Peng Peng and Jiugen Wang
It is a challenging task to analysis oxide wear particles when they are stuck together with other types of wear particles in complex ferrography images. Hence, this paper aims to…
Abstract
Purpose
It is a challenging task to analysis oxide wear particles when they are stuck together with other types of wear particles in complex ferrography images. Hence, this paper aims to propose a method of ferrography image segmentation to analysis oxide wear debris in complex ferrography images.
Design/methodology/approach
First, ferrography images are segmented with watershed transform. Then, two region merging rules are proposed to improve the initial segmentation results. Finally, the features of each particle are extracted to detect and assess the oxide wear particles.
Findings
The results show that the proposed method outperforms other methods of ferrography image segmentation, and the overlapping wear particles in complex ferrography images can be well separated. Moreover, the features of each separated wear particles can be easily extracted to analysis the oxide wear particles.
Practical implications
The proposed method provides a useful approach for the automatic detection and assessment of oxide wear particles in complex ferrography images.
Originality/value
The colours, edges and position information of wear debris are considered in the proposed method to improve the segmentation result. Moreover, the proposed method can not only detect oxide wear particles in ferrography images but also evaluate oxide wear severity in ferrography images.
Details
Keywords
The author proposed a mobile learning model of pervasive animated games which allows college students to learn via games accessed through a smartphone. It can develop the process…
Abstract
Purpose
The author proposed a mobile learning model of pervasive animated games which allows college students to learn via games accessed through a smartphone. It can develop the process of field observation and self-reflection to enhance learning effectiveness, and the motivation, and attitude of students towards learning.
Design/methodology/approach
The author proposed a model for teaching via pervasive animated games. The author used SPSS software and Pearson's correlation coefficients to explore different mobile learning strategies and their relationship with learning attitudes and achievement. Participants were vocational technology college students, who each experienced animated games in individual and group learning settings.
Findings
The results found that the learning performance of students in the individual learning group was better than that of the group learning group. A higher level of digital experience was associated with better learning performance, and a more positive attitude towards using mobile phones was associated with better learning performance.
Research limitations/implications
The learning method still has its limitations, the learner's digital information level, learning mode, learning attitudes will have an impact on the student playing teaching pervasive animation games. Therefore, improving student information level is one of the important topics of teaching pervasive animation games and mobile learning.
Originality/value
The author proposed a mobile learning strategy based on pervasive animated games. The result in the strategy of mobile learning shows that the level of students' digital experience and the overall design of animated games are important criteria for successful implementation.