Results 131 to 140 of about 6,293,684 (257)

Object‐based deep learning for probabilistic convective‐core nowcasting from satellite data

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Convective cores detected from Meteosat infrared imagery are represented as compact physical objects to generate probabilistic nowcasts up to 6 h ahead. A spatio‐temporal transformer models interactions among evolving core populations and produces gridded probability forecasts across the western Sahel.
Mendrika Rakotomanga, Douglas J. Parker, Nadhir Ben Rached, Seonaid R. Anderson, Cornelia Klein, Steven C. Wells   +5 more
wiley   +1 more source

M.Zigliotto, "Space vector Fourier analysis of SVM inverters in the overmodulation range

, 1996
-Voltage-source inverters with Space Vector Modulation (SVM) are largely adopted in power conversion for ac drives. In this contest, the pulse-width control in the overmodulation range is becoming a topic of considerable interest.
M Zigliotto, S Bolognani
core  

Dumpsite Seabed Characterization of the San Pedro Basin, CA, From Autonomous Vehicle Observations

Journal of Field Robotics, EarlyView.
ABSTRACT A wide‐area seabed survey was conducted using autonomous underwater vehicles (AUVs) in a known dumpsite off the coast of Southern California that has been found to have widespread sediment contamination from the chemical dichlorodiphenyltrichloroethane (DDT).
Ryan A. McCarthy, Dylan Kriegman, Sophia T. Merrifield, Heidi Batchelor, Eric J. Terrill   +4 more
wiley   +1 more source

Pulse width modulation for current source inverters with arbitrary number of phases

Scientific Reports
Modulation techniques for current source inverters (CSIs) have traditionally been derived from those used for voltage source inverters (VSIs), with space vector modulation (SVM) and pulse width modulation (PWM) being the most popular. Among these, PWM is
Predrag Pejović, Takanobu Ohno, Uroš Borović, Spasoje Mirić   +3 more
doaj   +1 more source

Space Vector Modulation of a Nine-Phase Voltage Source inverter

, 2007
A generalized multi-phase space vector theory is considered for developing the space vector modulation of a nine-phase voltage source inverter (VSI). The space vector modulation (SVM) is based on the control of the voltage vector in the first d-q plane ...
SERRA, GIOVANNI, TANI, ANGELO, GRANDI, GABRIELE   +2 more
core  

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Mapping Scytonemin Pigment Content and Biocrust Functional Indicators Using High‐Resolution Multispectral Imagery

Remote Sensing in Ecology and Conservation, EarlyView.
We demonstrate that high‐resolution multispectral imagery combined with machine learning can accurately predict key biocrust functional indicators, particularly the UV‐protective pigment scytonemin, across dryland ecosystems. Using fine‐scale imagery acquired in the Chihuahuan Desert and Colorado Plateau, we identified spectral bands strongly ...
Raúl Román, Tong Qiu, Fernando T. Maestre, Elizabeth A. La Rue, Sergio Vargas Zesati, Anthony Schaefer, Ryan V. Trexler, Nicole Pietrasiak, Estelle Couradeau   +8 more
wiley   +1 more source

SVM-Maj: a majorization approach to linear support vector machines with different hinge errors [PDF]

Support vector machines (SVM) are becoming increasingly popular for the prediction of a binary dependent variable. SVMs perform very well with respect to competing techniques. Often, the solution of an SVM is obtained by switching to the dual.
Groenen, P.J.F., Bioch, J.C., Nalbantov, G.I.   +2 more
core  

Uncertainty Characterization Framework for Machine Learning Based ACM in Q‐Band Satellite Links

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT Adaptive coding and modulation (ACM) is a widely utilized technique in satellite communication networks to mitigate the adverse effects of rain fades, particularly in extremely high frequency (EHF) bands. As a core component of fade mitigation techniques (FMTs), ACM improves signal resilience.
Kamolideen Abolarinwa, Kufre‐Mfon Ekerete, Ali Roula, Ifiok Otung   +3 more
wiley   +1 more source

Machine Learning for Programmable Nanosystems: From Liposome Formulation to DNA Origami and Hybrid Vesicles

Small, EarlyView.
This mini review highlights how machine learning can accelerate the design of programmable nanosystems. It summarizes data‐driven approaches for predicting liposome properties, guiding DNA origami design and image analysis, and optimizing emerging liposome‐DNA hybrid platforms.
Daniel Q. Zhang, Matthew A. B. Baker
wiley   +1 more source