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1 – 2 of 2Hanan AlMazrouei, Virginia Bodolica and Robert Zacca
This study aims to examine the relationship between cultural intelligence and organisational commitment and its effect on learning goal orientation and turnover intention within…
Abstract
Purpose
This study aims to examine the relationship between cultural intelligence and organisational commitment and its effect on learning goal orientation and turnover intention within the expatriate society of the United Arab Emirates (UAE).
Design/methodology/approach
A survey instrument was developed to collect data from 173 non-management expatriates employed by multinational corporations located in Dubai, UAE. SmartPLS bootstrap software was used to analyse the path coefficients and test the research hypotheses.
Findings
The results demonstrate that cultural intelligence enhances both learning goal orientation and turnover intention of expatriates. Moreover, organisational commitment partially mediates the relationship between cultural intelligence and turnover intention/learning goal orientation.
Originality/value
This study contributes by advancing extant knowledge with regard to cultural intelligence and organisational commitment effects on turnover intention and learning goal orientation of expatriates within a context of high cultural heterogeneity.
Details
Keywords
Yan Kan, Hao Li, Zhengtao Chen, Changjiang Sun, Hao Wang and Joachim Seidelmann
This paper aims to propose a stable and precise recognition and pose estimation method to deal with the difficulties that industrial parts often present, such as incomplete point…
Abstract
Purpose
This paper aims to propose a stable and precise recognition and pose estimation method to deal with the difficulties that industrial parts often present, such as incomplete point cloud data due to surface reflections, lack of color texture features and limited availability of effective three-dimensional geometric information. These challenges lead to less-than-ideal performance of existing object recognition and pose estimation methods based on two-dimensional images or three-dimensional point cloud features.
Design/methodology/approach
In this paper, an image-guided depth map completion method is proposed to improve the algorithm's adaptability to noise and incomplete point cloud scenes. Furthermore, this paper also proposes a pose estimation method based on contour feature matching.
Findings
Through experimental testing on real-world and virtual scene dataset, it has been verified that the image-guided depth map completion method exhibits higher accuracy in estimating depth values for depth map hole pixels. The pose estimation method proposed in this paper was applied to conduct pose estimation experiments on various parts. The average recognition accuracy in real-world scenes was 88.17%, whereas in virtual scenes, the average recognition accuracy reached 95%.
Originality/value
The proposed recognition and pose estimation method can stably and precisely deal with the difficulties that industrial parts present and improve the algorithm's adaptability to noise and incomplete point cloud scenes.
Details