Occlusal deviations in adolescents with idiopathic and congenital scoliosis

Zhang Hao,Ma Jingbo,Zhang Zhicheng,Feng Yafei,Cai Chuan,Wang Chao 대한치과교정학회 2022 대한치과교정학회지 Vol.52 No.3

Objective: This cross-sectional study aimed to investigate the characteristics of malocclusions in scoliotic patients through clinical examinations. Methods: Fifty-eight patients with idiopathic scoliosis (IS) and 48 patients with congenital scoliosis (CS) participated in the study. A randomly selected group of 152 orthopedically healthy children served as the control group. Standardized orthodontic and orthopedic examination protocols were used to record the occlusal patterns and type of scoliosis. Assessments were made by three experienced orthodontists and a spinal surgery team. The differences in the frequency distribution of occlusal patterns were evaluated by the chi-squared test. Results: In comparison with patients showing IS, patients with CS showed a higher incidence of Cobb angle ≥ 45° (p = 0.020) and included a higher proportion of patients receiving surgical treatments (p < 0.001). The distribution of the Angle Class II subgroup was significantly higher in the IS (p < 0.001) and CS (p = 0.031) groups than in the control group. In comparison with the healthy controls, the CS and IS groups showed significantly higher (p < 0.05) frequencies of asymmetric molar and asymmetric canine relationships, upper and lower middle line deviations, anterior deep overbite, unilateral posterior crossbite, and canted occlusal plane, with the frequencies being especially higher in CS patients and to a lesser extent in IS patients. Conclusions: Patients with scoliosis showed a high frequency of malocclusions, which were most obvious in patients with CS.

An active learning method with difficulty learning mechanism for crack detection

Zhicheng Zhang,Jiangpeng Shu,Jun Li,Jiawei Zhang,Weijian Zhao,Yuanfeng Duan 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.1

Crack detection is essential for inspection of existing structures and crack segmentation based on deep learning is asignificant solution. However, datasets are usually one of the key issues. When building a new dataset for deep learning, laborious and time-consuming annotation of a large number of crack images is an obstacle. The aim of this study is to develop an approach that can automatically select a small portion of the most informative crack images from a large pool in order to annotate them, not to label all crack images. An active learning method with difficulty learning mechanism for crack segmentation tasks is proposed. Experiments are carried out on a crack image dataset of a steel box girder, which contains 500 images of 320 × 320 size for training, 100 for validation, and 190 for testing. In active learning experiments, the 500 images for training are acted as unlabeled image. The acquisition function in our method is compared with traditional acquisition functions, i.e., Query-By-Committee (QBC), Entropy, and Core-set. Further, comparisons are made on four common segmentation networks: U-Net, DeepLabV3, Feature Pyramid Network (FPN), and PSPNet. The results show that when training occurs with 200 (40%) of the most informative crack images that are selected by our method, the four segmentation networks can achieve 92%-95% of the obtained performance when training takes place with 500 (100%) crack images. The acquisition function in our method shows more accurate measurements of informativeness for unlabeled crack images compared to the four traditional acquisition functions at most active learning stages. Our method can select the most informative images for annotation from many unlabeled crack images automatically and accurately. Additionally, the dataset built after selecting 40% of all crack images can support crack segmentation networks that perform more than 92% when all the images are used.

A new visual tracking approach based on salp swarm algorithm for abrupt motion tracking

( Huanlong Zhang ),( Junfeng Liu ),( Zhicheng Nie ),( Jie Zhang ),( Jianwei Zhang ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.3

Salp Swarm Algorithm (SSA) is a new nature-inspired swarm optimization algorithm that mimics the swarming behavior of salps navigating and foraging in the oceans. SSA has been proved to enable to avoid local optima and enhance convergence speed benefiting from the adaptive nonlinear mechanism and salp chains. In this paper, visual tracking is considered to be a process of locating the optimal position through the interaction between leaders and followers in successive images. A novel SSA-based tracking framework is proposed and the analysis and adjustment of parameters are discussed experimentally. Besides, the qualitative analysis and quantitative analysis are performed to demonstrate the tracking effect of our proposed approach by comparing with ten classical tracking algorithms. Extensive comparative experimental results show that our algorithm has good performance in visual tracking, especially for abrupt motion tracking.

