In recent years, plenty of advanced approaches for universal JPEG image steganalysis have been proposed due to the need of commercial and national security. Recently, a novel sparse-representation-based method was proposed, which applied sparse coding to image steganalysis [4]. Despite satisfying experimental results, the method emphasized too much on the role of l 1 -norm sparsity, while the effort of collaborative representation was totally ignored. In this paper, we focus on the least square problem in a binary classification model and present a similar yet much more efficient JPEG image steganalysis method based on collaborative representation. We still represent a testing sample collaboratively over the training samples from both classes (cover and stego), while the regularization term is changed from l 1 -norm to l 2 -norm and each class-specific representation residual owns an extra divisor. Experimental results show that our proposed steganalysis method performs better than the recently presented sparse-representation-based method as well as the traditional SVM-based method. Extensive experiments clearly show that our method has very competitive steganalysis performance, while it has significantly less complexity.
ZnO nanowires have been successfully fabricated on Si substrate by simple thermal evaporation of Zn powder under air ambient without any catalyst. Morphology and structure analyses indicated that ZnO nanowires had high purity and perfect crystallinity. The diameter of ZnO nanowires was 40 to 100 nm, and the length was about several tens of micrometers. The prepared ZnO nanowires exhibited a hexagonal wurtzite crystal structure. The growth of the ZnO nanostructure was explained by the vapor-solid mechanism. The simplicity, low cost and fewer necessary apparatuses of the process would suit the high-throughput fabrication of ZnO nanowires. The ZnO nanowires fabricated on Si substrate are compatible with state-of-the-art semiconductor industry. They are expected to have potential applications in functional nanodevices.
We report a remarkable improvement of photoluminescence from ZnO-core/a-SiN(x):H-shell nanorod arrays by modulating the bandgap of a-SiN(x):H shell. The a-SiN(x):H shell with a large bandgap can significantly enhance UV emission by more than 8 times compared with the uncoated ZnO nanorods. Moreover, it is found that the deep-level defect emission can be almost completely suppressed for all the core-shell nanostructures, which is independent of the bandgaps of a-SiN(x):H shells. Combining with the analysis of infrared absorption spectrum and luminescence characteristics of NH(x)-plasma treated ZnO nanorods, the improved photoluminescence is attributed to the decrease of nonradiative recombination probability and the reduction of surface band bending of ZnO cores due to the H and N passivation and the screening effect from the a-SiN(x):H shells. Our findings open up new possibilities for fabricating stable and efficient UV-only emitting devices.
The influence of N incorporation on the optical properties of Si-rich a-SiCx films deposited by very high-frequency plasma-enhanced chemical vapor deposition (VHF PECVD) was investigated. The increase in N content in the films was found to cause a remarkable enhancement in photoluminescence (PL). Relative to the sample without N incorporation, the sample incorporated with 33% N showed a 22-fold improvement in PL. As the N content increased, the PL band gradually blueshifted from the near-infrared to the blue region, and the optical bandgap increased from 2.3 eV to 5.0 eV. The enhancement of PL was suggested mainly from the effective passivation of N to the nonradiative recombination centers in the samples. Given the strong PL and wide bandgap of the N incorporated samples, they were used to further design an anti-counterfeiting label.
Nanocrystalline silicon films were prepared from SiH4 highly diluted with hydrogen by plasma enhanced chemical vapor deposition. The influence of excitation frequency on their growth properties was investigated. The cross-section transmisson electron microscopy images show that all the films grow with certain fastigiated structure in the crystalline region. However, the films deposited at 13.56 MHz undergo a transition from amorphous incubation layer to crystalline structure. In contrast, for the films deposited at a high excitation frequency (40.68 MHz), nanocrystalline silicon grains can directly grow on the amorphous substrates. Furthermore, the results of Raman spectra and Fourier transform infrared spectroscopy manifest that the nanocrystalline silicon films deposited at high excitation frequency (40.68 MHz) possess high crystalline fraction, low hydrogen content and small microstructure factor.
Online shopping is becoming more and more popular for a number of reasons; prices are often lower online, you don't have to queue up in busy shops and you can buy almost any product imaginable with just a few clicks of your mouse. But the general problems of shopping Web site is that, most of the existing online shops list products based on keywords. As the inherent limitation, keyword browsing makes it difficult to find the exact products that human being desire. In this paper, we propose a visual search algorithm based on contour salient. The proposed approach extracts the object edge using Canny edge detector, and then chooses the salient point from the contour based on the points' contour flexibility. We perform Fourier transformation to these salient points and a shape normalization procedure to generate the descriptor representing the shape feature. Finally, SVM and dynamic time warping method are used to train the database images and compute the distance between query image and test image. Experimental result shows our method is effective to search the similar product images with query.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)