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Jianming Zhou,Ahmad Tajuddin Othman,Ahmad Zamri Khairani 한국운동생리학회 2022 운동과학 Vol.31 No.3
PURPOSE: Aquatic training assists in reducing the risk of exercise on joints among children. This systematic review evaluated the effectiveness of aquatic training for children from the perspective of body composition. METHODS: A meta-analysis was performed to determine the potential impact of aquatic training in children. Four databases, namely Scopus, PubMed, Web of Science, and EBSCO, were used for the systematic search from September 2010 to November 2021. The mean differences in the data were analyzed using Stata 15.1 software with a 95% confidence interval. Outcome measures included weight, body mass index (BMI), fat percentage (Fat%), and waist circumference. RESULTS: Eleven studies, comprising eight randomized controlled trials (RCT) and three non-RCT studies, evaluating the effect of aquatic training on children were analyzed and reported. Aquatic training significantly improved the BMI (p<.01) and Fat% (p<.01) in children (ES (95% CI)=-0.23 (-0.38, -0.08) and ES (95% CI)=-0.27 (-0.45, -0.08). However, aquatic training had no significant effect on weight (p=.41), ES (95% CI)=-0.07 (-0.25, 0.10), and waist circumference (p=.11) in children, ES (95% CI)=-0.33 (- 0.74, 0.08). CONCLUSIONS: Aquatic training can improve children’s BMI and body fat% but not their weight, waist circumference, and muscle mass. Aquatic training may be a potential exercise program for improving body composition in children.
H<SUB>∞</SUB> Control of 2-D Discrete State Delay Systems
Jianming Xu,Li Yu 대한전기학회 2006 International Journal of Control, Automation, and Vol.4 No.4
This paper is concerned with the H∞ control problem of 2-D discrete state delay systems described by the Roesser model. The condition for the system to have a specified H∞ performance is derived via the linear matrix inequality (LMI) approach. Furthermore, a design procedure for H∞ state feedback controllers is given by solving a certain LMI. The design problem of optimal H∞ controllers is formulated as a convex optimization problem, which can be solved by existing convex optimization techniques. Simulation results are presented to illustrate the effectiveness of the proposed results.
Numerical analysis of a long-span bridge response to tornado-like winds
Jianming Hao,Teng Wu 한국풍공학회 2020 Wind and Structures, An International Journal (WAS Vol.31 No.5
This study focused on the non-synoptic, tornado-like wind-induced effects on flexible horizontal structures that are extremely sensitive to winds. More specifically, the nonuniform, intensive vertical wind-velocity and transient natures of tornado events and their effects on the global behavior of a long-span bridge were investigated. In addition to the static part in the modeling of tornado-like wind-induced loads, the motion-induced effects were modeled using the semi-empirical model with a two-dimensional (2-D) indicial response function. Both nonlinear wind-induced static analysis and linear aeroelastic analysis in the time domain were conducted based on a 3-D finite-element model to investigate the bridge performance under the most unfavorable tornado pattern considering wind-structure interactions. The results from the present study highlighted the important effects due to abovementioned tornado natures (i.e., nonuniform, intensive vertical wind-velocity and transient features) on the long-span bridge, and hence may facilitate more appropriate wind design of flexible horizontal structures in the tornado-prone areas.
Jianming Xu,Mingxuan Sun,Li Yu 대한전기학회 2008 International Journal of Control, Automation, and Vol.6 No.2
This paper addresses the synthesis of an iterative learning controller for a class of linear systems with norm-bounded parameter uncertainties. We take into account an iterative learning algorithm with current cycle feedback in order to achieve both robust convergence and robust stability. The synthesis problem of the developed iterative learning control (ILC) system is reformulated as the γ-suboptimal H∞ control problem via the linear fractional transformation (LFT). A sufficient convergence condition of the ILC system is presented in terms of linear matrix inequalities (LMIs). Furthermore, the ILC system with fast convergence rate is constructed using a convex optimization technique with LMI constraints. The simulation results demonstrate the effectiveness of the proposed method.
Small Sample Face Recognition Algorithm based on Novel Siamese Network
( Jianming Zhang ),( Xiaokang Jin ),( Yukai Liu ),( Arun Kumar Sangaiah ),( Jin Wang ) 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.6
In face recognition, sometimes the number of available training samples for single category is insufficient. Therefore, the performances of models trained by convolutional neural network are not ideal. The small sample face recognition algorithm based on novel Siamese network is proposed in this paper, which doesn’t need rich samples for training. The algorithm designs and realizes a new Siamese network model, SiameseFace1, which uses pairs of face images as inputs and maps them to target space so that the L2 norm distance in target space can represent the semantic distance in input space. The mapping is represented by the neural network in supervised learning. Moreover, a more lightweight Siamese network model, SiameseFace2, is designed to reduce the network parameters without losing accuracy. We also present a new method to generate training data and expand the number of training samples for single category in AR and labeled faces in the wild (LFW) datasets, which improves the recognition accuracy of the models. Four loss functions are adopted to carry out experiments on AR and LFW datasets. The results show that the contrastive loss function combined with new Siamese network model in this paper can effectively improve the accuracy of face recognition.