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Artificial intelligence (AI)-assisted computer vision is an evolving field in medical imaging. However, accuracy and precision suffer when using the existing AI models for small, easy-to-miss objects such as bone fractures, which affects the models' applicability and effectiveness in a clinical setting. The proposed integration of the Hybrid-Attention (HA) mechanism into the YOLOv8 architecture offers a robust solution to improve accuracy, reliability, and speed in medical imaging applications. Experimental results demonstrate that our HA-modified YOLOv8 models achieve a 20% higher Mean Average Precision (mAP 50) and improved processing speed in arm fracture detection. [ABSTRACT FROM AUTHOR]

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Travel demand management (TDM) strategies and behaviour change initiatives aim to improve travel conditions by reducing or redistribute demand where the transport system is most congested. TDM strategies with gamified design can provide positive incentives in the form of playing a game and providing rewards. Gamified design has recently been implemented for TDM strategies in the public transport field with some success. However, before implementing a TDM strategy with a gamified design, it is critical to understand how participants or users value the proposed strategy. This study explores which attitudes and perceptions make a gamified scheme successful in attracting users to participate. This study surveyed 160 participants in Taipei City and used structural equation modelling (SEM) with an extended technology acceptance model (extended TAM) to identify which user attitudes and perceptions are critical to influence respondents' intention to join the gamified scheme. This study finds the key element of 'to capture the fun and joy' of the gamified scheme or perceived enjoyment is positively related to perceived ease of use that is key in convincing people to participate as being perceived as easy to use means the target demographic feels no burden in "giving it a try". The results of this study may aid policy makers in designing gamification schemes that are more tailored for the specific purpose and thus more effective. [ABSTRACT FROM AUTHOR]

There is a long history in transport of implementing travel demand management (TDM) to manage users' behaviour. Recently, gamified interventions have been proposed as a better way to incentivise users to participate in TDM interventions. The concept of gamified design uses game design elements in non-game contexts. However, transport is complex and diverse and it is not clear whether gamified design is transferable between different transport applications such as increasing public transport use and improving road safety. The research question of this study is to investigate policy transfer effects of different gamified design applications. In order to explore this research question, this study designed two stated preference surveys with the same gamified design concepts but applied in two fields, including public transport with the aim to relieve congestion and for young drivers with the aim to improve road safety. Both surveys are held in Queensland, Australia. A multinomial logit modelling approach was used for both case studies. The marginal effect results were cross compared to draw out policy implications and potential policy transfer effects. The paper concludes that some users' attitudes and perceptions are transferrable, and gamified schemes are not particularly favoured. In particular, it is clear that irrespective of transport field, the design of a scheme for vehicle users must understand participants' intentions and that this is more important than capturing their beliefs. [ABSTRACT FROM AUTHOR]