In power inspection, uncertainties, such as wind gusts in the working environment, affect the trajectory of the inspection UAV (unmanned aerial vehicle), and a sliding mode adaptive robust control algorithm is proposed in this paper to solve this problem. For the nonlinear and under-driven characteristics of the inspection UAV system, a double closed-loop control system which includes a position loop and attitude loop is designed. Lyapunov stability analysis is used to determine whether the designed system could finally achieve asymptotic stability. Sliding-mode PID control and a backstepping control algorithm are applied to analyze the superiority of the control algorithm proposed in this paper. A PX4 based experimental platform system is built and experimental tests were carried out under outdoor environment. The effectiveness and superiority of the control algorithm are proposed in this paper. The experimental results show that the sliding mode PID control can achieve good accuracy with smaller computing costs. For nonlinear interference, the sliding mode adaptive robust control strategy can achieve higher trajectory tracking accuracy.
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http://dx.doi.org/10.3390/s22103648 | DOI Listing |
Mayo Clin Proc
January 2025
Division of Pediatric Cardiology, Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN; Department of Molecular Pharmacology and Experimental Therapeutics, Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, MN; Division of Heart Rhythm Services, Department of Cardiovascular Medicine, Windland Smith Rice Genetic Heart Rhythm Clinic, Mayo Clinic, Rochester, MN. Electronic address:
Objective: To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysis of the 12-lead electrocardiogram (ECG) can distinguish patients with long QT syndrome (LQTS) from those with acquired QT prolongation.
Methods: The study cohort included all patients with genetically confirmed LQTS evaluated in the Windland Smith Rice Genetic Heart Rhythm Clinic and controls from Mayo Clinic's ECG data vault comprising more than 2.5 million patients.
Nucleic Acids Res
January 2025
SynVaccine Ltd, Ramat Hachayal, 3 Golda Meir Street, Science Park, Nes Ziona 7403648, Israel.
Many viruses of the Flaviviridae family, including the Zika virus (ZIKV), are human pathogens of significant public health concerns. Despite extensive research, there are currently no approved vaccines available for ZIKV and specifically no live-attenuated Zika vaccine. In this current study, we suggest a novel computational algorithm for generating live-attenuated vaccines via the introduction of silent mutation into regions that undergo selection for strong or weak local RNA folding or into regions that exhibit medium levels of sequence conservation.
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January 2025
Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy.
The increasing demand for hazelnut kernels is favoring an upsurge in hazelnut cultivation worldwide, but ongoing climate change threatens this crop, affecting yield decreases and subject to uncontrolled pathogen and parasite attacks. Technical advances in precision agriculture are expected to support farmers to more efficiently control the physio-pathological status of crops. Here, we report a straightforward approach to monitoring hazelnut trees in an open field, using aerial multispectral pictures taken by drones.
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December 2024
Intelligent Manufacturing Laboratory, Production Engineering Institute, Faculty of Mechanical Engineering, University of Maribor, Smetanova ulica 17, 2000 Maribor, Slovenia.
Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time.
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December 2024
The College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Software-defined networking (SDN) offers an effective solution for flexible management of Wireless Sensor Networks (WSNs) by separating control logic from sensor nodes. This paper tackles the challenge of timely recovery from SDN controller failures and proposes a game theoretic model for multi-domain controllers. A game-enhanced autonomous fault recovery algorithm for SDN controllers is proposed, which boasts fast fault recovery and low migration costs.
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