Search

Your search keyword '"Li, Junyu"' showing total 602 results
Start Over Author "Li, Junyu" Publication Type Academic Journals
602 results on '"Li, Junyu"'

2. Deriving beliefs about children's moral responsibility from capacity beliefs

Author

Li, Junyu, Hardecker, Susanne, Haun, Daniel Benjamin Moritz, and Bohn, Manuel

Subjects
Philosophy, Psychology, Action, Reasoning, Theory of Mind
Abstract

Adults have rich beliefs about children's development timelines, and they interpret and react to children's behaviors across ages, holding children responsible to some degree. While children's mental capacity and potential could motivate moral agency attribution, a question remains whether a consistent relation exists between the empirical beliefs about children's various capacities and the responsibility attribution to their behaviors that manifest the corresponding capacities. Here, we tested 361 adults (UK, US) on their folk psychology and moral beliefs about different ages with vignettes that reflect agential control in various domains (motor control, inhibitory control, theory of mind, planning, moral evaluation) combined with several variants of scenarios. We characterized the relation between adults' expectations and responsibility attribution with mixed models. We found that this moral reasoning varies for targets of different ages and the amount of responsibility is mostly determined by age. We suggest an alternative mechanism between capacity- and moral beliefs.

Published
2024

7. Dynamic Adjustment Neural Network–Based Cooperative Control for Vehicle Platoons with State Constraints

Author

Wang Ping, Gao Min, Li Junyu, and Zhang Anguo

Subjects
vehicle platoon, dynamic adjustment neural network (dann), cooperative control, state constraint, Mathematics, QA1-939, Electronic computers. Computer science, QA75.5-76.95
Abstract

This paper addresses the challenge of managing state constraints in vehicle platoons, including maintaining safe distances and aligning velocities, which are key factors that contribute to performance degradation in platoon control. Traditional platoon control strategies, which rely on a constant time-headway policy, often lead to deteriorated performance and even instability, primarily during dynamic traffic conditions involving vehicle acceleration and deceleration. The underlying issue is the inadequacy of these methods to adapt to variable time-delays and to accurately modulate the spacing and speed among vehicles. To address these challenges, we propose a dynamic adjustment neural network (DANN) based cooperative control scheme. The proposed strategy employs neural networks to continuously learn and adjust to time varying conditions, thus enabling precise control of each vehicle’s state within the platoon. By integrating a DANN into the platoon control system, we ensure that both velocity and inter-vehicular spacing adapt in response to real-time traffic dynamics. The efficacy of our proposed control approach is validated using both Lyapunov stability theory and numeric simulation, which confirms substantial gains in stability and velocity tracking of the vehicle platoon.

Published
2024
Full Text
View/download PDF

47. SLEAP: A deep learning system for multi-animal pose tracking

Author

Pereira, Talmo D., Tabris, Nathaniel, Matsliah, Arie, Turner, David M., Li, Junyu, Ravindranath, Shruthi, Papadoyannis, Eleni S., Normand, Edna, Deutsch, David S., Wang, Z. Yan, McKenzie-Smith, Grace C., Mitelut, Catalin C., Castro, Marielisa Diez, D’Uva, John, Kislin, Mikhail, Sanes, Dan H., Kocher, Sarah D., Wang, Samuel S.-H., Falkner, Annegret L., Shaevitz, Joshua W., and Murthy, Mala

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results