Prediction-Error Negativity to Assess Singularity Avoidance Strategies in Physical Human-Robot Collaboration

Author(s):  
Stefano Aldini ◽  
Avinash K. Singh ◽  
Marc Carmichael ◽  
Yu-Kai Wang ◽  
Dikai Liu ◽  
...  
Author(s):  
Avinash Kumar Singh ◽  
Stefano Aldini ◽  
Daniel Leong ◽  
Yu-Kai Wang ◽  
Marc G. Carmichael ◽  
...  

2012 ◽  
Vol 43 (3) ◽  
pp. 115-126 ◽  
Author(s):  
Christina Matschke ◽  
Kai Sassenberg

Entering a new group provides the potential of forming a new social identity. Starting from self-regulation models, we propose that goals (e.g., internal motivation to enter the group), strategies (e.g., approach and avoidance strategies), and events (e.g., the group’s response) affect the development of the social self. In two studies we manipulated the group’s response (acceptance vs. rejection) and assessed internal motivation as well as approach and avoidance strategies. It was expected, and we found, that when newcomers are accepted, their use of approach strategies (but not avoidance strategies) facilitates social identification. In line with self-completion theory, for highly internally motivated individuals approach strategies facilitated social identification even upon rejection. The results underline the active role of newcomers in their social identity development.


2020 ◽  
Vol 149 (9) ◽  
pp. 1755-1766 ◽  
Author(s):  
William J. Villano ◽  
A. Ross Otto ◽  
C. E. Chiemeka Ezie ◽  
Roderick Gillis ◽  
Aaron S. Heller

Author(s):  
K.S. Klen ◽  
◽  
M.K. Yaremenko ◽  
V.Ya. Zhuykov ◽  
◽  
...  

The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.


Sign in / Sign up

Export Citation Format

Share Document