Online scams continue to be a pervasive issue, and designing personalized scam warnings can effectively reduce the number of victims. This study explores how individual personality traits influence compliance with different persuasion strategies in China. We designed various scam warnings based on six key persuasion strategies and collected data from 1,186 Chinese participants through an online experiment. The results reveal that warnings using authority, social proof, and scarcity strategies significantly enhance effectiveness. Network analysis further uncovers the complex relationships between the Big Five personality traits and persuasion strategies. Individuals with higher conscientiousness respond more positively to consistency strategies, while those with high neuroticism are more influenced by social proof and authority strategies. In contrast, individuals with high openness show a greater responsiveness to reciprocity strategies and are less sensitive to authority and scarcity tactics. The findings highlight the importance of tailoring scam warnings based on personality traits to improve their effectiveness in China.

Augmented Reality Head-Up Display (AR-HUD) is a promising solution to the current warning system distraction problem. However, how to effectively convey warnings through AR graphics is still unclear. This study examines the effectiveness of the contact-analog graphic compared to the bounding box graphic in various collision types and traffic densities. Forty-eight participants watched AR-augmented driving videos and were instructed to respond to critical events. Reaction time, response rate, and subjective evaluations were compared for rear-end and pedestrian collisions in different traffic densities under different warnings. Both bounding box and contact-analog warnings improved driving performance compared to the non-warning group. The contact-analog warning performed better for rear-end collisions, while the bounding box warning had a lower reaction time for pedestrian collisions, regardless of traffic density.

Technically, Augmented Reality Head-Up Display (AR-HUD) technology can augment multiple targets in the scene. However, existing literature predominantly focuses on scenarios involving single-target augmentation. The understanding of multi-target augmentation and studies exploring effective presentation methods under such conditions are notably scarce. This study evaluates the efficacy of integrating color-based warning priority design across multi-target scenarios. 45 Participants in different warning modes (Equivalent, Hierarchical, and Baseline) view AR-augmented driving videos and respond to risky targets. Their behavioral performance and eye-tracking data are compared. Findings indicate that the equivalent warning mode, lacking in priority design, adversely affects driver performance, prolongs reaction times, and elevates saccade counts, and gaze entropy. Conversely, the hierarchical warning mode significantly ameliorates driver reaction times and the time to first fixation, while also reducing saccade counts and gaze entropy, demonstrating the efficacy of the warning priority design. The findings provide insight into the design of AR-HUD with multi-target augmentation.

Smartwatch comfort is a fundamental factor that significantly influences the user experience and provides crucial guidance for the evolution of wearable technology. However, there is currently a lack of a comprehensive theoretical model to describe the dimensions of smartwatch comfort and their corresponding influencing factors. Therefore, the present study employed a bottom-up grounded theory approach to construct a user-centered model for smartwatch comfort. Through the coding of in-depth interviews with 64 smartwatch users, we discovered that smartwatch comfort encompasses both physiological dimensions (e.g., pressure and foreign body sensation) and psychological dimensions (e.g., perceived intelligence and satisfaction of needs). Furthermore, the features of smartwatches, including physical attributes (e.g., size and material) and functionalities (e.g., interoperability and automation capabilities), directly impact the comfort experience. Additionally, individual and contextual factors can explain variations in the comfort experience of smartwatches. Users with different physiological characteristics (e.g., wrist size and body sensitivity) and psychological needs (e.g., utilitarian or hedonic needs) are influenced differently by the factors of smartwatches that affect their comfort experience. The adaptability of smartwatches across different contexts (including task context, social context, and temporal context) is also a significant influencing factor on comfort. This substantive grounded theory provides crucial guidance for the selection of core variables in future quantitative research and contributes to the development of smarter, more comfortable, and user-centric smartwatches.

Awareness of behavioral consequences significantly influences focus, priorities, and emotions. This study investigates the impact of informing drivers about potential takeover consequences on human-machine collaboration in conditional autonomous driving. We recruited 32 licensed drivers and randomly assigned them to groups with and without informed consequences. Each group completed 8 distinct takeover tasks, each with varying consequences of not taking over. We assessed takeover performance, subjective evaluations (situational awareness, workload), and physiological stress responses (electrocardiogram, electromyogram) to provide a comprehensive evaluation of takeover safety. Our findings indicate that drivers informed of the consequences demonstrated superior takeover performance, evidenced by increased time-to-collision, reduced maximum lateral acceleration, and decreased trajectory deviation. Additionally, disclosing consequences increased drivers’ perceived attentional demands, elevating workload while maintaining stable stress levels during takeover. Future research should explore how to balance workload with driving performance when informing drivers of the consequences of not taking over.

