ABSTRACT
Intelligent technology has been recently more developed which is due to the advancement in the technology sector. Moreover, every industry is now moving toward adoption of the intelligent technology to provide better services along with informed decisions which are possible only if devices have built-in intelligence. Likewise, in football simulation league, assigning suitable roles to each robot according to the real-time characteristics of complex and changeable field conditions is the key to win the game. In order to solve the problems of low research efficiency and poor simulation effect, this paper aims to deeply explore the application of RoboCup 3D and intelligent technology in football simulation league. Firstly, the movement speed, shooting speed, and direction of the players are measured. Secondly, a highly intelligent goal keeping and defense method and triangle attack strategy are proposed. The defense strategy is mainly that when the other team is in the state of attack, we send players to intercept the other player with the ball, and the triangle attack strategy is to use the three players in the appropriate position to cooperate with each other. The triangular attack team is composed of core attacking players and two auxiliary attacking players. This method is applied to football simulation league. RoboCup 3D simulation experiments show that the proposed method has good simulation effects in terms of ball loss rate and winning streak, which shows that the proposed method can effectively improve the research efficiency and simulation effect and has certain practicability.
Subject(s)
Athletic Performance , Football , Soccer , Intelligence , TechnologyABSTRACT
The heart rate (HR) trajectory is a dynamic metric that shows how HR changes over time. Previous studies have demonstrated that elevated HR is associated with stroke events. However, little research has been done on the influence of shifting HR throughout the acute period on clinical outcomes. This study aims to investigate the effect of HR trajectories on functional outcomes in patients with acute ischemic stroke (AIS). A total of 981 AIS patients were included in the study. A latent mixture model was used to assess HR trends over the first 7 days following disease onset. The patients were divided into four groups based on different HR trajectories: markedly decreasing in 48 h (T1), mildly decreasing in 48 h (T2), sustained moderate in 7 days (T3), and sustained high in 7 days (T4). Poor outcome was defined as a modified Rankin Scale (mRS) score of ≥3 in 3 months. Logistic regression was used to analyze the correlation between different HR trajectories and outcomes. The incidence of poor outcomes was 9.02%, 10.80%, 11.79%, 16.36% in T1 (n = 133), T2 (n = 352), T3 (n = 441), and T4 (n = 55) groups, respectively. Compared with T1 group, T4 group was significantly associated with a higher risk of poor outcome at 3 months (odds ratio = 3.00, 95% confidence interval = 1.06-8.54, p value = .0392). This suggests that in AIS patients, a sustained high HR trajectory is linked to a greater likelihood of poor functional outcome than a markedly decreasing HR trajectory. HR trajectories demonstrate the utility of repeated HR measurements for outcome assessment.
