ABSTRACT
Shared bikes can help cities achieve carbon neutrality goals. Cleaning and disinfection are vital procedures of the maintenance of shared bikes, especially during the COVID-19 pandemic because shared bikes could be a transmission intermediary of viruses. This study proposes an optimization model of the cleaning and disinfection scheme of the dockless shared bikes. The disinfection is assumed to be performed at night, when the usage is lowest. By regarding the disinfection staff as traveling salesmen, the model is formulated as an extension of the Multidepot Multiple Traveling Salesman Problem (MDMTSP). The objective function is to minimize the total cost;which consists of the cost associated with the working time and per-capita cost of the disinfection staff. A heuristic algorithm combining k -means clustering and genetic algorithm (K-GA) is adopted to find the lower bound solution. Then, the K-GA-adjustment algorithm has been adopted to find the solutions that satisfy the constraints. To reduce the computing time needed, an approximate function for the lower bound of the optimal number of disinfection staff is obtained by constructing a Continuous Approximation (CA) model. A case study based on real location data of shared bikes in Chengdu, China, is performed to show how the maintenance department could adopt the optimization framework to design an efficient scheme to clean and disinfect the shared bikes. [ABSTRACT FROM AUTHOR] Copyright of Journal of Advanced Transportation is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
ABSTRACT
Due to the spread of COVID-19 worldwide, a large number of universities had to close their campuses. To maintain teaching and learning during this disruption to the traditional teaching, most universities have adopted online teaching model. The current study aimed at investigating the efficacy of various online teaching modes as well as comparing a proposed combined model of online and flipped learning to other online and traditional models. The Learning under COVID-19questionnaire was designed and administered to undergraduate engineering students at Chengdu University of Information Technology (CUIT). The questionnaire included five parts: demographic questions, frequencies of online courses, types of online courses, the communication and Q&A in online classes and the effect of online classes, as well as the effect of combined model learning. The results of the study showed that, students were dissatisfied with online learning in general, and they were especially dissatisfied with the communication and Q&A modes. In addition, the combined model of online teaching with the flipped learning improved students' learning, attention, and evaluation of courses. [ABSTRACT FROM AUTHOR] Copyright of Interactive Learning Environments is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
ABSTRACT
Space-time flexibility is defined as the extent to which individuals can participate in activities at different lo-cations and different times. High space-time flexibility of travel enables people more freedom to choose when and where to make trips and assists in achieving both environmental and social sustainability. Applying a quasi -experimental approach - propensity score matching - to data obtained from 624 interviews in Chengdu (China), this paper aims to examine the effects of metro accessibility on space-time flexibility of shopping travel for non -daily goods. The results show that people residing around metro stations (i.e., high calculated accessibility) have a higher level of space-time flexibility of shopping travel than those living elsewhere. Meanwhile, people who perceive easy access to metro services (i.e., high perceived accessibility) are also likely to have a higher level of space-time flexibility. The findings highlight the importance of metro accessibility from the perspective of time geography. In practice, improving calculated and perceived accessibility to metro services may be an effective urban planning strategy to increase residents' space-time flexibility of shopping travel and inform policy rec-ommendations for the design of sustainable cities.