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Computer Simulation

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Deep reinforcement learning for decision making of autonomous vehicle in non-lane-based traffic environments.

PloS one
Existing research on decision-making of autonomous vehicles (AVs) has mainly focused on normal road sections, with limited exploration of decision-making in complex traffic environments without lane markings. Taking toll plaza diverging area as an ex...

Tracking control of robotic manipulator end-effector trajectory based on robust sliding mode method.

PloS one
This paper addresses the precise trajectory tracking of robotic manipulators (RMs) in automation tasks, particularly in hazardous environments. A dynamic model of the end-effector in Cartesian coordinates is developed to represent the system's motion...

Efficient, Robust, and Accurate CNN Predictor for Neuronal Activation in Directional Deep Brain Stimulation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The programming of clinical deep brain stimulation (DBS) systems involves numerous combinations of stimulation parameters, such as stimulus amplitude, pulse width, and frequency. As more complex electrode designs, such as directional electrodes, are ...

Prediction and Prioritisation of Novel Anthelmintic Candidates from Public Databases Using Deep Learning and Available Bioactivity Data Sets.

International journal of molecular sciences
The control of socioeconomically important parasitic roundworms (nematodes) of animals has become challenging or ineffective due to problems associated with widespread resistance in these worms to most classes of chemotherapeutic drugs (anthelmintics...

Surrogate Model Development for Digital Experiments in Welding.

Journal of visualized experiments : JoVE
The manufacturing industry heavily relies on welding processes to join materials, forming integral components across various sectors. Many aspects will influence the quality of the weld and finally affect the structure integrity of the weldment. Weld...

A deep learning framework leveraging spatiotemporal feature fusion for electrophysiological source imaging.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Electrophysiological source imaging (ESI) is a challenging technique for noninvasively measuring brain activity, which involves solving a highly ill-posed inverse problem. Traditional methods attempt to address this challen...

Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management.

Computers in biology and medicine
BACKGROUND: Managing blood glucose levels in Type 1 Diabetes Mellitus (T1DM) is essential to prevent complications. Traditional insulin delivery methods often require significant patient involvement, limiting automation. Reinforcement Learning (RL)-b...

Reinforcement learning using neural networks in estimating an optimal dynamic treatment regime in patients with sepsis.

Computer methods and programs in biomedicine
OBJECTIVE: Early fluid resuscitation is crucial in the treatment of sepsis, yet the optimal dosage remains debated. This study aims to determine the optimal multi-stage fluid resuscitation dosage for sepsis patients.

A Neural Network Finite Element Trileaflet Heart Valve Model Incorporating Multi-Body Contact.

International journal for numerical methods in biomedical engineering
The use of patient-specific computational modeling of cardiovascular diseases has become increasingly popular to improve patient standard of care. Most simulation approaches currently utilize the finite element method (FEM), which is very well establ...

Bioinspired adaptive visual servoing control for quadrotors.

Bioinspiration & biomimetics
Since every flight ends in a landing and every landing is a potential crash, deceleration during landing is one of the most critical flying maneuvers. Here we implement a recently-discovered insect visual-guided landing strategy in which the divergen...