The Relationship between the Depth of Vocabulary Knowledge and Chinese MA Students’ Use of Vocabulary Learning Strategy and L2 Contact ina Study-Abroad Context

Xiaofei Liu 범태평양 응용언어학회 2018 범태평양응용언어학회지 Vol.22 No.2

The purpose of the study was to investigate the relationship between Chinese MA students’ depth of vocabulary knowledge, their use of L2 vocabulary learning strategy (VLS), and the types of L2 contact they encountered while studying abroad. 165 Chinese MA students from a British university participated in the study by filling out the questionnaire which comprised a measure of L2 contact (Freed, Dewey, Segalowitz, & Halter, 2004), a survey of vocabulary learning strategy (Gu, 2005), and a vocabulary test based on the Word Associates Format (WAF) (Read, 2000) used for measuring their vocabulary knowledge depth. Exploratory factor analysis yielded five types of VLS and five types of L2 contact. Results of stepwise regression analysis indicated that strategies related to contextual guessing and using a dictionary as well as L2 contact variables of reading and interacting in English were positive predictors of vocabulary knowledge depth. However, Pearson’s correlation coefficients revealed no relationship between the vocabulary test results and the variables of either VLS or L2 contact. Implications of the findings suggested how advanced Chinese ESL learners could maximize their lexical gains by using VLS and engaging L2 contact while studying abroad.

Observer-based Composite Adaptive Dynamic Terminal Sliding-mode Controller for Nonlinear Uncertain SISO Systems

Xiaofei Liu,Shengbo Qi,Reza Malekain,Zhixiong Li 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.1

In the present paper, the observer-based composite adaptive terminal sliding-mode control is investigatedfor the nonlinear uncertain system. First, an adaptive observer is designed to estimate the unavailable high-orderderivative of the output. Then, a new dynamic terminal sliding surface is proposed with a state filter, which aims todevelop the dynamic terminal sliding mode controller. By the composite adaptive control methods, a new adaptivelaw is designed, and the stability of the overall system is proofed based on the Lyapunov method. Finally, somenumerical simulations are conducted to validate the effectiveness of the proposed algorithm.

Size-Controlled Silver Nanoparticles Confined in Ordered Mesoporous Silica and Their Enhanced Catalytic Activities

Xiaofei Zhou,Jiawei Wan,Yefeng Liu,Di Liu,Hong Wang,Xiaoyong Lai,Yanzhao Zou,Guo Lin,Jian Chen 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2017 NANO Vol.12 No.9

A cooperative assembly route has been developed, by which silver nanoparticles with controlled sizes are incorporated into the channels of ordered cubic mesoporous silica (KIT-6) with different pore sizes (4.3–6.4 nm). The samples were characterized by XRD, TEM, FT-IR, UV-Vis and N2 physisorption. The pore wall of mesoporous silica can efficiently confine the growth of silver nanoparticles within the channels and their average sizes decreased with the pore size reduction of KIT-6. Catalytic activities of the resultant Ag/KIT-6-x (x stands for hydrothermal temperature) composite for reducing harmful organic dye Rhodamine B (Rh B) by sodium borohydride (NaBH4) were investigated. All the Ag/KIT-6 composite samples show great catalytic activities, among which Ag/KIT-6-80 with higher loading and smaller size of Ag nanoparticles exhibits higher catalytic activity than those of Ag/KIT-6-60 and Ag/KIT-6-100.

Application of artificial intelligence for solving the engineering problems

Xiaofei Liu,Xiaoli Wang 국제구조공학회 2023 Structural Engineering and Mechanics, An Int'l Jou Vol.85 No.1

Using artificial intelligence and internet of things methods in engineering and industrial problems has become a widespread method in recent years. The low computational costs and high accuracy without the need to engage human resources in comparison to engineering demands are the main advantages of artificial intelligence. In the present paper, a deep neural network (DNN) with a specific method of optimization is utilize to predict fundamental natural frequency of a cylindrical structure. To provide data for training the DNN, a detailed numerical analysis is presented with the aid of functionally modified couple stress theory (FMCS) and first-order shear deformation theory (FSDT). The governing equations obtained using Hamilton’s principle, are further solved engaging generalized differential quadrature method. The results of the numerical solution are utilized to train and test the DNN model. The results are validated at the first step and a comprehensive parametric results are presented thereafter. The results show the high accuracy of the DNN results and effects of different geometrical, modeling and material parameters in the natural frequencies of the structure.

모바일 SNS 품질이 사용자 만족과 지속적인 사용의도에 미치는 영향에 관한 연구

유효비(LIU XIAOFEI),권순동 한국벤처창업학회 2012 한국벤처창업학회 학술대회 Vol.2012 No.8

Bio-inspired Micro Pump Model Based on the Movement Pattern of Sperm

Feifei Liu,Xiaofei Ren,Shoushui Wei,Zhiping Liu 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.11

Micro pumps play important roles in microfluidic system. Biologically inspired actuation mechanisms have great advantages in the micro pump design. This work aims to develop a numerical model for bio-inspired micro pump based on the specific and genuine movement pattern of the sperm. The model also employs a modified immersed boundary-lattice Boltzmann method. In the model, an elastic film is used to mimic a sperm moving with its head fixed. The fluctuation vibration of the film could then drive the static fluid to move. The modified immersed boundary-lattice Boltzmann method directly introduces the velocity information of the film into the traditional lattice Boltzmann equation, which improve the computational efficiency. Pressure distribution, streamlines and the flow rate curves are used to analyze the flow field dynamic process of the model. The effects of the model parameters (e.g. frequency, kinematic viscosity, amplitude and wavelength) on the stable flow rate are also studied comprehensively.

