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Biao Wang,Yan Huang,Yonghong Wang,Peizheng Yan,Qiaosheng Pan 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.5
The mechanical structures of micro-electro-mechanical systems (MEMS) are composed of different types of microstructures, and their mechanical properties are very important for the realisation and reliability of the system performance. One of the key problems in measuring the mechanical properties is the design and implementation of micro-nano displacement driving mechanisms. This paper describes a mechanism that adopts a two-level loading strategy, fast approach, and precise bending displacement loading structures, and has a theoretical analysis and optimal design based on optimal targets of resistance and displacement. The results show that the relative error is 6.98 % for the fast-approaching structure experiment and its optimal simulation and 4.26 % for the precise bending displacement loading structure (PBLS) experiment and its optimal simulation. The optimised micro-nano displacement loading mechanism can achieve optimal output performance under existing constraints.
Genome‑wide association analysis of salt tolerance QTLs with SNP markers in maize (Zea mays L.)
Yonghong Xie,Yan Feng,Qi Chen,Feike Zhao,Shuijuan Zhou,Ying Ding,Xianliang Song,Ping Li,Baohua Wang 한국유전학회 2019 Genes & Genomics Vol.41 No.10
Background Salt-tolerant breeding of maize has great significance to the development and utilization of saline–alkaline soil and the maintenance of grain security. Genome-wide association study (GWAS) has been widely used in maize genetics and breeding. Objective To discover new salt-tolerant genes in maize by association analysis, which can provide technical supports for the innovation and genetic improvement of salt-tolerant germplasm resources in maize. Methods Totally 150 maize inbred lines were genotyped with a high-density chip. GWAS was carried out to identify the significant single nucleotide polymorphisms (SNPs) which were associated with maize salt tolerance. Totally 34,972 SNPs with high quality and diversity were selected from 56,110 SNP markers, which were distributed on 10 chromosomes of maize. The GLM algorithm in TASSEL5.2 was used to analyze the five traits related to salt tolerance. Results Using a strict LOD threshold of 4.5, totally 7 SNP loci were identified, which were significantly correlated with plant height change rate and fresh weight change rate. The high density fingerprints of 150 inbred lines were clustered by TASSEL5.2 software to construct genetic clustering map to estimate the genetic distance and the subgroups. The 150 maize inbred lines were divided into two groups: SS group and NSS group, and the SNP loci of the salt-tolerant index showed difference in chromosome distribution. Based on previous studies, we screened 8 candidate genes for salt tolerance in maize and four of them were further validated by real-time quantitative PCR. Conclusion Totally 7 SNP loci and 8 candidate genes related to salt tolerance in maize were identified, which will be of special value in molecular breeding of salt-tolerant maize.
Stability of Wiener Systems with Dead-zone Using Optimal Position and Velocity Control
Tianyu Wang,Yonghong Tan,Ming Fang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.2
In this paper, a new sufficient condition for the stability of Wiener systems with dead-zone which are also non-smooth nonlinear systems is proposed. In order to analyze the stability, pseudo linearization is implementedto the system. Then, the optimal position and velocity control strategy is derived by minimizing the cost function. Based on the Lyapunov method, the stability condition is obtained. Afterward, simulation examples are presentedto validate the proposed method.
Color Image Blind Watermarking Algorithm Based on QR Decomposition and Voting in DWT Domain
Junxiang Wang,Ying Liu,Yonghong Zhu 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.11
To achieve a better trade-off between robustness and imperceptibility, a blind watermarking algorithm based on QR decomposition and voting for color image in DWT domain is proposed in the paper. Most of the existing QR decomposition based watermarking schemes take the first row of R matrix into consideration while in our approach the watermark is embedded by modifying the first column element of Q matrix. In the embedding process, DCT is applied to the R, G and B color components, respectively. Then DWT is utilized on the DCT coefficients of each component and acquire corresponding LL, HL, LH, and HH. Later, the associated DWT coefficients in LH and HH are decomposed with QR decomposition and the watermark message is embedded into the first column of Q matrix by changing Q21 and Q31 with stable characteristic. In the extraction phase, a redundant watermark scheme with voting method is used to improve the robustness of the watermarking algorithm. Experimental results show that the proposed algorithm, compared with the existing methods is robust enough to resist common signal attacks including filtering, noising, small cutting and JPEG compressing.
Influence of heat treatment on the wear life of hydraulic fracturing tools
Chao Zheng,Yonghong Liu,Hanxiang Wang,Jie Qin,Yang Shen,Shihong Zhang 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.2
Wear phenomenon has caused severe damage or failure of fracturing tools in oil and gas industry. In this paper, influence of heat treatment on the mechanical properties and wear resistance of fracturing tool made of lamellar graphite grey cast iron were investigated. The surface composition and microstructure were characterized by X-ray diffraction (XRD) and metallographic microscope. Sliding wear tests were performed to study the tribological behavior. Tests results showed that wear rates of treated specimens decreased by 33 %. Besides, worn morphology and wear debris were analyzed using Scanning electron microscope (SEM) and Energy dispersive Xray spectra (EDS). Wear failure mechanisms of specimens were identified. Furthermore, on-site experiment results indicated that wear loss of treated samples decreased by 37.5 %. The wear life of hydraulic fracturing tools can be improved obviously by the heat treatment.
A Novel Intrusion Detection Approach Based on Chaos Theory in Wireless Sensor Network
Xinling Kong,Yonghong Chen,HuiTian,Tian Wang,Yiqiao Cai 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.11
With the development of technology, wireless sensor networks(WSNs) has been widely used in military, political, medical and other fields, their characteristics of data-centric become increasingly prominent. In this paper, a data-oriented intruding detection method based on chaos theoy is proposed. We use the theory of chaotic system to analyze the internal rules of the sensory data and predict the data by RBF neural network firstly, then make an initial detection of false injected data attack according to whether the difference between the predicted and actual value is more than the threshold, finally confirming the attack by checking whether the number of abnormal within the cycle lies in the corresponding range. Experimental results show that RBF neural network predict sensory data more accurate, our approach can effectively distinguish the abnormal events caused by the attack or environmental factors and has high intrusion detection accuracy.
Robust multi-atlas label propagation by deep sparse representation
Zu, Chen,Wang, Zhengxia,Zhang, Daoqiang,Liang, Peipeng,Shi, Yonghong,Shen, Dinggang,Wu, Guorong Elsevier 2017 Pattern recognition Vol.63 No.-
<P><B>Abstract</B></P> <P>Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional <I>flat and shallow</I> dictionary to a deep multi-layer structure, where the top layer (<I>label-specific dictionaries</I>) consists of groups of representative atlas patches and the subsequent layers (<I>residual dictionaries</I>) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Develop a novel multi-atlas patch based label fusion method; </LI> <LI> Alter the conventional flat and shallow dictionary to a deep multi-layer structure; </LI> <LI> Obtain more accurate label fusion results than conventional state-of-the-art methods. </LI> </UL> </P>