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1 Two-level image authentication by two-step phase-shifting interferometry and compressive sensing 2017-08-12             

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Publication date: January 2018
Source:Optics and Lasers in Engineering, Volume 100

Author(s): Xue Zhang, Xiangfeng Meng, Yongkai Yin, Xiulun Yang, Yurong Wang, Xianye Li, Xiang Peng, Wenqi He, Guoyan Dong, Hongyi Chen

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.





2 Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing 2017-08-12             

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Publication date: 1 February 2018
Source:Mechanical Systems and Signal Processing, Volume 100

Author(s): Haidong Shao, Hongkai Jiang, Haizhou Zhang, Wenjing Duan, Tianchen Liang, Shuaipeng Wu

The vibration signals collected from rolling bearing are usually complex and non-stationary with heavy background noise. Therefore, it is a great challenge to efficiently learn the representative fault features of the collected vibration signals. In this paper, a novel method called improved convolutional deep belief network (CDBN) with compressed sensing (CS) is developed for feature learning and fault diagnosis of rolling bearing. Firstly, CS is adopted for reducing the vibration data amount to improve analysis efficiency. Secondly, a new CDBN model is constructed with Gaussian visible units to enhance the feature learning ability for the compressed data. Finally, exponential moving average (EMA) technique is employed to improve the generalization performance of the constructed deep model. The developed method is applied to analyze the experimental rolling bearing vibration signals. The results confirm that the developed method is more effective than the traditional methods.

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3 Research on barker coded excitation method for magneto-acoustic imaging 2017-08-11             

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Publication date: January 2018
Source:Biomedical Signal Processing and Control, Volume 39

Author(s): Shunqi Zhang, Xiaoqing Zhou, Shikun Liu, Tao Yin, Zhipeng Liu

Functional imaging method of biological electrical characteristics based on magneto-acoustic effect gives valuable information of tissue in early tumor diagnosis. Common exciting and measuring method is to use single pulse. The imaging quality and the imaging speed are limited by the signal to noise ratio (SNR). In this study, we propose a processing method based on coded excitation and pulse compression to improve SNR of magneto-acoustic imaging. Barker code is widely used in ultrasonic signal processing, which can effectively improve the signal to noise ratio. It is introduced to increase SNR of the magneto-acoustic signal. Simulations on magneto-acoustic signal and pulse compressed signal under Barker coded excitation with a group of bit lengths are computed. Experiments on sample made of pork and graphite slices are done to validate the proposed coded excitation method. The pork sample is imaged to validate this method. SNR is investigated using Barker codes with different bits. The results showed, the SNR of magneto-acoustic signal is improved by the coded excitation. When 13 bit Barker code mode is adopted as the exciting signal, SNR improved by 21.5dB. For a similar SNR improvement, the processing time of coded excitation method can be shortened by 95.8% compare with single pulse excitation method. In a conclusion, the coded excitation method is effective to improve the magneto-acoustic signal SNR and imaging quality. It also improves the magneto-acoustic imaging speed.





4 Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging 2017-08-11             

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Publication date: January 2018
Source:Optics and Lasers in Engineering, Volume 100

Author(s): Sheng Yuan, Yangrui Yang, Xuemei Liu, Xin Zhou, Zhenzhuo Wei

An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.





5 Fluorescence emission induced by the femtosecond filament transmitting through the butane/air flame 2017-08-06             

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Publication date: 15 January 2018
Source:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, Volume 189

Author(s): Suyu Li, Yanhua Li, Zhe Shi, Laizhi Sui, He Li, Qingyi Li, Anmin Chen, Yuanfei Jiang, Mingxing Jin

We measure the backward fluorescence spectra generated by the femtosecond filament transmitting through the butane/air flame, and study the fluorescence emission from combustion intermediates (CN, CH and C2 radicals), air (mainly N2 and N2 +). It is found that the fluorescence emission from combustion intermediates, N2 and N2 + shows difference when the femtosecond filament transmits through different parts of the butane/air flame, and we attempt to analyze it in this paper. This study demonstrates that the filament-induced fluorescence technique can be utilized to sense the combustion intermediates.

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6 Hierarchical ELM ensembles for visual descriptor fusion 2017-08-05             

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Publication date: May 2018
Source:Information Fusion, Volume 41

Author(s): Stevica Cvetković, Miloš B. Stojanović, Saša V. Nikolić

Extreme Learning Machines (ELM) have been successfully applied to variety of classification problems by utilizing a single descriptor type. However, a single descriptor may be insufficient for the visual classification task, due to the high level of intra-class variability coupled with low inter-class distance. Although several studies have investigated methods for combining multiple descriptors by ELM, they predominantly apply a simple concatenation of descriptors before classifying them. This type of descriptor fusion may impose problems of descriptor compatibility, high dimensionality and restricted accuracy. In this paper, we propose a hierarchical descriptors fusion strategy at the decision level (“late-fusion”), which relies on ELM ensembles (ELM-E). The proposed method, denoted as H-ELM-E, effectively combines multiple complementary descriptors by a two-level ELM-E based architecture, which ensures that a more informative descriptors will gain more impact on the final decision. In the first level, a separate ELM-E classifier is trained for every image descriptor. In the second level, the output scores from the previous level are aggregated into the mid-level representation which is conducted to an additional ELM-E classifier. The exhaustive experimental evaluation confirmed that the proposed hierarchical ELM-E based strategy is superior to the single-descriptor methods as well as “early fusion” of multiple descriptors, for the visual classification task. Additionally, it was shown that significant accuracy improvement is achieved by integrating ensembles of ELM as a basic classifier, instead of using a single ELM.





