IEEEXtreme

Data from vehicles driving on snowy nights reveal a range of challenges and trials. When the vehicle is driving on the snow, it needs a longer braking distance and is easy to lose control. The vehicle's powertrain may be affected by the slippery road surface, which reduces traction. Visibility may be reduced by snow and wind, making it difficult for drivers to see the road and other vehicles. Therefore, when driving on a snowy night, the driver needs to be extra careful, appropriately reduce the speed, maintain a safe distance, and ensure that the vehicle is in good working condition.

Mobile phones are central to modern communication, yet for individuals with tremors, the precision required for touch-based interfaces is a significant hurdle. In pursuit of social equality and to empower those with tremors to interact more effectively with mobile technology, this study introduces an optical see-through augmented reality (AR) system equipped with a stabilized filter.

Figure 7 illustrates that the proposed optimized algorithm reaches the optimal cumulative reward value of 41238.8 at the 300th time point, whereas the Greedy algorithm and Random algorithm achieve only 38713 and 29328, respectively. In terms of average reward values, the optimized algorithm is 137.5, the Greedy algorithm is 129, and the Random algorithm is 97.8. IoT technology plays a crucial role in optimizing algorithms by supporting information sharing and interaction among devices. This, in turn, improves the accuracy and efficiency of decision-making.

This dataset contains a total of 6605 submissions, with 13% correct solutions and 35% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/icecubes/ See the included PDF document for details about the original challenge.