Hybridizing Adaptive Genetic Algorithm with Chaos Searching Technique for Numerical Optimization

Dongping Tian 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.2

Genetic algorithm (GA) is a population-based approach for heuristic search in optimi- zation problems based on the principle of biologic evolution and natural selection. In this paper, we present a hybrid adaptive genetic algorithm with chaos searching technique for numerical optimization. On the one hand, two sets of crossover and mutation rates are for- mulated to automatically maintain the balance between exploration and exploitation during the genetic search process. On the other hand, the chaos searching technique is introduced into the adaptive genetic algorithm based on the decision mechanism for premature conver- gence adopted in this paper, whose main goal is to avoid being trapped into the local opti- mum. In addition, half of the total evolutionary generation is utilized as one of the decision conditions so as to speed up the convergent process. To validate the effectiveness and efficiency of the proposed approach, we apply it to four benchmark functions obtained from the literature, and the experimental results show that the proposed algorithm can find global optimal or the closer-to-optimal solutions and have faster search speed as well as higher convergence rate.

Particle Swarm Optimization with Chaotic Maps and Gaussian Mutation for Function Optimization

Dongping Tian 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.4

Particle swarm optimization (PSO) is a population-based stochastic optimization that has been widely applied to a variety of problems. However, it is easily trapped into the local optima and appears premature convergence during the search process. To address these problems, we propose a new particle swarm optimization by introducing chaotic maps (tent map and logistic map) and Gaussian mutation into the PSO algorithm. On the one hand, the chaotic map is employed to initialize uniform distributed particles so as to improve the quality of the initial population, which is a simple yet very efficient method to improve the quality of initial population. On the other hand, the Gaussian mutation mechanism based on the maximal focus distance is adopted to help the algorithm escape from the local optima and make the particles proceed with searching in other regions of the solution space until the global optimal or the closer-to-optimal solutions can be found. Experimental results on two benchmark functions demonstrate the effectiveness and efficiency of the PSO algorithm proposed in this paper.

An experimental study of a spring-loaded needle-free injector: Influence of the ejection volume and injector orifice diameter

Dongping Zeng,Ni Wu,Lu Xie,Xiaoxiao Xia,Yong Kang 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.11

Needle-free injection is an alternative strategy to conventional needle injection in the field of drug delivery. This approach offers a number of advantages, especially in reducing complaints of needle phobia and avoiding the occurrence of accidental needle stick injuries. The ejection volume and orifice diameter are inherently important in determining the injection depth and percent delivery. In this study, we investigate the dispersion pattern of liquid penetration into gels and porcine tissues using a needle-free injector with ejection volumes of 0.05 to 0.35 mL and orifice diameters of 0.17 to 0.50 mm. In addition, the influence of the two parameters is analyzed quantitatively on the dispersion pattern through impact experiments and injection experiments. Furthermore, an equation of the jet power calculated by the ejection volume and orifice diameter is proposed to describe the delivery fraction of the injection experiments. Controls of the ejection volume and orifice diameter are demonstrated to help achieve a more effective injection process and a better injection experience.

Experimental investigation on penetration performance of larger volume needle-free injection device

Dongping Zeng,Ni Wu,Lei Qian,Hanqing Shi,Yong Kang 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.9

The injection performance of a small volume of needle-free injection (up to 0.3 mL) has proven to be controllable and satisfactory in transdermal drug delivery. However, no comprehensive research on the behavior of larger volume injections with different requirements for clinical applications exists. This study aims to present the penetration characteristics of larger volume injections, including dynamic properties, dispersion pattern, and percent delivery. The researchers conduct impact and injection experiments with injection volumes from 0.1-1.0 mL, driving pressures of 0.5-1.75 MPa, and orifice diameters of 0.17-0.5 mm. This study uses high-speed photography and impact experiments to capture the dynamic properties of the liquid jet. The researchers observe the dispersion patterns of liquid penetration into the gels in the gel injection experiments and investigate the percentages of liquid delivered to the skin tissues in porcine tissues injection experiments. Moreover, this study uses the response surface methodology (RSM) to analyze the interactive effect between various injection parameters on the injection performance. Results describe the differences in penetration performance between larger volume injections and small volume injections, and the critical volume of the mentioned injections is approximately 0.6 mL.

Multiple-shot People Re-identify based on Feature Selection with Sparsity

Dongping Zhang,Yanjie Li,Jiao Xu,Ye Shen 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.1

In a video surveillance network, it is always required to track and recognize people when they move through the environment. This paper presents a novel re-identification method for multiple-people using feature selection with sparsity. By using the multiple-shot approach, each of appearance models is created in this method. The human body is divided into five parts form which the features of color, height, gradient were extracted respectively. Our appearance model is represented by linear regression method. Experimental results show that our appearance model is robust and attain a high precision rate and processing performance.

