Reversible Watermarking with Adaptive Embedding Threshold Matrix

( Guangyong Gao ),( Yun-qing Shi ),( Xingming Sun ),( Caixue Zhou ),( Zongmin Cui ),( Liya Xu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.9

In this paper, a new reversible watermarking algorithm with adaptive embedding threshold matrix is proposed. Firstly, to avoid the overflow and underflow, two flexible thresholds, TL and TR, are applied to preprocess the image histogram with least histogram shift cost. Secondly, for achieving an optimal or near optimal tradeoff between the embedding capacity and imperceptibility, the embedding threshold matrix, composed of the embedding thresholds of all blocks, is determined adaptively by the combination between the composite chaos and the average energy of Integer Wavelet Transform (IWT) block. As a non-liner system with good randomness, the composite chaos is suitable to search the optimal embedding thresholds. Meanwhile, the average energy of IWT block is calculated to adjust the block embedding capacity, and more data are embedded into those IWT blocks with larger average energy. The experimental results demonstrate that compared with the state-of-the-art reversible watermarking schemes, the proposed scheme has better performance for the tradeoff between the embedding capacity and imperceptibility.

Fatigue optimization with combined ensembles of surrogate modeling for a truck cab

Jianguang Fang,Yunkai Gao,Guangyong Sun,Chengmin Xu,Qing Li 대한기계학회 2014 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.28 No.11

In this study, we propose the ensembles of surrogates for an industrial application of fatigue optimization problem that aims to maximizea truck cab’s fatigue life. After validating the numerical model, different ensembles of surrogates comprised polynomial responsesurface (PRS), radial basis function (RBF) and Kriging (KRG) models are established to approximate the fatigue life function. A hybridPSO algorithm, which integrates the standard PSO with sequential quadratic programming (SQP), is implemented here to seek a quasiglobaloptimum. Compared with individual surrogates, the ensembles of surrogates can attain more competent optima and yield a smallersurrogate error at the optimal point. Moreover, the hybrid PSO technique proves to search the better optima than the standard PSO in thefatigue optimization problem considered. Finally, it is found that a more accurate surrogate model may not necessarily produce a betteroptimum for the ensembles of surrogates, thus multiple ensembles are recommended without increasing much extra computational cost.

Incremental Strategy-based Residual Regression Networks for Node Localization in Wireless Sensor Networks

Dongyao Zou,Guohao Sun,Zhigang Li,Guangyong Xi,Liping Wang 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.8

The easy scalability and low cost of range-free localization algorithms have led to their wide attention and application in node localization of wireless sensor networks. However, the existing range-free localization algorithms still have problems, such as large cumulative errors and poor localization performance. To solve these problems, an incremental strategy-based residual regression network is proposed for node localization in wireless sensor networks. The algorithm predicts the coordinates of the nodes to be solved by building a deep learning model and fine-tunes the prediction results by regression based on the intersection of the communication range between the predicted and real coordinates and the loss function, which improves the localization performance of the algorithm. Moreover, a correction scheme is proposed to correct the augmented data in the incremental strategy, which reduces the cumulative error generated during the algorithm localization. The analysis through simulation experiments demonstrates that our proposed algorithm has strong robustness and has obvious advantages in localization performance compared with other algorithms.

Experimental and Numerical Research on Process Formability in Magnetic Pulse Forming of AZ31 Magnesium Alloy Sheets

Jun-Rui Xu,Jun-Jia Cui,Guangyong Sun,Yan-Rong Li,Chun-Feng Li 한국정밀공학회 2015 International Journal of Precision Engineering and Vol. No.

The plain strain of AZ31 magnesium alloy sheet in magnetic pulse forming was investigated by numerical simulation and experimental method. Combination of uniform pressure coil and Holmberg's specimen was employed to evaluate the plain strain of AZ31 sheet. The numerical simulation for magnetic pulse plain strain of AZ31 sheet is performed by means of ANSYS FEA software. The magnetic flux density of uniform pressure coil was distributed uniformly, especially at the center of gauged area of AZ31 sheet directly in relation to the deformation behavior of AZ31 sheet. The velocity of typical point increases as increasing energy, and the more position closes to the center of sheet the higher velocity achieves. The forming height is increased with increasing discharge voltage. Compared with C=768 μF and C=1536 μF, the capacitance of 1152 μF is more effective for forming, which is confirmed by experiments. The peak velocity at the center of sheet is about 105 m/s. The major strains of magnetic pulse plane strain lie approximately in the strain ranges of 5.83-6.45%. However, the 3.22-3.82% (major strain) are the limit strains in quasi-static condition. The experimental results indicate that the major strain of AZ31 sheet improves about 75% compared with the quasi-static case.

Fingerprint Liveness Detection Using Difference Co-occurrence Matrix Based Texture Features

Zhihua Xia,Chengsheng Yuan,Xingming Sun,Rui Lv,Decai Sun,Guangyong Gao 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.11

Fingerprint authentication systems have been widely deployed in both civilian and government applications, however, whether fingerprint authentication systems is security or not has been an important issue under fraudulent attempts through artificial spoof fingerprints. In this paper, inspired by popular feature descriptors such as gray level co-occurrence matrix (GLCM) and Gradient (difference matrix (DM)), we propose a novel software-based fingerprint liveness detection algorithm called difference co-occurrence matrix (DCM). In doing so, quantization operation is firstly conducted on the images. DMs are constructed by calculating difference matrices of horizontal and vertical pixel values of images; difference co-occurrence arrays are constructed from the difference matrices between adjacent pixels. To reduce the influence of abnormal pixel values, truncation is used for DMs. Then, we compute four parameters (Angular Second Moment, Entropy, Inverse Differential Moment and Correlation) used as feature vectors of fingerprint images. For the first time in the fingerprint liveness detection, we construct eight difference co-occurrence matrices and extract texture features from processed DCMs. Finally, SVM classifier is used to predict classification accuracy. The experimental results reveal that our proposed method can achieve more accurate classification compared with the best algorithms of 2013 Fingerprint Liveness Detection Competition, while being able to recognize spoofed fingerprints with a better degree of accuracy.

On functionally-graded crashworthy shape of conical structures for multiple load cases

Tong Pang,Yinfeng Li,Hehe Kang,Guangyong Sun,Jianguang Fang,Qing Li 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.6

Many studies on energy absorbers have been focused on tapered tubes because they have significant advantages in crashworthinessand provide a desired constant load-deflection response. However, few studies have been reported on tapered tubes with nonlinearlyvariablediameters along the longitudinal direction. This paper presents thin-walled Functionally graded tapered tube (FGTT) with a diametervarying nonlinearly subject to axial (0°) and oblique (10°, 20°, 30°) impacts. To explore the advantages of FGTT, conventionalStraight/Conical circular tube (SCT/CCT) with the same mass are compared; and FGTTs with a gradient exponent n > 1 are found to bepreferable to others in terms of energy absorption capacity under small impact angles. Then, crashworthiness analyses of different crushingdistances are conducted and it is found that under a large impact angle (e.g. 20°, 30°), FGTT with a short crushing distance (e.g. 40mm) have a higher mean crashing force than long crushing distance (e.g. 120 mm), especially for n > 1. In addition, the effect of geometricparameters, such as the gradient exponent n and diameter range ΔD between top (incident) and bottom (distal) diameters of FGTTs,are also studied and it is found that the FGTT with ΔD = 40 mm and n > 1 exhibits better crashworthiness than the others under smallimpact angles (0°, 10°). This paper demonstrates that such FGTT structures have a certain potential to be an energy absorber.