of the adaptation to the primitive ecology and survival pressure.     

A forensic method for efficient file extraction in HDFS based on three-level mapping

The large scale and distribution of cloud computing storage have become the major challenges in cloud forensics for file extraction. Current disk forensic methods do not adapt to cloud computing well and the forensic research on distributed file system is inadequate. To address the forensic problems, this paper uses the Hadoop distributed file system (HDFS) as a case study and proposes a forensic method for efficient file extraction based on three-level (3L) mapping. First, HDFS is analyzed from overall architecture to local file system. Second, the 3L mapping of an HDFS file from HDFS namespace to data blocks on local file system is established and a recovery method for deleted files based on 3L mapping is presented. Third, a multi-node Hadoop framework via Xen virtualization platform is set up to test the performance of the method. The results indicate that the proposed method could succeed in efficient location of large files stored across data nodes, make selective image of disk data and get high recovery rate of deleted files.     

Biomimetic fluorapatite films for conservation of historic calcareous stones

Fluorapatite protective films were prepared on marble substrates using a biomimetic method. By mimicking the mineralization mechanism of enamel, phosphorus and fluorine were introduced on the surface of the marble substrate. In the presence of a biological template, namely collagen, an integrated fluorapatite film was produced and the marble substrate was entirely covered. The prepared fluorapatite films were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy dispersive X-ray (EDX) spectroscopy. The performances of the fluorapatite films were evaluated by color changes, capillary water absorption, and acid resistance tests. The results revealed that the fluorapatite films had good compatibility with the marble substrate; the physical properties such as color and capillary water adsorption of the marble substrates were unchanged. The fluorapatite films also had good acid resistance and were stable even in heavy acid rain.     

Measurement of Magnetization Curve and Magnetic Relaxation for 2H-NbSe2 Crystals

The characteristics of electronic transport properties: behaviors of magnetization curve and magnetic relaxation of a typical normal superconductor 2H-NbSe2 are investigated. The results show that Tc and △Tc of the samples are 7. 2,0. 18 K, indicating that superconducting energy gap at zero temperature is 1. 1 meV. No fish tail shape is found in the magnetization curves at several temperatures. The relationship between remnant magnetic moment and time reveals that the magnetic flux creep of the sample agrees with the Kim-Anderson thermal activation model with the relaxation rate S=0.000 36 at T=6 K.