Effect of Niobium on the Thermal Stability and Mechanical Properties of a Low-Carbon Ultrafine Grain Steel

Qingxiao Zhang,Wei Wang,Qing Yuan,Zhoutou Wang,Zhicheng Zhang,Guang Xu 대한금속·재료학회 2023 METALS AND MATERIALS International Vol.29 No.7

The effects of niobium (Nb) on the thermal stability and mechanical properties of a low-carbon ultrafine grain steel (UFG)were investigated. Results indicate that compared to the Nb-free UFG steel, the dissolved Nb in the Nb-UFG steel beforeannealing was beneficial to improve the thermal stability and strength but harmful to plasticity. The grain boundaries movementwas inhibited by numerous Nb(C, N) particles re-precipitated during annealing, leading to the refined ferrite grains,subsequently the higher thermal stability and strength of the Nb-UFG steel. The decreased elongation was attributed to thefiner ferrite grains and coarse Fe3Cparticles. However, the thermal stability and strength of the Nb-UFG steel were alsoenhanced without any elongation sacrifice when Nb was partially dissolved in matrix before annealing. The superior balancebetween strength and ductility is ascribed to the precipitation strengthening of fine Nb(C, N) particles, appropriate ferritegrain size and finer Fe3Cparticles. In addition, although the thermal stability of the steel with completely solute Nb beforeannealing was better than that with partially solute Nb, the strength and elongation of the former decreased due to the inferiorwork hardening ability caused by finer ferrite grains and larger Fe3Cparticles.

An adaptive marine predator algorithm based optimization method for hood lightweight design

Zhang Chenglin,He Zhicheng,Li Qiqi,Chen Yong,Chen Shaowei,NIE XINYU 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.3

The lightweight design of the hood is crucial for the structural optimization of an entire vehicle. However, traditional high-fidelity-based lightweight methods are time-consuming due to the complex structures of the hood, and the lightweight results heavily rely on engineering experiences. To this end, an improved adaptive marine predator algorithm (AMPA) is proposed to solve this problem. Compared to the original marine predator algorithm (MPA), the proposed AMPA adapts to optimization problems through three enhancements, including chaotic theory-based initialization, a mixed search strategy, and dynamic partitioning of iteration phases. Experimental comparisons of AMPA, MPA, and eight state-of-the-art algorithms are conducted on IEEE CEC2017 benchmark functions. AMPA outperforms the others in both 30- and 50-dimensional experiments. Friedman and Wilcoxon’s sign-rank tests further confirm AMPA’s superiority and statistical significance. An implicit parametric model of the hood is generated, and the critical design variables are determined through global sensitivity analysis to realize hood lightweight. The stacking method is employed to construct a surrogate meta-model of the hood to accelerate the optimization efficiency of the vehicle hood. Utilizing the meta-model and the proposed AMPA, the hood mass is reduced by 7.43% while all six static and dynamic stiffness metrics are enhanced. The effectiveness of the proposed optimization method is validated through finite element analysis.

