An Efficient Provable Data Possession based on Elliptic Curves in Cloud Storage

Hongyuan Wang,Liehuang Zhu,Feng Wang,Yijia Lilong,Yu Chen,Chang Liu 보안공학연구지원센터 2014 International Journal of Security and Its Applicat Vol.8 No.5

A hybrid identification method on butterfly optimization and differential evolution algorithm

Hongyuan Zhou,Guangcai Zhang,Xiaojuan Wang,Pinghe Ni,Jian Zhang 국제구조공학회 2020 Smart Structures and Systems, An International Jou Vol.26 No.3

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

Evolutionary Neural Network based on Quantum Elephant Herding Algorithm for Modulation Recognition in Impulse Noise

( Hongyuan Gao ),( Shihao Wang ),( Yumeng Su ),( Helin Sun ),( Zhiwei Zhang ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.7

In this paper, we proposed a novel modulation recognition method based on quantum elephant herding algorithm (QEHA) evolving neural network under impulse noise environment. We use the adaptive weight myriad filter to preprocess the received digital modulation signals which passing through the impulsive noise channel, and then the instantaneous characteristics and high order cumulant features of digital modulation signals are extracted as classification feature set, finally, the BP neural network (BPNN) model as a classifier for automatic digital modulation recognition. Besides, based on the elephant herding optimization (EHO) algorithm and quantum computing mechanism, we design a quantum elephant herding algorithm (QEHA) to optimize the initial thresholds and weights of the BPNN, which solves the problem that traditional BPNN is easy into local minimum values and poor robustness. The experimental results prove that the adaptive weight myriad filter we used can remove the impulsive noise effectively, and the proposed QEHA-BPNN classifier has better recognition performance than other conventional pattern recognition classifiers. Compared with other global optimization algorithms, the QEHA designed in this paper has a faster convergence speed and higher convergence accuracy. Furthermore, the effect of symbol shape has been considered, which can satisfy the need for engineering.

Portal Absorption of Feed Oligo-peptides in Chickens

Wang, Lijuan,Ma, Qiugang,Cheng, Ji,Guo, Baohai,Yue, Hongyuan Asian Australasian Association of Animal Productio 2004 Animal Bioscience Vol.17 No.9

The effect of duodenal infusion with feed oligo-peptide solution on portal absorption of amino acids was investigated in poultry under unanaesthetized conditions. Four peptide solutions were used in the experiment: enzymatic hydrolysates from fish meal, soybean meal, cottonseed meal and rapeseed meal proteins with average molecular weights less than 3,000 Da and 1,000 Da, respectively. Intestinal absorptions of these oligo-peptide solutions were compared by determining the concentration of free amino acid (FAA) in portal blood after the duodenal administrations of oligo-peptide solutions. Absorptive intensity and balance were used to estimate the intestinal absorption rate of amino acids. The absorptive intensities of amino acids were highest for the fish and soybean meal oligo-peptides. The ratios of amino acids absorbed in the portal blood from fish and soybean meal oligo-peptides were more similar to the composition of the infused amino acids than that observed from the cottonseed and rapeseed meal oligo-peptides. A positive correlation was found between absorption rate and proportion of PAA in the oligo-peptides. The higher absorption rate could be contributed to the higher proportion of peptide bound amino acids (PAA). The results suggest that fish and soybean meal protein are significantly more easily hydrolyzed into oligo-peptides (p<0.05) in the gastrointestinal tracts of poultry and as such can be utilized more effectively by body tissues.

Tough antifouling organogels reinforced by the synergistic effect of oleophobic and dipole–dipole interactions

Liangpeng Zeng,Hongyuan Cui,Yi Liu,Xinxing Lin,Ziang Wang,Hui Guo,Wei-Hua Li 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.114 No.-

Slippery organogels have gained increasing interest as competitive candidates for antifouling applications. However, it remains challenging to develop tough organogels suitable for fouling resistance indynamic and flexible application scenarios. Herein, a kind of physically crosslinked organogels with acombination of desirable properties, including high toughness, transparency, surface slipperiness, andfouling resistance is developed. The representative pAL organogels, constructed by poly(acrylonitrileco-lauryl acrylate) (pAL) copolymer and infiltrated with n-hexadecane as a lubricating solvent, possesshigh tensile fracture stress, fracture strain, Young’s modulus, and toughness of 4.28 MPa, 517%,2.52 MPa, and 11.19 MJ m3. In the organogels, the polar cyano groups from the pAN segments serveas physical cross-linking points, where the synergistic effects played by oleophobic and dipole–dipoleinteractions significantly toughen the materials. Meanwhile, the soft oleophilic poly(lauryl acrylate)chains offer considerable solvent content, giving rise to satisfactory surface slipperiness. Therefore, theorganogels bring about a 57.16% and 81.50% reduction of protein and bacteria adhesion in comparisonto the control. The satisfactory antifouling performance has been further confirmed with Spirulina platensis. It is deemed that this organogel may provide great potential for various applications in the future suchas anti-adhesion materials and self-cleaning coating.