7 Cross-talk free selective reconstruction of individual objects from multiplexed optical field data 2017-08-04             

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Publication date: January 2018
Source:Optics and Lasers in Engineering, Volume 100

Author(s): Alejandro Velez Zea, John Fredy Barrera, Roberto Torroba

In this paper we present a data multiplexing method for simultaneous storage in a single package composed by several optical fields of tridimensional (3D) objects, and their individual cross-talk free retrieval. Optical field data are extracted from off axis Fourier holograms, and then sampled by multiplying them with random binary masks. The resulting sampled optical fields can be used to reconstruct the original objects. Sampling causes a loss of quality that can be controlled by the number of white pixels in the binary masks and by applying a padding procedure on the optical field data. This process can be performed using a different binary mask for each optical field, and then added to form a multiplexed package. With the adequate choice of sampling and padding, we can achieve a volume reduction in the multiplexed package over the addition of all individual optical fields. Moreover, the package can be multiplied by a binary mask to select a specific optical field, and after the reconstruction procedure, the corresponding 3D object is recovered without any cross-talk. We demonstrate the effectiveness of our proposal for data compression with a comparison with discrete cosine transform filtering. Experimental results confirm the validity of our proposal.





8 Ultra-sensitive NH3 sensor based on flower-shaped SnS2 nanostructures with sub-ppm detection ability 2017-08-02             

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Publication date: 5 November 2018
Source:Journal of Hazardous Materials, Volume 341

Author(s): Ya Xiong, Wangwang Xu, Degong Ding, Wenbo Lu, Lei Zhu, Zongye Zhu, Ying Wang, Qingzhong Xue

Layered metal dichalcogenides (LMDs) semiconducting materials have recently attracted tremendous attention as high performance gas sensors due to unique chemical and physical properties of thin layers. Here, three-dimensional SnS2 nanoflower structures assembled with thin nanosheets were synthesized via a facile solvothermal process. When applied to detect 100ppm NH3 at 200°C, the SnS2 based sensor exhibited high response value of 7.4, short response/recovery time of 40.6s/624s. Moreover, the sensor demonstrated a low detection limit of 0.5ppm NH3 and superb selectivity to NH3 against CO2, CH4, H2, ethanol and acetone. The excellent performance is attributed to the unique thin layers assembled flower-like nanoarchitecture, which facilitates both the carrier charge transfer process and the adsorption/desorption reaction. More importantly, it was found that the sensor response enhanced with increasing oxygen content in background and was improved by 3.57 times with oxygen content increasing from 0 to 40%. The increased response is owing to the enhanced binding energies between SnS2 and NH3 moleculers. Theoretically, density functional theory was employed to reveal the NH3 adsorption mechanism in different background oxygen contents, which opens a new horizon for LMD based structures applied in various gas sensing fields.

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9 The interaction between predator strategy and prey competition in a pair of multi-predator multi-prey lattices 2017-08-01             

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Publication date: March 2018
Source:Communications in Nonlinear Science and Numerical Simulation, Volume 56

Author(s): Gavin M. Abernethy, Mark McCartney, David H. Glass

A computational study of a system of ten prey phenotypes and either one or ten predator phenotypes with a range of foraging behaviours, arranged on two separate one-dimensional lattices, is presented. Mutation between nearest neighbours along the prey lattice occurs at a constant rate, and mutation may or may not be enabled for the predators. The significance of competition amongst the prey is investigated by testing a variety of distributions of the relative intraspecific and interspecific competition. We also study the influence this has on the survival and population size of predator phenotypes with a variety of foraging strategies. Our results indicate that the distribution of competition amongst prey is of little significance, provided that intraspecific is stronger than the interspecific, and that it is typically preferable for a predator to adopt a foraging strategy that scales linearly with prey population sizes if it is alone. In an environment of multiple predator phenotypes, the least or most-focused predators are most likely to persist, dependent on the feeding parameter.





10 Chapter 15 Bending of open and closed, thin-walled beams 2017-08-01             

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Publication date: 2018
Source:Introduction to Aircraft Structural Analysis

Author(s): T.H.G. Megson

Expressions for the direct stress distributions and the displacements due to the bending of symmetrical and unsymmetrical section beams are derived. Anticlastic bending is discussed and the sign conventions and notation established. A method for the resolution of bending moments is presented and load intensity, shear force and bending moment relationships obtained; illustrative examples on their use are given. The use of singularity functions is described and these are then applied to the solution of beam deflection problems. Beam section properties are calculated and the approximations used to calculate the properties of thin-walled sections included. The application of bending theory is discussed and the effect of temperature variation on thin-walled beam sections is investigated.





 
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