Augmented reality head-up display (AR HUD) is a new technology in assisted driving, which can add extra information to the driving environment in real-time to help the driver better perceive road situation. AR HUD can enhance driving safety but may also encourage inattentional blindness. Hence, this study aims to examine whether AR HUD-induces inattentional blindness and determine whether workload intensifies their relationship. In experiment 1, 60 participants were randomly assigned to three groups and watched three types of augmented reality (AR)-augmented driving videos, respectively. They were instructed to respond to any critical events, but only their responses to road-crossing pedestrians were recorded. Results show that AR HUD reduces inattentional blindness when pedestrians are augmented but encourages inattentional blindness when pedestrians are not augmented. In experiment 2, 20 participants viewed AR-augmented driving videos of high and low workloads. Pedestrians were not augmented in all videos. Result reveals that a high workload induces more inattentional blindness than low workload. The finding confirms that AR HUD induces inattentional blindness, and a high workload will intensify this relationship. The future design of the AR HUD assisted-driving system should consider the risk of inattentional blindness and come up with corresponding countermeasures.

With the advent of the information age, the function and value of information begin to be fully understood and used by people. As a comprehensive sector of the national economy, banks need to use advanced management system to improve their service ability and service efficiency if they want to maintain their competitiveness and expand their profitability in the fiercely competitive society. This design system uses cross-platform Qt Creator as the system development tool, builds the interface of banking system on Qt Creator, adopts C/S architecture, uses Mysql database to store the managed information and the data are added, deleted, modified and checked. The system is mainly composed of teller interface and client interface. The Banking business mainly includes the functions of opening an account, depositing, withdrawing, transferring, inquiring the balance, etc., which realizes the basic business management of the bank and can accurately and timely display the required information to customers.

In order to solve the problem of poor infrastructure and lack of automatic disaster prevention and mitigation measures in response to frost disaster in Northern Shaanxi mountain Apple planting area, resulting in production reduction or even no harvest, a frost disaster prevention and mitigation system suitable for mountainous areas was designed and implemented. The system is based on LoRa (low-power long-range) wireless communication technology, which is composed of meteorological monitoring unit, gateway, server and defrosting equipment control unit. Through collecting and analyzing the spatial and temporal distribution characteristics of ground temperature in mountainous orchards in frost weather, the system provides early warning of frost disaster and automatically controls the start and stop of defrosting equipment. The system is tested under the condition of simulating the temporal and spatial distribution of ground temperature when frost comes. The system can meet the requirements of automatic control of defrosting equipment.

Warning systems play a crucial role in the takeover of conditional automated driving. However, the widely used single-stage warning systems in takeover had inevitable and critical issues in situation awareness (SA), driving stress, and takeover performance. As such, two-stage warning systems might be an optimal solution to alleviate these problems. On this basis, this study investigated the effect of warning types (single-stage vs two-stage warning systems) and non-driving related tasks (NDRTs) (playing Tetris game vs monitoring automated systems) on takeover. A total of 32 participants were recruited to join our driving-simulated study. These participants responded to different types of takeover warning systems upon receipt while engaging in NDRTs. Simultaneously, the SA, physiology stress, takeover performance, and acceptance data of the participants were recorded. Results showed that the drivers exhibited higher SA, lower physiology stress, better takeover performance, and higher acceptance ratings in the two-stage warning systems than in the single-stage warning systems. In conclusion, two-stage warning systems are promising in improving takeover safety based on connected vehicle technologies in the future. These findings can provide some guidelines for designers and engineers when applying the warning systems in automated driving.

With the development of cutting-edge technology in the area of driving performance, driver warning systems based on head up displays (HUD) are considered to have the potential to improve driving safety in the future. The location of HUD warning graphics is a vital component to ensure that drivers obtain information the first time and avoid cognitive tunneling when coming across hazards; however, few studies have critically examined this. The present study investigated the advantages of HUD in presenting warning graphics in comparison with traditional head down display (HDD) in vehicles, and further explored the effect of HUD location based on comprehensive indicators, including behavior performance, eye movement data, and subjective assessment. The results revealed that compared with HDD, presenting warning graphics to drivers on HUD could significantly improve driving performance and eye movement patterns, and HUD was the preferential mode for drivers. Results also demonstrated that presenting HUD warning graphics at a location of 8°below the sight line was associated with the worst results in driving performance, eye movement patterns and subjective assessment. Other locations of HUD presentation were not associated with any significant differences for most indicators. These findings have some reference implications for automobile designers as they construct and implement HUD warning systems.

This study aims to investigate the usability of a head-up display (HUD) in presenting warning messages during driving and create a new and effective vehicle early warning system for drivers. Two experiments were conducted. In Experiment 1, 36 drivers were randomly assigned to a group using HUD and a control group. The simulated driving performance of the two groups was compared to determine if the HUD graphic early warning system facilitates driving safety. Results revealed that the HUD-using group demonstrated better driving performance than the control group in terms of collision, mean deceleration, accelerator release reaction time, brake reaction time, reduced velocity, reduced energy, steering reaction time, mean reaction time, and minimum reaction time. We investigated the influence of the presentation mode of warning messages on simulated driving performance in Experiment 2. Forty-eight drivers were randomly assigned to an HUD warning group, an audio warning group, and an audiovisual group that integrated HUD and audio warning. The drivers in the HUD warning group performed better than those in the two other groups in terms of mean deceleration. The audiovisual group that integrated HUD and audio warning showed an advantage in reduced velocity. The findings indicated that HUD technology has the potential to promote safe driving by improving the early warning system.