Analysis of influencing factors of traffic accidents on urban ring road based on the SVM model optimized by Bayesian method.

Based on small scale sample of accident data from specific scenarios, fully exploring the potential influencing factors of the severity of traffic accidents has become a key and effective research method. In order to analyze the factors mentioned above in the scenario of urban ring roads, this paper collected data records of 1250 traffic accidents involving different severity on urban ring road of a central city in northwest China in the past 3 years. Firstly, the Support Vector Machine (SVM) model of non-parametric method is utilized to analyze the data above, and three kernel functions of linear, inhomogeneous polynomial and Gaussian radial basis are constructed respectively.

Towards higher load capacity: innovative design of a robotic hand with soft jointed structure.

In this paper, the innovative design of a robotic hand with soft jointed structure is carried out and a tendon-driven mechanism, a master-slave motor coordinated drive mechanism, a thumb coupling transmission mechanism and a thumb steering mechanism are proposed. These innovative designs allow for more effective actuation in each finger, enhancing the load capacity of the robotic hand while maintaining key performance indicators such as dexterity and adaptability. A mechanical model of the robotic finger was made to determine the application limitations and load capacity.

Research on obstacle avoidance algorithm for unmanned ground vehicle based on multi-sensor information fusion.

With the wide application of unmanned ground vehicles (UGV) in a complex environment, the research on the obstacle avoidance system has gradually become an important research part in the field of the UGV system. Aiming at the complex working environment, a sensor detection system mounted on UGV is designed and the kinematic estimation model of UGV is studied. In order to meet the obstacle avoidance requirements of UGVs in a complex environment, a fuzzy neural network obstacle avoidance algorithm based on multi-sensor information fusion is designed in this paper.

Study of the action of Se and Cu on the growth metabolism of Escherichia coli by microcalorimetry.

The biological effect of Se and Cu²(+) on Escherichia coli (E. coli) growth was studied by using a 3114/3236 TAM Air Isothermal Calorimeter, ampoule method, at 37°C. From the thermogenesis curves, the thermokinetic equations were established under different conditions.