Forthcoming and Online First Articles

International Journal of Chinese Culture and Management

International Journal of Chinese Culture and Management (IJCCM)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Chinese Culture and Management (2 papers in press)

Regular Issues

  • UAV aided fruit picking strategy for emergency harvesting   Order a copy of this article
    by Shuping Pang, Jun Yang, Guilu Lu, Xuan Wang, Yunpeng Wang, Junhao Geng, Huibo Bi 
    Abstract: The COVID-19 pandemic has introduced a new type of emergency situation which features the long lasting nature and rigid restrictions in human activities. In agriculture, the pandemic has severely restricted the fruit harvesting activities due to their labour-intensive characteristic. Hence, in this paper, we proposes an unmanned aerial vehicles aided approach to speed up the fruit picking process in both normal and emergency situations (such as the current COVID-19 pandemic or extreme weather conditions). The fruit picking process is modelled as an assignment problem and the time cost in both travelling and picking actions is taken into consideration. The simulation results show that the proposed algorithm remarkably improves the efficiency of the fruit picking process.
    Keywords: fruit harvesting; unmanned aerial vehicles; assignment problem; simulation of urban mobility; SUMO.
    DOI: 10.1504/IJCCM.2022.10049571
     
  • Designing of intersection driving behaviours based on reward points in congestion-induced emergency situations   Order a copy of this article
    by Dexian Zeng, Wen-Long Shang, Huibo Bi 
    Abstract: With the ubiquity of portable smart devices, the perception, calculation, and communication capabilities of drivers have been greatly improved, and they have gradually changed from the pure service object of the transportation system to co-decision-makers. Therefore, this paper proposes an intersection-targeted driving behaviour optimisation mechanism by encouraging drivers to conduct the traffic flow ratio changing tasks in exchange for reward points. We first formalise compliance rate-reward value functions by using a number of questionnaire-based surveys. Then we employ a reinforcement learning model to optimise the traffic flow ratios at intersections of a road network, and publish reward gaining tasks to dynamically optimise the traffic flow ratios based on the current traffic flow ratios and the number of vehicles at the intersections. The experimental results show that the introduction of points-based rewards can effectively improve the traffic efficiency at intersections.
    Keywords: points based reward; driving behaviour optimisation; reinforcement learning; Simulation of Urban MObility; SUMO.
    DOI: 10.1504/IJCCM.2022.10051068