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Generating unseen diseases patient data using ontology enhanced generative adversarial networks.
NPJ Digit Med
January 2025
Institute of Data Science, Faculty of Science and Engineering, Maastricht University, Maastricht, the Netherlands.
Generating realistic synthetic health data (e.g., electronic health records), holds promise for fundamental research, AI model development, and enhancing data privacy safeguards.
View Article and Find Full Text PDFThe two sides of Phobos: Gray and white matter abnormalities in phobic individuals.
Cogn Affect Behav Neurosci
January 2025
Departamento de Psicología ClínicaPsicobiología y MetodologíaFacultad de Psicología, Universidad de La Laguna, La Laguna, 38200, Tenerife, Spain.
Small animal phobia (SAP) is a subtype of specific phobia characterized by an intense and irrational fear of small animals, which has been underexplored in the neuroscientific literature. Previous studies often faced limitations, such as small sample sizes, focusing on only one neuroimaging modality, and reliance on univariate analyses, which produced inconsistent findings. This study was designed to overcome these issues by using for the first time advanced multivariate machine-learning techniques to identify the neural mechanisms underlying SAP.
View Article and Find Full Text PDFSVM directed machine learning classifier for human action recognition network.
Sci Rep
January 2025
Department of Electrical and Computer Engineering, Hawassa University, Hawassa 05, Ethiopia.
Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neural networks (3D CNN) and two-stream neural networks (2SNN) have computational hurdles due to the significant parameterization they require. In this paper, we offer HARNet, a specialized lightweight residual 3D CNN that is built on directed acyclic graphs and was created expressly to handle these issues and achieve effective human action detection.
View Article and Find Full Text PDFValidation of energy valley optimization for adaptive fuzzy logic controller of DFIG-based wind turbines.
Sci Rep
January 2025
Electrical Computer and Control Engineering Department, Faculty of Engineering, Suez Canal University, Ismailia, 41522, Egypt.
This study presents a novel optimization algorithm known as the Energy Valley Optimizer Approach (EVOA) designed to effectively develop six optimal adaptive fuzzy logic controllers (AFLCs) comprising 30 parameters for a grid-tied doubly fed induction generator (DFIG) utilized in wind power plants (WPP). The primary objective of implementing EVOA-based AFLCs is to maximize power extraction from the DFIG in wind energy applications while simultaneously improving dynamic response and minimizing errors during operation. The performance of the EVOA-based AFLCs is thoroughly investigated and benchmarked against alternative optimization techniques, specifically chaotic billiards optimization (C-BO), genetic algorithms (GA), and marine predator algorithm (MPA)-based optimal proportional-integral (PI) controllers.
View Article and Find Full Text PDFTriboelectric tactile sensor for pressure and temperature sensing in high-temperature applications.
Nat Commun
January 2025
Guangxi Key Laboratory of Clean Pulp & Papermaking and Pollution Control, School of Light Industry and Food Engineering, Guangxi University, Nanning, 530004, PR China.
Skin-like sensors capable of detecting multiple stimuli simultaneously have great potential in cutting-edge human-machine interaction. However, realizing multimodal tactile recognition beyond human tactile perception still faces significant challenges. Here, an extreme environments-adaptive multimodal triboelectric sensor was developed, capable of detecting pressure/temperatures beyond the range of human perception.
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