Mediastinal Emphysema, Giant Bulla, and Pneumothorax Developed during the Course of COVID-19 Pneumonia

Ruihong Sun,Hongyuan Liu,Xiang Wang 대한영상의학회 2020 Korean Journal of Radiology Vol.21 No.5

The coronavirus disease 2019 (COVID-19) pneumonia is a recent outbreak in mainland China and has rapidly spread to multiple countries worldwide. Pulmonary parenchymal opacities are often observed during chest radiography. Currently, few cases have reported the complications of severe COVID-19 pneumonia. We report a case where serial follow-up chest computed tomography revealed progression of pulmonary lesions into confluent bilateral consolidation with lower lung predominance, thereby confirming COVID-19 pneumonia. Furthermore, complications such as mediastinal emphysema, giant bulla, and pneumothorax were also observed during the course of the disease.

Impact response of a novel flat steel-concrete-corrugated steel panel

Jingyi Lu,Yonghui Wang,Ximei Zhai,Hongyuan Zhou 국제구조공학회 2022 Steel and Composite Structures, An International J Vol.42 No.2

A novel flat steel plate-concrete-corrugated steel plate (FS-C-CS) sandwich panel was proposed for resisting impact load. The failure mode, impact force and displacement response of the FS-C-CS panel under impact loading were studied via drop-weight impact tests. The combined global flexure and local indentation deformation mode of the FS-C-CS panel was observed, and three stages of impact process were identified. Moreover, the effects of corrugated plate height and steel plate thickness on the impact responses of the FS-C-CS panels were quantitatively analysed, and the impact resistant performance of the FS-C-CS panel was found to be generally improved on increasing corrugated plate height and thickness in terms of smaller deformation as well as larger impact force and post-peak mean force. The Finite Element (FE) model of the FS-C-CS panel under impact loading was established to predict its dynamic response and further reveal its failure mode and impact energy dissipation mechanism. The numerical results indicated that the concrete core and corrugated steel plate dissipated the majority of impact energy. In addition, employing end plates and high strength bolts as shear connectors could prevent the slip between steel plates and concrete core and assure the full composite action of the FS-C-CS panel.

Finite Horizon Robust Optimal Tracking Control Based on Approximate Dynamic Programming for Switched Systems with Uncertainties

Shangwei Zhao,Jingcheng Wang,Haotian Xu,Hongyuan Wang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.4

In this paper, an approximate dynamic programming (ADP)-based approach is developed to handle the robust optimal tracking control problem for switched systems with uncertainties in the finite horizon. The switched systems with unknown matched uncertainties are formulated by virtue of system dynamics and reference trajectory, where the complicated tracking problem is converted to a stabilizing robust optimal control problem. To avoid the requirement of system dynamics knowledge, a neural network (NN)-based identifier is utilized to estimate the unknown switched systems dynamics. The actor-critic NNs are constructed to approximate the optimal control input and the corresponding performance index, where the weights are trained backward-in-time in an off-line manner. Benefiting from the Lipschitz continuous condition, the convergence of the proposed approach is proved, which illustrates the iteration approach will converge to the unique solution under a small enough sampling time interval. Finally, two numerical simulation cases are employed to verify the effectiveness of the proposed approach.

Output-only structural damage detection under multiple unknown white noise excitations

Pinghe Nia,Xiaojuan Wang,Hongyuan Zhou 국제구조공학회 2021 Structural Engineering and Mechanics, An Int'l Jou Vol.79 No.3

Most of the existing output-only damage detection methods require the number of sensors should be larger than the number of unknown excitation force, and the force location should be available. This paper presents a novel output-only damage detection method without these requirements. The proposed method is based on the correlation function of acceleration responses. When the structure is under white noise excitations (or ambient excitations), the correlation function of acceleration responses can be treated as free vibration responses with unknown initial conditions. The unknown structural parameters and initial conditions can be simultaneously identified by minimizing the difference between the measured and calculated correlation functions. The unknown initial conditions are identified with state space method and the unknown structural parameters are updated with sensitivity method. Numerical studies of a 2D truss and a five-bay 3D frame structure are conducted to demonstrate the accuracy, effectiveness, and robustness of the proposed method. Experimental studies on an eight-floor steel frame are further carried out. Results show that the proposed method is not only insensitive to environmental noise but also applicable when the number of sensors is less than that of unknown excitations. Also, the proposed method can be used for damage detection when the force location is unknown.

Human Activities Recognition Based on Skeleton Information via Sparse Representation

Suolan Liu,Lizhi Kong,Hongyuan Wang 한국정보과학회 2018 Journal of Computing Science and Engineering Vol.12 No.1

Human activities recognition is a challenging task due to its complexity of human movements and the variety performed by different subjects for the same action. This paper presents a recognition algorithm by using skeleton information generated from depth maps. Concatenating motion features and temporal constraint feature produces feature vector. Reducing dictionary scale proposes an improved fast classifier based on sparse representation. The developed method is shown to be effective by recognizing different activities on the UTD-MHAD dataset. Comparison results indicate superior performance of our method over some existing methods.