The Benefits of Indirect Exposure to Trauma

Xiaofei Kang,Yueyan Fang,Sihan Li,Yadong Liu,Di Zhao,Xiujuan Feng,Yaqi Wang,Ping Li 대한신경정신의학회 2018 PSYCHIATRY INVESTIGATION Vol.15 No.5

Objective Ambulance personnel who witness trauma experienced by patients have been reported to experience positive changes, known as vicarious posttraumatic growth (VPTG). We examined VPTG and its relationship with social support and resilience among ambulance personnel. Methods The sample (n=227) was recruited from six emergency centers in China. The measures included the Posttraumatic Growth Inventory (PTGI), the Social Support Rating Scale (SSRS), and the 10-item Connor-Davidson Resilience Scale (CD-RISC-10). Structure Equation Modeling (SEM) and the bootstrapping procedure were used to examine indirect effects. Results The participants’ mean score for VPTG was 68.96 (SD=15.51). Social support had significant direct effects on resilience (β=0.51, p<0.001) and VPTG (β=0.25, p=0.001), and resilience (β=0.58, p<0.001) had a significant direct effect on VPTG. Furthermore, social support had a significant indirect effect (0.51×0.58=0.30, p<0.001) on VPTG through resilience. Conclusion Although the nature of the work of ambulance personnel is not expected to change, the negative effects of the trauma they encounter can be reduced by providing them with more support resources and interventions to foster their resilience, which in turn, promote VPTG.

Segmented Douglas-Peucker Algorithm Based on the Node Importance

( Xiaofei Wang ),( Wei Yang ),( Yan Liu ),( Rui Sun ),( Jun Hu ),( Longcheng Yang ),( Boyang Hou ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.4

Vector data compression algorithm can meet requirements of different levels and scales by reducing the data amount of vector graphics, so as to reduce the transmission, processing time and storage overhead of data. In view of the fact that large threshold leading to comparatively large error in Douglas-Peucker vector data compression algorithm, which has difficulty in maintaining the uncertainty of shape features and threshold selection, a segmented Douglas-Peucker algorithm based on node importance is proposed. Firstly, the algorithm uses the vertical chord ratio as the main feature to detect and extract the critical points with large contribution to the shape of the curve, so as to ensure its basic shape. Then, combined with the radial distance constraint, it selects the maximum point as the critical point, and introduces the threshold related to the scale to merge and adjust the critical points, so as to realize local feature extraction between two critical points to meet the requirements in accuracy. Finally, through a large number of different vector data sets, the improved algorithm is analyzed and evaluated from qualitative and quantitative aspects. Experimental results indicate that the improved vector data compression algorithm is better than Douglas-Peucker algorithm in shape retention, compression error, results simplification and time efficiency.

A Framework for Human Motion Segmentation Based on Multiple Information of Motion Data

( Xiaofei Zan ),( Weibin Liu ),( Weiwei Xing ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.9

With the development of films, games and animation industry, analysis and reuse of human motion capture data become more and more important. Human motion segmentation, which divides a long motion sequence into different types of fragments, is a key part of mocap-based techniques. However, most of the segmentation methods only take into account low-level physical information (motion characteristics) or high-level data information (statistical characteristics) of motion data. They cannot use the data information fully. In this paper, we propose an unsupervised framework using both low-level physical information and high-level data information of human motion data to solve the human segmentation problem. First, we introduce the algorithm of CFSFDP and optimize it to carry out initial segmentation and obtain a good result quickly. Second, we use the ACA method to perform optimized segmentation for improving the result of segmentation. The experiments demonstrate that our framework has an excellent performance.

A Dominant Mutation in ARL2 Causes Impaired Adventitious Root Development in Rice

Shiping Liu,Yanhong Xue,Xiaofei Wang,Botao Zhang,Yuting Bi,Min Qiu,Guangxi Wang,Ping Wu 한국식물학회 2011 Journal of Plant Biology Vol.54 No.4

Adventitious roots are vital for water and nutrient assimilation by cereal crops because they comprise the bulk of the fibrous root system. We isolated and analyzed a rice mutant, adventitious rootless 2 (arl2), which failed to initiate adventitious root primordia during early development. Its seminal root produced fewer lateral roots than from the wild type. This mutant also exhibited pleiotropic phenotypes of longer and thicker seminal roots, a different morphology for the first leaf, delayed heading, and a greater tiller angle. Physiological experiments showed that exogenous auxin and ethylene could rescue adventitious root growth, a response opposite that for two previously reported mutants, arl1 and gnom1. Activity in the auxin signal pathway and the polar auxin transport system was normal for arl2. Compared with the wild type, arl2 plants showed enhanced sensitivity to ethephon but decreased sensitivity to AgNO_3, an inhibitor of ethylene. Genetics analysis demonstrated that this mutant is controlled by a single dominant gene; ARL2 was mapped within a 100-kb interval on the short arm of chromosome 2.