AIMC Topic: Algorithms

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Feasibility of a deep learning algorithm to achieve the low-dose Ga-FAPI/the fast-scan PET images: a multicenter study.

The British journal of radiology
OBJECTIVES: Our work aims to study the feasibility of a deep learning algorithm to reduce the Ga-FAPI radiotracer injected activity and/or shorten the scanning time and to investigate its effects on image quality and lesion detection ability.

Safe control of logical control networks with random impulses.

Neural networks : the official journal of the International Neural Network Society
Under the framework of a hybrid-index model, this paper investigates safe control problems of state-dependent random impulsive logical control networks (RILCNs) on both finite and infinite horizons, respectively. By using the ΞΎ-domain method and the ...

Machine learning-based model predictive controller design for cell culture processes.

Biotechnology and bioengineering
The biopharmaceutical industry continuously seeks to optimize the critical quality attributes to maintain the reliability and cost-effectiveness of its products. Such optimization demands a scalable and optimal control strategy to meet the process co...

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems.

Sensors (Basel, Switzerland)
In this paper, the authors investigate the possibility of applying artificial intelligence algorithms to the outputs of a low-cost Kalman filter-based navigation solution in order to achieve performance similar to that of high-end MEMS inertial senso...

Application of Deep Learning Algorithm to Monitor Upper Extremity Task Practice.

Sensors (Basel, Switzerland)
Upper extremity hemiplegia is a serious problem affecting the lives of many people post-stroke. Motor recovery requires high repetitions and quality of task-specific practice. Sufficient practice cannot be completed during therapy sessions, requiring...

Domain Adaptation Based on Semi-Supervised Cross-Domain Mean Discriminative Analysis and Kernel Transfer Extreme Learning Machine.

Sensors (Basel, Switzerland)
Good data feature representation and high precision classifiers are the key steps for pattern recognition. However, when the data distributions between testing samples and training samples do not match, the traditional feature extraction methods and ...

DeepdlncUD: Predicting regulation types of small molecule inhibitors on modulating lncRNA expression by deep learning.

Computers in biology and medicine
Targeting lncRNAs by small molecules (SM-lncR) to alter their expression levels has emerged as an important therapeutic modality for disease treatment. To date, no computational tools have been dedicated to predicting small molecule-mediated upregula...

Network Security Situation Prediction Based on Optimized Clock-Cycle Recurrent Neural Network for Sensor-Enabled Networks.

Sensors (Basel, Switzerland)
We propose an optimized Clockwork Recurrent Neural Network (CW-RNN) based approach to address temporal dynamics and nonlinearity in network security situations, improving prediction accuracy and real-time performance. By leveraging the clock-cycle RN...

Particle Swarm Algorithm Path-Planning Method for Mobile Robots Based on Artificial Potential Fields.

Sensors (Basel, Switzerland)
Path planning is an important part of the navigation control system of mobile robots since it plays a decisive role in whether mobile robots can realize autonomy and intelligence. The particle swarm algorithm can effectively solve the path-planning p...