Support Vector Machine for Automatic Image Annotation

Dongping Tian 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11

Automatic image annotation (AIA) is an active topic of research in computer vision and pattern recognition. In the last two decades, large amount of researches on AIA have been proposed, mainly including classification-based methods and probabilistic modeling methods. As one of the most common methods for AIA, support vector machine (SVM) has been widely applied in the multimedia research community, especially for image classification, image annotation and retrieval. However, compared with various SVM methods and their corresponding applications in the literature, there is almost no review research and analysis about SVM related studies. So the current paper, to start with, elaborates the basic principles of SVM. Followed by it summarizes SVM with applications to image annotation from three aspects of SVM ensemble for AIA, SVM with mixture of kernels for AIA and hybrid SVM for AIA respectively. In addition, SVM exploited in several other applications are also briefly reviewed. Finally, we end this paper with a summary of some important conclusions and highlight the potential research directions of SVM in automatic image annotation for the future.

Abnormal Crowd Motion Detection with Hidden Conditional Random Fields Model

Dongping Zhang,Kaihang Xu,Yafei Lu,Chen Pan,Huailiang Peng 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.10

Crowd motion analysis in public places is an important research subject in the monitoring field. This paper proposes an approach for detecting abnormal crowd motion using Hidden Conditional Random Fields Model (HCRF). This approach derives variations of motion patterns from direction distribution of the crowd motion obtained by the optical flow and these variations are encoded with HCRF to allow for the detection of abnormal crowd motion. Modeling the temporal neighborhood relations in a video sequence based on HCRF can incorporate hidden states and label the video depending on long range observations. The experimental results show that this proposed algorithm can achieve better results than HMM and CRF.

Characteristics and Mitigation Measures of Floor Heave in Operational High-Speed Railway Tunnels

Dongping Zhao,Haobo Fan,Lingli Jia 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.4

The rapid development of high-speed railway tunnels has resulted in the increased application of ballastless track slabs. However, floor heave induces ballastless track slab deformation as a result of surrounding rock pressure, imposing serious challenges to the safety of railway systems. In this study, the characteristic of floor heave was analyzed based on field monitoring data. A new tunnel lining structure was then proposed to reduce the effect of floor heave on the slab track. The stress and deformation characteristics of the lining structure under different floor heave loads were analyzed through three-dimensional load structure numerical simulation, and the adaptability of the new tunnel lining structure was numerically studied. The results show that the floor heave typically occurred in the deep-buried sections of tunnel and the maximum floor heave was less than 50 mm during the operation of high-speed railway tunnels. When the new type of tunnel lining was adopted, the influence of the floor heave on the slab track was very small due to the reserved groove of the upper part of the invert and the high rigidity of the steel-reinforced concrete slab, thus effectively reducing the deformation of the tunnel floor heave. This research can be beneficial in the structural design of high-speed railway tunnels and the prevention of tunnel floor heave.

LncRNA HOTAIRM1 knockdown inhibits cell glycolysis metabolism and tumor progression by miR-498/ABCE1 axis in non‐small cell lung cancer

Dongping Chen,Yashan Li,Yukang Wang,Jinlian Xu 한국유전학회 2021 Genes & Genomics Vol.43 No.2

Background Non-small cell lung cancer (NSCLC) is a major contributor of cancer-related mortality. Long non-coding RNAs (lncRNAs) are indicated to participate in the pathogenesis of NSCLC. Objective In this research, the efects of lncRNA HOXA transcript antisense RNA, myeloid-specifc 1 (HOTAIRM1) on NSCLC progression and underlying mechanism were revealed. Methods The expression levels of HOTAIRM1 and microRNA-498 (miR-498) were detected by quantitative real time polymerase chain reaction (qRT-PCR) in NSCLC tissues, cells or exosomes. The protein expression of CD63, CD81, hexokinase 2 (HK2) and ATP binding cassette subfamily E member 1 (ABCE1) was determined by western blot. Cell viability, apoptosis, migration and invasion were investigated by cell counting kit-8 (CCK-8), fow cytometry, transwell migration and invasion assays, respectively. Cell glycolysis metabolism was revealed by glucose uptake and lactate production assays and western blot analysis. The binding relationship between miR-498 and HOTAIRM1 or ABCE1 was predicted by DIANA-LncBase v2 and starBase online database, and identifed by dual-luciferase reporter assay. The efects of HOTAIRM1 on NSCLC growth in vivo were revealed by in vivo tumor formation assay. Results HOTAIRM1 expression was dramatically upregulated, whereas miR-498 expression was signifcantly downregulated in NSCLC tissues cells or exosomes as compared to control groups. Mechanistically, HOTAIRM1 knockdown repressed cell viability, migration, invasion and glycolysis metabolism, whereas induced cell apoptosis in NSCLC; however, miR498 inhibitor hindered these efects. Functionally, HOTAIRM1 functioned as a sponge of miR-498 and miR-498 targeted ABCE1. In addition, HOTAIRM1 silencing inhibited NSCLC growth in vivo by downregulating ABCE1 and upregulating miR-498 expression. Conclusions HOTAIRM1 knockdown repressed cell glycolysis metabolism and tumor development by reducing ABCE1 expression through sponging miR-498 in NSCLC, which provided a theoretical basis for further studying NSCLC progression.

Semi-supervised Learning for Automatic Image Annotation Based on Bayesian Framework

Dongping Tian 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.6