The Role of Input and Interaction in the Acquisition of Chinese as a Second Language

Input and interaction have received great attention in second language research due to their dominant role in second language teaching and learning. However, empirical studies that have examined their effects on the acquisition of Chinese as a second language remain scarce. This study fills this gap by comparing the effects of teacher-student interaction and student-student interaction on vocabulary acquisition in Chinese as a second language. Thirty-six adult beginners of Chinese completed ten weeks\u27 study in Australia, in addition to pre- and post- tests and a background questionnaire. Selected participants attended a focus group interview. Statistical analyses show that both types of interaction facilitate learning but their effects depend on the mode of tests. There was no statistically significant difference between the teacher-student interaction and student-student interaction in their effects on the acquisition of word meaning based on written scores, whereas the teacher-student group outperformed the student-student group in pronunciation. There was no statistically significant difference between the written and spoken scores of the teacher-student group, whereas the student-student group had higher written scores than spoken scores. The results suggest when learners are allowed to select learning content and provided with the learning materials prepared by teachers, the student-student interaction may achieve the same results as teacherstudent interaction in the acquisition of word meaning. The findings lend support to the Input and Interaction Hypothesis by showing that negotiation of meaning and comprehended input facilitated vocabulary acquisition, and extend the effects of interactions to the acquisition of Chinese as second language by pure beginners using their first language. The findings and their pedagogical implications are discussed and contextualised within Chinese-as-a-second-language teaching

Design and Realization of On-line Enterprise Office Automation System

AbstractThis paper discusses the online business office automation system development process, office automation system requirement analysis, system function design, database design and implementation of the system is introduced, the system function and database design and realization of the system. Through the system function data flow analysis, get the logical structure of database system, and on this basis, the physical structure of database to create all kinds of information inquiry, update operation

An oil painters recognition method based on cluster multiple kernel learning algorithm

A lot of image processing research works focus on natural images, such as in classification, clustering, and the research on the recognition of artworks (such as oil paintings), from feature extraction to classifier design, is relatively few. This paper focuses on oil painter recognition and tries to find the mobile application to recognize the painter. This paper proposes a cluster multiple kernel learning algorithm, which extracts oil painting features from three aspects: color, texture, and spatial layout, and generates multiple candidate kernels with different kernel functions. With the results of clustering numerous candidate kernels, we selected the sub-kernels with better classification performance, and use the traditional multiple kernel learning algorithm to carry out the multi-feature fusion classification. The algorithm achieves a better result on the Painting91 than using traditional multiple kernel learning directly

Anisotropic mechanical behavior of thermally bonded nonwoven fabric

Anisotropic properties of thermally bonded nonwoven fabric (polypropylene) have been investigated. Firstly, the orientation distribution function of fibre is obtained by applying Hough transform technique to scanning electron microscopy of nonwoven fabric. Secondly, the influence of specimen width on mechanical behavior of nonwoven fabric has been studied, and the relationships between tensile strength of nonwoven fabric and specimen width are acquired by applying nonlinear fitting. Finally, the anisotropic creep behavior of nonwoven is investigated at different stress levels, different directions of nonwoven and different durations by applying nonlinear fitting, and the empirical model for calculating creep elongation is deduced. The results show that the tensile and creep behaviors of nonwoven fabric are influenced significantly by the fibre distribution. The creep elongation of nonwoven fabric is proportional to the level of loading and time. The creep elongation of nonwoven fabrics follows exponential relationships with time and this is true for all the directions of load and for all the levels of loading

Organically Structured Control of Large-Scale Systems with Expanding Construction Based on State Observation

This paper presents a new method on the problem of organically structured control based on state observation for a class of large-scale systems with expanding construction. This problem is to design a local state feedback controller and an observer for a new subsystem which is added to a large-scale system without changing the decentralized state feedback control laws of the original construction, so that both the new subsystem and the resulting expanded system are robustly connectively stable. Firstly, based on state observers, the mathematical model of a large-scale system with expanding construction is reestablished and analyzed. In addition, the sufficient condition for robust decentralized connective stabilization of the expanded construction of large-scale systems is deduced by taking an LMI approach, which is further relaxed by removing the square matrix condition on the output matrix. This problem is transformed into solving an LMI problem. The new design method of an organically structured controller and observer for the expanded construction is also given. Finally, the simulation examples show the effectiveness of the proposed method

Pd-Doped SnO 2

Methane (CH4), ethane (C2H6), ethylene (C2H4), and acetylene (C2C2) are important fault characteristic hydrocarbon gases dissolved in power transformer oil. Online monitoring these gaseous components and their generation rates can present the operational state of power transformer timely and effectively. Gas sensing technology is the most sticky and tricky point in online monitoring system. In this paper, pure and Pd-doped SnO2 nanoparticles were synthesized by hydrothermal method and characterized by X-ray powder diffraction, field-emission scanning electron microscopy, and energy dispersive X-ray spectroscopy, respectively. The gas sensors were fabricated by side-heated preparation, and their gas sensing properties against CH4, C2H6, C2H4, and C2H2 were measured. Pd doping increases the electric conductance of the prepared SnO2 sensors and improves their gas sensing performances to hydrocarbon gases. In addition based on the frontier molecular orbital theory, the highest occupied molecular orbital energy and the lowest unoccupied molecular orbital energy were calculated. Calculation results demonstrate that C2H4 has the highest occupied molecular orbital energy among CH4, C2H6, C2H4, and C2H2, which promotes charge transfer in gas sensing process, and SnO2 surfaces capture a relatively larger amount of electric charge from adsorbed C2H4

Fractal Behavior in the Clarification Process of Cane Sugar Production

Cane sugar production is an important industrial process. One of the most important steps in cane sugar production is the clarification process, which provides high-quality, concentrated sugar syrup crystal for further processing. To gain fundamental understanding of the physical and chemical processes associated with the clarification process and help design better approaches to improve the clarification of the mixed juice, we explore the fractal behavior of the variables pertinent to the clarification process. We show that the major variables in this key process all show persistent long-range correlations, for time scales up to at least a few days. Persistent long-range correlations amount to unilateral deviations from a preset target. This means that when the process is in a desired mode such that the target variables, color of the produced sugar and its clarity degree, both satisfy preset conditions, they will remain so for a long period of time. However, adversity could happen, in the sense that when they do not satisfy the requirements, the adverse situation may last quite long. These findings have to be explicitly accounted for when designing active controlling strategies to improve the quality of the produced sugar