Interaction Matrix Based Analysis and Asymptotic Cooperative Control of Multi-agent Systems

Zhicheng Hou,Jianxin Xu,Gong Zhang,Weijun Wang,Changsoo Han 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.5

In this paper, we investigate a decentralized asymptotic cooperative control problem of multi-agent systems with leader-follower configuration. We firstly develop a new method using a proposed “interaction matrix” for the analysis of cooperation convergence of multi-agent systems, i.e. both consensus of the agents states and trajectory tracking of the whole group can be instantaneously concluded only by observing the minimum eigenvalue of the interaction matrix. For a multi-agent system, the external given desired trajectory can be partially obtained (through sensing or detecting) by the leaders, but higher-order derivatives such as acceleration and jerk of the desired trajectory cannot be obtained. In this case, by using some conventional control methods, the trajectory tracking performance is always not satisfactory when a trajectory varies aggressively w.r.t. time. For the sake of asymptotic tracking of an arbitrary given external trajectory of a multi-agent system, we develop a nonlinear cooperative controller based on the robust integral of signum of cooperative error (RISCE) technique, where the interaction matrix is used. The simulation results show asymptotic convergence of cooperation by using the proposed control, and better performance compared to composited nonlinear feedback based PD (CNF-PD) control.

THE EXISTENCE OF PERIODIC SOLUTION OF A TWO-PATCHES PREDATOR-PREY DISPERSION DELAY MODELS WITH FUNCTIONAL RESPONSE

Zhang, Zhengqiu,Wang, Zhicheng Korean Mathematical Society 2003 대한수학회지 Vol.40 No.5

In this paper, a nonautonomous predator-prey dispersion delay models with functional response is studied. By using the continuation theorem of coincidence degree theory, the existence of a positive periodic solution for above models is established.

The existence of periodic solution of a two-patches predator-prey Dispersion Delay Models with Functional Response

Zhengqiu Zhang,Zhicheng Wang 대한수학회 2003 대한수학회지 Vol.40 No.5

In this paper, a nonautonomous predator-preydispersion delay models with functional response is studied. Byusing the continuation theorem of coincidence degree theory,the existence of a positive periodic solution for above modelsis established.

Improvement of comprehensive performance of compound green soil in sponge city

Lei Zhang,Zhicheng Li,Tianliang Yang,Ping Yang 대한환경공학회 2021 Environmental Engineering Research Vol.26 No.5

Large-scale constructions of urbanization increase the impervious areas of city, leading to the urban hydrological effects such as urban waterlogging and rainwater runoff pollution. To this end, China proposed to adopt the measure to build sponge cities. However, the existing green soil cannot meet the comprehensive needs of sponge city. In order to quickly evaluate the comprehensive performance of the soil in sponge city, a comprehensive evaluation criterion was designed, which is related to the characteristics of greening soil permeability, porosity, pH, salinity and fertility. Based on the criterion, a new type of composite green soil was obtained with the silt soil: medium sand: sawdust ratio of 72.5%: 20%: 7.5%. Finally, compared with the existing soil, the new green soil not only meets the comprehensive performance requirements of the green soil’s fertility, pH, permeability and other factors, but also has higher permeability and water retention. It was proved that the new green soil has apparent advantages in the control of rainwater.

Knowledge Transfer Using User-Generated Data within Real-Time Cloud Services

( Jing Zhang ),( Jianhan Pan ),( Zhicheng Cai ),( Min Li ),( Lin Cui ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.1

When automatic speech recognition (ASR) is provided as a cloud service, it is easy to collect voice and application domain data from users. Harnessing these data will facilitate the provision of more personalized services. In this paper, we demonstrate our transfer learning-based knowledge service that built with the user-generated data collected through our novel system that deliveries personalized ASR service. First, we discuss the motivation, challenges, and prospects of building up such a knowledge-based service-oriented system. Second, we present a Quadruple Transfer Learning (QTL) method that can learn a classification model from a source domain and transfer it to a target domain. Third, we provide an overview architecture of our novel system that collects voice data from mobile users, labels the data via crowdsourcing, utilises these collected user-generated data to train different machine learning models, and delivers the personalised real-time cloud services. Finally, we use the E-Book data collected from our system to train classification models and apply them in the smart TV domain, and the experimental results show that our QTL method is effective in two classification tasks, which confirms that the knowledge transfer provides a value-added service for the upper-layer mobile applications in different domains.