A class of superordination-preserving integral operators
Teodor Bulboacӑ
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Gender-based food intake stereotype scale (GBFISS) for adolescents: development and psychometric evaluation. [PDF]
Monge-Rojas R+2 more
europepmc +1 more source
Subordination and superordination for univalent solutions for fractional differential equations
Rabha W. Ibrahim, Maslina Darus
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Differential sandwich theorems of symmetric points associated with Dziok-Srivastava operator
In this paper we obtain some applications of theory of differential subordination, superordination and sandwich results for the classes of symmetric points associated with Dziok-Srivastava operator.
Rabba M. El-Ashwah+3 more
doaj
Model Predictive Trajectory Optimization With Dynamically Changing Waypoints for Serial Manipulators [PDF]
Systematically including dynamically changing waypoints as desired discrete actions, for instance, resulting from superordinate task planning, has been challenging for online model predictive trajectory optimization with short planning horizons. This paper presents a novel waypoint model predictive control (wMPC) concept for online replanning tasks ...
arxiv
On applications of differential subordination and superordination
N. Marikkannan, C. Ganesa Moorthy
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Differential Subordination and Superordination Results Using Fractional Integral of Confluent Hypergeometric Function [PDF]
Alina Alb Lupaş, Georgia Irina Oros
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In this paper, we obtain some subordination and superordination-preserving results of analytic functions associated with the Wright generalized hypergeometric function. Sandwich-type result involving this operator is also derived.
Jamal shenan
doaj
Safe and Stable Closed-Loop Learning for Neural-Network-Supported Model Predictive Control [PDF]
Safe learning of control policies remains challenging, both in optimal control and reinforcement learning. In this article, we consider safe learning of parametrized predictive controllers that operate with incomplete information about the underlying process. To this end, we employ Bayesian optimization for learning the best parameters from closed-loop
arxiv
From Concrete to Abstract: A Multimodal Generative Approach to Abstract Concept Learning [PDF]
Understanding and manipulating concrete and abstract concepts is fundamental to human intelligence. Yet, they remain challenging for artificial agents. This paper introduces a multimodal generative approach to high order abstract concept learning, which integrates visual and categorical linguistic information from concrete ones.
arxiv