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1 – 5 of 5Yi-Fan Liu, Wu-Yuin Hwang and Sherry Chen
This paper aims to examine how gender differences influence students’ reactions to the use of the annotatable multimedia e-reader (AME). To reach this aim, we develop an AME where…
Abstract
Purpose
This paper aims to examine how gender differences influence students’ reactions to the use of the annotatable multimedia e-reader (AME). To reach this aim, we develop an AME where various annotation tools are provided to help students learn English in-class and after-class.
Design/methodology/approach
An empirical study was conducted with 63 fifth-grade students from an elementary school. A pre-test and post-test were used to identify their prior knowledge and learning achievement, respectively. A questionnaire was applied to identify participants’ perceptions towards the AME.
Findings
The results show that students’ post-test scores are significantly related to after-class behaviour, instead of in-class behaviour. Females prefer to use the text annotation and teachers’ voice, but it is voice annotation that is beneficial to improve their learning achievement. Conversely, males prefer to use the text-to-speech only, but it is text annotation that is helpful to improve their learning achievement. Additionally, the ease of use affects males’ intention to use the AME to learn English after-class while it has no effects on females.
Originality/value
This study not only shows the importance of gender differences but also demonstrates the essence of after-class learning behaviour. More importantly, a framework is proposed to support designers to develop e-readers that can accommodate the preferences of females and males.
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Keywords
Shi Zhou, Jia Zhao, Yi Shan Shi, Yi Fan Wang and Shun Qi Mei
In the fabric manufacturing industry, various unfavorable factors, including machine fault and yarn breakage, can easily cause fabric defects and affect product quality, begetting…
Abstract
Purpose
In the fabric manufacturing industry, various unfavorable factors, including machine fault and yarn breakage, can easily cause fabric defects and affect product quality, begetting huge economic losses to enterprises. Thus, automatic fabric defect detection systems have become an important development direction. Herein, the most common defects in the fabric production process, like ribbon yarn, broken yarn, cotton ball, holes, yarn shedding and stains, are detected. Current fabric defect detection systems afford low detection accuracy and a high missed detection rate for small target fabric defects. Therefore, this study proposes deep learning technology for automatically detecting fabric defects by improving the YOLOv5s target detection algorithm. The improved algorithm is termed YOLOv5s-4SCK, which can effectively detect fabric defects. This study aims to discuss the aforementioned issues.
Design/methodology/approach
Specifically, based on the YOLOv5s algorithm, first, the structure of YOLOv5s is modified to add a small target detection layer, fully utilize deep and shallow features and reduce the missed detection rate of small target fabric defects. Second, the integration of CARAFE upsampling enables the effective retention of feature information and maintenance of a certain computational efficiency, thereby improving the detection accuracy. Finally, the K-Means++ clustering algorithm is used to analyze the position of the center point of the prior box to better obtain the anchor box and improve the average accuracy and evaluation index of detection.
Findings
The research results show that the YOLOv5s-4SCK algorithm increases the accuracy by 4.1% and the detection speed by 2 f.s-1 compared to the original YOLOv5s algorithm, and it effectively improves the original YOLOv5s problem of high missed detection rate of small targets.
Research limitations/implications
The YOLOv5s-4SCK proposed in this paper can effectively reduce the missed detection rate of fabric defects, improve the detection efficiency and has certain industrial value.
Practical implications
The proposed algorithm can quickly identify fabric defects, effectively improving the detection rate. In the future, the proposed algorithm will be applied in the actual industry.
Social implications
Automatic fabric defect detection reduces the manpower of inspectors, and the proposed YOLOv5s-4SCK algorithm is also suitable for other recognition fields.
Originality/value
The proposed YOLOv5s-4SCK algorithm has been tested using real cloth to ensure its accuracy, and its performance is better than the original YOLOv5s algorithm.
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Fan Yi, Wang Qingfeng and Yang Wenxiu
The purpose of this study is to study the pitting caused by Ca-Al-O-S composite inclusions of low-alloy steel in 3 Wt.% NaCl solution and 0.01M NaHSO3 solution.
Abstract
Purpose
The purpose of this study is to study the pitting caused by Ca-Al-O-S composite inclusions of low-alloy steel in 3 Wt.% NaCl solution and 0.01M NaHSO3 solution.
Design/methodology/approach
The corrosion in 0.01M NaHSO3 was much weaker than in 3 Wt.% NaCl 3D display of the pitting formation and development process that has been calculated using scanning electron microscope (SEM) and laser scanning confocal microscopy (LSCM). In addition, a corrosion mechanism of pitting formation by galvanic interaction of composite inclusion and base metal has been proposed.
Findings
Results show that in immersion test, metal base around inclusions was dissolved due to corrosion. Corrosion on the metal base closer to inclusions was more severe.
Originality/value
A corrosion mechanism of pitting formation by galvanic interaction of composite inclusion and base metal has been proposed.
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Jiaxing Cai, Xuequn Cheng, Baijie Zhao, Linheng Chen, Yi Fan, Qinqin Dai, Hongchi Ma and Xiaogang Li
The purpose of this paper is to understand the process of failure of scale and the corrosion resistance of scale to the substrate in an atmospheric environment.
Abstract
Purpose
The purpose of this paper is to understand the process of failure of scale and the corrosion resistance of scale to the substrate in an atmospheric environment.
Design/methodology/approach
The corrosion behaviour of X65 pipeline steel with different types of oxide scale was analysed using the natural environment exposure corrosion test, scanning electron microscopy analysis, electrochemical corrosion polarization curve test and other methods in a warehouse environment.
Findings
The results of this research show that one type of oxide scale, which is rough, has an uneven microstructure, and exhibits weak adhesion to the matrix, does not protect the substrate from corrosion. Conversely, the uniform, dense oxide scale, which exhibits strong adhesion to the matrix, provides effective protection to the steel. However, as the corrosion develops, the corrosion rate of the substrate tends to accelerate, especially when the structure of the oxide scale is damaged to a certain extent.
Originality/value
The corrosion mechanism of the oxide scale on hot rolled steel in an atmospheric environment has been proposed.
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Kwok Wah Ronnie Lui and Sarojni Choy
This paper aims to report on a study that used the practice theory lens to understand how Chinese ethnic culture influences restaurant workers' learning through engagement in…
Abstract
Purpose
This paper aims to report on a study that used the practice theory lens to understand how Chinese ethnic culture influences restaurant workers' learning through engagement in everyday work practices.
Design/methodology/approach
A multiple case study approach was used. Data were collected from semi-structured interviews and site observations. Thematic analysis was conducted to identify how workers learnt the sayings, doings and relatings in their workplaces.
Findings
The findings show that the ethnic culture of the participants influences and enriches their learning in practice settings such as small Chinese restaurants.
Research limitations/implications
The understandings presented here need to be verified through more research in different regions and nations. In addition, cross-cultural studies on other ethnic restaurants may contribute to deeper understandings of the influences of ethnic culture on practice-based learning.
Social implications
The research contributes to understanding the influence of ethnic culture on practice-based learning.
Originality/value
The understandings gained from the findings of this study form a useful basis for curriculum development and instructional design of training programmes for practice-based as well as work-integrated-learning components of vocational curriculum. Furthermore, awareness of the strengths of the ethnic culture is of interest to owner/managers of small Chinese restaurants to afford supportive learning environments for workers.
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