A new control strategy based on the root tree optimization (RTO) is presented in order to reduce the chattering phenomena in active and reactive powers, and to minimize the harmonic currents which appear mostly at the level of the rotor side converter (RSC), in a doubly-fed induction generator (DFIG). The root tree optimization is used to adjust the parameters (K,K) of PI controller (RTO-PI). Simulation results are presented to demonstrate the effectiveness of the new proposed technique. Besides, the system associated with this metaheuristic algorithm can effectively give better dynamic and steady performance. The results with the RTO-PI controller show more performances than the results compared with the classical PI.
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http://dx.doi.org/10.1016/j.isatra.2018.11.023 | DOI Listing |
Peptide therapeutics, a major class of medicines, have achieved remarkable success across diseases such as diabetes and cancer, with landmark examples such as GLP-1 receptor agonists revolutionizing the treatment of type-2 diabetes and obesity. Despite their success, designing peptides that satisfy multiple conflicting objectives, such as target binding affinity, solubility, and membrane permeability, remains a major challenge. Classical drug development and structure-based design are ineffective for such tasks, as they fail to optimize global functional properties critical for therapeutic efficacy.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
Dental age estimation, as an important part of forensic anthropology, has a wide range of applications for its results in legal practice. Given the lowered legal age for criminal responsibility in China and the increasing juvenile delinquency, we establish a morphological database targeting the second (M2) and third molars (M3) of the Southern Chinese population. Full mouth orthopantomography from 1486 individuals aged 8.
View Article and Find Full Text PDFSci Rep
January 2025
Young Researchers and Elite Club, Omidiyeh Branch, Islamic Azad University, Omidiyeh, Iran.
Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil - nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs.
View Article and Find Full Text PDFSci Rep
January 2025
School of Foreign Languages, Quanzhou Normal University, Quanzhou, 362000, Fujian, China.
With the advancement of internet of things (IoT) and artificial intelligence (AI) technology, access to large-scale bilingual parallel data has become more efficient, thereby accelerating the development and application of machine translation. Given the increasing cultural exchanges between China and Japan, many scholars have begun to study the Chinese translation of Japanese waka poetry. Based on this, the study first explores the structure of waka and the current state of its Chinese translations, analyzing existing translation disputes and introducing a data collection method for waka using IoT.
View Article and Find Full Text PDFNeuroimage
January 2025
Division of Arts and Sciences, NYU Shanghai, 567 West Yangsi Road, Pudong New District, 200124, Shanghai, China; Center for Neural Science, New York University, 4 Washington Place, NY, 10003, NY, USA; NYU-ECNU Institute of Brain and Cognitive Science, 3663 Zhongshan Road North, Putuo District, 200062, Shanghai, China. Electronic address:
BOLD response can be fitted using the population receptive field (PRF) model to reveal how visual input is represented on the cortex (Dumoulin and Wandell, 2008). Fitting the PRF model costs considerable time, often requiring days to analyze BOLD signals for a small cohort of subjects. We introduce the qPRF ("quick PRF"), a system for accelerated PRF modeling that reduced the computation time by a factor ¿1,000 without losing goodness-of-fit when compared to another widely available PRF modeling package (Kay et al.
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